| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798991001011021031041051061071081091101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491501511521531541551561571581591601611621631641651661671681691701711721731741751761771781791801811821831841851861871881891901911921931941951961971981992002012022032042052062072082092102112122132142152162172182192202212222232242252262272282292302312322332342352362372382392402412422432442452462472482492502512522532542552562572582592602612622632642652662672682692702712722732742752762772782792802812822832842852862872882892902912922932942952962972982993003013023033043053063073083093103113123133143153163173183193203213223233243253263273283293303313323333343353363373383393403413423433443453463473483493503513523533543553563573583593603613623633643653663673683693703713723733743753763773783793803813823833843853863873883893903913923933943953963973983994004014024034044054064074084094104114124134144154164174184194204214224234244254264274284294304314324334344354364374384394404414424434444454464474484494504514524534544554564574584594604614624634644654664674684694704714724734744754764774784794804814824834844854864874884894904914924934944954964974984995005015025035045055065075085095105115125135145155165175185195205215225235245255265275285295305315325335345355365375385395405415425435445455465475485495505515525535545555565575585595605615625635645655665675685695705715725735745755765775785795805815825835845855865875885895905915925935945955965975985996006016026036046056066076086096106116126136146156166176186196206216226236246256266276286296306316326336346356366376386396406416426436446456466476486496506516526536546556566576586596606616626636646656666676686696706716726736746756766776786796806816826836846856866876886896906916926936946956966976986997007017027037047057067077087097107117127137147157167177187197207217227237247257267277287297307317327337347357367377387397407417427437447457467477487497507517527537547557567577587597607617627637647657667677687697707717727737747757767777787797807817827837847857867877887897907917927937947957967977987998008018028038048058068078088098108118128138148158168178188198208218228238248258268278288298308318328338348358368378388398408418428438448458468478488498508518528538548558568578588598608618628638648658668678688698708718728738748758768778788798808818828838848858868878888898908918928938948958968978988999009019029039049059069079089099109119129139149159169179189199209219229239249259269279289299309319329339349359369379389399409419429439449459469479489499509519529539549559569579589599609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959969979989991000100110021003100410051006100710081009101010111012101310141015101610171018101910201021102210231024102510261027102810291030103110321033103410351036103710381039104010411042104310441045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810891090109110921093109410951096109710981099110011011102110311041105110611071108110911101111111211131114111511161117111811191120112111221123112411251126112711281129113011311132113311341135113611371138113911401141114211431144114511461147114811491150115111521153115411551156115711581159116011611162116311641165116611671168116911701171117211731174117511761177117811791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240124112421243124412451246124712481249125012511252125312541255125612571258125912601261126212631264126512661267126812691270127112721273127412751276127712781279128012811282128312841285128612871288128912901291129212931294129512961297129812991300130113021303130413051306130713081309131013111312131313141315131613171318131913201321132213231324132513261327132813291330133113321333133413351336133713381339134013411342134313441345134613471348134913501351135213531354135513561357135813591360136113621363136413651366136713681369137013711372137313741375137613771378137913801381138213831384138513861387138813891390139113921393139413951396139713981399140014011402140314041405140614071408140914101411141214131414141514161417141814191420142114221423142414251426142714281429143014311432143314341435143614371438143914401441144214431444144514461447144814491450145114521453145414551456145714581459146014611462146314641465146614671468146914701471147214731474147514761477147814791480148114821483148414851486148714881489149014911492149314941495149614971498149915001501150215031504150515061507150815091510151115121513151415151516151715181519152015211522152315241525152615271528152915301531153215331534153515361537153815391540154115421543154415451546154715481549155015511552155315541555155615571558155915601561156215631564156515661567156815691570157115721573157415751576157715781579158015811582158315841585158615871588158915901591159215931594159515961597159815991600160116021603160416051606160716081609161016111612161316141615161616171618161916201621162216231624162516261627162816291630163116321633163416351636163716381639164016411642164316441645164616471648164916501651165216531654165516561657165816591660166116621663166416651666166716681669167016711672167316741675167616771678167916801681168216831684168516861687168816891690169116921693169416951696169716981699170017011702170317041705170617071708170917101711171217131714171517161717171817191720172117221723172417251726172717281729173017311732173317341735173617371738173917401741174217431744174517461747174817491750175117521753175417551756175717581759176017611762176317641765176617671768176917701771177217731774177517761777177817791780178117821783178417851786178717881789179017911792179317941795179617971798179918001801180218031804180518061807180818091810181118121813181418151816181718181819182018211822182318241825182618271828182918301831183218331834183518361837183818391840184118421843184418451846184718481849185018511852185318541855185618571858185918601861186218631864186518661867186818691870187118721873187418751876187718781879188018811882188318841885188618871888188918901891189218931894189518961897189818991900190119021903190419051906190719081909191019111912191319141915191619171918191919201921192219231924192519261927192819291930193119321933193419351936193719381939194019411942194319441945194619471948194919501951195219531954195519561957195819591960196119621963196419651966196719681969197019711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044204520462047204820492050205120522053205420552056205720582059206020612062206320642065206620672068206920702071207220732074207520762077207820792080208120822083208420852086208720882089209020912092209320942095209620972098209921002101210221032104210521062107210821092110211121122113211421152116211721182119212021212122212321242125212621272128212921302131213221332134213521362137213821392140214121422143214421452146214721482149215021512152215321542155215621572158215921602161216221632164216521662167216821692170217121722173217421752176217721782179218021812182218321842185218621872188218921902191219221932194219521962197219821992200220122022203220422052206220722082209221022112212221322142215221622172218221922202221222222232224222522262227222822292230223122322233223422352236223722382239224022412242224322442245224622472248224922502251225222532254225522562257225822592260226122622263226422652266226722682269227022712272227322742275227622772278227922802281228222832284228522862287228822892290229122922293229422952296229722982299230023012302230323042305230623072308230923102311231223132314231523162317231823192320232123222323232423252326232723282329233023312332233323342335233623372338233923402341234223432344234523462347234823492350235123522353235423552356235723582359236023612362236323642365236623672368236923702371237223732374237523762377237823792380238123822383238423852386238723882389239023912392239323942395239623972398239924002401240224032404240524062407240824092410241124122413241424152416241724182419242024212422242324242425242624272428242924302431243224332434243524362437243824392440244124422443244424452446244724482449245024512452245324542455245624572458245924602461246224632464246524662467246824692470247124722473247424752476247724782479248024812482248324842485248624872488248924902491249224932494249524962497249824992500250125022503250425052506250725082509251025112512251325142515251625172518251925202521252225232524252525262527252825292530253125322533253425352536253725382539254025412542254325442545254625472548254925502551255225532554255525562557255825592560256125622563256425652566256725682569257025712572257325742575257625772578257925802581258225832584258525862587258825892590259125922593259425952596259725982599260026012602260326042605260626072608260926102611261226132614261526162617261826192620262126222623262426252626262726282629263026312632263326342635263626372638263926402641264226432644264526462647264826492650265126522653265426552656265726582659266026612662266326642665266626672668266926702671267226732674267526762677267826792680268126822683268426852686268726882689269026912692269326942695269626972698269927002701270227032704270527062707270827092710271127122713271427152716271727182719272027212722272327242725272627272728272927302731273227332734273527362737273827392740274127422743274427452746274727482749275027512752275327542755275627572758275927602761276227632764276527662767276827692770277127722773277427752776277727782779278027812782278327842785278627872788278927902791279227932794279527962797279827992800280128022803280428052806280728082809281028112812281328142815281628172818281928202821282228232824282528262827282828292830283128322833283428352836283728382839284028412842284328442845284628472848284928502851285228532854285528562857285828592860286128622863286428652866286728682869287028712872287328742875287628772878287928802881288228832884288528862887288828892890289128922893289428952896289728982899290029012902290329042905290629072908290929102911291229132914291529162917291829192920292129222923292429252926292729282929293029312932293329342935293629372938293929402941294229432944294529462947294829492950295129522953295429552956295729582959296029612962296329642965296629672968296929702971297229732974297529762977297829792980298129822983298429852986298729882989299029912992299329942995299629972998299930003001300230033004300530063007300830093010301130123013301430153016301730183019302030213022302330243025302630273028302930303031303230333034303530363037303830393040304130423043304430453046304730483049305030513052305330543055305630573058305930603061306230633064306530663067306830693070307130723073307430753076307730783079308030813082308330843085308630873088308930903091309230933094309530963097309830993100310131023103310431053106310731083109311031113112311331143115311631173118311931203121312231233124312531263127312831293130313131323133313431353136313731383139314031413142314331443145314631473148314931503151315231533154315531563157315831593160316131623163316431653166316731683169317031713172317331743175317631773178317931803181318231833184318531863187318831893190319131923193319431953196319731983199320032013202320332043205320632073208320932103211321232133214321532163217321832193220322132223223322432253226322732283229323032313232323332343235323632373238323932403241324232433244324532463247324832493250325132523253325432553256325732583259326032613262326332643265326632673268326932703271327232733274327532763277327832793280328132823283328432853286328732883289329032913292329332943295329632973298329933003301330233033304330533063307330833093310331133123313331433153316331733183319332033213322332333243325332633273328332933303331333233333334333533363337333833393340334133423343334433453346334733483349335033513352335333543355335633573358335933603361336233633364336533663367336833693370337133723373337433753376337733783379338033813382338333843385338633873388338933903391339233933394339533963397339833993400340134023403340434053406340734083409341034113412341334143415341634173418341934203421342234233424342534263427342834293430343134323433343434353436343734383439344034413442344334443445344634473448344934503451345234533454345534563457345834593460346134623463346434653466346734683469347034713472347334743475347634773478347934803481348234833484348534863487348834893490349134923493349434953496349734983499350035013502350335043505350635073508350935103511351235133514351535163517351835193520352135223523352435253526352735283529353035313532353335343535353635373538353935403541354235433544354535463547354835493550355135523553355435553556355735583559356035613562356335643565356635673568356935703571357235733574357535763577357835793580358135823583358435853586358735883589359035913592359335943595359635973598359936003601360236033604360536063607360836093610361136123613361436153616361736183619362036213622362336243625362636273628362936303631363236333634363536363637363836393640364136423643364436453646364736483649365036513652365336543655365636573658365936603661366236633664366536663667366836693670367136723673367436753676367736783679368036813682368336843685368636873688368936903691369236933694369536963697369836993700370137023703370437053706370737083709371037113712371337143715371637173718371937203721372237233724372537263727372837293730373137323733373437353736373737383739374037413742374337443745374637473748374937503751375237533754375537563757375837593760376137623763376437653766376737683769377037713772377337743775377637773778377937803781378237833784378537863787378837893790379137923793379437953796379737983799380038013802380338043805380638073808380938103811381238133814381538163817381838193820382138223823382438253826382738283829383038313832383338343835383638373838383938403841384238433844384538463847384838493850385138523853385438553856385738583859386038613862386338643865386638673868386938703871387238733874387538763877387838793880388138823883388438853886388738883889389038913892389338943895389638973898389939003901390239033904390539063907390839093910391139123913391439153916391739183919392039213922392339243925392639273928392939303931393239333934393539363937393839393940394139423943394439453946394739483949395039513952395339543955395639573958395939603961396239633964396539663967396839693970397139723973397439753976397739783979398039813982398339843985398639873988398939903991399239933994399539963997399839994000400140024003400440054006400740084009401040114012401340144015401640174018401940204021402240234024402540264027402840294030403140324033403440354036403740384039404040414042404340444045404640474048404940504051405240534054405540564057405840594060406140624063406440654066406740684069407040714072407340744075407640774078407940804081408240834084408540864087408840894090409140924093409440954096409740984099410041014102410341044105410641074108410941104111411241134114411541164117411841194120412141224123412441254126412741284129413041314132413341344135413641374138413941404141414241434144414541464147414841494150415141524153415441554156415741584159416041614162416341644165416641674168416941704171417241734174417541764177417841794180418141824183418441854186418741884189419041914192419341944195419641974198419942004201420242034204420542064207420842094210421142124213421442154216421742184219422042214222422342244225422642274228422942304231423242334234423542364237423842394240424142424243424442454246424742484249425042514252425342544255425642574258425942604261426242634264426542664267426842694270427142724273427442754276427742784279428042814282428342844285428642874288428942904291429242934294429542964297429842994300430143024303430443054306430743084309431043114312431343144315431643174318431943204321432243234324432543264327432843294330433143324333433443354336433743384339434043414342434343444345434643474348434943504351435243534354435543564357435843594360436143624363436443654366436743684369437043714372437343744375437643774378437943804381438243834384438543864387438843894390439143924393439443954396439743984399440044014402440344044405440644074408440944104411441244134414441544164417441844194420442144224423442444254426442744284429443044314432443344344435443644374438443944404441444244434444444544464447444844494450445144524453445444554456445744584459446044614462446344644465446644674468446944704471447244734474447544764477447844794480448144824483448444854486448744884489449044914492449344944495449644974498449945004501450245034504450545064507450845094510451145124513451445154516451745184519452045214522452345244525452645274528452945304531453245334534453545364537453845394540454145424543454445454546454745484549455045514552455345544555455645574558455945604561456245634564456545664567456845694570457145724573457445754576457745784579458045814582458345844585458645874588458945904591459245934594459545964597459845994600460146024603460446054606460746084609461046114612461346144615461646174618461946204621462246234624462546264627462846294630463146324633463446354636463746384639464046414642464346444645464646474648464946504651465246534654465546564657465846594660466146624663466446654666466746684669467046714672467346744675467646774678467946804681468246834684468546864687468846894690469146924693469446954696469746984699470047014702470347044705470647074708470947104711471247134714471547164717471847194720472147224723472447254726472747284729473047314732473347344735473647374738473947404741474247434744474547464747474847494750475147524753475447554756475747584759476047614762476347644765476647674768476947704771477247734774477547764777477847794780478147824783478447854786478747884789479047914792479347944795479647974798479948004801480248034804480548064807480848094810481148124813481448154816481748184819482048214822482348244825482648274828482948304831483248334834483548364837483848394840484148424843484448454846484748484849485048514852485348544855485648574858485948604861486248634864486548664867486848694870487148724873487448754876487748784879488048814882488348844885488648874888488948904891489248934894489548964897489848994900490149024903490449054906490749084909491049114912491349144915491649174918491949204921492249234924492549264927492849294930493149324933493449354936493749384939494049414942494349444945494649474948494949504951495249534954495549564957495849594960496149624963496449654966496749684969497049714972497349744975497649774978497949804981498249834984498549864987498849894990499149924993499449954996499749984999500050015002500350045005500650075008500950105011501250135014501550165017501850195020502150225023502450255026502750285029503050315032503350345035503650375038503950405041504250435044504550465047504850495050505150525053505450555056505750585059506050615062506350645065506650675068506950705071507250735074507550765077507850795080508150825083508450855086508750885089509050915092509350945095509650975098509951005101510251035104510551065107510851095110511151125113511451155116511751185119512051215122512351245125512651275128512951305131513251335134513551365137513851395140514151425143514451455146514751485149515051515152515351545155515651575158515951605161516251635164516551665167516851695170517151725173517451755176517751785179518051815182518351845185518651875188518951905191519251935194519551965197519851995200520152025203520452055206520752085209521052115212521352145215521652175218521952205221522252235224522552265227522852295230523152325233523452355236523752385239524052415242524352445245524652475248524952505251525252535254525552565257525852595260526152625263526452655266526752685269527052715272527352745275527652775278527952805281528252835284528552865287528852895290529152925293529452955296529752985299530053015302530353045305530653075308530953105311531253135314531553165317531853195320532153225323532453255326532753285329533053315332533353345335533653375338533953405341534253435344534553465347534853495350535153525353535453555356535753585359536053615362536353645365536653675368536953705371537253735374537553765377537853795380538153825383538453855386538753885389539053915392539353945395539653975398539954005401540254035404540554065407540854095410541154125413541454155416541754185419542054215422542354245425542654275428542954305431543254335434543554365437543854395440544154425443544454455446544754485449545054515452545354545455545654575458545954605461546254635464546554665467546854695470547154725473547454755476547754785479548054815482548354845485548654875488548954905491549254935494549554965497549854995500550155025503550455055506550755085509551055115512551355145515551655175518551955205521552255235524552555265527552855295530553155325533553455355536553755385539554055415542554355445545554655475548554955505551555255535554555555565557555855595560556155625563556455655566556755685569557055715572557355745575557655775578557955805581558255835584558555865587558855895590559155925593559455955596559755985599560056015602560356045605560656075608560956105611561256135614561556165617561856195620562156225623562456255626562756285629563056315632563356345635563656375638563956405641564256435644564556465647564856495650565156525653565456555656565756585659566056615662566356645665566656675668566956705671567256735674567556765677567856795680568156825683568456855686568756885689569056915692569356945695569656975698569957005701570257035704570557065707570857095710571157125713571457155716571757185719572057215722572357245725572657275728572957305731573257335734573557365737573857395740574157425743574457455746574757485749575057515752575357545755575657575758575957605761576257635764576557665767576857695770577157725773577457755776577757785779578057815782578357845785578657875788578957905791579257935794579557965797579857995800580158025803580458055806580758085809581058115812581358145815581658175818581958205821582258235824582558265827582858295830583158325833583458355836583758385839584058415842584358445845584658475848584958505851585258535854585558565857585858595860586158625863586458655866586758685869587058715872587358745875587658775878587958805881588258835884588558865887588858895890589158925893589458955896589758985899590059015902590359045905590659075908590959105911591259135914591559165917591859195920592159225923592459255926592759285929593059315932593359345935593659375938593959405941594259435944594559465947594859495950595159525953595459555956595759585959596059615962596359645965596659675968596959705971597259735974597559765977597859795980598159825983598459855986598759885989599059915992599359945995599659975998599960006001600260036004600560066007600860096010601160126013601460156016601760186019602060216022602360246025602660276028602960306031603260336034603560366037603860396040604160426043604460456046604760486049605060516052605360546055605660576058605960606061606260636064606560666067606860696070607160726073607460756076607760786079608060816082608360846085608660876088608960906091609260936094609560966097609860996100610161026103610461056106610761086109611061116112611361146115611661176118611961206121612261236124612561266127612861296130613161326133613461356136613761386139614061416142614361446145614661476148614961506151615261536154615561566157615861596160616161626163616461656166616761686169617061716172617361746175617661776178617961806181618261836184618561866187618861896190619161926193619461956196619761986199620062016202620362046205620662076208620962106211621262136214621562166217621862196220622162226223622462256226622762286229623062316232623362346235623662376238623962406241624262436244624562466247624862496250625162526253625462556256625762586259626062616262626362646265626662676268626962706271627262736274627562766277627862796280628162826283628462856286628762886289629062916292629362946295629662976298629963006301630263036304630563066307630863096310631163126313631463156316631763186319632063216322632363246325632663276328632963306331633263336334633563366337633863396340634163426343634463456346634763486349635063516352635363546355635663576358635963606361636263636364636563666367636863696370637163726373637463756376637763786379638063816382638363846385638663876388638963906391639263936394639563966397639863996400640164026403640464056406640764086409641064116412641364146415641664176418641964206421642264236424642564266427642864296430643164326433643464356436643764386439644064416442644364446445644664476448644964506451645264536454645564566457645864596460646164626463646464656466646764686469647064716472647364746475647664776478647964806481648264836484648564866487648864896490649164926493649464956496649764986499650065016502650365046505650665076508650965106511651265136514651565166517651865196520652165226523652465256526652765286529653065316532653365346535653665376538653965406541654265436544654565466547654865496550655165526553655465556556655765586559656065616562656365646565656665676568656965706571657265736574657565766577657865796580658165826583658465856586658765886589659065916592659365946595659665976598659966006601660266036604660566066607660866096610661166126613661466156616661766186619662066216622662366246625662666276628662966306631663266336634663566366637663866396640664166426643664466456646664766486649665066516652665366546655665666576658665966606661666266636664666566666667666866696670667166726673667466756676667766786679668066816682668366846685668666876688668966906691669266936694669566966697669866996700670167026703670467056706670767086709671067116712671367146715671667176718671967206721672267236724672567266727672867296730673167326733673467356736673767386739674067416742674367446745674667476748674967506751675267536754675567566757675867596760676167626763676467656766676767686769677067716772677367746775677667776778677967806781678267836784678567866787678867896790679167926793679467956796679767986799680068016802680368046805680668076808680968106811681268136814681568166817681868196820682168226823682468256826682768286829683068316832683368346835683668376838683968406841684268436844684568466847684868496850685168526853685468556856685768586859686068616862686368646865686668676868686968706871687268736874687568766877687868796880688168826883688468856886688768886889689068916892689368946895689668976898689969006901690269036904690569066907690869096910691169126913691469156916691769186919692069216922692369246925692669276928692969306931693269336934693569366937693869396940694169426943694469456946694769486949695069516952695369546955695669576958695969606961696269636964696569666967696869696970697169726973697469756976697769786979698069816982698369846985698669876988698969906991699269936994699569966997699869997000700170027003700470057006700770087009701070117012701370147015701670177018701970207021702270237024702570267027702870297030703170327033703470357036703770387039704070417042704370447045704670477048704970507051705270537054705570567057705870597060706170627063706470657066706770687069707070717072707370747075707670777078707970807081708270837084708570867087708870897090709170927093709470957096709770987099710071017102710371047105710671077108710971107111711271137114711571167117711871197120712171227123712471257126712771287129713071317132713371347135713671377138713971407141714271437144714571467147714871497150715171527153715471557156715771587159716071617162716371647165716671677168716971707171717271737174717571767177717871797180718171827183718471857186718771887189719071917192719371947195719671977198719972007201720272037204720572067207720872097210721172127213721472157216721772187219722072217222722372247225722672277228722972307231723272337234723572367237723872397240724172427243724472457246724772487249725072517252725372547255725672577258725972607261726272637264726572667267726872697270727172727273727472757276727772787279728072817282728372847285728672877288728972907291729272937294729572967297729872997300730173027303730473057306730773087309731073117312731373147315731673177318731973207321732273237324732573267327732873297330733173327333733473357336733773387339734073417342734373447345734673477348734973507351735273537354735573567357735873597360736173627363736473657366736773687369737073717372737373747375737673777378737973807381738273837384738573867387738873897390739173927393739473957396739773987399740074017402740374047405740674077408740974107411741274137414741574167417741874197420742174227423742474257426742774287429743074317432743374347435743674377438743974407441744274437444744574467447744874497450745174527453745474557456745774587459746074617462746374647465746674677468746974707471747274737474747574767477747874797480748174827483748474857486748774887489749074917492749374947495749674977498749975007501750275037504750575067507750875097510751175127513751475157516751775187519752075217522752375247525752675277528752975307531753275337534753575367537753875397540754175427543754475457546754775487549755075517552755375547555755675577558755975607561756275637564756575667567756875697570757175727573757475757576757775787579758075817582758375847585758675877588758975907591759275937594759575967597759875997600760176027603760476057606760776087609761076117612761376147615761676177618761976207621762276237624762576267627762876297630763176327633763476357636763776387639764076417642764376447645764676477648764976507651765276537654765576567657765876597660766176627663766476657666766776687669767076717672767376747675767676777678767976807681768276837684768576867687768876897690769176927693769476957696769776987699770077017702770377047705770677077708770977107711771277137714771577167717771877197720772177227723772477257726772777287729773077317732773377347735773677377738773977407741774277437744774577467747774877497750775177527753775477557756775777587759776077617762776377647765776677677768776977707771777277737774777577767777777877797780778177827783778477857786778777887789779077917792779377947795779677977798779978007801780278037804780578067807780878097810781178127813781478157816781778187819782078217822782378247825782678277828782978307831783278337834783578367837783878397840784178427843784478457846784778487849785078517852785378547855785678577858785978607861786278637864786578667867786878697870787178727873787478757876787778787879788078817882788378847885788678877888788978907891789278937894789578967897789878997900790179027903790479057906790779087909791079117912791379147915791679177918791979207921792279237924792579267927792879297930793179327933793479357936793779387939794079417942794379447945794679477948794979507951795279537954795579567957795879597960796179627963796479657966796779687969797079717972797379747975797679777978797979807981798279837984798579867987798879897990799179927993799479957996799779987999800080018002800380048005800680078008800980108011801280138014801580168017801880198020802180228023802480258026802780288029803080318032803380348035803680378038803980408041804280438044804580468047804880498050805180528053805480558056805780588059806080618062806380648065806680678068806980708071807280738074807580768077807880798080808180828083808480858086808780888089809080918092809380948095809680978098809981008101810281038104810581068107810881098110811181128113811481158116811781188119812081218122812381248125812681278128812981308131813281338134813581368137813881398140814181428143814481458146814781488149815081518152815381548155815681578158815981608161816281638164816581668167816881698170817181728173817481758176817781788179818081818182818381848185818681878188818981908191819281938194819581968197819881998200820182028203820482058206820782088209821082118212821382148215821682178218821982208221822282238224822582268227822882298230823182328233823482358236823782388239824082418242824382448245824682478248824982508251825282538254825582568257825882598260826182628263826482658266826782688269827082718272827382748275827682778278827982808281828282838284828582868287828882898290829182928293829482958296829782988299830083018302830383048305830683078308830983108311831283138314831583168317831883198320832183228323832483258326832783288329833083318332833383348335833683378338833983408341834283438344834583468347834883498350835183528353835483558356835783588359836083618362836383648365836683678368836983708371837283738374837583768377837883798380838183828383838483858386838783888389839083918392839383948395839683978398839984008401840284038404840584068407840884098410841184128413841484158416841784188419842084218422842384248425842684278428842984308431843284338434843584368437843884398440844184428443844484458446844784488449845084518452845384548455845684578458845984608461846284638464846584668467846884698470847184728473847484758476847784788479848084818482848384848485848684878488848984908491849284938494849584968497849884998500850185028503850485058506850785088509851085118512851385148515851685178518851985208521852285238524852585268527852885298530853185328533853485358536853785388539854085418542854385448545854685478548854985508551855285538554855585568557855885598560856185628563856485658566856785688569857085718572857385748575857685778578857985808581858285838584858585868587858885898590859185928593859485958596859785988599860086018602860386048605860686078608860986108611861286138614861586168617861886198620862186228623862486258626862786288629863086318632863386348635863686378638863986408641864286438644864586468647864886498650865186528653865486558656865786588659866086618662866386648665866686678668866986708671867286738674867586768677867886798680868186828683868486858686868786888689869086918692869386948695869686978698869987008701870287038704870587068707870887098710871187128713871487158716871787188719872087218722872387248725872687278728872987308731873287338734873587368737873887398740874187428743874487458746874787488749875087518752875387548755875687578758875987608761876287638764876587668767876887698770877187728773877487758776877787788779878087818782878387848785878687878788878987908791879287938794879587968797879887998800880188028803880488058806880788088809881088118812881388148815881688178818881988208821882288238824882588268827882888298830883188328833883488358836883788388839884088418842884388448845884688478848884988508851885288538854885588568857885888598860886188628863886488658866886788688869887088718872887388748875887688778878887988808881888288838884888588868887888888898890889188928893889488958896889788988899890089018902890389048905890689078908890989108911891289138914891589168917891889198920892189228923892489258926892789288929893089318932893389348935893689378938893989408941894289438944894589468947894889498950895189528953895489558956895789588959896089618962896389648965896689678968896989708971897289738974897589768977897889798980898189828983898489858986898789888989899089918992899389948995899689978998899990009001900290039004900590069007900890099010901190129013901490159016901790189019902090219022902390249025902690279028902990309031903290339034903590369037903890399040904190429043904490459046904790489049905090519052905390549055905690579058905990609061906290639064906590669067906890699070907190729073907490759076907790789079908090819082908390849085908690879088908990909091909290939094909590969097909890999100910191029103910491059106910791089109911091119112911391149115911691179118911991209121912291239124912591269127912891299130913191329133913491359136913791389139914091419142914391449145914691479148914991509151915291539154915591569157915891599160916191629163916491659166916791689169917091719172917391749175917691779178917991809181918291839184918591869187918891899190919191929193919491959196919791989199920092019202920392049205920692079208920992109211921292139214921592169217921892199220922192229223922492259226922792289229923092319232923392349235923692379238923992409241924292439244924592469247924892499250925192529253925492559256925792589259926092619262926392649265926692679268926992709271927292739274927592769277927892799280928192829283928492859286928792889289929092919292929392949295929692979298929993009301930293039304930593069307930893099310931193129313931493159316931793189319932093219322932393249325932693279328932993309331933293339334933593369337933893399340934193429343934493459346934793489349935093519352935393549355935693579358935993609361936293639364936593669367936893699370937193729373937493759376937793789379938093819382938393849385938693879388938993909391939293939394939593969397939893999400940194029403940494059406940794089409941094119412941394149415941694179418941994209421942294239424942594269427942894299430943194329433943494359436943794389439944094419442944394449445944694479448944994509451945294539454945594569457945894599460946194629463946494659466946794689469947094719472947394749475947694779478947994809481948294839484948594869487948894899490949194929493949494959496949794989499950095019502950395049505950695079508950995109511951295139514951595169517951895199520952195229523952495259526952795289529953095319532953395349535953695379538953995409541954295439544954595469547954895499550955195529553955495559556955795589559956095619562956395649565956695679568956995709571957295739574957595769577957895799580958195829583958495859586958795889589959095919592959395949595959695979598959996009601960296039604960596069607960896099610961196129613961496159616961796189619962096219622962396249625962696279628962996309631963296339634963596369637963896399640964196429643964496459646964796489649965096519652965396549655965696579658965996609661966296639664966596669667966896699670967196729673967496759676967796789679968096819682968396849685968696879688968996909691969296939694969596969697969896999700970197029703970497059706970797089709971097119712971397149715971697179718971997209721972297239724972597269727972897299730973197329733973497359736973797389739974097419742974397449745974697479748974997509751975297539754975597569757975897599760976197629763976497659766976797689769977097719772977397749775977697779778977997809781978297839784978597869787978897899790979197929793979497959796979797989799980098019802980398049805980698079808980998109811981298139814981598169817981898199820982198229823982498259826982798289829983098319832983398349835983698379838983998409841984298439844984598469847984898499850985198529853985498559856985798589859986098619862986398649865986698679868986998709871987298739874987598769877987898799880988198829883988498859886988798889889989098919892989398949895989698979898989999009901990299039904990599069907990899099910991199129913991499159916991799189919992099219922992399249925992699279928992999309931993299339934993599369937993899399940994199429943994499459946994799489949995099519952995399549955995699579958995999609961996299639964996599669967996899699970997199729973997499759976997799789979998099819982998399849985998699879988998999909991999299939994999599969997999899991000010001100021000310004100051000610007100081000910010100111001210013100141001510016100171001810019100201002110022100231002410025100261002710028100291003010031100321003310034100351003610037100381003910040100411004210043100441004510046100471004810049100501005110052100531005410055100561005710058100591006010061100621006310064100651006610067100681006910070100711007210073100741007510076100771007810079100801008110082100831008410085100861008710088100891009010091100921009310094100951009610097100981009910100101011010210103101041010510106101071010810109101101011110112101131011410115101161011710118101191012010121101221012310124101251012610127101281012910130101311013210133101341013510136101371013810139101401014110142101431014410145101461014710148101491015010151101521015310154101551015610157101581015910160101611016210163101641016510166101671016810169101701017110172101731017410175101761017710178101791018010181101821018310184101851018610187101881018910190101911019210193101941019510196101971019810199102001020110202102031020410205102061020710208102091021010211102121021310214102151021610217102181021910220102211022210223102241022510226102271022810229102301023110232102331023410235102361023710238102391024010241102421024310244102451024610247102481024910250102511025210253102541025510256102571025810259102601026110262102631026410265102661026710268102691027010271102721027310274102751027610277102781027910280102811028210283102841028510286102871028810289102901029110292102931029410295102961029710298102991030010301103021030310304103051030610307103081030910310103111031210313103141031510316103171031810319103201032110322103231032410325103261032710328103291033010331103321033310334103351033610337103381033910340103411034210343103441034510346103471034810349103501035110352103531035410355103561035710358103591036010361103621036310364103651036610367103681036910370103711037210373103741037510376103771037810379103801038110382103831038410385103861038710388103891039010391103921039310394103951039610397103981039910400104011040210403104041040510406104071040810409104101041110412104131041410415104161041710418104191042010421104221042310424104251042610427104281042910430104311043210433104341043510436104371043810439104401044110442104431044410445104461044710448104491045010451104521045310454104551045610457104581045910460104611046210463104641046510466104671046810469104701047110472104731047410475104761047710478104791048010481104821048310484104851048610487104881048910490104911049210493104941049510496104971049810499105001050110502105031050410505105061050710508105091051010511105121051310514105151051610517105181051910520105211052210523105241052510526105271052810529105301053110532105331053410535105361053710538105391054010541105421054310544105451054610547105481054910550105511055210553105541055510556105571055810559105601056110562105631056410565105661056710568105691057010571105721057310574105751057610577105781057910580105811058210583105841058510586105871058810589105901059110592105931059410595105961059710598105991060010601106021060310604106051060610607106081060910610106111061210613106141061510616106171061810619106201062110622106231062410625106261062710628106291063010631106321063310634106351063610637106381063910640106411064210643106441064510646106471064810649106501065110652106531065410655106561065710658106591066010661106621066310664106651066610667106681066910670106711067210673106741067510676106771067810679106801068110682106831068410685106861068710688106891069010691106921069310694106951069610697106981069910700107011070210703107041070510706107071070810709107101071110712107131071410715107161071710718107191072010721107221072310724107251072610727107281072910730107311073210733107341073510736107371073810739107401074110742107431074410745107461074710748107491075010751107521075310754107551075610757107581075910760107611076210763107641076510766107671076810769107701077110772107731077410775107761077710778107791078010781107821078310784107851078610787107881078910790107911079210793107941079510796107971079810799108001080110802108031080410805108061080710808108091081010811108121081310814108151081610817108181081910820108211082210823108241082510826108271082810829108301083110832108331083410835108361083710838108391084010841108421084310844108451084610847108481084910850108511085210853108541085510856108571085810859108601086110862108631086410865108661086710868108691087010871108721087310874108751087610877108781087910880108811088210883108841088510886108871088810889108901089110892108931089410895108961089710898108991090010901109021090310904109051090610907109081090910910109111091210913109141091510916109171091810919109201092110922109231092410925109261092710928109291093010931109321093310934109351093610937109381093910940109411094210943109441094510946109471094810949109501095110952109531095410955109561095710958109591096010961109621096310964109651096610967109681096910970109711097210973109741097510976109771097810979109801098110982109831098410985109861098710988109891099010991109921099310994109951099610997109981099911000110011100211003110041100511006110071100811009110101101111012110131101411015110161101711018110191102011021110221102311024110251102611027110281102911030110311103211033110341103511036110371103811039110401104111042110431104411045110461104711048110491105011051110521105311054110551105611057110581105911060110611106211063110641106511066110671106811069110701107111072110731107411075110761107711078110791108011081110821108311084110851108611087110881108911090110911109211093110941109511096110971109811099111001110111102111031110411105111061110711108111091111011111111121111311114111151111611117111181111911120111211112211123111241112511126111271112811129111301113111132111331113411135111361113711138111391114011141111421114311144111451114611147111481114911150111511115211153111541115511156111571115811159111601116111162111631116411165111661116711168111691117011171111721117311174111751117611177111781117911180111811118211183111841118511186111871118811189111901119111192111931119411195111961119711198111991120011201112021120311204112051120611207112081120911210112111121211213112141121511216112171121811219112201122111222112231122411225112261122711228112291123011231112321123311234112351123611237112381123911240112411124211243112441124511246112471124811249112501125111252112531125411255112561125711258112591126011261112621126311264112651126611267112681126911270112711127211273112741127511276112771127811279112801128111282112831128411285112861128711288112891129011291112921129311294112951129611297112981129911300113011130211303113041130511306113071130811309113101131111312113131131411315113161131711318113191132011321113221132311324113251132611327113281132911330113311133211333113341133511336113371133811339113401134111342113431134411345113461134711348113491135011351113521135311354113551135611357113581135911360113611136211363113641136511366113671136811369113701137111372113731137411375113761137711378113791138011381113821138311384113851138611387113881138911390113911139211393113941139511396113971139811399114001140111402114031140411405114061140711408114091141011411114121141311414114151141611417114181141911420114211142211423114241142511426114271142811429114301143111432114331143411435114361143711438114391144011441114421144311444114451144611447114481144911450114511145211453114541145511456114571145811459114601146111462114631146411465114661146711468114691147011471114721147311474114751147611477114781147911480114811148211483114841148511486114871148811489114901149111492114931149411495114961149711498114991150011501115021150311504115051150611507115081150911510115111151211513115141151511516115171151811519115201152111522115231152411525115261152711528115291153011531115321153311534115351153611537115381153911540115411154211543115441154511546115471154811549115501155111552115531155411555115561155711558115591156011561115621156311564115651156611567115681156911570115711157211573115741157511576115771157811579115801158111582115831158411585115861158711588115891159011591115921159311594115951159611597115981159911600116011160211603116041160511606116071160811609116101161111612116131161411615116161161711618116191162011621116221162311624116251162611627116281162911630116311163211633116341163511636116371163811639116401164111642116431164411645116461164711648116491165011651116521165311654116551165611657116581165911660116611166211663116641166511666116671166811669116701167111672116731167411675116761167711678116791168011681116821168311684116851168611687116881168911690116911169211693116941169511696116971169811699117001170111702117031170411705117061170711708117091171011711117121171311714117151171611717117181171911720117211172211723117241172511726117271172811729117301173111732117331173411735117361173711738117391174011741117421174311744117451174611747117481174911750117511175211753117541175511756117571175811759117601176111762117631176411765117661176711768117691177011771117721177311774117751177611777117781177911780117811178211783117841178511786117871178811789117901179111792117931179411795117961179711798117991180011801118021180311804118051180611807118081180911810118111181211813118141181511816118171181811819118201182111822118231182411825118261182711828118291183011831118321183311834118351183611837118381183911840118411184211843118441184511846118471184811849118501185111852118531185411855118561185711858118591186011861118621186311864118651186611867118681186911870118711187211873118741187511876118771187811879118801188111882118831188411885118861188711888118891189011891118921189311894118951189611897118981189911900119011190211903119041190511906119071190811909119101191111912119131191411915119161191711918119191192011921119221192311924119251192611927119281192911930119311193211933119341193511936119371193811939119401194111942119431194411945119461194711948119491195011951119521195311954119551195611957119581195911960119611196211963119641196511966119671196811969119701197111972119731197411975119761197711978119791198011981119821198311984119851198611987119881198911990119911199211993119941199511996119971199811999120001200112002120031200412005120061200712008120091201012011120121201312014120151201612017120181201912020120211202212023120241202512026120271202812029120301203112032120331203412035120361203712038120391204012041120421204312044120451204612047120481204912050120511205212053120541205512056120571205812059120601206112062120631206412065120661206712068120691207012071120721207312074120751207612077120781207912080120811208212083120841208512086120871208812089120901209112092120931209412095120961209712098120991210012101121021210312104121051210612107121081210912110121111211212113121141211512116121171211812119121201212112122121231212412125121261212712128121291213012131121321213312134121351213612137121381213912140121411214212143121441214512146121471214812149121501215112152121531215412155121561215712158121591216012161121621216312164121651216612167121681216912170121711217212173121741217512176121771217812179121801218112182121831218412185121861218712188121891219012191121921219312194121951219612197121981219912200122011220212203122041220512206122071220812209122101221112212122131221412215122161221712218122191222012221122221222312224122251222612227122281222912230122311223212233122341223512236122371223812239122401224112242122431224412245122461224712248122491225012251122521225312254122551225612257122581225912260122611226212263122641226512266122671226812269122701227112272122731227412275122761227712278122791228012281122821228312284122851228612287122881228912290122911229212293122941229512296122971229812299123001230112302123031230412305123061230712308123091231012311123121231312314123151231612317123181231912320123211232212323123241232512326123271232812329123301233112332123331233412335123361233712338123391234012341123421234312344123451234612347123481234912350123511235212353123541235512356123571235812359123601236112362123631236412365123661236712368123691237012371123721237312374123751237612377123781237912380123811238212383123841238512386123871238812389123901239112392123931239412395123961239712398123991240012401124021240312404124051240612407124081240912410124111241212413124141241512416124171241812419124201242112422124231242412425124261242712428124291243012431124321243312434124351243612437124381243912440124411244212443124441244512446124471244812449124501245112452124531245412455124561245712458124591246012461124621246312464124651246612467124681246912470124711247212473124741247512476124771247812479124801248112482124831248412485124861248712488124891249012491124921249312494124951249612497124981249912500125011250212503125041250512506125071250812509125101251112512125131251412515125161251712518125191252012521125221252312524125251252612527125281252912530125311253212533125341253512536125371253812539125401254112542125431254412545125461254712548125491255012551125521255312554125551255612557125581255912560125611256212563125641256512566125671256812569125701257112572125731257412575125761257712578125791258012581125821258312584125851258612587125881258912590125911259212593125941259512596125971259812599126001260112602126031260412605126061260712608126091261012611126121261312614126151261612617126181261912620126211262212623126241262512626126271262812629126301263112632126331263412635126361263712638126391264012641126421264312644126451264612647126481264912650126511265212653126541265512656126571265812659126601266112662126631266412665126661266712668126691267012671126721267312674126751267612677126781267912680126811268212683126841268512686126871268812689126901269112692126931269412695126961269712698126991270012701127021270312704127051270612707127081270912710127111271212713127141271512716127171271812719127201272112722127231272412725127261272712728127291273012731127321273312734127351273612737127381273912740127411274212743127441274512746127471274812749127501275112752127531275412755127561275712758127591276012761127621276312764127651276612767127681276912770127711277212773127741277512776127771277812779127801278112782127831278412785127861278712788127891279012791127921279312794127951279612797127981279912800128011280212803128041280512806128071280812809128101281112812128131281412815128161281712818128191282012821128221282312824128251282612827128281282912830128311283212833128341283512836128371283812839128401284112842128431284412845128461284712848128491285012851128521285312854128551285612857128581285912860128611286212863128641286512866128671286812869128701287112872128731287412875128761287712878128791288012881128821288312884128851288612887128881288912890128911289212893128941289512896128971289812899129001290112902129031290412905129061290712908129091291012911129121291312914129151291612917129181291912920129211292212923129241292512926129271292812929129301293112932129331293412935129361293712938129391294012941129421294312944129451294612947129481294912950129511295212953129541295512956129571295812959129601296112962129631296412965129661296712968129691297012971129721297312974129751297612977129781297912980129811298212983129841298512986129871298812989129901299112992129931299412995129961299712998129991300013001130021300313004130051300613007130081300913010130111301213013130141301513016130171301813019130201302113022130231302413025130261302713028130291303013031130321303313034130351303613037130381303913040130411304213043130441304513046130471304813049130501305113052130531305413055130561305713058130591306013061130621306313064130651306613067130681306913070130711307213073130741307513076130771307813079130801308113082130831308413085130861308713088130891309013091130921309313094130951309613097130981309913100131011310213103131041310513106131071310813109131101311113112131131311413115131161311713118131191312013121131221312313124131251312613127131281312913130131311313213133131341313513136131371313813139131401314113142131431314413145131461314713148131491315013151131521315313154131551315613157131581315913160131611316213163131641316513166131671316813169131701317113172131731317413175131761317713178131791318013181131821318313184131851318613187131881318913190131911319213193131941319513196131971319813199132001320113202132031320413205132061320713208132091321013211132121321313214132151321613217132181321913220132211322213223132241322513226132271322813229132301323113232132331323413235132361323713238132391324013241132421324313244132451324613247132481324913250132511325213253132541325513256132571325813259132601326113262132631326413265132661326713268132691327013271132721327313274132751327613277132781327913280132811328213283132841328513286132871328813289132901329113292132931329413295132961329713298132991330013301133021330313304133051330613307133081330913310133111331213313133141331513316133171331813319133201332113322133231332413325133261332713328133291333013331133321333313334133351333613337133381333913340133411334213343133441334513346133471334813349133501335113352133531335413355133561335713358133591336013361133621336313364133651336613367133681336913370133711337213373133741337513376133771337813379133801338113382133831338413385133861338713388133891339013391133921339313394133951339613397133981339913400134011340213403134041340513406134071340813409134101341113412134131341413415134161341713418134191342013421134221342313424134251342613427134281342913430134311343213433134341343513436134371343813439134401344113442134431344413445134461344713448134491345013451134521345313454134551345613457134581345913460134611346213463134641346513466134671346813469134701347113472134731347413475134761347713478134791348013481134821348313484134851348613487134881348913490134911349213493134941349513496134971349813499135001350113502135031350413505135061350713508135091351013511135121351313514135151351613517135181351913520135211352213523135241352513526135271352813529135301353113532135331353413535135361353713538135391354013541135421354313544135451354613547135481354913550135511355213553135541355513556135571355813559135601356113562135631356413565135661356713568135691357013571135721357313574135751357613577135781357913580135811358213583135841358513586135871358813589135901359113592135931359413595135961359713598135991360013601136021360313604136051360613607136081360913610136111361213613136141361513616136171361813619136201362113622136231362413625136261362713628136291363013631136321363313634136351363613637136381363913640136411364213643136441364513646136471364813649136501365113652136531365413655136561365713658136591366013661136621366313664136651366613667136681366913670136711367213673136741367513676136771367813679136801368113682136831368413685136861368713688136891369013691136921369313694136951369613697136981369913700137011370213703137041370513706137071370813709137101371113712137131371413715137161371713718137191372013721137221372313724137251372613727137281372913730137311373213733137341373513736137371373813739137401374113742137431374413745137461374713748137491375013751137521375313754137551375613757137581375913760137611376213763137641376513766137671376813769137701377113772137731377413775137761377713778137791378013781137821378313784137851378613787137881378913790137911379213793137941379513796137971379813799138001380113802138031380413805138061380713808 |
- <!DOCTYPE html>
- <html>
- <head><meta charset="utf-8" />
- <title>dog_app</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
- <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>
- <style type="text/css">
- /*!
- *
- * Twitter Bootstrap
- *
- */
- /*!
- * Bootstrap v3.3.7 (http://getbootstrap.com)
- * Copyright 2011-2016 Twitter, Inc.
- * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
- */
- /*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
- html {
- font-family: sans-serif;
- -ms-text-size-adjust: 100%;
- -webkit-text-size-adjust: 100%;
- }
- body {
- margin: 0;
- }
- article,
- aside,
- details,
- figcaption,
- figure,
- footer,
- header,
- hgroup,
- main,
- menu,
- nav,
- section,
- summary {
- display: block;
- }
- audio,
- canvas,
- progress,
- video {
- display: inline-block;
- vertical-align: baseline;
- }
- audio:not([controls]) {
- display: none;
- height: 0;
- }
- [hidden],
- template {
- display: none;
- }
- a {
- background-color: transparent;
- }
- a:active,
- a:hover {
- outline: 0;
- }
- abbr[title] {
- border-bottom: 1px dotted;
- }
- b,
- strong {
- font-weight: bold;
- }
- dfn {
- font-style: italic;
- }
- h1 {
- font-size: 2em;
- margin: 0.67em 0;
- }
- mark {
- background: #ff0;
- color: #000;
- }
- small {
- font-size: 80%;
- }
- sub,
- sup {
- font-size: 75%;
- line-height: 0;
- position: relative;
- vertical-align: baseline;
- }
- sup {
- top: -0.5em;
- }
- sub {
- bottom: -0.25em;
- }
- img {
- border: 0;
- }
- svg:not(:root) {
- overflow: hidden;
- }
- figure {
- margin: 1em 40px;
- }
- hr {
- box-sizing: content-box;
- height: 0;
- }
- pre {
- overflow: auto;
- }
- code,
- kbd,
- pre,
- samp {
- font-family: monospace, monospace;
- font-size: 1em;
- }
- button,
- input,
- optgroup,
- select,
- textarea {
- color: inherit;
- font: inherit;
- margin: 0;
- }
- button {
- overflow: visible;
- }
- button,
- select {
- text-transform: none;
- }
- button,
- html input[type="button"],
- input[type="reset"],
- input[type="submit"] {
- -webkit-appearance: button;
- cursor: pointer;
- }
- button[disabled],
- html input[disabled] {
- cursor: default;
- }
- button::-moz-focus-inner,
- input::-moz-focus-inner {
- border: 0;
- padding: 0;
- }
- input {
- line-height: normal;
- }
- input[type="checkbox"],
- input[type="radio"] {
- box-sizing: border-box;
- padding: 0;
- }
- input[type="number"]::-webkit-inner-spin-button,
- input[type="number"]::-webkit-outer-spin-button {
- height: auto;
- }
- input[type="search"] {
- -webkit-appearance: textfield;
- box-sizing: content-box;
- }
- input[type="search"]::-webkit-search-cancel-button,
- input[type="search"]::-webkit-search-decoration {
- -webkit-appearance: none;
- }
- fieldset {
- border: 1px solid #c0c0c0;
- margin: 0 2px;
- padding: 0.35em 0.625em 0.75em;
- }
- legend {
- border: 0;
- padding: 0;
- }
- textarea {
- overflow: auto;
- }
- optgroup {
- font-weight: bold;
- }
- table {
- border-collapse: collapse;
- border-spacing: 0;
- }
- td,
- th {
- padding: 0;
- }
- /*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
- @media print {
- *,
- *:before,
- *:after {
- background: transparent !important;
- color: #000 !important;
- box-shadow: none !important;
- text-shadow: none !important;
- }
- a,
- a:visited {
- text-decoration: underline;
- }
- a[href]:after {
- content: " (" attr(href) ")";
- }
- abbr[title]:after {
- content: " (" attr(title) ")";
- }
- a[href^="#"]:after,
- a[href^="javascript:"]:after {
- content: "";
- }
- pre,
- blockquote {
- border: 1px solid #999;
- page-break-inside: avoid;
- }
- thead {
- display: table-header-group;
- }
- tr,
- img {
- page-break-inside: avoid;
- }
- img {
- max-width: 100% !important;
- }
- p,
- h2,
- h3 {
- orphans: 3;
- widows: 3;
- }
- h2,
- h3 {
- page-break-after: avoid;
- }
- .navbar {
- display: none;
- }
- .btn > .caret,
- .dropup > .btn > .caret {
- border-top-color: #000 !important;
- }
- .label {
- border: 1px solid #000;
- }
- .table {
- border-collapse: collapse !important;
- }
- .table td,
- .table th {
- background-color: #fff !important;
- }
- .table-bordered th,
- .table-bordered td {
- border: 1px solid #ddd !important;
- }
- }
- @font-face {
- font-family: 'Glyphicons Halflings';
- src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
- src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
- }
- .glyphicon {
- position: relative;
- top: 1px;
- display: inline-block;
- font-family: 'Glyphicons Halflings';
- font-style: normal;
- font-weight: normal;
- line-height: 1;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- }
- .glyphicon-asterisk:before {
- content: "\002a";
- }
- .glyphicon-plus:before {
- content: "\002b";
- }
- .glyphicon-euro:before,
- .glyphicon-eur:before {
- content: "\20ac";
- }
- .glyphicon-minus:before {
- content: "\2212";
- }
- .glyphicon-cloud:before {
- content: "\2601";
- }
- .glyphicon-envelope:before {
- content: "\2709";
- }
- .glyphicon-pencil:before {
- content: "\270f";
- }
- .glyphicon-glass:before {
- content: "\e001";
- }
- .glyphicon-music:before {
- content: "\e002";
- }
- .glyphicon-search:before {
- content: "\e003";
- }
- .glyphicon-heart:before {
- content: "\e005";
- }
- .glyphicon-star:before {
- content: "\e006";
- }
- .glyphicon-star-empty:before {
- content: "\e007";
- }
- .glyphicon-user:before {
- content: "\e008";
- }
- .glyphicon-film:before {
- content: "\e009";
- }
- .glyphicon-th-large:before {
- content: "\e010";
- }
- .glyphicon-th:before {
- content: "\e011";
- }
- .glyphicon-th-list:before {
- content: "\e012";
- }
- .glyphicon-ok:before {
- content: "\e013";
- }
- .glyphicon-remove:before {
- content: "\e014";
- }
- .glyphicon-zoom-in:before {
- content: "\e015";
- }
- .glyphicon-zoom-out:before {
- content: "\e016";
- }
- .glyphicon-off:before {
- content: "\e017";
- }
- .glyphicon-signal:before {
- content: "\e018";
- }
- .glyphicon-cog:before {
- content: "\e019";
- }
- .glyphicon-trash:before {
- content: "\e020";
- }
- .glyphicon-home:before {
- content: "\e021";
- }
- .glyphicon-file:before {
- content: "\e022";
- }
- .glyphicon-time:before {
- content: "\e023";
- }
- .glyphicon-road:before {
- content: "\e024";
- }
- .glyphicon-download-alt:before {
- content: "\e025";
- }
- .glyphicon-download:before {
- content: "\e026";
- }
- .glyphicon-upload:before {
- content: "\e027";
- }
- .glyphicon-inbox:before {
- content: "\e028";
- }
- .glyphicon-play-circle:before {
- content: "\e029";
- }
- .glyphicon-repeat:before {
- content: "\e030";
- }
- .glyphicon-refresh:before {
- content: "\e031";
- }
- .glyphicon-list-alt:before {
- content: "\e032";
- }
- .glyphicon-lock:before {
- content: "\e033";
- }
- .glyphicon-flag:before {
- content: "\e034";
- }
- .glyphicon-headphones:before {
- content: "\e035";
- }
- .glyphicon-volume-off:before {
- content: "\e036";
- }
- .glyphicon-volume-down:before {
- content: "\e037";
- }
- .glyphicon-volume-up:before {
- content: "\e038";
- }
- .glyphicon-qrcode:before {
- content: "\e039";
- }
- .glyphicon-barcode:before {
- content: "\e040";
- }
- .glyphicon-tag:before {
- content: "\e041";
- }
- .glyphicon-tags:before {
- content: "\e042";
- }
- .glyphicon-book:before {
- content: "\e043";
- }
- .glyphicon-bookmark:before {
- content: "\e044";
- }
- .glyphicon-print:before {
- content: "\e045";
- }
- .glyphicon-camera:before {
- content: "\e046";
- }
- .glyphicon-font:before {
- content: "\e047";
- }
- .glyphicon-bold:before {
- content: "\e048";
- }
- .glyphicon-italic:before {
- content: "\e049";
- }
- .glyphicon-text-height:before {
- content: "\e050";
- }
- .glyphicon-text-width:before {
- content: "\e051";
- }
- .glyphicon-align-left:before {
- content: "\e052";
- }
- .glyphicon-align-center:before {
- content: "\e053";
- }
- .glyphicon-align-right:before {
- content: "\e054";
- }
- .glyphicon-align-justify:before {
- content: "\e055";
- }
- .glyphicon-list:before {
- content: "\e056";
- }
- .glyphicon-indent-left:before {
- content: "\e057";
- }
- .glyphicon-indent-right:before {
- content: "\e058";
- }
- .glyphicon-facetime-video:before {
- content: "\e059";
- }
- .glyphicon-picture:before {
- content: "\e060";
- }
- .glyphicon-map-marker:before {
- content: "\e062";
- }
- .glyphicon-adjust:before {
- content: "\e063";
- }
- .glyphicon-tint:before {
- content: "\e064";
- }
- .glyphicon-edit:before {
- content: "\e065";
- }
- .glyphicon-share:before {
- content: "\e066";
- }
- .glyphicon-check:before {
- content: "\e067";
- }
- .glyphicon-move:before {
- content: "\e068";
- }
- .glyphicon-step-backward:before {
- content: "\e069";
- }
- .glyphicon-fast-backward:before {
- content: "\e070";
- }
- .glyphicon-backward:before {
- content: "\e071";
- }
- .glyphicon-play:before {
- content: "\e072";
- }
- .glyphicon-pause:before {
- content: "\e073";
- }
- .glyphicon-stop:before {
- content: "\e074";
- }
- .glyphicon-forward:before {
- content: "\e075";
- }
- .glyphicon-fast-forward:before {
- content: "\e076";
- }
- .glyphicon-step-forward:before {
- content: "\e077";
- }
- .glyphicon-eject:before {
- content: "\e078";
- }
- .glyphicon-chevron-left:before {
- content: "\e079";
- }
- .glyphicon-chevron-right:before {
- content: "\e080";
- }
- .glyphicon-plus-sign:before {
- content: "\e081";
- }
- .glyphicon-minus-sign:before {
- content: "\e082";
- }
- .glyphicon-remove-sign:before {
- content: "\e083";
- }
- .glyphicon-ok-sign:before {
- content: "\e084";
- }
- .glyphicon-question-sign:before {
- content: "\e085";
- }
- .glyphicon-info-sign:before {
- content: "\e086";
- }
- .glyphicon-screenshot:before {
- content: "\e087";
- }
- .glyphicon-remove-circle:before {
- content: "\e088";
- }
- .glyphicon-ok-circle:before {
- content: "\e089";
- }
- .glyphicon-ban-circle:before {
- content: "\e090";
- }
- .glyphicon-arrow-left:before {
- content: "\e091";
- }
- .glyphicon-arrow-right:before {
- content: "\e092";
- }
- .glyphicon-arrow-up:before {
- content: "\e093";
- }
- .glyphicon-arrow-down:before {
- content: "\e094";
- }
- .glyphicon-share-alt:before {
- content: "\e095";
- }
- .glyphicon-resize-full:before {
- content: "\e096";
- }
- .glyphicon-resize-small:before {
- content: "\e097";
- }
- .glyphicon-exclamation-sign:before {
- content: "\e101";
- }
- .glyphicon-gift:before {
- content: "\e102";
- }
- .glyphicon-leaf:before {
- content: "\e103";
- }
- .glyphicon-fire:before {
- content: "\e104";
- }
- .glyphicon-eye-open:before {
- content: "\e105";
- }
- .glyphicon-eye-close:before {
- content: "\e106";
- }
- .glyphicon-warning-sign:before {
- content: "\e107";
- }
- .glyphicon-plane:before {
- content: "\e108";
- }
- .glyphicon-calendar:before {
- content: "\e109";
- }
- .glyphicon-random:before {
- content: "\e110";
- }
- .glyphicon-comment:before {
- content: "\e111";
- }
- .glyphicon-magnet:before {
- content: "\e112";
- }
- .glyphicon-chevron-up:before {
- content: "\e113";
- }
- .glyphicon-chevron-down:before {
- content: "\e114";
- }
- .glyphicon-retweet:before {
- content: "\e115";
- }
- .glyphicon-shopping-cart:before {
- content: "\e116";
- }
- .glyphicon-folder-close:before {
- content: "\e117";
- }
- .glyphicon-folder-open:before {
- content: "\e118";
- }
- .glyphicon-resize-vertical:before {
- content: "\e119";
- }
- .glyphicon-resize-horizontal:before {
- content: "\e120";
- }
- .glyphicon-hdd:before {
- content: "\e121";
- }
- .glyphicon-bullhorn:before {
- content: "\e122";
- }
- .glyphicon-bell:before {
- content: "\e123";
- }
- .glyphicon-certificate:before {
- content: "\e124";
- }
- .glyphicon-thumbs-up:before {
- content: "\e125";
- }
- .glyphicon-thumbs-down:before {
- content: "\e126";
- }
- .glyphicon-hand-right:before {
- content: "\e127";
- }
- .glyphicon-hand-left:before {
- content: "\e128";
- }
- .glyphicon-hand-up:before {
- content: "\e129";
- }
- .glyphicon-hand-down:before {
- content: "\e130";
- }
- .glyphicon-circle-arrow-right:before {
- content: "\e131";
- }
- .glyphicon-circle-arrow-left:before {
- content: "\e132";
- }
- .glyphicon-circle-arrow-up:before {
- content: "\e133";
- }
- .glyphicon-circle-arrow-down:before {
- content: "\e134";
- }
- .glyphicon-globe:before {
- content: "\e135";
- }
- .glyphicon-wrench:before {
- content: "\e136";
- }
- .glyphicon-tasks:before {
- content: "\e137";
- }
- .glyphicon-filter:before {
- content: "\e138";
- }
- .glyphicon-briefcase:before {
- content: "\e139";
- }
- .glyphicon-fullscreen:before {
- content: "\e140";
- }
- .glyphicon-dashboard:before {
- content: "\e141";
- }
- .glyphicon-paperclip:before {
- content: "\e142";
- }
- .glyphicon-heart-empty:before {
- content: "\e143";
- }
- .glyphicon-link:before {
- content: "\e144";
- }
- .glyphicon-phone:before {
- content: "\e145";
- }
- .glyphicon-pushpin:before {
- content: "\e146";
- }
- .glyphicon-usd:before {
- content: "\e148";
- }
- .glyphicon-gbp:before {
- content: "\e149";
- }
- .glyphicon-sort:before {
- content: "\e150";
- }
- .glyphicon-sort-by-alphabet:before {
- content: "\e151";
- }
- .glyphicon-sort-by-alphabet-alt:before {
- content: "\e152";
- }
- .glyphicon-sort-by-order:before {
- content: "\e153";
- }
- .glyphicon-sort-by-order-alt:before {
- content: "\e154";
- }
- .glyphicon-sort-by-attributes:before {
- content: "\e155";
- }
- .glyphicon-sort-by-attributes-alt:before {
- content: "\e156";
- }
- .glyphicon-unchecked:before {
- content: "\e157";
- }
- .glyphicon-expand:before {
- content: "\e158";
- }
- .glyphicon-collapse-down:before {
- content: "\e159";
- }
- .glyphicon-collapse-up:before {
- content: "\e160";
- }
- .glyphicon-log-in:before {
- content: "\e161";
- }
- .glyphicon-flash:before {
- content: "\e162";
- }
- .glyphicon-log-out:before {
- content: "\e163";
- }
- .glyphicon-new-window:before {
- content: "\e164";
- }
- .glyphicon-record:before {
- content: "\e165";
- }
- .glyphicon-save:before {
- content: "\e166";
- }
- .glyphicon-open:before {
- content: "\e167";
- }
- .glyphicon-saved:before {
- content: "\e168";
- }
- .glyphicon-import:before {
- content: "\e169";
- }
- .glyphicon-export:before {
- content: "\e170";
- }
- .glyphicon-send:before {
- content: "\e171";
- }
- .glyphicon-floppy-disk:before {
- content: "\e172";
- }
- .glyphicon-floppy-saved:before {
- content: "\e173";
- }
- .glyphicon-floppy-remove:before {
- content: "\e174";
- }
- .glyphicon-floppy-save:before {
- content: "\e175";
- }
- .glyphicon-floppy-open:before {
- content: "\e176";
- }
- .glyphicon-credit-card:before {
- content: "\e177";
- }
- .glyphicon-transfer:before {
- content: "\e178";
- }
- .glyphicon-cutlery:before {
- content: "\e179";
- }
- .glyphicon-header:before {
- content: "\e180";
- }
- .glyphicon-compressed:before {
- content: "\e181";
- }
- .glyphicon-earphone:before {
- content: "\e182";
- }
- .glyphicon-phone-alt:before {
- content: "\e183";
- }
- .glyphicon-tower:before {
- content: "\e184";
- }
- .glyphicon-stats:before {
- content: "\e185";
- }
- .glyphicon-sd-video:before {
- content: "\e186";
- }
- .glyphicon-hd-video:before {
- content: "\e187";
- }
- .glyphicon-subtitles:before {
- content: "\e188";
- }
- .glyphicon-sound-stereo:before {
- content: "\e189";
- }
- .glyphicon-sound-dolby:before {
- content: "\e190";
- }
- .glyphicon-sound-5-1:before {
- content: "\e191";
- }
- .glyphicon-sound-6-1:before {
- content: "\e192";
- }
- .glyphicon-sound-7-1:before {
- content: "\e193";
- }
- .glyphicon-copyright-mark:before {
- content: "\e194";
- }
- .glyphicon-registration-mark:before {
- content: "\e195";
- }
- .glyphicon-cloud-download:before {
- content: "\e197";
- }
- .glyphicon-cloud-upload:before {
- content: "\e198";
- }
- .glyphicon-tree-conifer:before {
- content: "\e199";
- }
- .glyphicon-tree-deciduous:before {
- content: "\e200";
- }
- .glyphicon-cd:before {
- content: "\e201";
- }
- .glyphicon-save-file:before {
- content: "\e202";
- }
- .glyphicon-open-file:before {
- content: "\e203";
- }
- .glyphicon-level-up:before {
- content: "\e204";
- }
- .glyphicon-copy:before {
- content: "\e205";
- }
- .glyphicon-paste:before {
- content: "\e206";
- }
- .glyphicon-alert:before {
- content: "\e209";
- }
- .glyphicon-equalizer:before {
- content: "\e210";
- }
- .glyphicon-king:before {
- content: "\e211";
- }
- .glyphicon-queen:before {
- content: "\e212";
- }
- .glyphicon-pawn:before {
- content: "\e213";
- }
- .glyphicon-bishop:before {
- content: "\e214";
- }
- .glyphicon-knight:before {
- content: "\e215";
- }
- .glyphicon-baby-formula:before {
- content: "\e216";
- }
- .glyphicon-tent:before {
- content: "\26fa";
- }
- .glyphicon-blackboard:before {
- content: "\e218";
- }
- .glyphicon-bed:before {
- content: "\e219";
- }
- .glyphicon-apple:before {
- content: "\f8ff";
- }
- .glyphicon-erase:before {
- content: "\e221";
- }
- .glyphicon-hourglass:before {
- content: "\231b";
- }
- .glyphicon-lamp:before {
- content: "\e223";
- }
- .glyphicon-duplicate:before {
- content: "\e224";
- }
- .glyphicon-piggy-bank:before {
- content: "\e225";
- }
- .glyphicon-scissors:before {
- content: "\e226";
- }
- .glyphicon-bitcoin:before {
- content: "\e227";
- }
- .glyphicon-btc:before {
- content: "\e227";
- }
- .glyphicon-xbt:before {
- content: "\e227";
- }
- .glyphicon-yen:before {
- content: "\00a5";
- }
- .glyphicon-jpy:before {
- content: "\00a5";
- }
- .glyphicon-ruble:before {
- content: "\20bd";
- }
- .glyphicon-rub:before {
- content: "\20bd";
- }
- .glyphicon-scale:before {
- content: "\e230";
- }
- .glyphicon-ice-lolly:before {
- content: "\e231";
- }
- .glyphicon-ice-lolly-tasted:before {
- content: "\e232";
- }
- .glyphicon-education:before {
- content: "\e233";
- }
- .glyphicon-option-horizontal:before {
- content: "\e234";
- }
- .glyphicon-option-vertical:before {
- content: "\e235";
- }
- .glyphicon-menu-hamburger:before {
- content: "\e236";
- }
- .glyphicon-modal-window:before {
- content: "\e237";
- }
- .glyphicon-oil:before {
- content: "\e238";
- }
- .glyphicon-grain:before {
- content: "\e239";
- }
- .glyphicon-sunglasses:before {
- content: "\e240";
- }
- .glyphicon-text-size:before {
- content: "\e241";
- }
- .glyphicon-text-color:before {
- content: "\e242";
- }
- .glyphicon-text-background:before {
- content: "\e243";
- }
- .glyphicon-object-align-top:before {
- content: "\e244";
- }
- .glyphicon-object-align-bottom:before {
- content: "\e245";
- }
- .glyphicon-object-align-horizontal:before {
- content: "\e246";
- }
- .glyphicon-object-align-left:before {
- content: "\e247";
- }
- .glyphicon-object-align-vertical:before {
- content: "\e248";
- }
- .glyphicon-object-align-right:before {
- content: "\e249";
- }
- .glyphicon-triangle-right:before {
- content: "\e250";
- }
- .glyphicon-triangle-left:before {
- content: "\e251";
- }
- .glyphicon-triangle-bottom:before {
- content: "\e252";
- }
- .glyphicon-triangle-top:before {
- content: "\e253";
- }
- .glyphicon-console:before {
- content: "\e254";
- }
- .glyphicon-superscript:before {
- content: "\e255";
- }
- .glyphicon-subscript:before {
- content: "\e256";
- }
- .glyphicon-menu-left:before {
- content: "\e257";
- }
- .glyphicon-menu-right:before {
- content: "\e258";
- }
- .glyphicon-menu-down:before {
- content: "\e259";
- }
- .glyphicon-menu-up:before {
- content: "\e260";
- }
- * {
- -webkit-box-sizing: border-box;
- -moz-box-sizing: border-box;
- box-sizing: border-box;
- }
- *:before,
- *:after {
- -webkit-box-sizing: border-box;
- -moz-box-sizing: border-box;
- box-sizing: border-box;
- }
- html {
- font-size: 10px;
- -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
- }
- body {
- font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
- font-size: 13px;
- line-height: 1.42857143;
- color: #000;
- background-color: #fff;
- }
- input,
- button,
- select,
- textarea {
- font-family: inherit;
- font-size: inherit;
- line-height: inherit;
- }
- a {
- color: #337ab7;
- text-decoration: none;
- }
- a:hover,
- a:focus {
- color: #23527c;
- text-decoration: underline;
- }
- a:focus {
- outline: 5px auto -webkit-focus-ring-color;
- outline-offset: -2px;
- }
- figure {
- margin: 0;
- }
- img {
- vertical-align: middle;
- }
- .img-responsive,
- .thumbnail > img,
- .thumbnail a > img,
- .carousel-inner > .item > img,
- .carousel-inner > .item > a > img {
- display: block;
- max-width: 100%;
- height: auto;
- }
- .img-rounded {
- border-radius: 3px;
- }
- .img-thumbnail {
- padding: 4px;
- line-height: 1.42857143;
- background-color: #fff;
- border: 1px solid #ddd;
- border-radius: 2px;
- -webkit-transition: all 0.2s ease-in-out;
- -o-transition: all 0.2s ease-in-out;
- transition: all 0.2s ease-in-out;
- display: inline-block;
- max-width: 100%;
- height: auto;
- }
- .img-circle {
- border-radius: 50%;
- }
- hr {
- margin-top: 18px;
- margin-bottom: 18px;
- border: 0;
- border-top: 1px solid #eeeeee;
- }
- .sr-only {
- position: absolute;
- width: 1px;
- height: 1px;
- margin: -1px;
- padding: 0;
- overflow: hidden;
- clip: rect(0, 0, 0, 0);
- border: 0;
- }
- .sr-only-focusable:active,
- .sr-only-focusable:focus {
- position: static;
- width: auto;
- height: auto;
- margin: 0;
- overflow: visible;
- clip: auto;
- }
- [role="button"] {
- cursor: pointer;
- }
- h1,
- h2,
- h3,
- h4,
- h5,
- h6,
- .h1,
- .h2,
- .h3,
- .h4,
- .h5,
- .h6 {
- font-family: inherit;
- font-weight: 500;
- line-height: 1.1;
- color: inherit;
- }
- h1 small,
- h2 small,
- h3 small,
- h4 small,
- h5 small,
- h6 small,
- .h1 small,
- .h2 small,
- .h3 small,
- .h4 small,
- .h5 small,
- .h6 small,
- h1 .small,
- h2 .small,
- h3 .small,
- h4 .small,
- h5 .small,
- h6 .small,
- .h1 .small,
- .h2 .small,
- .h3 .small,
- .h4 .small,
- .h5 .small,
- .h6 .small {
- font-weight: normal;
- line-height: 1;
- color: #777777;
- }
- h1,
- .h1,
- h2,
- .h2,
- h3,
- .h3 {
- margin-top: 18px;
- margin-bottom: 9px;
- }
- h1 small,
- .h1 small,
- h2 small,
- .h2 small,
- h3 small,
- .h3 small,
- h1 .small,
- .h1 .small,
- h2 .small,
- .h2 .small,
- h3 .small,
- .h3 .small {
- font-size: 65%;
- }
- h4,
- .h4,
- h5,
- .h5,
- h6,
- .h6 {
- margin-top: 9px;
- margin-bottom: 9px;
- }
- h4 small,
- .h4 small,
- h5 small,
- .h5 small,
- h6 small,
- .h6 small,
- h4 .small,
- .h4 .small,
- h5 .small,
- .h5 .small,
- h6 .small,
- .h6 .small {
- font-size: 75%;
- }
- h1,
- .h1 {
- font-size: 33px;
- }
- h2,
- .h2 {
- font-size: 27px;
- }
- h3,
- .h3 {
- font-size: 23px;
- }
- h4,
- .h4 {
- font-size: 17px;
- }
- h5,
- .h5 {
- font-size: 13px;
- }
- h6,
- .h6 {
- font-size: 12px;
- }
- p {
- margin: 0 0 9px;
- }
- .lead {
- margin-bottom: 18px;
- font-size: 14px;
- font-weight: 300;
- line-height: 1.4;
- }
- @media (min-width: 768px) {
- .lead {
- font-size: 19.5px;
- }
- }
- small,
- .small {
- font-size: 92%;
- }
- mark,
- .mark {
- background-color: #fcf8e3;
- padding: .2em;
- }
- .text-left {
- text-align: left;
- }
- .text-right {
- text-align: right;
- }
- .text-center {
- text-align: center;
- }
- .text-justify {
- text-align: justify;
- }
- .text-nowrap {
- white-space: nowrap;
- }
- .text-lowercase {
- text-transform: lowercase;
- }
- .text-uppercase {
- text-transform: uppercase;
- }
- .text-capitalize {
- text-transform: capitalize;
- }
- .text-muted {
- color: #777777;
- }
- .text-primary {
- color: #337ab7;
- }
- a.text-primary:hover,
- a.text-primary:focus {
- color: #286090;
- }
- .text-success {
- color: #3c763d;
- }
- a.text-success:hover,
- a.text-success:focus {
- color: #2b542c;
- }
- .text-info {
- color: #31708f;
- }
- a.text-info:hover,
- a.text-info:focus {
- color: #245269;
- }
- .text-warning {
- color: #8a6d3b;
- }
- a.text-warning:hover,
- a.text-warning:focus {
- color: #66512c;
- }
- .text-danger {
- color: #a94442;
- }
- a.text-danger:hover,
- a.text-danger:focus {
- color: #843534;
- }
- .bg-primary {
- color: #fff;
- background-color: #337ab7;
- }
- a.bg-primary:hover,
- a.bg-primary:focus {
- background-color: #286090;
- }
- .bg-success {
- background-color: #dff0d8;
- }
- a.bg-success:hover,
- a.bg-success:focus {
- background-color: #c1e2b3;
- }
- .bg-info {
- background-color: #d9edf7;
- }
- a.bg-info:hover,
- a.bg-info:focus {
- background-color: #afd9ee;
- }
- .bg-warning {
- background-color: #fcf8e3;
- }
- a.bg-warning:hover,
- a.bg-warning:focus {
- background-color: #f7ecb5;
- }
- .bg-danger {
- background-color: #f2dede;
- }
- a.bg-danger:hover,
- a.bg-danger:focus {
- background-color: #e4b9b9;
- }
- .page-header {
- padding-bottom: 8px;
- margin: 36px 0 18px;
- border-bottom: 1px solid #eeeeee;
- }
- ul,
- ol {
- margin-top: 0;
- margin-bottom: 9px;
- }
- ul ul,
- ol ul,
- ul ol,
- ol ol {
- margin-bottom: 0;
- }
- .list-unstyled {
- padding-left: 0;
- list-style: none;
- }
- .list-inline {
- padding-left: 0;
- list-style: none;
- margin-left: -5px;
- }
- .list-inline > li {
- display: inline-block;
- padding-left: 5px;
- padding-right: 5px;
- }
- dl {
- margin-top: 0;
- margin-bottom: 18px;
- }
- dt,
- dd {
- line-height: 1.42857143;
- }
- dt {
- font-weight: bold;
- }
- dd {
- margin-left: 0;
- }
- @media (min-width: 541px) {
- .dl-horizontal dt {
- float: left;
- width: 160px;
- clear: left;
- text-align: right;
- overflow: hidden;
- text-overflow: ellipsis;
- white-space: nowrap;
- }
- .dl-horizontal dd {
- margin-left: 180px;
- }
- }
- abbr[title],
- abbr[data-original-title] {
- cursor: help;
- border-bottom: 1px dotted #777777;
- }
- .initialism {
- font-size: 90%;
- text-transform: uppercase;
- }
- blockquote {
- padding: 9px 18px;
- margin: 0 0 18px;
- font-size: inherit;
- border-left: 5px solid #eeeeee;
- }
- blockquote p:last-child,
- blockquote ul:last-child,
- blockquote ol:last-child {
- margin-bottom: 0;
- }
- blockquote footer,
- blockquote small,
- blockquote .small {
- display: block;
- font-size: 80%;
- line-height: 1.42857143;
- color: #777777;
- }
- blockquote footer:before,
- blockquote small:before,
- blockquote .small:before {
- content: '\2014 \00A0';
- }
- .blockquote-reverse,
- blockquote.pull-right {
- padding-right: 15px;
- padding-left: 0;
- border-right: 5px solid #eeeeee;
- border-left: 0;
- text-align: right;
- }
- .blockquote-reverse footer:before,
- blockquote.pull-right footer:before,
- .blockquote-reverse small:before,
- blockquote.pull-right small:before,
- .blockquote-reverse .small:before,
- blockquote.pull-right .small:before {
- content: '';
- }
- .blockquote-reverse footer:after,
- blockquote.pull-right footer:after,
- .blockquote-reverse small:after,
- blockquote.pull-right small:after,
- .blockquote-reverse .small:after,
- blockquote.pull-right .small:after {
- content: '\00A0 \2014';
- }
- address {
- margin-bottom: 18px;
- font-style: normal;
- line-height: 1.42857143;
- }
- code,
- kbd,
- pre,
- samp {
- font-family: monospace;
- }
- code {
- padding: 2px 4px;
- font-size: 90%;
- color: #c7254e;
- background-color: #f9f2f4;
- border-radius: 2px;
- }
- kbd {
- padding: 2px 4px;
- font-size: 90%;
- color: #888;
- background-color: transparent;
- border-radius: 1px;
- box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
- }
- kbd kbd {
- padding: 0;
- font-size: 100%;
- font-weight: bold;
- box-shadow: none;
- }
- pre {
- display: block;
- padding: 8.5px;
- margin: 0 0 9px;
- font-size: 12px;
- line-height: 1.42857143;
- word-break: break-all;
- word-wrap: break-word;
- color: #333333;
- background-color: #f5f5f5;
- border: 1px solid #ccc;
- border-radius: 2px;
- }
- pre code {
- padding: 0;
- font-size: inherit;
- color: inherit;
- white-space: pre-wrap;
- background-color: transparent;
- border-radius: 0;
- }
- .pre-scrollable {
- max-height: 340px;
- overflow-y: scroll;
- }
- .container {
- margin-right: auto;
- margin-left: auto;
- padding-left: 0px;
- padding-right: 0px;
- }
- @media (min-width: 768px) {
- .container {
- width: 768px;
- }
- }
- @media (min-width: 992px) {
- .container {
- width: 940px;
- }
- }
- @media (min-width: 1200px) {
- .container {
- width: 1140px;
- }
- }
- .container-fluid {
- margin-right: auto;
- margin-left: auto;
- padding-left: 0px;
- padding-right: 0px;
- }
- .row {
- margin-left: 0px;
- margin-right: 0px;
- }
- .col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
- position: relative;
- min-height: 1px;
- padding-left: 0px;
- padding-right: 0px;
- }
- .col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
- float: left;
- }
- .col-xs-12 {
- width: 100%;
- }
- .col-xs-11 {
- width: 91.66666667%;
- }
- .col-xs-10 {
- width: 83.33333333%;
- }
- .col-xs-9 {
- width: 75%;
- }
- .col-xs-8 {
- width: 66.66666667%;
- }
- .col-xs-7 {
- width: 58.33333333%;
- }
- .col-xs-6 {
- width: 50%;
- }
- .col-xs-5 {
- width: 41.66666667%;
- }
- .col-xs-4 {
- width: 33.33333333%;
- }
- .col-xs-3 {
- width: 25%;
- }
- .col-xs-2 {
- width: 16.66666667%;
- }
- .col-xs-1 {
- width: 8.33333333%;
- }
- .col-xs-pull-12 {
- right: 100%;
- }
- .col-xs-pull-11 {
- right: 91.66666667%;
- }
- .col-xs-pull-10 {
- right: 83.33333333%;
- }
- .col-xs-pull-9 {
- right: 75%;
- }
- .col-xs-pull-8 {
- right: 66.66666667%;
- }
- .col-xs-pull-7 {
- right: 58.33333333%;
- }
- .col-xs-pull-6 {
- right: 50%;
- }
- .col-xs-pull-5 {
- right: 41.66666667%;
- }
- .col-xs-pull-4 {
- right: 33.33333333%;
- }
- .col-xs-pull-3 {
- right: 25%;
- }
- .col-xs-pull-2 {
- right: 16.66666667%;
- }
- .col-xs-pull-1 {
- right: 8.33333333%;
- }
- .col-xs-pull-0 {
- right: auto;
- }
- .col-xs-push-12 {
- left: 100%;
- }
- .col-xs-push-11 {
- left: 91.66666667%;
- }
- .col-xs-push-10 {
- left: 83.33333333%;
- }
- .col-xs-push-9 {
- left: 75%;
- }
- .col-xs-push-8 {
- left: 66.66666667%;
- }
- .col-xs-push-7 {
- left: 58.33333333%;
- }
- .col-xs-push-6 {
- left: 50%;
- }
- .col-xs-push-5 {
- left: 41.66666667%;
- }
- .col-xs-push-4 {
- left: 33.33333333%;
- }
- .col-xs-push-3 {
- left: 25%;
- }
- .col-xs-push-2 {
- left: 16.66666667%;
- }
- .col-xs-push-1 {
- left: 8.33333333%;
- }
- .col-xs-push-0 {
- left: auto;
- }
- .col-xs-offset-12 {
- margin-left: 100%;
- }
- .col-xs-offset-11 {
- margin-left: 91.66666667%;
- }
- .col-xs-offset-10 {
- margin-left: 83.33333333%;
- }
- .col-xs-offset-9 {
- margin-left: 75%;
- }
- .col-xs-offset-8 {
- margin-left: 66.66666667%;
- }
- .col-xs-offset-7 {
- margin-left: 58.33333333%;
- }
- .col-xs-offset-6 {
- margin-left: 50%;
- }
- .col-xs-offset-5 {
- margin-left: 41.66666667%;
- }
- .col-xs-offset-4 {
- margin-left: 33.33333333%;
- }
- .col-xs-offset-3 {
- margin-left: 25%;
- }
- .col-xs-offset-2 {
- margin-left: 16.66666667%;
- }
- .col-xs-offset-1 {
- margin-left: 8.33333333%;
- }
- .col-xs-offset-0 {
- margin-left: 0%;
- }
- @media (min-width: 768px) {
- .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
- float: left;
- }
- .col-sm-12 {
- width: 100%;
- }
- .col-sm-11 {
- width: 91.66666667%;
- }
- .col-sm-10 {
- width: 83.33333333%;
- }
- .col-sm-9 {
- width: 75%;
- }
- .col-sm-8 {
- width: 66.66666667%;
- }
- .col-sm-7 {
- width: 58.33333333%;
- }
- .col-sm-6 {
- width: 50%;
- }
- .col-sm-5 {
- width: 41.66666667%;
- }
- .col-sm-4 {
- width: 33.33333333%;
- }
- .col-sm-3 {
- width: 25%;
- }
- .col-sm-2 {
- width: 16.66666667%;
- }
- .col-sm-1 {
- width: 8.33333333%;
- }
- .col-sm-pull-12 {
- right: 100%;
- }
- .col-sm-pull-11 {
- right: 91.66666667%;
- }
- .col-sm-pull-10 {
- right: 83.33333333%;
- }
- .col-sm-pull-9 {
- right: 75%;
- }
- .col-sm-pull-8 {
- right: 66.66666667%;
- }
- .col-sm-pull-7 {
- right: 58.33333333%;
- }
- .col-sm-pull-6 {
- right: 50%;
- }
- .col-sm-pull-5 {
- right: 41.66666667%;
- }
- .col-sm-pull-4 {
- right: 33.33333333%;
- }
- .col-sm-pull-3 {
- right: 25%;
- }
- .col-sm-pull-2 {
- right: 16.66666667%;
- }
- .col-sm-pull-1 {
- right: 8.33333333%;
- }
- .col-sm-pull-0 {
- right: auto;
- }
- .col-sm-push-12 {
- left: 100%;
- }
- .col-sm-push-11 {
- left: 91.66666667%;
- }
- .col-sm-push-10 {
- left: 83.33333333%;
- }
- .col-sm-push-9 {
- left: 75%;
- }
- .col-sm-push-8 {
- left: 66.66666667%;
- }
- .col-sm-push-7 {
- left: 58.33333333%;
- }
- .col-sm-push-6 {
- left: 50%;
- }
- .col-sm-push-5 {
- left: 41.66666667%;
- }
- .col-sm-push-4 {
- left: 33.33333333%;
- }
- .col-sm-push-3 {
- left: 25%;
- }
- .col-sm-push-2 {
- left: 16.66666667%;
- }
- .col-sm-push-1 {
- left: 8.33333333%;
- }
- .col-sm-push-0 {
- left: auto;
- }
- .col-sm-offset-12 {
- margin-left: 100%;
- }
- .col-sm-offset-11 {
- margin-left: 91.66666667%;
- }
- .col-sm-offset-10 {
- margin-left: 83.33333333%;
- }
- .col-sm-offset-9 {
- margin-left: 75%;
- }
- .col-sm-offset-8 {
- margin-left: 66.66666667%;
- }
- .col-sm-offset-7 {
- margin-left: 58.33333333%;
- }
- .col-sm-offset-6 {
- margin-left: 50%;
- }
- .col-sm-offset-5 {
- margin-left: 41.66666667%;
- }
- .col-sm-offset-4 {
- margin-left: 33.33333333%;
- }
- .col-sm-offset-3 {
- margin-left: 25%;
- }
- .col-sm-offset-2 {
- margin-left: 16.66666667%;
- }
- .col-sm-offset-1 {
- margin-left: 8.33333333%;
- }
- .col-sm-offset-0 {
- margin-left: 0%;
- }
- }
- @media (min-width: 992px) {
- .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
- float: left;
- }
- .col-md-12 {
- width: 100%;
- }
- .col-md-11 {
- width: 91.66666667%;
- }
- .col-md-10 {
- width: 83.33333333%;
- }
- .col-md-9 {
- width: 75%;
- }
- .col-md-8 {
- width: 66.66666667%;
- }
- .col-md-7 {
- width: 58.33333333%;
- }
- .col-md-6 {
- width: 50%;
- }
- .col-md-5 {
- width: 41.66666667%;
- }
- .col-md-4 {
- width: 33.33333333%;
- }
- .col-md-3 {
- width: 25%;
- }
- .col-md-2 {
- width: 16.66666667%;
- }
- .col-md-1 {
- width: 8.33333333%;
- }
- .col-md-pull-12 {
- right: 100%;
- }
- .col-md-pull-11 {
- right: 91.66666667%;
- }
- .col-md-pull-10 {
- right: 83.33333333%;
- }
- .col-md-pull-9 {
- right: 75%;
- }
- .col-md-pull-8 {
- right: 66.66666667%;
- }
- .col-md-pull-7 {
- right: 58.33333333%;
- }
- .col-md-pull-6 {
- right: 50%;
- }
- .col-md-pull-5 {
- right: 41.66666667%;
- }
- .col-md-pull-4 {
- right: 33.33333333%;
- }
- .col-md-pull-3 {
- right: 25%;
- }
- .col-md-pull-2 {
- right: 16.66666667%;
- }
- .col-md-pull-1 {
- right: 8.33333333%;
- }
- .col-md-pull-0 {
- right: auto;
- }
- .col-md-push-12 {
- left: 100%;
- }
- .col-md-push-11 {
- left: 91.66666667%;
- }
- .col-md-push-10 {
- left: 83.33333333%;
- }
- .col-md-push-9 {
- left: 75%;
- }
- .col-md-push-8 {
- left: 66.66666667%;
- }
- .col-md-push-7 {
- left: 58.33333333%;
- }
- .col-md-push-6 {
- left: 50%;
- }
- .col-md-push-5 {
- left: 41.66666667%;
- }
- .col-md-push-4 {
- left: 33.33333333%;
- }
- .col-md-push-3 {
- left: 25%;
- }
- .col-md-push-2 {
- left: 16.66666667%;
- }
- .col-md-push-1 {
- left: 8.33333333%;
- }
- .col-md-push-0 {
- left: auto;
- }
- .col-md-offset-12 {
- margin-left: 100%;
- }
- .col-md-offset-11 {
- margin-left: 91.66666667%;
- }
- .col-md-offset-10 {
- margin-left: 83.33333333%;
- }
- .col-md-offset-9 {
- margin-left: 75%;
- }
- .col-md-offset-8 {
- margin-left: 66.66666667%;
- }
- .col-md-offset-7 {
- margin-left: 58.33333333%;
- }
- .col-md-offset-6 {
- margin-left: 50%;
- }
- .col-md-offset-5 {
- margin-left: 41.66666667%;
- }
- .col-md-offset-4 {
- margin-left: 33.33333333%;
- }
- .col-md-offset-3 {
- margin-left: 25%;
- }
- .col-md-offset-2 {
- margin-left: 16.66666667%;
- }
- .col-md-offset-1 {
- margin-left: 8.33333333%;
- }
- .col-md-offset-0 {
- margin-left: 0%;
- }
- }
- @media (min-width: 1200px) {
- .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
- float: left;
- }
- .col-lg-12 {
- width: 100%;
- }
- .col-lg-11 {
- width: 91.66666667%;
- }
- .col-lg-10 {
- width: 83.33333333%;
- }
- .col-lg-9 {
- width: 75%;
- }
- .col-lg-8 {
- width: 66.66666667%;
- }
- .col-lg-7 {
- width: 58.33333333%;
- }
- .col-lg-6 {
- width: 50%;
- }
- .col-lg-5 {
- width: 41.66666667%;
- }
- .col-lg-4 {
- width: 33.33333333%;
- }
- .col-lg-3 {
- width: 25%;
- }
- .col-lg-2 {
- width: 16.66666667%;
- }
- .col-lg-1 {
- width: 8.33333333%;
- }
- .col-lg-pull-12 {
- right: 100%;
- }
- .col-lg-pull-11 {
- right: 91.66666667%;
- }
- .col-lg-pull-10 {
- right: 83.33333333%;
- }
- .col-lg-pull-9 {
- right: 75%;
- }
- .col-lg-pull-8 {
- right: 66.66666667%;
- }
- .col-lg-pull-7 {
- right: 58.33333333%;
- }
- .col-lg-pull-6 {
- right: 50%;
- }
- .col-lg-pull-5 {
- right: 41.66666667%;
- }
- .col-lg-pull-4 {
- right: 33.33333333%;
- }
- .col-lg-pull-3 {
- right: 25%;
- }
- .col-lg-pull-2 {
- right: 16.66666667%;
- }
- .col-lg-pull-1 {
- right: 8.33333333%;
- }
- .col-lg-pull-0 {
- right: auto;
- }
- .col-lg-push-12 {
- left: 100%;
- }
- .col-lg-push-11 {
- left: 91.66666667%;
- }
- .col-lg-push-10 {
- left: 83.33333333%;
- }
- .col-lg-push-9 {
- left: 75%;
- }
- .col-lg-push-8 {
- left: 66.66666667%;
- }
- .col-lg-push-7 {
- left: 58.33333333%;
- }
- .col-lg-push-6 {
- left: 50%;
- }
- .col-lg-push-5 {
- left: 41.66666667%;
- }
- .col-lg-push-4 {
- left: 33.33333333%;
- }
- .col-lg-push-3 {
- left: 25%;
- }
- .col-lg-push-2 {
- left: 16.66666667%;
- }
- .col-lg-push-1 {
- left: 8.33333333%;
- }
- .col-lg-push-0 {
- left: auto;
- }
- .col-lg-offset-12 {
- margin-left: 100%;
- }
- .col-lg-offset-11 {
- margin-left: 91.66666667%;
- }
- .col-lg-offset-10 {
- margin-left: 83.33333333%;
- }
- .col-lg-offset-9 {
- margin-left: 75%;
- }
- .col-lg-offset-8 {
- margin-left: 66.66666667%;
- }
- .col-lg-offset-7 {
- margin-left: 58.33333333%;
- }
- .col-lg-offset-6 {
- margin-left: 50%;
- }
- .col-lg-offset-5 {
- margin-left: 41.66666667%;
- }
- .col-lg-offset-4 {
- margin-left: 33.33333333%;
- }
- .col-lg-offset-3 {
- margin-left: 25%;
- }
- .col-lg-offset-2 {
- margin-left: 16.66666667%;
- }
- .col-lg-offset-1 {
- margin-left: 8.33333333%;
- }
- .col-lg-offset-0 {
- margin-left: 0%;
- }
- }
- table {
- background-color: transparent;
- }
- caption {
- padding-top: 8px;
- padding-bottom: 8px;
- color: #777777;
- text-align: left;
- }
- th {
- text-align: left;
- }
- .table {
- width: 100%;
- max-width: 100%;
- margin-bottom: 18px;
- }
- .table > thead > tr > th,
- .table > tbody > tr > th,
- .table > tfoot > tr > th,
- .table > thead > tr > td,
- .table > tbody > tr > td,
- .table > tfoot > tr > td {
- padding: 8px;
- line-height: 1.42857143;
- vertical-align: top;
- border-top: 1px solid #ddd;
- }
- .table > thead > tr > th {
- vertical-align: bottom;
- border-bottom: 2px solid #ddd;
- }
- .table > caption + thead > tr:first-child > th,
- .table > colgroup + thead > tr:first-child > th,
- .table > thead:first-child > tr:first-child > th,
- .table > caption + thead > tr:first-child > td,
- .table > colgroup + thead > tr:first-child > td,
- .table > thead:first-child > tr:first-child > td {
- border-top: 0;
- }
- .table > tbody + tbody {
- border-top: 2px solid #ddd;
- }
- .table .table {
- background-color: #fff;
- }
- .table-condensed > thead > tr > th,
- .table-condensed > tbody > tr > th,
- .table-condensed > tfoot > tr > th,
- .table-condensed > thead > tr > td,
- .table-condensed > tbody > tr > td,
- .table-condensed > tfoot > tr > td {
- padding: 5px;
- }
- .table-bordered {
- border: 1px solid #ddd;
- }
- .table-bordered > thead > tr > th,
- .table-bordered > tbody > tr > th,
- .table-bordered > tfoot > tr > th,
- .table-bordered > thead > tr > td,
- .table-bordered > tbody > tr > td,
- .table-bordered > tfoot > tr > td {
- border: 1px solid #ddd;
- }
- .table-bordered > thead > tr > th,
- .table-bordered > thead > tr > td {
- border-bottom-width: 2px;
- }
- .table-striped > tbody > tr:nth-of-type(odd) {
- background-color: #f9f9f9;
- }
- .table-hover > tbody > tr:hover {
- background-color: #f5f5f5;
- }
- table col[class*="col-"] {
- position: static;
- float: none;
- display: table-column;
- }
- table td[class*="col-"],
- table th[class*="col-"] {
- position: static;
- float: none;
- display: table-cell;
- }
- .table > thead > tr > td.active,
- .table > tbody > tr > td.active,
- .table > tfoot > tr > td.active,
- .table > thead > tr > th.active,
- .table > tbody > tr > th.active,
- .table > tfoot > tr > th.active,
- .table > thead > tr.active > td,
- .table > tbody > tr.active > td,
- .table > tfoot > tr.active > td,
- .table > thead > tr.active > th,
- .table > tbody > tr.active > th,
- .table > tfoot > tr.active > th {
- background-color: #f5f5f5;
- }
- .table-hover > tbody > tr > td.active:hover,
- .table-hover > tbody > tr > th.active:hover,
- .table-hover > tbody > tr.active:hover > td,
- .table-hover > tbody > tr:hover > .active,
- .table-hover > tbody > tr.active:hover > th {
- background-color: #e8e8e8;
- }
- .table > thead > tr > td.success,
- .table > tbody > tr > td.success,
- .table > tfoot > tr > td.success,
- .table > thead > tr > th.success,
- .table > tbody > tr > th.success,
- .table > tfoot > tr > th.success,
- .table > thead > tr.success > td,
- .table > tbody > tr.success > td,
- .table > tfoot > tr.success > td,
- .table > thead > tr.success > th,
- .table > tbody > tr.success > th,
- .table > tfoot > tr.success > th {
- background-color: #dff0d8;
- }
- .table-hover > tbody > tr > td.success:hover,
- .table-hover > tbody > tr > th.success:hover,
- .table-hover > tbody > tr.success:hover > td,
- .table-hover > tbody > tr:hover > .success,
- .table-hover > tbody > tr.success:hover > th {
- background-color: #d0e9c6;
- }
- .table > thead > tr > td.info,
- .table > tbody > tr > td.info,
- .table > tfoot > tr > td.info,
- .table > thead > tr > th.info,
- .table > tbody > tr > th.info,
- .table > tfoot > tr > th.info,
- .table > thead > tr.info > td,
- .table > tbody > tr.info > td,
- .table > tfoot > tr.info > td,
- .table > thead > tr.info > th,
- .table > tbody > tr.info > th,
- .table > tfoot > tr.info > th {
- background-color: #d9edf7;
- }
- .table-hover > tbody > tr > td.info:hover,
- .table-hover > tbody > tr > th.info:hover,
- .table-hover > tbody > tr.info:hover > td,
- .table-hover > tbody > tr:hover > .info,
- .table-hover > tbody > tr.info:hover > th {
- background-color: #c4e3f3;
- }
- .table > thead > tr > td.warning,
- .table > tbody > tr > td.warning,
- .table > tfoot > tr > td.warning,
- .table > thead > tr > th.warning,
- .table > tbody > tr > th.warning,
- .table > tfoot > tr > th.warning,
- .table > thead > tr.warning > td,
- .table > tbody > tr.warning > td,
- .table > tfoot > tr.warning > td,
- .table > thead > tr.warning > th,
- .table > tbody > tr.warning > th,
- .table > tfoot > tr.warning > th {
- background-color: #fcf8e3;
- }
- .table-hover > tbody > tr > td.warning:hover,
- .table-hover > tbody > tr > th.warning:hover,
- .table-hover > tbody > tr.warning:hover > td,
- .table-hover > tbody > tr:hover > .warning,
- .table-hover > tbody > tr.warning:hover > th {
- background-color: #faf2cc;
- }
- .table > thead > tr > td.danger,
- .table > tbody > tr > td.danger,
- .table > tfoot > tr > td.danger,
- .table > thead > tr > th.danger,
- .table > tbody > tr > th.danger,
- .table > tfoot > tr > th.danger,
- .table > thead > tr.danger > td,
- .table > tbody > tr.danger > td,
- .table > tfoot > tr.danger > td,
- .table > thead > tr.danger > th,
- .table > tbody > tr.danger > th,
- .table > tfoot > tr.danger > th {
- background-color: #f2dede;
- }
- .table-hover > tbody > tr > td.danger:hover,
- .table-hover > tbody > tr > th.danger:hover,
- .table-hover > tbody > tr.danger:hover > td,
- .table-hover > tbody > tr:hover > .danger,
- .table-hover > tbody > tr.danger:hover > th {
- background-color: #ebcccc;
- }
- .table-responsive {
- overflow-x: auto;
- min-height: 0.01%;
- }
- @media screen and (max-width: 767px) {
- .table-responsive {
- width: 100%;
- margin-bottom: 13.5px;
- overflow-y: hidden;
- -ms-overflow-style: -ms-autohiding-scrollbar;
- border: 1px solid #ddd;
- }
- .table-responsive > .table {
- margin-bottom: 0;
- }
- .table-responsive > .table > thead > tr > th,
- .table-responsive > .table > tbody > tr > th,
- .table-responsive > .table > tfoot > tr > th,
- .table-responsive > .table > thead > tr > td,
- .table-responsive > .table > tbody > tr > td,
- .table-responsive > .table > tfoot > tr > td {
- white-space: nowrap;
- }
- .table-responsive > .table-bordered {
- border: 0;
- }
- .table-responsive > .table-bordered > thead > tr > th:first-child,
- .table-responsive > .table-bordered > tbody > tr > th:first-child,
- .table-responsive > .table-bordered > tfoot > tr > th:first-child,
- .table-responsive > .table-bordered > thead > tr > td:first-child,
- .table-responsive > .table-bordered > tbody > tr > td:first-child,
- .table-responsive > .table-bordered > tfoot > tr > td:first-child {
- border-left: 0;
- }
- .table-responsive > .table-bordered > thead > tr > th:last-child,
- .table-responsive > .table-bordered > tbody > tr > th:last-child,
- .table-responsive > .table-bordered > tfoot > tr > th:last-child,
- .table-responsive > .table-bordered > thead > tr > td:last-child,
- .table-responsive > .table-bordered > tbody > tr > td:last-child,
- .table-responsive > .table-bordered > tfoot > tr > td:last-child {
- border-right: 0;
- }
- .table-responsive > .table-bordered > tbody > tr:last-child > th,
- .table-responsive > .table-bordered > tfoot > tr:last-child > th,
- .table-responsive > .table-bordered > tbody > tr:last-child > td,
- .table-responsive > .table-bordered > tfoot > tr:last-child > td {
- border-bottom: 0;
- }
- }
- fieldset {
- padding: 0;
- margin: 0;
- border: 0;
- min-width: 0;
- }
- legend {
- display: block;
- width: 100%;
- padding: 0;
- margin-bottom: 18px;
- font-size: 19.5px;
- line-height: inherit;
- color: #333333;
- border: 0;
- border-bottom: 1px solid #e5e5e5;
- }
- label {
- display: inline-block;
- max-width: 100%;
- margin-bottom: 5px;
- font-weight: bold;
- }
- input[type="search"] {
- -webkit-box-sizing: border-box;
- -moz-box-sizing: border-box;
- box-sizing: border-box;
- }
- input[type="radio"],
- input[type="checkbox"] {
- margin: 4px 0 0;
- margin-top: 1px \9;
- line-height: normal;
- }
- input[type="file"] {
- display: block;
- }
- input[type="range"] {
- display: block;
- width: 100%;
- }
- select[multiple],
- select[size] {
- height: auto;
- }
- input[type="file"]:focus,
- input[type="radio"]:focus,
- input[type="checkbox"]:focus {
- outline: 5px auto -webkit-focus-ring-color;
- outline-offset: -2px;
- }
- output {
- display: block;
- padding-top: 7px;
- font-size: 13px;
- line-height: 1.42857143;
- color: #555555;
- }
- .form-control {
- display: block;
- width: 100%;
- height: 32px;
- padding: 6px 12px;
- font-size: 13px;
- line-height: 1.42857143;
- color: #555555;
- background-color: #fff;
- background-image: none;
- border: 1px solid #ccc;
- border-radius: 2px;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- }
- .form-control:focus {
- border-color: #66afe9;
- outline: 0;
- -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
- box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
- }
- .form-control::-moz-placeholder {
- color: #999;
- opacity: 1;
- }
- .form-control:-ms-input-placeholder {
- color: #999;
- }
- .form-control::-webkit-input-placeholder {
- color: #999;
- }
- .form-control::-ms-expand {
- border: 0;
- background-color: transparent;
- }
- .form-control[disabled],
- .form-control[readonly],
- fieldset[disabled] .form-control {
- background-color: #eeeeee;
- opacity: 1;
- }
- .form-control[disabled],
- fieldset[disabled] .form-control {
- cursor: not-allowed;
- }
- textarea.form-control {
- height: auto;
- }
- input[type="search"] {
- -webkit-appearance: none;
- }
- @media screen and (-webkit-min-device-pixel-ratio: 0) {
- input[type="date"].form-control,
- input[type="time"].form-control,
- input[type="datetime-local"].form-control,
- input[type="month"].form-control {
- line-height: 32px;
- }
- input[type="date"].input-sm,
- input[type="time"].input-sm,
- input[type="datetime-local"].input-sm,
- input[type="month"].input-sm,
- .input-group-sm input[type="date"],
- .input-group-sm input[type="time"],
- .input-group-sm input[type="datetime-local"],
- .input-group-sm input[type="month"] {
- line-height: 30px;
- }
- input[type="date"].input-lg,
- input[type="time"].input-lg,
- input[type="datetime-local"].input-lg,
- input[type="month"].input-lg,
- .input-group-lg input[type="date"],
- .input-group-lg input[type="time"],
- .input-group-lg input[type="datetime-local"],
- .input-group-lg input[type="month"] {
- line-height: 45px;
- }
- }
- .form-group {
- margin-bottom: 15px;
- }
- .radio,
- .checkbox {
- position: relative;
- display: block;
- margin-top: 10px;
- margin-bottom: 10px;
- }
- .radio label,
- .checkbox label {
- min-height: 18px;
- padding-left: 20px;
- margin-bottom: 0;
- font-weight: normal;
- cursor: pointer;
- }
- .radio input[type="radio"],
- .radio-inline input[type="radio"],
- .checkbox input[type="checkbox"],
- .checkbox-inline input[type="checkbox"] {
- position: absolute;
- margin-left: -20px;
- margin-top: 4px \9;
- }
- .radio + .radio,
- .checkbox + .checkbox {
- margin-top: -5px;
- }
- .radio-inline,
- .checkbox-inline {
- position: relative;
- display: inline-block;
- padding-left: 20px;
- margin-bottom: 0;
- vertical-align: middle;
- font-weight: normal;
- cursor: pointer;
- }
- .radio-inline + .radio-inline,
- .checkbox-inline + .checkbox-inline {
- margin-top: 0;
- margin-left: 10px;
- }
- input[type="radio"][disabled],
- input[type="checkbox"][disabled],
- input[type="radio"].disabled,
- input[type="checkbox"].disabled,
- fieldset[disabled] input[type="radio"],
- fieldset[disabled] input[type="checkbox"] {
- cursor: not-allowed;
- }
- .radio-inline.disabled,
- .checkbox-inline.disabled,
- fieldset[disabled] .radio-inline,
- fieldset[disabled] .checkbox-inline {
- cursor: not-allowed;
- }
- .radio.disabled label,
- .checkbox.disabled label,
- fieldset[disabled] .radio label,
- fieldset[disabled] .checkbox label {
- cursor: not-allowed;
- }
- .form-control-static {
- padding-top: 7px;
- padding-bottom: 7px;
- margin-bottom: 0;
- min-height: 31px;
- }
- .form-control-static.input-lg,
- .form-control-static.input-sm {
- padding-left: 0;
- padding-right: 0;
- }
- .input-sm {
- height: 30px;
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- }
- select.input-sm {
- height: 30px;
- line-height: 30px;
- }
- textarea.input-sm,
- select[multiple].input-sm {
- height: auto;
- }
- .form-group-sm .form-control {
- height: 30px;
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- }
- .form-group-sm select.form-control {
- height: 30px;
- line-height: 30px;
- }
- .form-group-sm textarea.form-control,
- .form-group-sm select[multiple].form-control {
- height: auto;
- }
- .form-group-sm .form-control-static {
- height: 30px;
- min-height: 30px;
- padding: 6px 10px;
- font-size: 12px;
- line-height: 1.5;
- }
- .input-lg {
- height: 45px;
- padding: 10px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- border-radius: 3px;
- }
- select.input-lg {
- height: 45px;
- line-height: 45px;
- }
- textarea.input-lg,
- select[multiple].input-lg {
- height: auto;
- }
- .form-group-lg .form-control {
- height: 45px;
- padding: 10px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- border-radius: 3px;
- }
- .form-group-lg select.form-control {
- height: 45px;
- line-height: 45px;
- }
- .form-group-lg textarea.form-control,
- .form-group-lg select[multiple].form-control {
- height: auto;
- }
- .form-group-lg .form-control-static {
- height: 45px;
- min-height: 35px;
- padding: 11px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- }
- .has-feedback {
- position: relative;
- }
- .has-feedback .form-control {
- padding-right: 40px;
- }
- .form-control-feedback {
- position: absolute;
- top: 0;
- right: 0;
- z-index: 2;
- display: block;
- width: 32px;
- height: 32px;
- line-height: 32px;
- text-align: center;
- pointer-events: none;
- }
- .input-lg + .form-control-feedback,
- .input-group-lg + .form-control-feedback,
- .form-group-lg .form-control + .form-control-feedback {
- width: 45px;
- height: 45px;
- line-height: 45px;
- }
- .input-sm + .form-control-feedback,
- .input-group-sm + .form-control-feedback,
- .form-group-sm .form-control + .form-control-feedback {
- width: 30px;
- height: 30px;
- line-height: 30px;
- }
- .has-success .help-block,
- .has-success .control-label,
- .has-success .radio,
- .has-success .checkbox,
- .has-success .radio-inline,
- .has-success .checkbox-inline,
- .has-success.radio label,
- .has-success.checkbox label,
- .has-success.radio-inline label,
- .has-success.checkbox-inline label {
- color: #3c763d;
- }
- .has-success .form-control {
- border-color: #3c763d;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- }
- .has-success .form-control:focus {
- border-color: #2b542c;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
- }
- .has-success .input-group-addon {
- color: #3c763d;
- border-color: #3c763d;
- background-color: #dff0d8;
- }
- .has-success .form-control-feedback {
- color: #3c763d;
- }
- .has-warning .help-block,
- .has-warning .control-label,
- .has-warning .radio,
- .has-warning .checkbox,
- .has-warning .radio-inline,
- .has-warning .checkbox-inline,
- .has-warning.radio label,
- .has-warning.checkbox label,
- .has-warning.radio-inline label,
- .has-warning.checkbox-inline label {
- color: #8a6d3b;
- }
- .has-warning .form-control {
- border-color: #8a6d3b;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- }
- .has-warning .form-control:focus {
- border-color: #66512c;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
- }
- .has-warning .input-group-addon {
- color: #8a6d3b;
- border-color: #8a6d3b;
- background-color: #fcf8e3;
- }
- .has-warning .form-control-feedback {
- color: #8a6d3b;
- }
- .has-error .help-block,
- .has-error .control-label,
- .has-error .radio,
- .has-error .checkbox,
- .has-error .radio-inline,
- .has-error .checkbox-inline,
- .has-error.radio label,
- .has-error.checkbox label,
- .has-error.radio-inline label,
- .has-error.checkbox-inline label {
- color: #a94442;
- }
- .has-error .form-control {
- border-color: #a94442;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- }
- .has-error .form-control:focus {
- border-color: #843534;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
- }
- .has-error .input-group-addon {
- color: #a94442;
- border-color: #a94442;
- background-color: #f2dede;
- }
- .has-error .form-control-feedback {
- color: #a94442;
- }
- .has-feedback label ~ .form-control-feedback {
- top: 23px;
- }
- .has-feedback label.sr-only ~ .form-control-feedback {
- top: 0;
- }
- .help-block {
- display: block;
- margin-top: 5px;
- margin-bottom: 10px;
- color: #404040;
- }
- @media (min-width: 768px) {
- .form-inline .form-group {
- display: inline-block;
- margin-bottom: 0;
- vertical-align: middle;
- }
- .form-inline .form-control {
- display: inline-block;
- width: auto;
- vertical-align: middle;
- }
- .form-inline .form-control-static {
- display: inline-block;
- }
- .form-inline .input-group {
- display: inline-table;
- vertical-align: middle;
- }
- .form-inline .input-group .input-group-addon,
- .form-inline .input-group .input-group-btn,
- .form-inline .input-group .form-control {
- width: auto;
- }
- .form-inline .input-group > .form-control {
- width: 100%;
- }
- .form-inline .control-label {
- margin-bottom: 0;
- vertical-align: middle;
- }
- .form-inline .radio,
- .form-inline .checkbox {
- display: inline-block;
- margin-top: 0;
- margin-bottom: 0;
- vertical-align: middle;
- }
- .form-inline .radio label,
- .form-inline .checkbox label {
- padding-left: 0;
- }
- .form-inline .radio input[type="radio"],
- .form-inline .checkbox input[type="checkbox"] {
- position: relative;
- margin-left: 0;
- }
- .form-inline .has-feedback .form-control-feedback {
- top: 0;
- }
- }
- .form-horizontal .radio,
- .form-horizontal .checkbox,
- .form-horizontal .radio-inline,
- .form-horizontal .checkbox-inline {
- margin-top: 0;
- margin-bottom: 0;
- padding-top: 7px;
- }
- .form-horizontal .radio,
- .form-horizontal .checkbox {
- min-height: 25px;
- }
- .form-horizontal .form-group {
- margin-left: 0px;
- margin-right: 0px;
- }
- @media (min-width: 768px) {
- .form-horizontal .control-label {
- text-align: right;
- margin-bottom: 0;
- padding-top: 7px;
- }
- }
- .form-horizontal .has-feedback .form-control-feedback {
- right: 0px;
- }
- @media (min-width: 768px) {
- .form-horizontal .form-group-lg .control-label {
- padding-top: 11px;
- font-size: 17px;
- }
- }
- @media (min-width: 768px) {
- .form-horizontal .form-group-sm .control-label {
- padding-top: 6px;
- font-size: 12px;
- }
- }
- .btn {
- display: inline-block;
- margin-bottom: 0;
- font-weight: normal;
- text-align: center;
- vertical-align: middle;
- touch-action: manipulation;
- cursor: pointer;
- background-image: none;
- border: 1px solid transparent;
- white-space: nowrap;
- padding: 6px 12px;
- font-size: 13px;
- line-height: 1.42857143;
- border-radius: 2px;
- -webkit-user-select: none;
- -moz-user-select: none;
- -ms-user-select: none;
- user-select: none;
- }
- .btn:focus,
- .btn:active:focus,
- .btn.active:focus,
- .btn.focus,
- .btn:active.focus,
- .btn.active.focus {
- outline: 5px auto -webkit-focus-ring-color;
- outline-offset: -2px;
- }
- .btn:hover,
- .btn:focus,
- .btn.focus {
- color: #333;
- text-decoration: none;
- }
- .btn:active,
- .btn.active {
- outline: 0;
- background-image: none;
- -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
- box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
- }
- .btn.disabled,
- .btn[disabled],
- fieldset[disabled] .btn {
- cursor: not-allowed;
- opacity: 0.65;
- filter: alpha(opacity=65);
- -webkit-box-shadow: none;
- box-shadow: none;
- }
- a.btn.disabled,
- fieldset[disabled] a.btn {
- pointer-events: none;
- }
- .btn-default {
- color: #333;
- background-color: #fff;
- border-color: #ccc;
- }
- .btn-default:focus,
- .btn-default.focus {
- color: #333;
- background-color: #e6e6e6;
- border-color: #8c8c8c;
- }
- .btn-default:hover {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- .btn-default:active,
- .btn-default.active,
- .open > .dropdown-toggle.btn-default {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- .btn-default:active:hover,
- .btn-default.active:hover,
- .open > .dropdown-toggle.btn-default:hover,
- .btn-default:active:focus,
- .btn-default.active:focus,
- .open > .dropdown-toggle.btn-default:focus,
- .btn-default:active.focus,
- .btn-default.active.focus,
- .open > .dropdown-toggle.btn-default.focus {
- color: #333;
- background-color: #d4d4d4;
- border-color: #8c8c8c;
- }
- .btn-default:active,
- .btn-default.active,
- .open > .dropdown-toggle.btn-default {
- background-image: none;
- }
- .btn-default.disabled:hover,
- .btn-default[disabled]:hover,
- fieldset[disabled] .btn-default:hover,
- .btn-default.disabled:focus,
- .btn-default[disabled]:focus,
- fieldset[disabled] .btn-default:focus,
- .btn-default.disabled.focus,
- .btn-default[disabled].focus,
- fieldset[disabled] .btn-default.focus {
- background-color: #fff;
- border-color: #ccc;
- }
- .btn-default .badge {
- color: #fff;
- background-color: #333;
- }
- .btn-primary {
- color: #fff;
- background-color: #337ab7;
- border-color: #2e6da4;
- }
- .btn-primary:focus,
- .btn-primary.focus {
- color: #fff;
- background-color: #286090;
- border-color: #122b40;
- }
- .btn-primary:hover {
- color: #fff;
- background-color: #286090;
- border-color: #204d74;
- }
- .btn-primary:active,
- .btn-primary.active,
- .open > .dropdown-toggle.btn-primary {
- color: #fff;
- background-color: #286090;
- border-color: #204d74;
- }
- .btn-primary:active:hover,
- .btn-primary.active:hover,
- .open > .dropdown-toggle.btn-primary:hover,
- .btn-primary:active:focus,
- .btn-primary.active:focus,
- .open > .dropdown-toggle.btn-primary:focus,
- .btn-primary:active.focus,
- .btn-primary.active.focus,
- .open > .dropdown-toggle.btn-primary.focus {
- color: #fff;
- background-color: #204d74;
- border-color: #122b40;
- }
- .btn-primary:active,
- .btn-primary.active,
- .open > .dropdown-toggle.btn-primary {
- background-image: none;
- }
- .btn-primary.disabled:hover,
- .btn-primary[disabled]:hover,
- fieldset[disabled] .btn-primary:hover,
- .btn-primary.disabled:focus,
- .btn-primary[disabled]:focus,
- fieldset[disabled] .btn-primary:focus,
- .btn-primary.disabled.focus,
- .btn-primary[disabled].focus,
- fieldset[disabled] .btn-primary.focus {
- background-color: #337ab7;
- border-color: #2e6da4;
- }
- .btn-primary .badge {
- color: #337ab7;
- background-color: #fff;
- }
- .btn-success {
- color: #fff;
- background-color: #5cb85c;
- border-color: #4cae4c;
- }
- .btn-success:focus,
- .btn-success.focus {
- color: #fff;
- background-color: #449d44;
- border-color: #255625;
- }
- .btn-success:hover {
- color: #fff;
- background-color: #449d44;
- border-color: #398439;
- }
- .btn-success:active,
- .btn-success.active,
- .open > .dropdown-toggle.btn-success {
- color: #fff;
- background-color: #449d44;
- border-color: #398439;
- }
- .btn-success:active:hover,
- .btn-success.active:hover,
- .open > .dropdown-toggle.btn-success:hover,
- .btn-success:active:focus,
- .btn-success.active:focus,
- .open > .dropdown-toggle.btn-success:focus,
- .btn-success:active.focus,
- .btn-success.active.focus,
- .open > .dropdown-toggle.btn-success.focus {
- color: #fff;
- background-color: #398439;
- border-color: #255625;
- }
- .btn-success:active,
- .btn-success.active,
- .open > .dropdown-toggle.btn-success {
- background-image: none;
- }
- .btn-success.disabled:hover,
- .btn-success[disabled]:hover,
- fieldset[disabled] .btn-success:hover,
- .btn-success.disabled:focus,
- .btn-success[disabled]:focus,
- fieldset[disabled] .btn-success:focus,
- .btn-success.disabled.focus,
- .btn-success[disabled].focus,
- fieldset[disabled] .btn-success.focus {
- background-color: #5cb85c;
- border-color: #4cae4c;
- }
- .btn-success .badge {
- color: #5cb85c;
- background-color: #fff;
- }
- .btn-info {
- color: #fff;
- background-color: #5bc0de;
- border-color: #46b8da;
- }
- .btn-info:focus,
- .btn-info.focus {
- color: #fff;
- background-color: #31b0d5;
- border-color: #1b6d85;
- }
- .btn-info:hover {
- color: #fff;
- background-color: #31b0d5;
- border-color: #269abc;
- }
- .btn-info:active,
- .btn-info.active,
- .open > .dropdown-toggle.btn-info {
- color: #fff;
- background-color: #31b0d5;
- border-color: #269abc;
- }
- .btn-info:active:hover,
- .btn-info.active:hover,
- .open > .dropdown-toggle.btn-info:hover,
- .btn-info:active:focus,
- .btn-info.active:focus,
- .open > .dropdown-toggle.btn-info:focus,
- .btn-info:active.focus,
- .btn-info.active.focus,
- .open > .dropdown-toggle.btn-info.focus {
- color: #fff;
- background-color: #269abc;
- border-color: #1b6d85;
- }
- .btn-info:active,
- .btn-info.active,
- .open > .dropdown-toggle.btn-info {
- background-image: none;
- }
- .btn-info.disabled:hover,
- .btn-info[disabled]:hover,
- fieldset[disabled] .btn-info:hover,
- .btn-info.disabled:focus,
- .btn-info[disabled]:focus,
- fieldset[disabled] .btn-info:focus,
- .btn-info.disabled.focus,
- .btn-info[disabled].focus,
- fieldset[disabled] .btn-info.focus {
- background-color: #5bc0de;
- border-color: #46b8da;
- }
- .btn-info .badge {
- color: #5bc0de;
- background-color: #fff;
- }
- .btn-warning {
- color: #fff;
- background-color: #f0ad4e;
- border-color: #eea236;
- }
- .btn-warning:focus,
- .btn-warning.focus {
- color: #fff;
- background-color: #ec971f;
- border-color: #985f0d;
- }
- .btn-warning:hover {
- color: #fff;
- background-color: #ec971f;
- border-color: #d58512;
- }
- .btn-warning:active,
- .btn-warning.active,
- .open > .dropdown-toggle.btn-warning {
- color: #fff;
- background-color: #ec971f;
- border-color: #d58512;
- }
- .btn-warning:active:hover,
- .btn-warning.active:hover,
- .open > .dropdown-toggle.btn-warning:hover,
- .btn-warning:active:focus,
- .btn-warning.active:focus,
- .open > .dropdown-toggle.btn-warning:focus,
- .btn-warning:active.focus,
- .btn-warning.active.focus,
- .open > .dropdown-toggle.btn-warning.focus {
- color: #fff;
- background-color: #d58512;
- border-color: #985f0d;
- }
- .btn-warning:active,
- .btn-warning.active,
- .open > .dropdown-toggle.btn-warning {
- background-image: none;
- }
- .btn-warning.disabled:hover,
- .btn-warning[disabled]:hover,
- fieldset[disabled] .btn-warning:hover,
- .btn-warning.disabled:focus,
- .btn-warning[disabled]:focus,
- fieldset[disabled] .btn-warning:focus,
- .btn-warning.disabled.focus,
- .btn-warning[disabled].focus,
- fieldset[disabled] .btn-warning.focus {
- background-color: #f0ad4e;
- border-color: #eea236;
- }
- .btn-warning .badge {
- color: #f0ad4e;
- background-color: #fff;
- }
- .btn-danger {
- color: #fff;
- background-color: #d9534f;
- border-color: #d43f3a;
- }
- .btn-danger:focus,
- .btn-danger.focus {
- color: #fff;
- background-color: #c9302c;
- border-color: #761c19;
- }
- .btn-danger:hover {
- color: #fff;
- background-color: #c9302c;
- border-color: #ac2925;
- }
- .btn-danger:active,
- .btn-danger.active,
- .open > .dropdown-toggle.btn-danger {
- color: #fff;
- background-color: #c9302c;
- border-color: #ac2925;
- }
- .btn-danger:active:hover,
- .btn-danger.active:hover,
- .open > .dropdown-toggle.btn-danger:hover,
- .btn-danger:active:focus,
- .btn-danger.active:focus,
- .open > .dropdown-toggle.btn-danger:focus,
- .btn-danger:active.focus,
- .btn-danger.active.focus,
- .open > .dropdown-toggle.btn-danger.focus {
- color: #fff;
- background-color: #ac2925;
- border-color: #761c19;
- }
- .btn-danger:active,
- .btn-danger.active,
- .open > .dropdown-toggle.btn-danger {
- background-image: none;
- }
- .btn-danger.disabled:hover,
- .btn-danger[disabled]:hover,
- fieldset[disabled] .btn-danger:hover,
- .btn-danger.disabled:focus,
- .btn-danger[disabled]:focus,
- fieldset[disabled] .btn-danger:focus,
- .btn-danger.disabled.focus,
- .btn-danger[disabled].focus,
- fieldset[disabled] .btn-danger.focus {
- background-color: #d9534f;
- border-color: #d43f3a;
- }
- .btn-danger .badge {
- color: #d9534f;
- background-color: #fff;
- }
- .btn-link {
- color: #337ab7;
- font-weight: normal;
- border-radius: 0;
- }
- .btn-link,
- .btn-link:active,
- .btn-link.active,
- .btn-link[disabled],
- fieldset[disabled] .btn-link {
- background-color: transparent;
- -webkit-box-shadow: none;
- box-shadow: none;
- }
- .btn-link,
- .btn-link:hover,
- .btn-link:focus,
- .btn-link:active {
- border-color: transparent;
- }
- .btn-link:hover,
- .btn-link:focus {
- color: #23527c;
- text-decoration: underline;
- background-color: transparent;
- }
- .btn-link[disabled]:hover,
- fieldset[disabled] .btn-link:hover,
- .btn-link[disabled]:focus,
- fieldset[disabled] .btn-link:focus {
- color: #777777;
- text-decoration: none;
- }
- .btn-lg,
- .btn-group-lg > .btn {
- padding: 10px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- border-radius: 3px;
- }
- .btn-sm,
- .btn-group-sm > .btn {
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- }
- .btn-xs,
- .btn-group-xs > .btn {
- padding: 1px 5px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- }
- .btn-block {
- display: block;
- width: 100%;
- }
- .btn-block + .btn-block {
- margin-top: 5px;
- }
- input[type="submit"].btn-block,
- input[type="reset"].btn-block,
- input[type="button"].btn-block {
- width: 100%;
- }
- .fade {
- opacity: 0;
- -webkit-transition: opacity 0.15s linear;
- -o-transition: opacity 0.15s linear;
- transition: opacity 0.15s linear;
- }
- .fade.in {
- opacity: 1;
- }
- .collapse {
- display: none;
- }
- .collapse.in {
- display: block;
- }
- tr.collapse.in {
- display: table-row;
- }
- tbody.collapse.in {
- display: table-row-group;
- }
- .collapsing {
- position: relative;
- height: 0;
- overflow: hidden;
- -webkit-transition-property: height, visibility;
- transition-property: height, visibility;
- -webkit-transition-duration: 0.35s;
- transition-duration: 0.35s;
- -webkit-transition-timing-function: ease;
- transition-timing-function: ease;
- }
- .caret {
- display: inline-block;
- width: 0;
- height: 0;
- margin-left: 2px;
- vertical-align: middle;
- border-top: 4px dashed;
- border-top: 4px solid \9;
- border-right: 4px solid transparent;
- border-left: 4px solid transparent;
- }
- .dropup,
- .dropdown {
- position: relative;
- }
- .dropdown-toggle:focus {
- outline: 0;
- }
- .dropdown-menu {
- position: absolute;
- top: 100%;
- left: 0;
- z-index: 1000;
- display: none;
- float: left;
- min-width: 160px;
- padding: 5px 0;
- margin: 2px 0 0;
- list-style: none;
- font-size: 13px;
- text-align: left;
- background-color: #fff;
- border: 1px solid #ccc;
- border: 1px solid rgba(0, 0, 0, 0.15);
- border-radius: 2px;
- -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
- box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
- background-clip: padding-box;
- }
- .dropdown-menu.pull-right {
- right: 0;
- left: auto;
- }
- .dropdown-menu .divider {
- height: 1px;
- margin: 8px 0;
- overflow: hidden;
- background-color: #e5e5e5;
- }
- .dropdown-menu > li > a {
- display: block;
- padding: 3px 20px;
- clear: both;
- font-weight: normal;
- line-height: 1.42857143;
- color: #333333;
- white-space: nowrap;
- }
- .dropdown-menu > li > a:hover,
- .dropdown-menu > li > a:focus {
- text-decoration: none;
- color: #262626;
- background-color: #f5f5f5;
- }
- .dropdown-menu > .active > a,
- .dropdown-menu > .active > a:hover,
- .dropdown-menu > .active > a:focus {
- color: #fff;
- text-decoration: none;
- outline: 0;
- background-color: #337ab7;
- }
- .dropdown-menu > .disabled > a,
- .dropdown-menu > .disabled > a:hover,
- .dropdown-menu > .disabled > a:focus {
- color: #777777;
- }
- .dropdown-menu > .disabled > a:hover,
- .dropdown-menu > .disabled > a:focus {
- text-decoration: none;
- background-color: transparent;
- background-image: none;
- filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
- cursor: not-allowed;
- }
- .open > .dropdown-menu {
- display: block;
- }
- .open > a {
- outline: 0;
- }
- .dropdown-menu-right {
- left: auto;
- right: 0;
- }
- .dropdown-menu-left {
- left: 0;
- right: auto;
- }
- .dropdown-header {
- display: block;
- padding: 3px 20px;
- font-size: 12px;
- line-height: 1.42857143;
- color: #777777;
- white-space: nowrap;
- }
- .dropdown-backdrop {
- position: fixed;
- left: 0;
- right: 0;
- bottom: 0;
- top: 0;
- z-index: 990;
- }
- .pull-right > .dropdown-menu {
- right: 0;
- left: auto;
- }
- .dropup .caret,
- .navbar-fixed-bottom .dropdown .caret {
- border-top: 0;
- border-bottom: 4px dashed;
- border-bottom: 4px solid \9;
- content: "";
- }
- .dropup .dropdown-menu,
- .navbar-fixed-bottom .dropdown .dropdown-menu {
- top: auto;
- bottom: 100%;
- margin-bottom: 2px;
- }
- @media (min-width: 541px) {
- .navbar-right .dropdown-menu {
- left: auto;
- right: 0;
- }
- .navbar-right .dropdown-menu-left {
- left: 0;
- right: auto;
- }
- }
- .btn-group,
- .btn-group-vertical {
- position: relative;
- display: inline-block;
- vertical-align: middle;
- }
- .btn-group > .btn,
- .btn-group-vertical > .btn {
- position: relative;
- float: left;
- }
- .btn-group > .btn:hover,
- .btn-group-vertical > .btn:hover,
- .btn-group > .btn:focus,
- .btn-group-vertical > .btn:focus,
- .btn-group > .btn:active,
- .btn-group-vertical > .btn:active,
- .btn-group > .btn.active,
- .btn-group-vertical > .btn.active {
- z-index: 2;
- }
- .btn-group .btn + .btn,
- .btn-group .btn + .btn-group,
- .btn-group .btn-group + .btn,
- .btn-group .btn-group + .btn-group {
- margin-left: -1px;
- }
- .btn-toolbar {
- margin-left: -5px;
- }
- .btn-toolbar .btn,
- .btn-toolbar .btn-group,
- .btn-toolbar .input-group {
- float: left;
- }
- .btn-toolbar > .btn,
- .btn-toolbar > .btn-group,
- .btn-toolbar > .input-group {
- margin-left: 5px;
- }
- .btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
- border-radius: 0;
- }
- .btn-group > .btn:first-child {
- margin-left: 0;
- }
- .btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
- border-bottom-right-radius: 0;
- border-top-right-radius: 0;
- }
- .btn-group > .btn:last-child:not(:first-child),
- .btn-group > .dropdown-toggle:not(:first-child) {
- border-bottom-left-radius: 0;
- border-top-left-radius: 0;
- }
- .btn-group > .btn-group {
- float: left;
- }
- .btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
- border-radius: 0;
- }
- .btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
- .btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
- border-bottom-right-radius: 0;
- border-top-right-radius: 0;
- }
- .btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
- border-bottom-left-radius: 0;
- border-top-left-radius: 0;
- }
- .btn-group .dropdown-toggle:active,
- .btn-group.open .dropdown-toggle {
- outline: 0;
- }
- .btn-group > .btn + .dropdown-toggle {
- padding-left: 8px;
- padding-right: 8px;
- }
- .btn-group > .btn-lg + .dropdown-toggle {
- padding-left: 12px;
- padding-right: 12px;
- }
- .btn-group.open .dropdown-toggle {
- -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
- box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
- }
- .btn-group.open .dropdown-toggle.btn-link {
- -webkit-box-shadow: none;
- box-shadow: none;
- }
- .btn .caret {
- margin-left: 0;
- }
- .btn-lg .caret {
- border-width: 5px 5px 0;
- border-bottom-width: 0;
- }
- .dropup .btn-lg .caret {
- border-width: 0 5px 5px;
- }
- .btn-group-vertical > .btn,
- .btn-group-vertical > .btn-group,
- .btn-group-vertical > .btn-group > .btn {
- display: block;
- float: none;
- width: 100%;
- max-width: 100%;
- }
- .btn-group-vertical > .btn-group > .btn {
- float: none;
- }
- .btn-group-vertical > .btn + .btn,
- .btn-group-vertical > .btn + .btn-group,
- .btn-group-vertical > .btn-group + .btn,
- .btn-group-vertical > .btn-group + .btn-group {
- margin-top: -1px;
- margin-left: 0;
- }
- .btn-group-vertical > .btn:not(:first-child):not(:last-child) {
- border-radius: 0;
- }
- .btn-group-vertical > .btn:first-child:not(:last-child) {
- border-top-right-radius: 2px;
- border-top-left-radius: 2px;
- border-bottom-right-radius: 0;
- border-bottom-left-radius: 0;
- }
- .btn-group-vertical > .btn:last-child:not(:first-child) {
- border-top-right-radius: 0;
- border-top-left-radius: 0;
- border-bottom-right-radius: 2px;
- border-bottom-left-radius: 2px;
- }
- .btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
- border-radius: 0;
- }
- .btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
- .btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
- border-bottom-right-radius: 0;
- border-bottom-left-radius: 0;
- }
- .btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
- border-top-right-radius: 0;
- border-top-left-radius: 0;
- }
- .btn-group-justified {
- display: table;
- width: 100%;
- table-layout: fixed;
- border-collapse: separate;
- }
- .btn-group-justified > .btn,
- .btn-group-justified > .btn-group {
- float: none;
- display: table-cell;
- width: 1%;
- }
- .btn-group-justified > .btn-group .btn {
- width: 100%;
- }
- .btn-group-justified > .btn-group .dropdown-menu {
- left: auto;
- }
- [data-toggle="buttons"] > .btn input[type="radio"],
- [data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
- [data-toggle="buttons"] > .btn input[type="checkbox"],
- [data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
- position: absolute;
- clip: rect(0, 0, 0, 0);
- pointer-events: none;
- }
- .input-group {
- position: relative;
- display: table;
- border-collapse: separate;
- }
- .input-group[class*="col-"] {
- float: none;
- padding-left: 0;
- padding-right: 0;
- }
- .input-group .form-control {
- position: relative;
- z-index: 2;
- float: left;
- width: 100%;
- margin-bottom: 0;
- }
- .input-group .form-control:focus {
- z-index: 3;
- }
- .input-group-lg > .form-control,
- .input-group-lg > .input-group-addon,
- .input-group-lg > .input-group-btn > .btn {
- height: 45px;
- padding: 10px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- border-radius: 3px;
- }
- select.input-group-lg > .form-control,
- select.input-group-lg > .input-group-addon,
- select.input-group-lg > .input-group-btn > .btn {
- height: 45px;
- line-height: 45px;
- }
- textarea.input-group-lg > .form-control,
- textarea.input-group-lg > .input-group-addon,
- textarea.input-group-lg > .input-group-btn > .btn,
- select[multiple].input-group-lg > .form-control,
- select[multiple].input-group-lg > .input-group-addon,
- select[multiple].input-group-lg > .input-group-btn > .btn {
- height: auto;
- }
- .input-group-sm > .form-control,
- .input-group-sm > .input-group-addon,
- .input-group-sm > .input-group-btn > .btn {
- height: 30px;
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- }
- select.input-group-sm > .form-control,
- select.input-group-sm > .input-group-addon,
- select.input-group-sm > .input-group-btn > .btn {
- height: 30px;
- line-height: 30px;
- }
- textarea.input-group-sm > .form-control,
- textarea.input-group-sm > .input-group-addon,
- textarea.input-group-sm > .input-group-btn > .btn,
- select[multiple].input-group-sm > .form-control,
- select[multiple].input-group-sm > .input-group-addon,
- select[multiple].input-group-sm > .input-group-btn > .btn {
- height: auto;
- }
- .input-group-addon,
- .input-group-btn,
- .input-group .form-control {
- display: table-cell;
- }
- .input-group-addon:not(:first-child):not(:last-child),
- .input-group-btn:not(:first-child):not(:last-child),
- .input-group .form-control:not(:first-child):not(:last-child) {
- border-radius: 0;
- }
- .input-group-addon,
- .input-group-btn {
- width: 1%;
- white-space: nowrap;
- vertical-align: middle;
- }
- .input-group-addon {
- padding: 6px 12px;
- font-size: 13px;
- font-weight: normal;
- line-height: 1;
- color: #555555;
- text-align: center;
- background-color: #eeeeee;
- border: 1px solid #ccc;
- border-radius: 2px;
- }
- .input-group-addon.input-sm {
- padding: 5px 10px;
- font-size: 12px;
- border-radius: 1px;
- }
- .input-group-addon.input-lg {
- padding: 10px 16px;
- font-size: 17px;
- border-radius: 3px;
- }
- .input-group-addon input[type="radio"],
- .input-group-addon input[type="checkbox"] {
- margin-top: 0;
- }
- .input-group .form-control:first-child,
- .input-group-addon:first-child,
- .input-group-btn:first-child > .btn,
- .input-group-btn:first-child > .btn-group > .btn,
- .input-group-btn:first-child > .dropdown-toggle,
- .input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
- .input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
- border-bottom-right-radius: 0;
- border-top-right-radius: 0;
- }
- .input-group-addon:first-child {
- border-right: 0;
- }
- .input-group .form-control:last-child,
- .input-group-addon:last-child,
- .input-group-btn:last-child > .btn,
- .input-group-btn:last-child > .btn-group > .btn,
- .input-group-btn:last-child > .dropdown-toggle,
- .input-group-btn:first-child > .btn:not(:first-child),
- .input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
- border-bottom-left-radius: 0;
- border-top-left-radius: 0;
- }
- .input-group-addon:last-child {
- border-left: 0;
- }
- .input-group-btn {
- position: relative;
- font-size: 0;
- white-space: nowrap;
- }
- .input-group-btn > .btn {
- position: relative;
- }
- .input-group-btn > .btn + .btn {
- margin-left: -1px;
- }
- .input-group-btn > .btn:hover,
- .input-group-btn > .btn:focus,
- .input-group-btn > .btn:active {
- z-index: 2;
- }
- .input-group-btn:first-child > .btn,
- .input-group-btn:first-child > .btn-group {
- margin-right: -1px;
- }
- .input-group-btn:last-child > .btn,
- .input-group-btn:last-child > .btn-group {
- z-index: 2;
- margin-left: -1px;
- }
- .nav {
- margin-bottom: 0;
- padding-left: 0;
- list-style: none;
- }
- .nav > li {
- position: relative;
- display: block;
- }
- .nav > li > a {
- position: relative;
- display: block;
- padding: 10px 15px;
- }
- .nav > li > a:hover,
- .nav > li > a:focus {
- text-decoration: none;
- background-color: #eeeeee;
- }
- .nav > li.disabled > a {
- color: #777777;
- }
- .nav > li.disabled > a:hover,
- .nav > li.disabled > a:focus {
- color: #777777;
- text-decoration: none;
- background-color: transparent;
- cursor: not-allowed;
- }
- .nav .open > a,
- .nav .open > a:hover,
- .nav .open > a:focus {
- background-color: #eeeeee;
- border-color: #337ab7;
- }
- .nav .nav-divider {
- height: 1px;
- margin: 8px 0;
- overflow: hidden;
- background-color: #e5e5e5;
- }
- .nav > li > a > img {
- max-width: none;
- }
- .nav-tabs {
- border-bottom: 1px solid #ddd;
- }
- .nav-tabs > li {
- float: left;
- margin-bottom: -1px;
- }
- .nav-tabs > li > a {
- margin-right: 2px;
- line-height: 1.42857143;
- border: 1px solid transparent;
- border-radius: 2px 2px 0 0;
- }
- .nav-tabs > li > a:hover {
- border-color: #eeeeee #eeeeee #ddd;
- }
- .nav-tabs > li.active > a,
- .nav-tabs > li.active > a:hover,
- .nav-tabs > li.active > a:focus {
- color: #555555;
- background-color: #fff;
- border: 1px solid #ddd;
- border-bottom-color: transparent;
- cursor: default;
- }
- .nav-tabs.nav-justified {
- width: 100%;
- border-bottom: 0;
- }
- .nav-tabs.nav-justified > li {
- float: none;
- }
- .nav-tabs.nav-justified > li > a {
- text-align: center;
- margin-bottom: 5px;
- }
- .nav-tabs.nav-justified > .dropdown .dropdown-menu {
- top: auto;
- left: auto;
- }
- @media (min-width: 768px) {
- .nav-tabs.nav-justified > li {
- display: table-cell;
- width: 1%;
- }
- .nav-tabs.nav-justified > li > a {
- margin-bottom: 0;
- }
- }
- .nav-tabs.nav-justified > li > a {
- margin-right: 0;
- border-radius: 2px;
- }
- .nav-tabs.nav-justified > .active > a,
- .nav-tabs.nav-justified > .active > a:hover,
- .nav-tabs.nav-justified > .active > a:focus {
- border: 1px solid #ddd;
- }
- @media (min-width: 768px) {
- .nav-tabs.nav-justified > li > a {
- border-bottom: 1px solid #ddd;
- border-radius: 2px 2px 0 0;
- }
- .nav-tabs.nav-justified > .active > a,
- .nav-tabs.nav-justified > .active > a:hover,
- .nav-tabs.nav-justified > .active > a:focus {
- border-bottom-color: #fff;
- }
- }
- .nav-pills > li {
- float: left;
- }
- .nav-pills > li > a {
- border-radius: 2px;
- }
- .nav-pills > li + li {
- margin-left: 2px;
- }
- .nav-pills > li.active > a,
- .nav-pills > li.active > a:hover,
- .nav-pills > li.active > a:focus {
- color: #fff;
- background-color: #337ab7;
- }
- .nav-stacked > li {
- float: none;
- }
- .nav-stacked > li + li {
- margin-top: 2px;
- margin-left: 0;
- }
- .nav-justified {
- width: 100%;
- }
- .nav-justified > li {
- float: none;
- }
- .nav-justified > li > a {
- text-align: center;
- margin-bottom: 5px;
- }
- .nav-justified > .dropdown .dropdown-menu {
- top: auto;
- left: auto;
- }
- @media (min-width: 768px) {
- .nav-justified > li {
- display: table-cell;
- width: 1%;
- }
- .nav-justified > li > a {
- margin-bottom: 0;
- }
- }
- .nav-tabs-justified {
- border-bottom: 0;
- }
- .nav-tabs-justified > li > a {
- margin-right: 0;
- border-radius: 2px;
- }
- .nav-tabs-justified > .active > a,
- .nav-tabs-justified > .active > a:hover,
- .nav-tabs-justified > .active > a:focus {
- border: 1px solid #ddd;
- }
- @media (min-width: 768px) {
- .nav-tabs-justified > li > a {
- border-bottom: 1px solid #ddd;
- border-radius: 2px 2px 0 0;
- }
- .nav-tabs-justified > .active > a,
- .nav-tabs-justified > .active > a:hover,
- .nav-tabs-justified > .active > a:focus {
- border-bottom-color: #fff;
- }
- }
- .tab-content > .tab-pane {
- display: none;
- }
- .tab-content > .active {
- display: block;
- }
- .nav-tabs .dropdown-menu {
- margin-top: -1px;
- border-top-right-radius: 0;
- border-top-left-radius: 0;
- }
- .navbar {
- position: relative;
- min-height: 30px;
- margin-bottom: 18px;
- border: 1px solid transparent;
- }
- @media (min-width: 541px) {
- .navbar {
- border-radius: 2px;
- }
- }
- @media (min-width: 541px) {
- .navbar-header {
- float: left;
- }
- }
- .navbar-collapse {
- overflow-x: visible;
- padding-right: 0px;
- padding-left: 0px;
- border-top: 1px solid transparent;
- box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
- -webkit-overflow-scrolling: touch;
- }
- .navbar-collapse.in {
- overflow-y: auto;
- }
- @media (min-width: 541px) {
- .navbar-collapse {
- width: auto;
- border-top: 0;
- box-shadow: none;
- }
- .navbar-collapse.collapse {
- display: block !important;
- height: auto !important;
- padding-bottom: 0;
- overflow: visible !important;
- }
- .navbar-collapse.in {
- overflow-y: visible;
- }
- .navbar-fixed-top .navbar-collapse,
- .navbar-static-top .navbar-collapse,
- .navbar-fixed-bottom .navbar-collapse {
- padding-left: 0;
- padding-right: 0;
- }
- }
- .navbar-fixed-top .navbar-collapse,
- .navbar-fixed-bottom .navbar-collapse {
- max-height: 340px;
- }
- @media (max-device-width: 540px) and (orientation: landscape) {
- .navbar-fixed-top .navbar-collapse,
- .navbar-fixed-bottom .navbar-collapse {
- max-height: 200px;
- }
- }
- .container > .navbar-header,
- .container-fluid > .navbar-header,
- .container > .navbar-collapse,
- .container-fluid > .navbar-collapse {
- margin-right: 0px;
- margin-left: 0px;
- }
- @media (min-width: 541px) {
- .container > .navbar-header,
- .container-fluid > .navbar-header,
- .container > .navbar-collapse,
- .container-fluid > .navbar-collapse {
- margin-right: 0;
- margin-left: 0;
- }
- }
- .navbar-static-top {
- z-index: 1000;
- border-width: 0 0 1px;
- }
- @media (min-width: 541px) {
- .navbar-static-top {
- border-radius: 0;
- }
- }
- .navbar-fixed-top,
- .navbar-fixed-bottom {
- position: fixed;
- right: 0;
- left: 0;
- z-index: 1030;
- }
- @media (min-width: 541px) {
- .navbar-fixed-top,
- .navbar-fixed-bottom {
- border-radius: 0;
- }
- }
- .navbar-fixed-top {
- top: 0;
- border-width: 0 0 1px;
- }
- .navbar-fixed-bottom {
- bottom: 0;
- margin-bottom: 0;
- border-width: 1px 0 0;
- }
- .navbar-brand {
- float: left;
- padding: 6px 0px;
- font-size: 17px;
- line-height: 18px;
- height: 30px;
- }
- .navbar-brand:hover,
- .navbar-brand:focus {
- text-decoration: none;
- }
- .navbar-brand > img {
- display: block;
- }
- @media (min-width: 541px) {
- .navbar > .container .navbar-brand,
- .navbar > .container-fluid .navbar-brand {
- margin-left: 0px;
- }
- }
- .navbar-toggle {
- position: relative;
- float: right;
- margin-right: 0px;
- padding: 9px 10px;
- margin-top: -2px;
- margin-bottom: -2px;
- background-color: transparent;
- background-image: none;
- border: 1px solid transparent;
- border-radius: 2px;
- }
- .navbar-toggle:focus {
- outline: 0;
- }
- .navbar-toggle .icon-bar {
- display: block;
- width: 22px;
- height: 2px;
- border-radius: 1px;
- }
- .navbar-toggle .icon-bar + .icon-bar {
- margin-top: 4px;
- }
- @media (min-width: 541px) {
- .navbar-toggle {
- display: none;
- }
- }
- .navbar-nav {
- margin: 3px 0px;
- }
- .navbar-nav > li > a {
- padding-top: 10px;
- padding-bottom: 10px;
- line-height: 18px;
- }
- @media (max-width: 540px) {
- .navbar-nav .open .dropdown-menu {
- position: static;
- float: none;
- width: auto;
- margin-top: 0;
- background-color: transparent;
- border: 0;
- box-shadow: none;
- }
- .navbar-nav .open .dropdown-menu > li > a,
- .navbar-nav .open .dropdown-menu .dropdown-header {
- padding: 5px 15px 5px 25px;
- }
- .navbar-nav .open .dropdown-menu > li > a {
- line-height: 18px;
- }
- .navbar-nav .open .dropdown-menu > li > a:hover,
- .navbar-nav .open .dropdown-menu > li > a:focus {
- background-image: none;
- }
- }
- @media (min-width: 541px) {
- .navbar-nav {
- float: left;
- margin: 0;
- }
- .navbar-nav > li {
- float: left;
- }
- .navbar-nav > li > a {
- padding-top: 6px;
- padding-bottom: 6px;
- }
- }
- .navbar-form {
- margin-left: 0px;
- margin-right: 0px;
- padding: 10px 0px;
- border-top: 1px solid transparent;
- border-bottom: 1px solid transparent;
- -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
- box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
- margin-top: -1px;
- margin-bottom: -1px;
- }
- @media (min-width: 768px) {
- .navbar-form .form-group {
- display: inline-block;
- margin-bottom: 0;
- vertical-align: middle;
- }
- .navbar-form .form-control {
- display: inline-block;
- width: auto;
- vertical-align: middle;
- }
- .navbar-form .form-control-static {
- display: inline-block;
- }
- .navbar-form .input-group {
- display: inline-table;
- vertical-align: middle;
- }
- .navbar-form .input-group .input-group-addon,
- .navbar-form .input-group .input-group-btn,
- .navbar-form .input-group .form-control {
- width: auto;
- }
- .navbar-form .input-group > .form-control {
- width: 100%;
- }
- .navbar-form .control-label {
- margin-bottom: 0;
- vertical-align: middle;
- }
- .navbar-form .radio,
- .navbar-form .checkbox {
- display: inline-block;
- margin-top: 0;
- margin-bottom: 0;
- vertical-align: middle;
- }
- .navbar-form .radio label,
- .navbar-form .checkbox label {
- padding-left: 0;
- }
- .navbar-form .radio input[type="radio"],
- .navbar-form .checkbox input[type="checkbox"] {
- position: relative;
- margin-left: 0;
- }
- .navbar-form .has-feedback .form-control-feedback {
- top: 0;
- }
- }
- @media (max-width: 540px) {
- .navbar-form .form-group {
- margin-bottom: 5px;
- }
- .navbar-form .form-group:last-child {
- margin-bottom: 0;
- }
- }
- @media (min-width: 541px) {
- .navbar-form {
- width: auto;
- border: 0;
- margin-left: 0;
- margin-right: 0;
- padding-top: 0;
- padding-bottom: 0;
- -webkit-box-shadow: none;
- box-shadow: none;
- }
- }
- .navbar-nav > li > .dropdown-menu {
- margin-top: 0;
- border-top-right-radius: 0;
- border-top-left-radius: 0;
- }
- .navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
- margin-bottom: 0;
- border-top-right-radius: 2px;
- border-top-left-radius: 2px;
- border-bottom-right-radius: 0;
- border-bottom-left-radius: 0;
- }
- .navbar-btn {
- margin-top: -1px;
- margin-bottom: -1px;
- }
- .navbar-btn.btn-sm {
- margin-top: 0px;
- margin-bottom: 0px;
- }
- .navbar-btn.btn-xs {
- margin-top: 4px;
- margin-bottom: 4px;
- }
- .navbar-text {
- margin-top: 6px;
- margin-bottom: 6px;
- }
- @media (min-width: 541px) {
- .navbar-text {
- float: left;
- margin-left: 0px;
- margin-right: 0px;
- }
- }
- @media (min-width: 541px) {
- .navbar-left {
- float: left !important;
- float: left;
- }
- .navbar-right {
- float: right !important;
- float: right;
- margin-right: 0px;
- }
- .navbar-right ~ .navbar-right {
- margin-right: 0;
- }
- }
- .navbar-default {
- background-color: #f8f8f8;
- border-color: #e7e7e7;
- }
- .navbar-default .navbar-brand {
- color: #777;
- }
- .navbar-default .navbar-brand:hover,
- .navbar-default .navbar-brand:focus {
- color: #5e5e5e;
- background-color: transparent;
- }
- .navbar-default .navbar-text {
- color: #777;
- }
- .navbar-default .navbar-nav > li > a {
- color: #777;
- }
- .navbar-default .navbar-nav > li > a:hover,
- .navbar-default .navbar-nav > li > a:focus {
- color: #333;
- background-color: transparent;
- }
- .navbar-default .navbar-nav > .active > a,
- .navbar-default .navbar-nav > .active > a:hover,
- .navbar-default .navbar-nav > .active > a:focus {
- color: #555;
- background-color: #e7e7e7;
- }
- .navbar-default .navbar-nav > .disabled > a,
- .navbar-default .navbar-nav > .disabled > a:hover,
- .navbar-default .navbar-nav > .disabled > a:focus {
- color: #ccc;
- background-color: transparent;
- }
- .navbar-default .navbar-toggle {
- border-color: #ddd;
- }
- .navbar-default .navbar-toggle:hover,
- .navbar-default .navbar-toggle:focus {
- background-color: #ddd;
- }
- .navbar-default .navbar-toggle .icon-bar {
- background-color: #888;
- }
- .navbar-default .navbar-collapse,
- .navbar-default .navbar-form {
- border-color: #e7e7e7;
- }
- .navbar-default .navbar-nav > .open > a,
- .navbar-default .navbar-nav > .open > a:hover,
- .navbar-default .navbar-nav > .open > a:focus {
- background-color: #e7e7e7;
- color: #555;
- }
- @media (max-width: 540px) {
- .navbar-default .navbar-nav .open .dropdown-menu > li > a {
- color: #777;
- }
- .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
- .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
- color: #333;
- background-color: transparent;
- }
- .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
- .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
- .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
- color: #555;
- background-color: #e7e7e7;
- }
- .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
- .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
- .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
- color: #ccc;
- background-color: transparent;
- }
- }
- .navbar-default .navbar-link {
- color: #777;
- }
- .navbar-default .navbar-link:hover {
- color: #333;
- }
- .navbar-default .btn-link {
- color: #777;
- }
- .navbar-default .btn-link:hover,
- .navbar-default .btn-link:focus {
- color: #333;
- }
- .navbar-default .btn-link[disabled]:hover,
- fieldset[disabled] .navbar-default .btn-link:hover,
- .navbar-default .btn-link[disabled]:focus,
- fieldset[disabled] .navbar-default .btn-link:focus {
- color: #ccc;
- }
- .navbar-inverse {
- background-color: #222;
- border-color: #080808;
- }
- .navbar-inverse .navbar-brand {
- color: #9d9d9d;
- }
- .navbar-inverse .navbar-brand:hover,
- .navbar-inverse .navbar-brand:focus {
- color: #fff;
- background-color: transparent;
- }
- .navbar-inverse .navbar-text {
- color: #9d9d9d;
- }
- .navbar-inverse .navbar-nav > li > a {
- color: #9d9d9d;
- }
- .navbar-inverse .navbar-nav > li > a:hover,
- .navbar-inverse .navbar-nav > li > a:focus {
- color: #fff;
- background-color: transparent;
- }
- .navbar-inverse .navbar-nav > .active > a,
- .navbar-inverse .navbar-nav > .active > a:hover,
- .navbar-inverse .navbar-nav > .active > a:focus {
- color: #fff;
- background-color: #080808;
- }
- .navbar-inverse .navbar-nav > .disabled > a,
- .navbar-inverse .navbar-nav > .disabled > a:hover,
- .navbar-inverse .navbar-nav > .disabled > a:focus {
- color: #444;
- background-color: transparent;
- }
- .navbar-inverse .navbar-toggle {
- border-color: #333;
- }
- .navbar-inverse .navbar-toggle:hover,
- .navbar-inverse .navbar-toggle:focus {
- background-color: #333;
- }
- .navbar-inverse .navbar-toggle .icon-bar {
- background-color: #fff;
- }
- .navbar-inverse .navbar-collapse,
- .navbar-inverse .navbar-form {
- border-color: #101010;
- }
- .navbar-inverse .navbar-nav > .open > a,
- .navbar-inverse .navbar-nav > .open > a:hover,
- .navbar-inverse .navbar-nav > .open > a:focus {
- background-color: #080808;
- color: #fff;
- }
- @media (max-width: 540px) {
- .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
- border-color: #080808;
- }
- .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
- background-color: #080808;
- }
- .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
- color: #9d9d9d;
- }
- .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
- .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
- color: #fff;
- background-color: transparent;
- }
- .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
- .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
- .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
- color: #fff;
- background-color: #080808;
- }
- .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
- .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
- .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
- color: #444;
- background-color: transparent;
- }
- }
- .navbar-inverse .navbar-link {
- color: #9d9d9d;
- }
- .navbar-inverse .navbar-link:hover {
- color: #fff;
- }
- .navbar-inverse .btn-link {
- color: #9d9d9d;
- }
- .navbar-inverse .btn-link:hover,
- .navbar-inverse .btn-link:focus {
- color: #fff;
- }
- .navbar-inverse .btn-link[disabled]:hover,
- fieldset[disabled] .navbar-inverse .btn-link:hover,
- .navbar-inverse .btn-link[disabled]:focus,
- fieldset[disabled] .navbar-inverse .btn-link:focus {
- color: #444;
- }
- .breadcrumb {
- padding: 8px 15px;
- margin-bottom: 18px;
- list-style: none;
- background-color: #f5f5f5;
- border-radius: 2px;
- }
- .breadcrumb > li {
- display: inline-block;
- }
- .breadcrumb > li + li:before {
- content: "/\00a0";
- padding: 0 5px;
- color: #5e5e5e;
- }
- .breadcrumb > .active {
- color: #777777;
- }
- .pagination {
- display: inline-block;
- padding-left: 0;
- margin: 18px 0;
- border-radius: 2px;
- }
- .pagination > li {
- display: inline;
- }
- .pagination > li > a,
- .pagination > li > span {
- position: relative;
- float: left;
- padding: 6px 12px;
- line-height: 1.42857143;
- text-decoration: none;
- color: #337ab7;
- background-color: #fff;
- border: 1px solid #ddd;
- margin-left: -1px;
- }
- .pagination > li:first-child > a,
- .pagination > li:first-child > span {
- margin-left: 0;
- border-bottom-left-radius: 2px;
- border-top-left-radius: 2px;
- }
- .pagination > li:last-child > a,
- .pagination > li:last-child > span {
- border-bottom-right-radius: 2px;
- border-top-right-radius: 2px;
- }
- .pagination > li > a:hover,
- .pagination > li > span:hover,
- .pagination > li > a:focus,
- .pagination > li > span:focus {
- z-index: 2;
- color: #23527c;
- background-color: #eeeeee;
- border-color: #ddd;
- }
- .pagination > .active > a,
- .pagination > .active > span,
- .pagination > .active > a:hover,
- .pagination > .active > span:hover,
- .pagination > .active > a:focus,
- .pagination > .active > span:focus {
- z-index: 3;
- color: #fff;
- background-color: #337ab7;
- border-color: #337ab7;
- cursor: default;
- }
- .pagination > .disabled > span,
- .pagination > .disabled > span:hover,
- .pagination > .disabled > span:focus,
- .pagination > .disabled > a,
- .pagination > .disabled > a:hover,
- .pagination > .disabled > a:focus {
- color: #777777;
- background-color: #fff;
- border-color: #ddd;
- cursor: not-allowed;
- }
- .pagination-lg > li > a,
- .pagination-lg > li > span {
- padding: 10px 16px;
- font-size: 17px;
- line-height: 1.3333333;
- }
- .pagination-lg > li:first-child > a,
- .pagination-lg > li:first-child > span {
- border-bottom-left-radius: 3px;
- border-top-left-radius: 3px;
- }
- .pagination-lg > li:last-child > a,
- .pagination-lg > li:last-child > span {
- border-bottom-right-radius: 3px;
- border-top-right-radius: 3px;
- }
- .pagination-sm > li > a,
- .pagination-sm > li > span {
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- }
- .pagination-sm > li:first-child > a,
- .pagination-sm > li:first-child > span {
- border-bottom-left-radius: 1px;
- border-top-left-radius: 1px;
- }
- .pagination-sm > li:last-child > a,
- .pagination-sm > li:last-child > span {
- border-bottom-right-radius: 1px;
- border-top-right-radius: 1px;
- }
- .pager {
- padding-left: 0;
- margin: 18px 0;
- list-style: none;
- text-align: center;
- }
- .pager li {
- display: inline;
- }
- .pager li > a,
- .pager li > span {
- display: inline-block;
- padding: 5px 14px;
- background-color: #fff;
- border: 1px solid #ddd;
- border-radius: 15px;
- }
- .pager li > a:hover,
- .pager li > a:focus {
- text-decoration: none;
- background-color: #eeeeee;
- }
- .pager .next > a,
- .pager .next > span {
- float: right;
- }
- .pager .previous > a,
- .pager .previous > span {
- float: left;
- }
- .pager .disabled > a,
- .pager .disabled > a:hover,
- .pager .disabled > a:focus,
- .pager .disabled > span {
- color: #777777;
- background-color: #fff;
- cursor: not-allowed;
- }
- .label {
- display: inline;
- padding: .2em .6em .3em;
- font-size: 75%;
- font-weight: bold;
- line-height: 1;
- color: #fff;
- text-align: center;
- white-space: nowrap;
- vertical-align: baseline;
- border-radius: .25em;
- }
- a.label:hover,
- a.label:focus {
- color: #fff;
- text-decoration: none;
- cursor: pointer;
- }
- .label:empty {
- display: none;
- }
- .btn .label {
- position: relative;
- top: -1px;
- }
- .label-default {
- background-color: #777777;
- }
- .label-default[href]:hover,
- .label-default[href]:focus {
- background-color: #5e5e5e;
- }
- .label-primary {
- background-color: #337ab7;
- }
- .label-primary[href]:hover,
- .label-primary[href]:focus {
- background-color: #286090;
- }
- .label-success {
- background-color: #5cb85c;
- }
- .label-success[href]:hover,
- .label-success[href]:focus {
- background-color: #449d44;
- }
- .label-info {
- background-color: #5bc0de;
- }
- .label-info[href]:hover,
- .label-info[href]:focus {
- background-color: #31b0d5;
- }
- .label-warning {
- background-color: #f0ad4e;
- }
- .label-warning[href]:hover,
- .label-warning[href]:focus {
- background-color: #ec971f;
- }
- .label-danger {
- background-color: #d9534f;
- }
- .label-danger[href]:hover,
- .label-danger[href]:focus {
- background-color: #c9302c;
- }
- .badge {
- display: inline-block;
- min-width: 10px;
- padding: 3px 7px;
- font-size: 12px;
- font-weight: bold;
- color: #fff;
- line-height: 1;
- vertical-align: middle;
- white-space: nowrap;
- text-align: center;
- background-color: #777777;
- border-radius: 10px;
- }
- .badge:empty {
- display: none;
- }
- .btn .badge {
- position: relative;
- top: -1px;
- }
- .btn-xs .badge,
- .btn-group-xs > .btn .badge {
- top: 0;
- padding: 1px 5px;
- }
- a.badge:hover,
- a.badge:focus {
- color: #fff;
- text-decoration: none;
- cursor: pointer;
- }
- .list-group-item.active > .badge,
- .nav-pills > .active > a > .badge {
- color: #337ab7;
- background-color: #fff;
- }
- .list-group-item > .badge {
- float: right;
- }
- .list-group-item > .badge + .badge {
- margin-right: 5px;
- }
- .nav-pills > li > a > .badge {
- margin-left: 3px;
- }
- .jumbotron {
- padding-top: 30px;
- padding-bottom: 30px;
- margin-bottom: 30px;
- color: inherit;
- background-color: #eeeeee;
- }
- .jumbotron h1,
- .jumbotron .h1 {
- color: inherit;
- }
- .jumbotron p {
- margin-bottom: 15px;
- font-size: 20px;
- font-weight: 200;
- }
- .jumbotron > hr {
- border-top-color: #d5d5d5;
- }
- .container .jumbotron,
- .container-fluid .jumbotron {
- border-radius: 3px;
- padding-left: 0px;
- padding-right: 0px;
- }
- .jumbotron .container {
- max-width: 100%;
- }
- @media screen and (min-width: 768px) {
- .jumbotron {
- padding-top: 48px;
- padding-bottom: 48px;
- }
- .container .jumbotron,
- .container-fluid .jumbotron {
- padding-left: 60px;
- padding-right: 60px;
- }
- .jumbotron h1,
- .jumbotron .h1 {
- font-size: 59px;
- }
- }
- .thumbnail {
- display: block;
- padding: 4px;
- margin-bottom: 18px;
- line-height: 1.42857143;
- background-color: #fff;
- border: 1px solid #ddd;
- border-radius: 2px;
- -webkit-transition: border 0.2s ease-in-out;
- -o-transition: border 0.2s ease-in-out;
- transition: border 0.2s ease-in-out;
- }
- .thumbnail > img,
- .thumbnail a > img {
- margin-left: auto;
- margin-right: auto;
- }
- a.thumbnail:hover,
- a.thumbnail:focus,
- a.thumbnail.active {
- border-color: #337ab7;
- }
- .thumbnail .caption {
- padding: 9px;
- color: #000;
- }
- .alert {
- padding: 15px;
- margin-bottom: 18px;
- border: 1px solid transparent;
- border-radius: 2px;
- }
- .alert h4 {
- margin-top: 0;
- color: inherit;
- }
- .alert .alert-link {
- font-weight: bold;
- }
- .alert > p,
- .alert > ul {
- margin-bottom: 0;
- }
- .alert > p + p {
- margin-top: 5px;
- }
- .alert-dismissable,
- .alert-dismissible {
- padding-right: 35px;
- }
- .alert-dismissable .close,
- .alert-dismissible .close {
- position: relative;
- top: -2px;
- right: -21px;
- color: inherit;
- }
- .alert-success {
- background-color: #dff0d8;
- border-color: #d6e9c6;
- color: #3c763d;
- }
- .alert-success hr {
- border-top-color: #c9e2b3;
- }
- .alert-success .alert-link {
- color: #2b542c;
- }
- .alert-info {
- background-color: #d9edf7;
- border-color: #bce8f1;
- color: #31708f;
- }
- .alert-info hr {
- border-top-color: #a6e1ec;
- }
- .alert-info .alert-link {
- color: #245269;
- }
- .alert-warning {
- background-color: #fcf8e3;
- border-color: #faebcc;
- color: #8a6d3b;
- }
- .alert-warning hr {
- border-top-color: #f7e1b5;
- }
- .alert-warning .alert-link {
- color: #66512c;
- }
- .alert-danger {
- background-color: #f2dede;
- border-color: #ebccd1;
- color: #a94442;
- }
- .alert-danger hr {
- border-top-color: #e4b9c0;
- }
- .alert-danger .alert-link {
- color: #843534;
- }
- @-webkit-keyframes progress-bar-stripes {
- from {
- background-position: 40px 0;
- }
- to {
- background-position: 0 0;
- }
- }
- @keyframes progress-bar-stripes {
- from {
- background-position: 40px 0;
- }
- to {
- background-position: 0 0;
- }
- }
- .progress {
- overflow: hidden;
- height: 18px;
- margin-bottom: 18px;
- background-color: #f5f5f5;
- border-radius: 2px;
- -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
- box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
- }
- .progress-bar {
- float: left;
- width: 0%;
- height: 100%;
- font-size: 12px;
- line-height: 18px;
- color: #fff;
- text-align: center;
- background-color: #337ab7;
- -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
- box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
- -webkit-transition: width 0.6s ease;
- -o-transition: width 0.6s ease;
- transition: width 0.6s ease;
- }
- .progress-striped .progress-bar,
- .progress-bar-striped {
- background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-size: 40px 40px;
- }
- .progress.active .progress-bar,
- .progress-bar.active {
- -webkit-animation: progress-bar-stripes 2s linear infinite;
- -o-animation: progress-bar-stripes 2s linear infinite;
- animation: progress-bar-stripes 2s linear infinite;
- }
- .progress-bar-success {
- background-color: #5cb85c;
- }
- .progress-striped .progress-bar-success {
- background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- }
- .progress-bar-info {
- background-color: #5bc0de;
- }
- .progress-striped .progress-bar-info {
- background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- }
- .progress-bar-warning {
- background-color: #f0ad4e;
- }
- .progress-striped .progress-bar-warning {
- background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- }
- .progress-bar-danger {
- background-color: #d9534f;
- }
- .progress-striped .progress-bar-danger {
- background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
- }
- .media {
- margin-top: 15px;
- }
- .media:first-child {
- margin-top: 0;
- }
- .media,
- .media-body {
- zoom: 1;
- overflow: hidden;
- }
- .media-body {
- width: 10000px;
- }
- .media-object {
- display: block;
- }
- .media-object.img-thumbnail {
- max-width: none;
- }
- .media-right,
- .media > .pull-right {
- padding-left: 10px;
- }
- .media-left,
- .media > .pull-left {
- padding-right: 10px;
- }
- .media-left,
- .media-right,
- .media-body {
- display: table-cell;
- vertical-align: top;
- }
- .media-middle {
- vertical-align: middle;
- }
- .media-bottom {
- vertical-align: bottom;
- }
- .media-heading {
- margin-top: 0;
- margin-bottom: 5px;
- }
- .media-list {
- padding-left: 0;
- list-style: none;
- }
- .list-group {
- margin-bottom: 20px;
- padding-left: 0;
- }
- .list-group-item {
- position: relative;
- display: block;
- padding: 10px 15px;
- margin-bottom: -1px;
- background-color: #fff;
- border: 1px solid #ddd;
- }
- .list-group-item:first-child {
- border-top-right-radius: 2px;
- border-top-left-radius: 2px;
- }
- .list-group-item:last-child {
- margin-bottom: 0;
- border-bottom-right-radius: 2px;
- border-bottom-left-radius: 2px;
- }
- a.list-group-item,
- button.list-group-item {
- color: #555;
- }
- a.list-group-item .list-group-item-heading,
- button.list-group-item .list-group-item-heading {
- color: #333;
- }
- a.list-group-item:hover,
- button.list-group-item:hover,
- a.list-group-item:focus,
- button.list-group-item:focus {
- text-decoration: none;
- color: #555;
- background-color: #f5f5f5;
- }
- button.list-group-item {
- width: 100%;
- text-align: left;
- }
- .list-group-item.disabled,
- .list-group-item.disabled:hover,
- .list-group-item.disabled:focus {
- background-color: #eeeeee;
- color: #777777;
- cursor: not-allowed;
- }
- .list-group-item.disabled .list-group-item-heading,
- .list-group-item.disabled:hover .list-group-item-heading,
- .list-group-item.disabled:focus .list-group-item-heading {
- color: inherit;
- }
- .list-group-item.disabled .list-group-item-text,
- .list-group-item.disabled:hover .list-group-item-text,
- .list-group-item.disabled:focus .list-group-item-text {
- color: #777777;
- }
- .list-group-item.active,
- .list-group-item.active:hover,
- .list-group-item.active:focus {
- z-index: 2;
- color: #fff;
- background-color: #337ab7;
- border-color: #337ab7;
- }
- .list-group-item.active .list-group-item-heading,
- .list-group-item.active:hover .list-group-item-heading,
- .list-group-item.active:focus .list-group-item-heading,
- .list-group-item.active .list-group-item-heading > small,
- .list-group-item.active:hover .list-group-item-heading > small,
- .list-group-item.active:focus .list-group-item-heading > small,
- .list-group-item.active .list-group-item-heading > .small,
- .list-group-item.active:hover .list-group-item-heading > .small,
- .list-group-item.active:focus .list-group-item-heading > .small {
- color: inherit;
- }
- .list-group-item.active .list-group-item-text,
- .list-group-item.active:hover .list-group-item-text,
- .list-group-item.active:focus .list-group-item-text {
- color: #c7ddef;
- }
- .list-group-item-success {
- color: #3c763d;
- background-color: #dff0d8;
- }
- a.list-group-item-success,
- button.list-group-item-success {
- color: #3c763d;
- }
- a.list-group-item-success .list-group-item-heading,
- button.list-group-item-success .list-group-item-heading {
- color: inherit;
- }
- a.list-group-item-success:hover,
- button.list-group-item-success:hover,
- a.list-group-item-success:focus,
- button.list-group-item-success:focus {
- color: #3c763d;
- background-color: #d0e9c6;
- }
- a.list-group-item-success.active,
- button.list-group-item-success.active,
- a.list-group-item-success.active:hover,
- button.list-group-item-success.active:hover,
- a.list-group-item-success.active:focus,
- button.list-group-item-success.active:focus {
- color: #fff;
- background-color: #3c763d;
- border-color: #3c763d;
- }
- .list-group-item-info {
- color: #31708f;
- background-color: #d9edf7;
- }
- a.list-group-item-info,
- button.list-group-item-info {
- color: #31708f;
- }
- a.list-group-item-info .list-group-item-heading,
- button.list-group-item-info .list-group-item-heading {
- color: inherit;
- }
- a.list-group-item-info:hover,
- button.list-group-item-info:hover,
- a.list-group-item-info:focus,
- button.list-group-item-info:focus {
- color: #31708f;
- background-color: #c4e3f3;
- }
- a.list-group-item-info.active,
- button.list-group-item-info.active,
- a.list-group-item-info.active:hover,
- button.list-group-item-info.active:hover,
- a.list-group-item-info.active:focus,
- button.list-group-item-info.active:focus {
- color: #fff;
- background-color: #31708f;
- border-color: #31708f;
- }
- .list-group-item-warning {
- color: #8a6d3b;
- background-color: #fcf8e3;
- }
- a.list-group-item-warning,
- button.list-group-item-warning {
- color: #8a6d3b;
- }
- a.list-group-item-warning .list-group-item-heading,
- button.list-group-item-warning .list-group-item-heading {
- color: inherit;
- }
- a.list-group-item-warning:hover,
- button.list-group-item-warning:hover,
- a.list-group-item-warning:focus,
- button.list-group-item-warning:focus {
- color: #8a6d3b;
- background-color: #faf2cc;
- }
- a.list-group-item-warning.active,
- button.list-group-item-warning.active,
- a.list-group-item-warning.active:hover,
- button.list-group-item-warning.active:hover,
- a.list-group-item-warning.active:focus,
- button.list-group-item-warning.active:focus {
- color: #fff;
- background-color: #8a6d3b;
- border-color: #8a6d3b;
- }
- .list-group-item-danger {
- color: #a94442;
- background-color: #f2dede;
- }
- a.list-group-item-danger,
- button.list-group-item-danger {
- color: #a94442;
- }
- a.list-group-item-danger .list-group-item-heading,
- button.list-group-item-danger .list-group-item-heading {
- color: inherit;
- }
- a.list-group-item-danger:hover,
- button.list-group-item-danger:hover,
- a.list-group-item-danger:focus,
- button.list-group-item-danger:focus {
- color: #a94442;
- background-color: #ebcccc;
- }
- a.list-group-item-danger.active,
- button.list-group-item-danger.active,
- a.list-group-item-danger.active:hover,
- button.list-group-item-danger.active:hover,
- a.list-group-item-danger.active:focus,
- button.list-group-item-danger.active:focus {
- color: #fff;
- background-color: #a94442;
- border-color: #a94442;
- }
- .list-group-item-heading {
- margin-top: 0;
- margin-bottom: 5px;
- }
- .list-group-item-text {
- margin-bottom: 0;
- line-height: 1.3;
- }
- .panel {
- margin-bottom: 18px;
- background-color: #fff;
- border: 1px solid transparent;
- border-radius: 2px;
- -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
- box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
- }
- .panel-body {
- padding: 15px;
- }
- .panel-heading {
- padding: 10px 15px;
- border-bottom: 1px solid transparent;
- border-top-right-radius: 1px;
- border-top-left-radius: 1px;
- }
- .panel-heading > .dropdown .dropdown-toggle {
- color: inherit;
- }
- .panel-title {
- margin-top: 0;
- margin-bottom: 0;
- font-size: 15px;
- color: inherit;
- }
- .panel-title > a,
- .panel-title > small,
- .panel-title > .small,
- .panel-title > small > a,
- .panel-title > .small > a {
- color: inherit;
- }
- .panel-footer {
- padding: 10px 15px;
- background-color: #f5f5f5;
- border-top: 1px solid #ddd;
- border-bottom-right-radius: 1px;
- border-bottom-left-radius: 1px;
- }
- .panel > .list-group,
- .panel > .panel-collapse > .list-group {
- margin-bottom: 0;
- }
- .panel > .list-group .list-group-item,
- .panel > .panel-collapse > .list-group .list-group-item {
- border-width: 1px 0;
- border-radius: 0;
- }
- .panel > .list-group:first-child .list-group-item:first-child,
- .panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
- border-top: 0;
- border-top-right-radius: 1px;
- border-top-left-radius: 1px;
- }
- .panel > .list-group:last-child .list-group-item:last-child,
- .panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
- border-bottom: 0;
- border-bottom-right-radius: 1px;
- border-bottom-left-radius: 1px;
- }
- .panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
- border-top-right-radius: 0;
- border-top-left-radius: 0;
- }
- .panel-heading + .list-group .list-group-item:first-child {
- border-top-width: 0;
- }
- .list-group + .panel-footer {
- border-top-width: 0;
- }
- .panel > .table,
- .panel > .table-responsive > .table,
- .panel > .panel-collapse > .table {
- margin-bottom: 0;
- }
- .panel > .table caption,
- .panel > .table-responsive > .table caption,
- .panel > .panel-collapse > .table caption {
- padding-left: 15px;
- padding-right: 15px;
- }
- .panel > .table:first-child,
- .panel > .table-responsive:first-child > .table:first-child {
- border-top-right-radius: 1px;
- border-top-left-radius: 1px;
- }
- .panel > .table:first-child > thead:first-child > tr:first-child,
- .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
- .panel > .table:first-child > tbody:first-child > tr:first-child,
- .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
- border-top-left-radius: 1px;
- border-top-right-radius: 1px;
- }
- .panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
- .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
- .panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
- .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
- .panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
- .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
- .panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
- .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
- border-top-left-radius: 1px;
- }
- .panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
- .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
- .panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
- .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
- .panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
- .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
- .panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
- .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
- border-top-right-radius: 1px;
- }
- .panel > .table:last-child,
- .panel > .table-responsive:last-child > .table:last-child {
- border-bottom-right-radius: 1px;
- border-bottom-left-radius: 1px;
- }
- .panel > .table:last-child > tbody:last-child > tr:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
- .panel > .table:last-child > tfoot:last-child > tr:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
- border-bottom-left-radius: 1px;
- border-bottom-right-radius: 1px;
- }
- .panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
- .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
- .panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
- .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
- .panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
- .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
- .panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
- .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
- border-bottom-left-radius: 1px;
- }
- .panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
- .panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
- .panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
- .panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
- .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
- border-bottom-right-radius: 1px;
- }
- .panel > .panel-body + .table,
- .panel > .panel-body + .table-responsive,
- .panel > .table + .panel-body,
- .panel > .table-responsive + .panel-body {
- border-top: 1px solid #ddd;
- }
- .panel > .table > tbody:first-child > tr:first-child th,
- .panel > .table > tbody:first-child > tr:first-child td {
- border-top: 0;
- }
- .panel > .table-bordered,
- .panel > .table-responsive > .table-bordered {
- border: 0;
- }
- .panel > .table-bordered > thead > tr > th:first-child,
- .panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
- .panel > .table-bordered > tbody > tr > th:first-child,
- .panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
- .panel > .table-bordered > tfoot > tr > th:first-child,
- .panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
- .panel > .table-bordered > thead > tr > td:first-child,
- .panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
- .panel > .table-bordered > tbody > tr > td:first-child,
- .panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
- .panel > .table-bordered > tfoot > tr > td:first-child,
- .panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
- border-left: 0;
- }
- .panel > .table-bordered > thead > tr > th:last-child,
- .panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
- .panel > .table-bordered > tbody > tr > th:last-child,
- .panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
- .panel > .table-bordered > tfoot > tr > th:last-child,
- .panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
- .panel > .table-bordered > thead > tr > td:last-child,
- .panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
- .panel > .table-bordered > tbody > tr > td:last-child,
- .panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
- .panel > .table-bordered > tfoot > tr > td:last-child,
- .panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
- border-right: 0;
- }
- .panel > .table-bordered > thead > tr:first-child > td,
- .panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
- .panel > .table-bordered > tbody > tr:first-child > td,
- .panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
- .panel > .table-bordered > thead > tr:first-child > th,
- .panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
- .panel > .table-bordered > tbody > tr:first-child > th,
- .panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
- border-bottom: 0;
- }
- .panel > .table-bordered > tbody > tr:last-child > td,
- .panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
- .panel > .table-bordered > tfoot > tr:last-child > td,
- .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
- .panel > .table-bordered > tbody > tr:last-child > th,
- .panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
- .panel > .table-bordered > tfoot > tr:last-child > th,
- .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
- border-bottom: 0;
- }
- .panel > .table-responsive {
- border: 0;
- margin-bottom: 0;
- }
- .panel-group {
- margin-bottom: 18px;
- }
- .panel-group .panel {
- margin-bottom: 0;
- border-radius: 2px;
- }
- .panel-group .panel + .panel {
- margin-top: 5px;
- }
- .panel-group .panel-heading {
- border-bottom: 0;
- }
- .panel-group .panel-heading + .panel-collapse > .panel-body,
- .panel-group .panel-heading + .panel-collapse > .list-group {
- border-top: 1px solid #ddd;
- }
- .panel-group .panel-footer {
- border-top: 0;
- }
- .panel-group .panel-footer + .panel-collapse .panel-body {
- border-bottom: 1px solid #ddd;
- }
- .panel-default {
- border-color: #ddd;
- }
- .panel-default > .panel-heading {
- color: #333333;
- background-color: #f5f5f5;
- border-color: #ddd;
- }
- .panel-default > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #ddd;
- }
- .panel-default > .panel-heading .badge {
- color: #f5f5f5;
- background-color: #333333;
- }
- .panel-default > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #ddd;
- }
- .panel-primary {
- border-color: #337ab7;
- }
- .panel-primary > .panel-heading {
- color: #fff;
- background-color: #337ab7;
- border-color: #337ab7;
- }
- .panel-primary > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #337ab7;
- }
- .panel-primary > .panel-heading .badge {
- color: #337ab7;
- background-color: #fff;
- }
- .panel-primary > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #337ab7;
- }
- .panel-success {
- border-color: #d6e9c6;
- }
- .panel-success > .panel-heading {
- color: #3c763d;
- background-color: #dff0d8;
- border-color: #d6e9c6;
- }
- .panel-success > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #d6e9c6;
- }
- .panel-success > .panel-heading .badge {
- color: #dff0d8;
- background-color: #3c763d;
- }
- .panel-success > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #d6e9c6;
- }
- .panel-info {
- border-color: #bce8f1;
- }
- .panel-info > .panel-heading {
- color: #31708f;
- background-color: #d9edf7;
- border-color: #bce8f1;
- }
- .panel-info > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #bce8f1;
- }
- .panel-info > .panel-heading .badge {
- color: #d9edf7;
- background-color: #31708f;
- }
- .panel-info > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #bce8f1;
- }
- .panel-warning {
- border-color: #faebcc;
- }
- .panel-warning > .panel-heading {
- color: #8a6d3b;
- background-color: #fcf8e3;
- border-color: #faebcc;
- }
- .panel-warning > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #faebcc;
- }
- .panel-warning > .panel-heading .badge {
- color: #fcf8e3;
- background-color: #8a6d3b;
- }
- .panel-warning > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #faebcc;
- }
- .panel-danger {
- border-color: #ebccd1;
- }
- .panel-danger > .panel-heading {
- color: #a94442;
- background-color: #f2dede;
- border-color: #ebccd1;
- }
- .panel-danger > .panel-heading + .panel-collapse > .panel-body {
- border-top-color: #ebccd1;
- }
- .panel-danger > .panel-heading .badge {
- color: #f2dede;
- background-color: #a94442;
- }
- .panel-danger > .panel-footer + .panel-collapse > .panel-body {
- border-bottom-color: #ebccd1;
- }
- .embed-responsive {
- position: relative;
- display: block;
- height: 0;
- padding: 0;
- overflow: hidden;
- }
- .embed-responsive .embed-responsive-item,
- .embed-responsive iframe,
- .embed-responsive embed,
- .embed-responsive object,
- .embed-responsive video {
- position: absolute;
- top: 0;
- left: 0;
- bottom: 0;
- height: 100%;
- width: 100%;
- border: 0;
- }
- .embed-responsive-16by9 {
- padding-bottom: 56.25%;
- }
- .embed-responsive-4by3 {
- padding-bottom: 75%;
- }
- .well {
- min-height: 20px;
- padding: 19px;
- margin-bottom: 20px;
- background-color: #f5f5f5;
- border: 1px solid #e3e3e3;
- border-radius: 2px;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
- }
- .well blockquote {
- border-color: #ddd;
- border-color: rgba(0, 0, 0, 0.15);
- }
- .well-lg {
- padding: 24px;
- border-radius: 3px;
- }
- .well-sm {
- padding: 9px;
- border-radius: 1px;
- }
- .close {
- float: right;
- font-size: 19.5px;
- font-weight: bold;
- line-height: 1;
- color: #000;
- text-shadow: 0 1px 0 #fff;
- opacity: 0.2;
- filter: alpha(opacity=20);
- }
- .close:hover,
- .close:focus {
- color: #000;
- text-decoration: none;
- cursor: pointer;
- opacity: 0.5;
- filter: alpha(opacity=50);
- }
- button.close {
- padding: 0;
- cursor: pointer;
- background: transparent;
- border: 0;
- -webkit-appearance: none;
- }
- .modal-open {
- overflow: hidden;
- }
- .modal {
- display: none;
- overflow: hidden;
- position: fixed;
- top: 0;
- right: 0;
- bottom: 0;
- left: 0;
- z-index: 1050;
- -webkit-overflow-scrolling: touch;
- outline: 0;
- }
- .modal.fade .modal-dialog {
- -webkit-transform: translate(0, -25%);
- -ms-transform: translate(0, -25%);
- -o-transform: translate(0, -25%);
- transform: translate(0, -25%);
- -webkit-transition: -webkit-transform 0.3s ease-out;
- -moz-transition: -moz-transform 0.3s ease-out;
- -o-transition: -o-transform 0.3s ease-out;
- transition: transform 0.3s ease-out;
- }
- .modal.in .modal-dialog {
- -webkit-transform: translate(0, 0);
- -ms-transform: translate(0, 0);
- -o-transform: translate(0, 0);
- transform: translate(0, 0);
- }
- .modal-open .modal {
- overflow-x: hidden;
- overflow-y: auto;
- }
- .modal-dialog {
- position: relative;
- width: auto;
- margin: 10px;
- }
- .modal-content {
- position: relative;
- background-color: #fff;
- border: 1px solid #999;
- border: 1px solid rgba(0, 0, 0, 0.2);
- border-radius: 3px;
- -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
- box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
- background-clip: padding-box;
- outline: 0;
- }
- .modal-backdrop {
- position: fixed;
- top: 0;
- right: 0;
- bottom: 0;
- left: 0;
- z-index: 1040;
- background-color: #000;
- }
- .modal-backdrop.fade {
- opacity: 0;
- filter: alpha(opacity=0);
- }
- .modal-backdrop.in {
- opacity: 0.5;
- filter: alpha(opacity=50);
- }
- .modal-header {
- padding: 15px;
- border-bottom: 1px solid #e5e5e5;
- }
- .modal-header .close {
- margin-top: -2px;
- }
- .modal-title {
- margin: 0;
- line-height: 1.42857143;
- }
- .modal-body {
- position: relative;
- padding: 15px;
- }
- .modal-footer {
- padding: 15px;
- text-align: right;
- border-top: 1px solid #e5e5e5;
- }
- .modal-footer .btn + .btn {
- margin-left: 5px;
- margin-bottom: 0;
- }
- .modal-footer .btn-group .btn + .btn {
- margin-left: -1px;
- }
- .modal-footer .btn-block + .btn-block {
- margin-left: 0;
- }
- .modal-scrollbar-measure {
- position: absolute;
- top: -9999px;
- width: 50px;
- height: 50px;
- overflow: scroll;
- }
- @media (min-width: 768px) {
- .modal-dialog {
- width: 600px;
- margin: 30px auto;
- }
- .modal-content {
- -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
- box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
- }
- .modal-sm {
- width: 300px;
- }
- }
- @media (min-width: 992px) {
- .modal-lg {
- width: 900px;
- }
- }
- .tooltip {
- position: absolute;
- z-index: 1070;
- display: block;
- font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
- font-style: normal;
- font-weight: normal;
- letter-spacing: normal;
- line-break: auto;
- line-height: 1.42857143;
- text-align: left;
- text-align: start;
- text-decoration: none;
- text-shadow: none;
- text-transform: none;
- white-space: normal;
- word-break: normal;
- word-spacing: normal;
- word-wrap: normal;
- font-size: 12px;
- opacity: 0;
- filter: alpha(opacity=0);
- }
- .tooltip.in {
- opacity: 0.9;
- filter: alpha(opacity=90);
- }
- .tooltip.top {
- margin-top: -3px;
- padding: 5px 0;
- }
- .tooltip.right {
- margin-left: 3px;
- padding: 0 5px;
- }
- .tooltip.bottom {
- margin-top: 3px;
- padding: 5px 0;
- }
- .tooltip.left {
- margin-left: -3px;
- padding: 0 5px;
- }
- .tooltip-inner {
- max-width: 200px;
- padding: 3px 8px;
- color: #fff;
- text-align: center;
- background-color: #000;
- border-radius: 2px;
- }
- .tooltip-arrow {
- position: absolute;
- width: 0;
- height: 0;
- border-color: transparent;
- border-style: solid;
- }
- .tooltip.top .tooltip-arrow {
- bottom: 0;
- left: 50%;
- margin-left: -5px;
- border-width: 5px 5px 0;
- border-top-color: #000;
- }
- .tooltip.top-left .tooltip-arrow {
- bottom: 0;
- right: 5px;
- margin-bottom: -5px;
- border-width: 5px 5px 0;
- border-top-color: #000;
- }
- .tooltip.top-right .tooltip-arrow {
- bottom: 0;
- left: 5px;
- margin-bottom: -5px;
- border-width: 5px 5px 0;
- border-top-color: #000;
- }
- .tooltip.right .tooltip-arrow {
- top: 50%;
- left: 0;
- margin-top: -5px;
- border-width: 5px 5px 5px 0;
- border-right-color: #000;
- }
- .tooltip.left .tooltip-arrow {
- top: 50%;
- right: 0;
- margin-top: -5px;
- border-width: 5px 0 5px 5px;
- border-left-color: #000;
- }
- .tooltip.bottom .tooltip-arrow {
- top: 0;
- left: 50%;
- margin-left: -5px;
- border-width: 0 5px 5px;
- border-bottom-color: #000;
- }
- .tooltip.bottom-left .tooltip-arrow {
- top: 0;
- right: 5px;
- margin-top: -5px;
- border-width: 0 5px 5px;
- border-bottom-color: #000;
- }
- .tooltip.bottom-right .tooltip-arrow {
- top: 0;
- left: 5px;
- margin-top: -5px;
- border-width: 0 5px 5px;
- border-bottom-color: #000;
- }
- .popover {
- position: absolute;
- top: 0;
- left: 0;
- z-index: 1060;
- display: none;
- max-width: 276px;
- padding: 1px;
- font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
- font-style: normal;
- font-weight: normal;
- letter-spacing: normal;
- line-break: auto;
- line-height: 1.42857143;
- text-align: left;
- text-align: start;
- text-decoration: none;
- text-shadow: none;
- text-transform: none;
- white-space: normal;
- word-break: normal;
- word-spacing: normal;
- word-wrap: normal;
- font-size: 13px;
- background-color: #fff;
- background-clip: padding-box;
- border: 1px solid #ccc;
- border: 1px solid rgba(0, 0, 0, 0.2);
- border-radius: 3px;
- -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
- box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
- }
- .popover.top {
- margin-top: -10px;
- }
- .popover.right {
- margin-left: 10px;
- }
- .popover.bottom {
- margin-top: 10px;
- }
- .popover.left {
- margin-left: -10px;
- }
- .popover-title {
- margin: 0;
- padding: 8px 14px;
- font-size: 13px;
- background-color: #f7f7f7;
- border-bottom: 1px solid #ebebeb;
- border-radius: 2px 2px 0 0;
- }
- .popover-content {
- padding: 9px 14px;
- }
- .popover > .arrow,
- .popover > .arrow:after {
- position: absolute;
- display: block;
- width: 0;
- height: 0;
- border-color: transparent;
- border-style: solid;
- }
- .popover > .arrow {
- border-width: 11px;
- }
- .popover > .arrow:after {
- border-width: 10px;
- content: "";
- }
- .popover.top > .arrow {
- left: 50%;
- margin-left: -11px;
- border-bottom-width: 0;
- border-top-color: #999999;
- border-top-color: rgba(0, 0, 0, 0.25);
- bottom: -11px;
- }
- .popover.top > .arrow:after {
- content: " ";
- bottom: 1px;
- margin-left: -10px;
- border-bottom-width: 0;
- border-top-color: #fff;
- }
- .popover.right > .arrow {
- top: 50%;
- left: -11px;
- margin-top: -11px;
- border-left-width: 0;
- border-right-color: #999999;
- border-right-color: rgba(0, 0, 0, 0.25);
- }
- .popover.right > .arrow:after {
- content: " ";
- left: 1px;
- bottom: -10px;
- border-left-width: 0;
- border-right-color: #fff;
- }
- .popover.bottom > .arrow {
- left: 50%;
- margin-left: -11px;
- border-top-width: 0;
- border-bottom-color: #999999;
- border-bottom-color: rgba(0, 0, 0, 0.25);
- top: -11px;
- }
- .popover.bottom > .arrow:after {
- content: " ";
- top: 1px;
- margin-left: -10px;
- border-top-width: 0;
- border-bottom-color: #fff;
- }
- .popover.left > .arrow {
- top: 50%;
- right: -11px;
- margin-top: -11px;
- border-right-width: 0;
- border-left-color: #999999;
- border-left-color: rgba(0, 0, 0, 0.25);
- }
- .popover.left > .arrow:after {
- content: " ";
- right: 1px;
- border-right-width: 0;
- border-left-color: #fff;
- bottom: -10px;
- }
- .carousel {
- position: relative;
- }
- .carousel-inner {
- position: relative;
- overflow: hidden;
- width: 100%;
- }
- .carousel-inner > .item {
- display: none;
- position: relative;
- -webkit-transition: 0.6s ease-in-out left;
- -o-transition: 0.6s ease-in-out left;
- transition: 0.6s ease-in-out left;
- }
- .carousel-inner > .item > img,
- .carousel-inner > .item > a > img {
- line-height: 1;
- }
- @media all and (transform-3d), (-webkit-transform-3d) {
- .carousel-inner > .item {
- -webkit-transition: -webkit-transform 0.6s ease-in-out;
- -moz-transition: -moz-transform 0.6s ease-in-out;
- -o-transition: -o-transform 0.6s ease-in-out;
- transition: transform 0.6s ease-in-out;
- -webkit-backface-visibility: hidden;
- -moz-backface-visibility: hidden;
- backface-visibility: hidden;
- -webkit-perspective: 1000px;
- -moz-perspective: 1000px;
- perspective: 1000px;
- }
- .carousel-inner > .item.next,
- .carousel-inner > .item.active.right {
- -webkit-transform: translate3d(100%, 0, 0);
- transform: translate3d(100%, 0, 0);
- left: 0;
- }
- .carousel-inner > .item.prev,
- .carousel-inner > .item.active.left {
- -webkit-transform: translate3d(-100%, 0, 0);
- transform: translate3d(-100%, 0, 0);
- left: 0;
- }
- .carousel-inner > .item.next.left,
- .carousel-inner > .item.prev.right,
- .carousel-inner > .item.active {
- -webkit-transform: translate3d(0, 0, 0);
- transform: translate3d(0, 0, 0);
- left: 0;
- }
- }
- .carousel-inner > .active,
- .carousel-inner > .next,
- .carousel-inner > .prev {
- display: block;
- }
- .carousel-inner > .active {
- left: 0;
- }
- .carousel-inner > .next,
- .carousel-inner > .prev {
- position: absolute;
- top: 0;
- width: 100%;
- }
- .carousel-inner > .next {
- left: 100%;
- }
- .carousel-inner > .prev {
- left: -100%;
- }
- .carousel-inner > .next.left,
- .carousel-inner > .prev.right {
- left: 0;
- }
- .carousel-inner > .active.left {
- left: -100%;
- }
- .carousel-inner > .active.right {
- left: 100%;
- }
- .carousel-control {
- position: absolute;
- top: 0;
- left: 0;
- bottom: 0;
- width: 15%;
- opacity: 0.5;
- filter: alpha(opacity=50);
- font-size: 20px;
- color: #fff;
- text-align: center;
- text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
- background-color: rgba(0, 0, 0, 0);
- }
- .carousel-control.left {
- background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
- background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
- background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
- background-repeat: repeat-x;
- filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
- }
- .carousel-control.right {
- left: auto;
- right: 0;
- background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
- background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
- background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
- background-repeat: repeat-x;
- filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
- }
- .carousel-control:hover,
- .carousel-control:focus {
- outline: 0;
- color: #fff;
- text-decoration: none;
- opacity: 0.9;
- filter: alpha(opacity=90);
- }
- .carousel-control .icon-prev,
- .carousel-control .icon-next,
- .carousel-control .glyphicon-chevron-left,
- .carousel-control .glyphicon-chevron-right {
- position: absolute;
- top: 50%;
- margin-top: -10px;
- z-index: 5;
- display: inline-block;
- }
- .carousel-control .icon-prev,
- .carousel-control .glyphicon-chevron-left {
- left: 50%;
- margin-left: -10px;
- }
- .carousel-control .icon-next,
- .carousel-control .glyphicon-chevron-right {
- right: 50%;
- margin-right: -10px;
- }
- .carousel-control .icon-prev,
- .carousel-control .icon-next {
- width: 20px;
- height: 20px;
- line-height: 1;
- font-family: serif;
- }
- .carousel-control .icon-prev:before {
- content: '\2039';
- }
- .carousel-control .icon-next:before {
- content: '\203a';
- }
- .carousel-indicators {
- position: absolute;
- bottom: 10px;
- left: 50%;
- z-index: 15;
- width: 60%;
- margin-left: -30%;
- padding-left: 0;
- list-style: none;
- text-align: center;
- }
- .carousel-indicators li {
- display: inline-block;
- width: 10px;
- height: 10px;
- margin: 1px;
- text-indent: -999px;
- border: 1px solid #fff;
- border-radius: 10px;
- cursor: pointer;
- background-color: #000 \9;
- background-color: rgba(0, 0, 0, 0);
- }
- .carousel-indicators .active {
- margin: 0;
- width: 12px;
- height: 12px;
- background-color: #fff;
- }
- .carousel-caption {
- position: absolute;
- left: 15%;
- right: 15%;
- bottom: 20px;
- z-index: 10;
- padding-top: 20px;
- padding-bottom: 20px;
- color: #fff;
- text-align: center;
- text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
- }
- .carousel-caption .btn {
- text-shadow: none;
- }
- @media screen and (min-width: 768px) {
- .carousel-control .glyphicon-chevron-left,
- .carousel-control .glyphicon-chevron-right,
- .carousel-control .icon-prev,
- .carousel-control .icon-next {
- width: 30px;
- height: 30px;
- margin-top: -10px;
- font-size: 30px;
- }
- .carousel-control .glyphicon-chevron-left,
- .carousel-control .icon-prev {
- margin-left: -10px;
- }
- .carousel-control .glyphicon-chevron-right,
- .carousel-control .icon-next {
- margin-right: -10px;
- }
- .carousel-caption {
- left: 20%;
- right: 20%;
- padding-bottom: 30px;
- }
- .carousel-indicators {
- bottom: 20px;
- }
- }
- .clearfix:before,
- .clearfix:after,
- .dl-horizontal dd:before,
- .dl-horizontal dd:after,
- .container:before,
- .container:after,
- .container-fluid:before,
- .container-fluid:after,
- .row:before,
- .row:after,
- .form-horizontal .form-group:before,
- .form-horizontal .form-group:after,
- .btn-toolbar:before,
- .btn-toolbar:after,
- .btn-group-vertical > .btn-group:before,
- .btn-group-vertical > .btn-group:after,
- .nav:before,
- .nav:after,
- .navbar:before,
- .navbar:after,
- .navbar-header:before,
- .navbar-header:after,
- .navbar-collapse:before,
- .navbar-collapse:after,
- .pager:before,
- .pager:after,
- .panel-body:before,
- .panel-body:after,
- .modal-header:before,
- .modal-header:after,
- .modal-footer:before,
- .modal-footer:after,
- .item_buttons:before,
- .item_buttons:after {
- content: " ";
- display: table;
- }
- .clearfix:after,
- .dl-horizontal dd:after,
- .container:after,
- .container-fluid:after,
- .row:after,
- .form-horizontal .form-group:after,
- .btn-toolbar:after,
- .btn-group-vertical > .btn-group:after,
- .nav:after,
- .navbar:after,
- .navbar-header:after,
- .navbar-collapse:after,
- .pager:after,
- .panel-body:after,
- .modal-header:after,
- .modal-footer:after,
- .item_buttons:after {
- clear: both;
- }
- .center-block {
- display: block;
- margin-left: auto;
- margin-right: auto;
- }
- .pull-right {
- float: right !important;
- }
- .pull-left {
- float: left !important;
- }
- .hide {
- display: none !important;
- }
- .show {
- display: block !important;
- }
- .invisible {
- visibility: hidden;
- }
- .text-hide {
- font: 0/0 a;
- color: transparent;
- text-shadow: none;
- background-color: transparent;
- border: 0;
- }
- .hidden {
- display: none !important;
- }
- .affix {
- position: fixed;
- }
- @-ms-viewport {
- width: device-width;
- }
- .visible-xs,
- .visible-sm,
- .visible-md,
- .visible-lg {
- display: none !important;
- }
- .visible-xs-block,
- .visible-xs-inline,
- .visible-xs-inline-block,
- .visible-sm-block,
- .visible-sm-inline,
- .visible-sm-inline-block,
- .visible-md-block,
- .visible-md-inline,
- .visible-md-inline-block,
- .visible-lg-block,
- .visible-lg-inline,
- .visible-lg-inline-block {
- display: none !important;
- }
- @media (max-width: 767px) {
- .visible-xs {
- display: block !important;
- }
- table.visible-xs {
- display: table !important;
- }
- tr.visible-xs {
- display: table-row !important;
- }
- th.visible-xs,
- td.visible-xs {
- display: table-cell !important;
- }
- }
- @media (max-width: 767px) {
- .visible-xs-block {
- display: block !important;
- }
- }
- @media (max-width: 767px) {
- .visible-xs-inline {
- display: inline !important;
- }
- }
- @media (max-width: 767px) {
- .visible-xs-inline-block {
- display: inline-block !important;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- .visible-sm {
- display: block !important;
- }
- table.visible-sm {
- display: table !important;
- }
- tr.visible-sm {
- display: table-row !important;
- }
- th.visible-sm,
- td.visible-sm {
- display: table-cell !important;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- .visible-sm-block {
- display: block !important;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- .visible-sm-inline {
- display: inline !important;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- .visible-sm-inline-block {
- display: inline-block !important;
- }
- }
- @media (min-width: 992px) and (max-width: 1199px) {
- .visible-md {
- display: block !important;
- }
- table.visible-md {
- display: table !important;
- }
- tr.visible-md {
- display: table-row !important;
- }
- th.visible-md,
- td.visible-md {
- display: table-cell !important;
- }
- }
- @media (min-width: 992px) and (max-width: 1199px) {
- .visible-md-block {
- display: block !important;
- }
- }
- @media (min-width: 992px) and (max-width: 1199px) {
- .visible-md-inline {
- display: inline !important;
- }
- }
- @media (min-width: 992px) and (max-width: 1199px) {
- .visible-md-inline-block {
- display: inline-block !important;
- }
- }
- @media (min-width: 1200px) {
- .visible-lg {
- display: block !important;
- }
- table.visible-lg {
- display: table !important;
- }
- tr.visible-lg {
- display: table-row !important;
- }
- th.visible-lg,
- td.visible-lg {
- display: table-cell !important;
- }
- }
- @media (min-width: 1200px) {
- .visible-lg-block {
- display: block !important;
- }
- }
- @media (min-width: 1200px) {
- .visible-lg-inline {
- display: inline !important;
- }
- }
- @media (min-width: 1200px) {
- .visible-lg-inline-block {
- display: inline-block !important;
- }
- }
- @media (max-width: 767px) {
- .hidden-xs {
- display: none !important;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- .hidden-sm {
- display: none !important;
- }
- }
- @media (min-width: 992px) and (max-width: 1199px) {
- .hidden-md {
- display: none !important;
- }
- }
- @media (min-width: 1200px) {
- .hidden-lg {
- display: none !important;
- }
- }
- .visible-print {
- display: none !important;
- }
- @media print {
- .visible-print {
- display: block !important;
- }
- table.visible-print {
- display: table !important;
- }
- tr.visible-print {
- display: table-row !important;
- }
- th.visible-print,
- td.visible-print {
- display: table-cell !important;
- }
- }
- .visible-print-block {
- display: none !important;
- }
- @media print {
- .visible-print-block {
- display: block !important;
- }
- }
- .visible-print-inline {
- display: none !important;
- }
- @media print {
- .visible-print-inline {
- display: inline !important;
- }
- }
- .visible-print-inline-block {
- display: none !important;
- }
- @media print {
- .visible-print-inline-block {
- display: inline-block !important;
- }
- }
- @media print {
- .hidden-print {
- display: none !important;
- }
- }
- /*!
- *
- * Font Awesome
- *
- */
- /*!
- * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
- * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
- */
- /* FONT PATH
- * -------------------------- */
- @font-face {
- font-family: 'FontAwesome';
- src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
- src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
- font-weight: normal;
- font-style: normal;
- }
- .fa {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- }
- /* makes the font 33% larger relative to the icon container */
- .fa-lg {
- font-size: 1.33333333em;
- line-height: 0.75em;
- vertical-align: -15%;
- }
- .fa-2x {
- font-size: 2em;
- }
- .fa-3x {
- font-size: 3em;
- }
- .fa-4x {
- font-size: 4em;
- }
- .fa-5x {
- font-size: 5em;
- }
- .fa-fw {
- width: 1.28571429em;
- text-align: center;
- }
- .fa-ul {
- padding-left: 0;
- margin-left: 2.14285714em;
- list-style-type: none;
- }
- .fa-ul > li {
- position: relative;
- }
- .fa-li {
- position: absolute;
- left: -2.14285714em;
- width: 2.14285714em;
- top: 0.14285714em;
- text-align: center;
- }
- .fa-li.fa-lg {
- left: -1.85714286em;
- }
- .fa-border {
- padding: .2em .25em .15em;
- border: solid 0.08em #eee;
- border-radius: .1em;
- }
- .pull-right {
- float: right;
- }
- .pull-left {
- float: left;
- }
- .fa.pull-left {
- margin-right: .3em;
- }
- .fa.pull-right {
- margin-left: .3em;
- }
- .fa-spin {
- -webkit-animation: fa-spin 2s infinite linear;
- animation: fa-spin 2s infinite linear;
- }
- @-webkit-keyframes fa-spin {
- 0% {
- -webkit-transform: rotate(0deg);
- transform: rotate(0deg);
- }
- 100% {
- -webkit-transform: rotate(359deg);
- transform: rotate(359deg);
- }
- }
- @keyframes fa-spin {
- 0% {
- -webkit-transform: rotate(0deg);
- transform: rotate(0deg);
- }
- 100% {
- -webkit-transform: rotate(359deg);
- transform: rotate(359deg);
- }
- }
- .fa-rotate-90 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
- -webkit-transform: rotate(90deg);
- -ms-transform: rotate(90deg);
- transform: rotate(90deg);
- }
- .fa-rotate-180 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
- -webkit-transform: rotate(180deg);
- -ms-transform: rotate(180deg);
- transform: rotate(180deg);
- }
- .fa-rotate-270 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
- -webkit-transform: rotate(270deg);
- -ms-transform: rotate(270deg);
- transform: rotate(270deg);
- }
- .fa-flip-horizontal {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
- -webkit-transform: scale(-1, 1);
- -ms-transform: scale(-1, 1);
- transform: scale(-1, 1);
- }
- .fa-flip-vertical {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
- -webkit-transform: scale(1, -1);
- -ms-transform: scale(1, -1);
- transform: scale(1, -1);
- }
- :root .fa-rotate-90,
- :root .fa-rotate-180,
- :root .fa-rotate-270,
- :root .fa-flip-horizontal,
- :root .fa-flip-vertical {
- filter: none;
- }
- .fa-stack {
- position: relative;
- display: inline-block;
- width: 2em;
- height: 2em;
- line-height: 2em;
- vertical-align: middle;
- }
- .fa-stack-1x,
- .fa-stack-2x {
- position: absolute;
- left: 0;
- width: 100%;
- text-align: center;
- }
- .fa-stack-1x {
- line-height: inherit;
- }
- .fa-stack-2x {
- font-size: 2em;
- }
- .fa-inverse {
- color: #fff;
- }
- /* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
- readers do not read off random characters that represent icons */
- .fa-glass:before {
- content: "\f000";
- }
- .fa-music:before {
- content: "\f001";
- }
- .fa-search:before {
- content: "\f002";
- }
- .fa-envelope-o:before {
- content: "\f003";
- }
- .fa-heart:before {
- content: "\f004";
- }
- .fa-star:before {
- content: "\f005";
- }
- .fa-star-o:before {
- content: "\f006";
- }
- .fa-user:before {
- content: "\f007";
- }
- .fa-film:before {
- content: "\f008";
- }
- .fa-th-large:before {
- content: "\f009";
- }
- .fa-th:before {
- content: "\f00a";
- }
- .fa-th-list:before {
- content: "\f00b";
- }
- .fa-check:before {
- content: "\f00c";
- }
- .fa-remove:before,
- .fa-close:before,
- .fa-times:before {
- content: "\f00d";
- }
- .fa-search-plus:before {
- content: "\f00e";
- }
- .fa-search-minus:before {
- content: "\f010";
- }
- .fa-power-off:before {
- content: "\f011";
- }
- .fa-signal:before {
- content: "\f012";
- }
- .fa-gear:before,
- .fa-cog:before {
- content: "\f013";
- }
- .fa-trash-o:before {
- content: "\f014";
- }
- .fa-home:before {
- content: "\f015";
- }
- .fa-file-o:before {
- content: "\f016";
- }
- .fa-clock-o:before {
- content: "\f017";
- }
- .fa-road:before {
- content: "\f018";
- }
- .fa-download:before {
- content: "\f019";
- }
- .fa-arrow-circle-o-down:before {
- content: "\f01a";
- }
- .fa-arrow-circle-o-up:before {
- content: "\f01b";
- }
- .fa-inbox:before {
- content: "\f01c";
- }
- .fa-play-circle-o:before {
- content: "\f01d";
- }
- .fa-rotate-right:before,
- .fa-repeat:before {
- content: "\f01e";
- }
- .fa-refresh:before {
- content: "\f021";
- }
- .fa-list-alt:before {
- content: "\f022";
- }
- .fa-lock:before {
- content: "\f023";
- }
- .fa-flag:before {
- content: "\f024";
- }
- .fa-headphones:before {
- content: "\f025";
- }
- .fa-volume-off:before {
- content: "\f026";
- }
- .fa-volume-down:before {
- content: "\f027";
- }
- .fa-volume-up:before {
- content: "\f028";
- }
- .fa-qrcode:before {
- content: "\f029";
- }
- .fa-barcode:before {
- content: "\f02a";
- }
- .fa-tag:before {
- content: "\f02b";
- }
- .fa-tags:before {
- content: "\f02c";
- }
- .fa-book:before {
- content: "\f02d";
- }
- .fa-bookmark:before {
- content: "\f02e";
- }
- .fa-print:before {
- content: "\f02f";
- }
- .fa-camera:before {
- content: "\f030";
- }
- .fa-font:before {
- content: "\f031";
- }
- .fa-bold:before {
- content: "\f032";
- }
- .fa-italic:before {
- content: "\f033";
- }
- .fa-text-height:before {
- content: "\f034";
- }
- .fa-text-width:before {
- content: "\f035";
- }
- .fa-align-left:before {
- content: "\f036";
- }
- .fa-align-center:before {
- content: "\f037";
- }
- .fa-align-right:before {
- content: "\f038";
- }
- .fa-align-justify:before {
- content: "\f039";
- }
- .fa-list:before {
- content: "\f03a";
- }
- .fa-dedent:before,
- .fa-outdent:before {
- content: "\f03b";
- }
- .fa-indent:before {
- content: "\f03c";
- }
- .fa-video-camera:before {
- content: "\f03d";
- }
- .fa-photo:before,
- .fa-image:before,
- .fa-picture-o:before {
- content: "\f03e";
- }
- .fa-pencil:before {
- content: "\f040";
- }
- .fa-map-marker:before {
- content: "\f041";
- }
- .fa-adjust:before {
- content: "\f042";
- }
- .fa-tint:before {
- content: "\f043";
- }
- .fa-edit:before,
- .fa-pencil-square-o:before {
- content: "\f044";
- }
- .fa-share-square-o:before {
- content: "\f045";
- }
- .fa-check-square-o:before {
- content: "\f046";
- }
- .fa-arrows:before {
- content: "\f047";
- }
- .fa-step-backward:before {
- content: "\f048";
- }
- .fa-fast-backward:before {
- content: "\f049";
- }
- .fa-backward:before {
- content: "\f04a";
- }
- .fa-play:before {
- content: "\f04b";
- }
- .fa-pause:before {
- content: "\f04c";
- }
- .fa-stop:before {
- content: "\f04d";
- }
- .fa-forward:before {
- content: "\f04e";
- }
- .fa-fast-forward:before {
- content: "\f050";
- }
- .fa-step-forward:before {
- content: "\f051";
- }
- .fa-eject:before {
- content: "\f052";
- }
- .fa-chevron-left:before {
- content: "\f053";
- }
- .fa-chevron-right:before {
- content: "\f054";
- }
- .fa-plus-circle:before {
- content: "\f055";
- }
- .fa-minus-circle:before {
- content: "\f056";
- }
- .fa-times-circle:before {
- content: "\f057";
- }
- .fa-check-circle:before {
- content: "\f058";
- }
- .fa-question-circle:before {
- content: "\f059";
- }
- .fa-info-circle:before {
- content: "\f05a";
- }
- .fa-crosshairs:before {
- content: "\f05b";
- }
- .fa-times-circle-o:before {
- content: "\f05c";
- }
- .fa-check-circle-o:before {
- content: "\f05d";
- }
- .fa-ban:before {
- content: "\f05e";
- }
- .fa-arrow-left:before {
- content: "\f060";
- }
- .fa-arrow-right:before {
- content: "\f061";
- }
- .fa-arrow-up:before {
- content: "\f062";
- }
- .fa-arrow-down:before {
- content: "\f063";
- }
- .fa-mail-forward:before,
- .fa-share:before {
- content: "\f064";
- }
- .fa-expand:before {
- content: "\f065";
- }
- .fa-compress:before {
- content: "\f066";
- }
- .fa-plus:before {
- content: "\f067";
- }
- .fa-minus:before {
- content: "\f068";
- }
- .fa-asterisk:before {
- content: "\f069";
- }
- .fa-exclamation-circle:before {
- content: "\f06a";
- }
- .fa-gift:before {
- content: "\f06b";
- }
- .fa-leaf:before {
- content: "\f06c";
- }
- .fa-fire:before {
- content: "\f06d";
- }
- .fa-eye:before {
- content: "\f06e";
- }
- .fa-eye-slash:before {
- content: "\f070";
- }
- .fa-warning:before,
- .fa-exclamation-triangle:before {
- content: "\f071";
- }
- .fa-plane:before {
- content: "\f072";
- }
- .fa-calendar:before {
- content: "\f073";
- }
- .fa-random:before {
- content: "\f074";
- }
- .fa-comment:before {
- content: "\f075";
- }
- .fa-magnet:before {
- content: "\f076";
- }
- .fa-chevron-up:before {
- content: "\f077";
- }
- .fa-chevron-down:before {
- content: "\f078";
- }
- .fa-retweet:before {
- content: "\f079";
- }
- .fa-shopping-cart:before {
- content: "\f07a";
- }
- .fa-folder:before {
- content: "\f07b";
- }
- .fa-folder-open:before {
- content: "\f07c";
- }
- .fa-arrows-v:before {
- content: "\f07d";
- }
- .fa-arrows-h:before {
- content: "\f07e";
- }
- .fa-bar-chart-o:before,
- .fa-bar-chart:before {
- content: "\f080";
- }
- .fa-twitter-square:before {
- content: "\f081";
- }
- .fa-facebook-square:before {
- content: "\f082";
- }
- .fa-camera-retro:before {
- content: "\f083";
- }
- .fa-key:before {
- content: "\f084";
- }
- .fa-gears:before,
- .fa-cogs:before {
- content: "\f085";
- }
- .fa-comments:before {
- content: "\f086";
- }
- .fa-thumbs-o-up:before {
- content: "\f087";
- }
- .fa-thumbs-o-down:before {
- content: "\f088";
- }
- .fa-star-half:before {
- content: "\f089";
- }
- .fa-heart-o:before {
- content: "\f08a";
- }
- .fa-sign-out:before {
- content: "\f08b";
- }
- .fa-linkedin-square:before {
- content: "\f08c";
- }
- .fa-thumb-tack:before {
- content: "\f08d";
- }
- .fa-external-link:before {
- content: "\f08e";
- }
- .fa-sign-in:before {
- content: "\f090";
- }
- .fa-trophy:before {
- content: "\f091";
- }
- .fa-github-square:before {
- content: "\f092";
- }
- .fa-upload:before {
- content: "\f093";
- }
- .fa-lemon-o:before {
- content: "\f094";
- }
- .fa-phone:before {
- content: "\f095";
- }
- .fa-square-o:before {
- content: "\f096";
- }
- .fa-bookmark-o:before {
- content: "\f097";
- }
- .fa-phone-square:before {
- content: "\f098";
- }
- .fa-twitter:before {
- content: "\f099";
- }
- .fa-facebook:before {
- content: "\f09a";
- }
- .fa-github:before {
- content: "\f09b";
- }
- .fa-unlock:before {
- content: "\f09c";
- }
- .fa-credit-card:before {
- content: "\f09d";
- }
- .fa-rss:before {
- content: "\f09e";
- }
- .fa-hdd-o:before {
- content: "\f0a0";
- }
- .fa-bullhorn:before {
- content: "\f0a1";
- }
- .fa-bell:before {
- content: "\f0f3";
- }
- .fa-certificate:before {
- content: "\f0a3";
- }
- .fa-hand-o-right:before {
- content: "\f0a4";
- }
- .fa-hand-o-left:before {
- content: "\f0a5";
- }
- .fa-hand-o-up:before {
- content: "\f0a6";
- }
- .fa-hand-o-down:before {
- content: "\f0a7";
- }
- .fa-arrow-circle-left:before {
- content: "\f0a8";
- }
- .fa-arrow-circle-right:before {
- content: "\f0a9";
- }
- .fa-arrow-circle-up:before {
- content: "\f0aa";
- }
- .fa-arrow-circle-down:before {
- content: "\f0ab";
- }
- .fa-globe:before {
- content: "\f0ac";
- }
- .fa-wrench:before {
- content: "\f0ad";
- }
- .fa-tasks:before {
- content: "\f0ae";
- }
- .fa-filter:before {
- content: "\f0b0";
- }
- .fa-briefcase:before {
- content: "\f0b1";
- }
- .fa-arrows-alt:before {
- content: "\f0b2";
- }
- .fa-group:before,
- .fa-users:before {
- content: "\f0c0";
- }
- .fa-chain:before,
- .fa-link:before {
- content: "\f0c1";
- }
- .fa-cloud:before {
- content: "\f0c2";
- }
- .fa-flask:before {
- content: "\f0c3";
- }
- .fa-cut:before,
- .fa-scissors:before {
- content: "\f0c4";
- }
- .fa-copy:before,
- .fa-files-o:before {
- content: "\f0c5";
- }
- .fa-paperclip:before {
- content: "\f0c6";
- }
- .fa-save:before,
- .fa-floppy-o:before {
- content: "\f0c7";
- }
- .fa-square:before {
- content: "\f0c8";
- }
- .fa-navicon:before,
- .fa-reorder:before,
- .fa-bars:before {
- content: "\f0c9";
- }
- .fa-list-ul:before {
- content: "\f0ca";
- }
- .fa-list-ol:before {
- content: "\f0cb";
- }
- .fa-strikethrough:before {
- content: "\f0cc";
- }
- .fa-underline:before {
- content: "\f0cd";
- }
- .fa-table:before {
- content: "\f0ce";
- }
- .fa-magic:before {
- content: "\f0d0";
- }
- .fa-truck:before {
- content: "\f0d1";
- }
- .fa-pinterest:before {
- content: "\f0d2";
- }
- .fa-pinterest-square:before {
- content: "\f0d3";
- }
- .fa-google-plus-square:before {
- content: "\f0d4";
- }
- .fa-google-plus:before {
- content: "\f0d5";
- }
- .fa-money:before {
- content: "\f0d6";
- }
- .fa-caret-down:before {
- content: "\f0d7";
- }
- .fa-caret-up:before {
- content: "\f0d8";
- }
- .fa-caret-left:before {
- content: "\f0d9";
- }
- .fa-caret-right:before {
- content: "\f0da";
- }
- .fa-columns:before {
- content: "\f0db";
- }
- .fa-unsorted:before,
- .fa-sort:before {
- content: "\f0dc";
- }
- .fa-sort-down:before,
- .fa-sort-desc:before {
- content: "\f0dd";
- }
- .fa-sort-up:before,
- .fa-sort-asc:before {
- content: "\f0de";
- }
- .fa-envelope:before {
- content: "\f0e0";
- }
- .fa-linkedin:before {
- content: "\f0e1";
- }
- .fa-rotate-left:before,
- .fa-undo:before {
- content: "\f0e2";
- }
- .fa-legal:before,
- .fa-gavel:before {
- content: "\f0e3";
- }
- .fa-dashboard:before,
- .fa-tachometer:before {
- content: "\f0e4";
- }
- .fa-comment-o:before {
- content: "\f0e5";
- }
- .fa-comments-o:before {
- content: "\f0e6";
- }
- .fa-flash:before,
- .fa-bolt:before {
- content: "\f0e7";
- }
- .fa-sitemap:before {
- content: "\f0e8";
- }
- .fa-umbrella:before {
- content: "\f0e9";
- }
- .fa-paste:before,
- .fa-clipboard:before {
- content: "\f0ea";
- }
- .fa-lightbulb-o:before {
- content: "\f0eb";
- }
- .fa-exchange:before {
- content: "\f0ec";
- }
- .fa-cloud-download:before {
- content: "\f0ed";
- }
- .fa-cloud-upload:before {
- content: "\f0ee";
- }
- .fa-user-md:before {
- content: "\f0f0";
- }
- .fa-stethoscope:before {
- content: "\f0f1";
- }
- .fa-suitcase:before {
- content: "\f0f2";
- }
- .fa-bell-o:before {
- content: "\f0a2";
- }
- .fa-coffee:before {
- content: "\f0f4";
- }
- .fa-cutlery:before {
- content: "\f0f5";
- }
- .fa-file-text-o:before {
- content: "\f0f6";
- }
- .fa-building-o:before {
- content: "\f0f7";
- }
- .fa-hospital-o:before {
- content: "\f0f8";
- }
- .fa-ambulance:before {
- content: "\f0f9";
- }
- .fa-medkit:before {
- content: "\f0fa";
- }
- .fa-fighter-jet:before {
- content: "\f0fb";
- }
- .fa-beer:before {
- content: "\f0fc";
- }
- .fa-h-square:before {
- content: "\f0fd";
- }
- .fa-plus-square:before {
- content: "\f0fe";
- }
- .fa-angle-double-left:before {
- content: "\f100";
- }
- .fa-angle-double-right:before {
- content: "\f101";
- }
- .fa-angle-double-up:before {
- content: "\f102";
- }
- .fa-angle-double-down:before {
- content: "\f103";
- }
- .fa-angle-left:before {
- content: "\f104";
- }
- .fa-angle-right:before {
- content: "\f105";
- }
- .fa-angle-up:before {
- content: "\f106";
- }
- .fa-angle-down:before {
- content: "\f107";
- }
- .fa-desktop:before {
- content: "\f108";
- }
- .fa-laptop:before {
- content: "\f109";
- }
- .fa-tablet:before {
- content: "\f10a";
- }
- .fa-mobile-phone:before,
- .fa-mobile:before {
- content: "\f10b";
- }
- .fa-circle-o:before {
- content: "\f10c";
- }
- .fa-quote-left:before {
- content: "\f10d";
- }
- .fa-quote-right:before {
- content: "\f10e";
- }
- .fa-spinner:before {
- content: "\f110";
- }
- .fa-circle:before {
- content: "\f111";
- }
- .fa-mail-reply:before,
- .fa-reply:before {
- content: "\f112";
- }
- .fa-github-alt:before {
- content: "\f113";
- }
- .fa-folder-o:before {
- content: "\f114";
- }
- .fa-folder-open-o:before {
- content: "\f115";
- }
- .fa-smile-o:before {
- content: "\f118";
- }
- .fa-frown-o:before {
- content: "\f119";
- }
- .fa-meh-o:before {
- content: "\f11a";
- }
- .fa-gamepad:before {
- content: "\f11b";
- }
- .fa-keyboard-o:before {
- content: "\f11c";
- }
- .fa-flag-o:before {
- content: "\f11d";
- }
- .fa-flag-checkered:before {
- content: "\f11e";
- }
- .fa-terminal:before {
- content: "\f120";
- }
- .fa-code:before {
- content: "\f121";
- }
- .fa-mail-reply-all:before,
- .fa-reply-all:before {
- content: "\f122";
- }
- .fa-star-half-empty:before,
- .fa-star-half-full:before,
- .fa-star-half-o:before {
- content: "\f123";
- }
- .fa-location-arrow:before {
- content: "\f124";
- }
- .fa-crop:before {
- content: "\f125";
- }
- .fa-code-fork:before {
- content: "\f126";
- }
- .fa-unlink:before,
- .fa-chain-broken:before {
- content: "\f127";
- }
- .fa-question:before {
- content: "\f128";
- }
- .fa-info:before {
- content: "\f129";
- }
- .fa-exclamation:before {
- content: "\f12a";
- }
- .fa-superscript:before {
- content: "\f12b";
- }
- .fa-subscript:before {
- content: "\f12c";
- }
- .fa-eraser:before {
- content: "\f12d";
- }
- .fa-puzzle-piece:before {
- content: "\f12e";
- }
- .fa-microphone:before {
- content: "\f130";
- }
- .fa-microphone-slash:before {
- content: "\f131";
- }
- .fa-shield:before {
- content: "\f132";
- }
- .fa-calendar-o:before {
- content: "\f133";
- }
- .fa-fire-extinguisher:before {
- content: "\f134";
- }
- .fa-rocket:before {
- content: "\f135";
- }
- .fa-maxcdn:before {
- content: "\f136";
- }
- .fa-chevron-circle-left:before {
- content: "\f137";
- }
- .fa-chevron-circle-right:before {
- content: "\f138";
- }
- .fa-chevron-circle-up:before {
- content: "\f139";
- }
- .fa-chevron-circle-down:before {
- content: "\f13a";
- }
- .fa-html5:before {
- content: "\f13b";
- }
- .fa-css3:before {
- content: "\f13c";
- }
- .fa-anchor:before {
- content: "\f13d";
- }
- .fa-unlock-alt:before {
- content: "\f13e";
- }
- .fa-bullseye:before {
- content: "\f140";
- }
- .fa-ellipsis-h:before {
- content: "\f141";
- }
- .fa-ellipsis-v:before {
- content: "\f142";
- }
- .fa-rss-square:before {
- content: "\f143";
- }
- .fa-play-circle:before {
- content: "\f144";
- }
- .fa-ticket:before {
- content: "\f145";
- }
- .fa-minus-square:before {
- content: "\f146";
- }
- .fa-minus-square-o:before {
- content: "\f147";
- }
- .fa-level-up:before {
- content: "\f148";
- }
- .fa-level-down:before {
- content: "\f149";
- }
- .fa-check-square:before {
- content: "\f14a";
- }
- .fa-pencil-square:before {
- content: "\f14b";
- }
- .fa-external-link-square:before {
- content: "\f14c";
- }
- .fa-share-square:before {
- content: "\f14d";
- }
- .fa-compass:before {
- content: "\f14e";
- }
- .fa-toggle-down:before,
- .fa-caret-square-o-down:before {
- content: "\f150";
- }
- .fa-toggle-up:before,
- .fa-caret-square-o-up:before {
- content: "\f151";
- }
- .fa-toggle-right:before,
- .fa-caret-square-o-right:before {
- content: "\f152";
- }
- .fa-euro:before,
- .fa-eur:before {
- content: "\f153";
- }
- .fa-gbp:before {
- content: "\f154";
- }
- .fa-dollar:before,
- .fa-usd:before {
- content: "\f155";
- }
- .fa-rupee:before,
- .fa-inr:before {
- content: "\f156";
- }
- .fa-cny:before,
- .fa-rmb:before,
- .fa-yen:before,
- .fa-jpy:before {
- content: "\f157";
- }
- .fa-ruble:before,
- .fa-rouble:before,
- .fa-rub:before {
- content: "\f158";
- }
- .fa-won:before,
- .fa-krw:before {
- content: "\f159";
- }
- .fa-bitcoin:before,
- .fa-btc:before {
- content: "\f15a";
- }
- .fa-file:before {
- content: "\f15b";
- }
- .fa-file-text:before {
- content: "\f15c";
- }
- .fa-sort-alpha-asc:before {
- content: "\f15d";
- }
- .fa-sort-alpha-desc:before {
- content: "\f15e";
- }
- .fa-sort-amount-asc:before {
- content: "\f160";
- }
- .fa-sort-amount-desc:before {
- content: "\f161";
- }
- .fa-sort-numeric-asc:before {
- content: "\f162";
- }
- .fa-sort-numeric-desc:before {
- content: "\f163";
- }
- .fa-thumbs-up:before {
- content: "\f164";
- }
- .fa-thumbs-down:before {
- content: "\f165";
- }
- .fa-youtube-square:before {
- content: "\f166";
- }
- .fa-youtube:before {
- content: "\f167";
- }
- .fa-xing:before {
- content: "\f168";
- }
- .fa-xing-square:before {
- content: "\f169";
- }
- .fa-youtube-play:before {
- content: "\f16a";
- }
- .fa-dropbox:before {
- content: "\f16b";
- }
- .fa-stack-overflow:before {
- content: "\f16c";
- }
- .fa-instagram:before {
- content: "\f16d";
- }
- .fa-flickr:before {
- content: "\f16e";
- }
- .fa-adn:before {
- content: "\f170";
- }
- .fa-bitbucket:before {
- content: "\f171";
- }
- .fa-bitbucket-square:before {
- content: "\f172";
- }
- .fa-tumblr:before {
- content: "\f173";
- }
- .fa-tumblr-square:before {
- content: "\f174";
- }
- .fa-long-arrow-down:before {
- content: "\f175";
- }
- .fa-long-arrow-up:before {
- content: "\f176";
- }
- .fa-long-arrow-left:before {
- content: "\f177";
- }
- .fa-long-arrow-right:before {
- content: "\f178";
- }
- .fa-apple:before {
- content: "\f179";
- }
- .fa-windows:before {
- content: "\f17a";
- }
- .fa-android:before {
- content: "\f17b";
- }
- .fa-linux:before {
- content: "\f17c";
- }
- .fa-dribbble:before {
- content: "\f17d";
- }
- .fa-skype:before {
- content: "\f17e";
- }
- .fa-foursquare:before {
- content: "\f180";
- }
- .fa-trello:before {
- content: "\f181";
- }
- .fa-female:before {
- content: "\f182";
- }
- .fa-male:before {
- content: "\f183";
- }
- .fa-gittip:before {
- content: "\f184";
- }
- .fa-sun-o:before {
- content: "\f185";
- }
- .fa-moon-o:before {
- content: "\f186";
- }
- .fa-archive:before {
- content: "\f187";
- }
- .fa-bug:before {
- content: "\f188";
- }
- .fa-vk:before {
- content: "\f189";
- }
- .fa-weibo:before {
- content: "\f18a";
- }
- .fa-renren:before {
- content: "\f18b";
- }
- .fa-pagelines:before {
- content: "\f18c";
- }
- .fa-stack-exchange:before {
- content: "\f18d";
- }
- .fa-arrow-circle-o-right:before {
- content: "\f18e";
- }
- .fa-arrow-circle-o-left:before {
- content: "\f190";
- }
- .fa-toggle-left:before,
- .fa-caret-square-o-left:before {
- content: "\f191";
- }
- .fa-dot-circle-o:before {
- content: "\f192";
- }
- .fa-wheelchair:before {
- content: "\f193";
- }
- .fa-vimeo-square:before {
- content: "\f194";
- }
- .fa-turkish-lira:before,
- .fa-try:before {
- content: "\f195";
- }
- .fa-plus-square-o:before {
- content: "\f196";
- }
- .fa-space-shuttle:before {
- content: "\f197";
- }
- .fa-slack:before {
- content: "\f198";
- }
- .fa-envelope-square:before {
- content: "\f199";
- }
- .fa-wordpress:before {
- content: "\f19a";
- }
- .fa-openid:before {
- content: "\f19b";
- }
- .fa-institution:before,
- .fa-bank:before,
- .fa-university:before {
- content: "\f19c";
- }
- .fa-mortar-board:before,
- .fa-graduation-cap:before {
- content: "\f19d";
- }
- .fa-yahoo:before {
- content: "\f19e";
- }
- .fa-google:before {
- content: "\f1a0";
- }
- .fa-reddit:before {
- content: "\f1a1";
- }
- .fa-reddit-square:before {
- content: "\f1a2";
- }
- .fa-stumbleupon-circle:before {
- content: "\f1a3";
- }
- .fa-stumbleupon:before {
- content: "\f1a4";
- }
- .fa-delicious:before {
- content: "\f1a5";
- }
- .fa-digg:before {
- content: "\f1a6";
- }
- .fa-pied-piper:before {
- content: "\f1a7";
- }
- .fa-pied-piper-alt:before {
- content: "\f1a8";
- }
- .fa-drupal:before {
- content: "\f1a9";
- }
- .fa-joomla:before {
- content: "\f1aa";
- }
- .fa-language:before {
- content: "\f1ab";
- }
- .fa-fax:before {
- content: "\f1ac";
- }
- .fa-building:before {
- content: "\f1ad";
- }
- .fa-child:before {
- content: "\f1ae";
- }
- .fa-paw:before {
- content: "\f1b0";
- }
- .fa-spoon:before {
- content: "\f1b1";
- }
- .fa-cube:before {
- content: "\f1b2";
- }
- .fa-cubes:before {
- content: "\f1b3";
- }
- .fa-behance:before {
- content: "\f1b4";
- }
- .fa-behance-square:before {
- content: "\f1b5";
- }
- .fa-steam:before {
- content: "\f1b6";
- }
- .fa-steam-square:before {
- content: "\f1b7";
- }
- .fa-recycle:before {
- content: "\f1b8";
- }
- .fa-automobile:before,
- .fa-car:before {
- content: "\f1b9";
- }
- .fa-cab:before,
- .fa-taxi:before {
- content: "\f1ba";
- }
- .fa-tree:before {
- content: "\f1bb";
- }
- .fa-spotify:before {
- content: "\f1bc";
- }
- .fa-deviantart:before {
- content: "\f1bd";
- }
- .fa-soundcloud:before {
- content: "\f1be";
- }
- .fa-database:before {
- content: "\f1c0";
- }
- .fa-file-pdf-o:before {
- content: "\f1c1";
- }
- .fa-file-word-o:before {
- content: "\f1c2";
- }
- .fa-file-excel-o:before {
- content: "\f1c3";
- }
- .fa-file-powerpoint-o:before {
- content: "\f1c4";
- }
- .fa-file-photo-o:before,
- .fa-file-picture-o:before,
- .fa-file-image-o:before {
- content: "\f1c5";
- }
- .fa-file-zip-o:before,
- .fa-file-archive-o:before {
- content: "\f1c6";
- }
- .fa-file-sound-o:before,
- .fa-file-audio-o:before {
- content: "\f1c7";
- }
- .fa-file-movie-o:before,
- .fa-file-video-o:before {
- content: "\f1c8";
- }
- .fa-file-code-o:before {
- content: "\f1c9";
- }
- .fa-vine:before {
- content: "\f1ca";
- }
- .fa-codepen:before {
- content: "\f1cb";
- }
- .fa-jsfiddle:before {
- content: "\f1cc";
- }
- .fa-life-bouy:before,
- .fa-life-buoy:before,
- .fa-life-saver:before,
- .fa-support:before,
- .fa-life-ring:before {
- content: "\f1cd";
- }
- .fa-circle-o-notch:before {
- content: "\f1ce";
- }
- .fa-ra:before,
- .fa-rebel:before {
- content: "\f1d0";
- }
- .fa-ge:before,
- .fa-empire:before {
- content: "\f1d1";
- }
- .fa-git-square:before {
- content: "\f1d2";
- }
- .fa-git:before {
- content: "\f1d3";
- }
- .fa-hacker-news:before {
- content: "\f1d4";
- }
- .fa-tencent-weibo:before {
- content: "\f1d5";
- }
- .fa-qq:before {
- content: "\f1d6";
- }
- .fa-wechat:before,
- .fa-weixin:before {
- content: "\f1d7";
- }
- .fa-send:before,
- .fa-paper-plane:before {
- content: "\f1d8";
- }
- .fa-send-o:before,
- .fa-paper-plane-o:before {
- content: "\f1d9";
- }
- .fa-history:before {
- content: "\f1da";
- }
- .fa-circle-thin:before {
- content: "\f1db";
- }
- .fa-header:before {
- content: "\f1dc";
- }
- .fa-paragraph:before {
- content: "\f1dd";
- }
- .fa-sliders:before {
- content: "\f1de";
- }
- .fa-share-alt:before {
- content: "\f1e0";
- }
- .fa-share-alt-square:before {
- content: "\f1e1";
- }
- .fa-bomb:before {
- content: "\f1e2";
- }
- .fa-soccer-ball-o:before,
- .fa-futbol-o:before {
- content: "\f1e3";
- }
- .fa-tty:before {
- content: "\f1e4";
- }
- .fa-binoculars:before {
- content: "\f1e5";
- }
- .fa-plug:before {
- content: "\f1e6";
- }
- .fa-slideshare:before {
- content: "\f1e7";
- }
- .fa-twitch:before {
- content: "\f1e8";
- }
- .fa-yelp:before {
- content: "\f1e9";
- }
- .fa-newspaper-o:before {
- content: "\f1ea";
- }
- .fa-wifi:before {
- content: "\f1eb";
- }
- .fa-calculator:before {
- content: "\f1ec";
- }
- .fa-paypal:before {
- content: "\f1ed";
- }
- .fa-google-wallet:before {
- content: "\f1ee";
- }
- .fa-cc-visa:before {
- content: "\f1f0";
- }
- .fa-cc-mastercard:before {
- content: "\f1f1";
- }
- .fa-cc-discover:before {
- content: "\f1f2";
- }
- .fa-cc-amex:before {
- content: "\f1f3";
- }
- .fa-cc-paypal:before {
- content: "\f1f4";
- }
- .fa-cc-stripe:before {
- content: "\f1f5";
- }
- .fa-bell-slash:before {
- content: "\f1f6";
- }
- .fa-bell-slash-o:before {
- content: "\f1f7";
- }
- .fa-trash:before {
- content: "\f1f8";
- }
- .fa-copyright:before {
- content: "\f1f9";
- }
- .fa-at:before {
- content: "\f1fa";
- }
- .fa-eyedropper:before {
- content: "\f1fb";
- }
- .fa-paint-brush:before {
- content: "\f1fc";
- }
- .fa-birthday-cake:before {
- content: "\f1fd";
- }
- .fa-area-chart:before {
- content: "\f1fe";
- }
- .fa-pie-chart:before {
- content: "\f200";
- }
- .fa-line-chart:before {
- content: "\f201";
- }
- .fa-lastfm:before {
- content: "\f202";
- }
- .fa-lastfm-square:before {
- content: "\f203";
- }
- .fa-toggle-off:before {
- content: "\f204";
- }
- .fa-toggle-on:before {
- content: "\f205";
- }
- .fa-bicycle:before {
- content: "\f206";
- }
- .fa-bus:before {
- content: "\f207";
- }
- .fa-ioxhost:before {
- content: "\f208";
- }
- .fa-angellist:before {
- content: "\f209";
- }
- .fa-cc:before {
- content: "\f20a";
- }
- .fa-shekel:before,
- .fa-sheqel:before,
- .fa-ils:before {
- content: "\f20b";
- }
- .fa-meanpath:before {
- content: "\f20c";
- }
- /*!
- *
- * IPython base
- *
- */
- .modal.fade .modal-dialog {
- -webkit-transform: translate(0, 0);
- -ms-transform: translate(0, 0);
- -o-transform: translate(0, 0);
- transform: translate(0, 0);
- }
- code {
- color: #000;
- }
- pre {
- font-size: inherit;
- line-height: inherit;
- }
- label {
- font-weight: normal;
- }
- /* Make the page background atleast 100% the height of the view port */
- /* Make the page itself atleast 70% the height of the view port */
- .border-box-sizing {
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- }
- .corner-all {
- border-radius: 2px;
- }
- .no-padding {
- padding: 0px;
- }
- /* Flexible box model classes */
- /* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
- /* This file is a compatability layer. It allows the usage of flexible box
- model layouts accross multiple browsers, including older browsers. The newest,
- universal implementation of the flexible box model is used when available (see
- `Modern browsers` comments below). Browsers that are known to implement this
- new spec completely include:
- Firefox 28.0+
- Chrome 29.0+
- Internet Explorer 11+
- Opera 17.0+
- Browsers not listed, including Safari, are supported via the styling under the
- `Old browsers` comments below.
- */
- .hbox {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- }
- .hbox > * {
- /* Old browsers */
- -webkit-box-flex: 0;
- -moz-box-flex: 0;
- box-flex: 0;
- /* Modern browsers */
- flex: none;
- }
- .vbox {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- }
- .vbox > * {
- /* Old browsers */
- -webkit-box-flex: 0;
- -moz-box-flex: 0;
- box-flex: 0;
- /* Modern browsers */
- flex: none;
- }
- .hbox.reverse,
- .vbox.reverse,
- .reverse {
- /* Old browsers */
- -webkit-box-direction: reverse;
- -moz-box-direction: reverse;
- box-direction: reverse;
- /* Modern browsers */
- flex-direction: row-reverse;
- }
- .hbox.box-flex0,
- .vbox.box-flex0,
- .box-flex0 {
- /* Old browsers */
- -webkit-box-flex: 0;
- -moz-box-flex: 0;
- box-flex: 0;
- /* Modern browsers */
- flex: none;
- width: auto;
- }
- .hbox.box-flex1,
- .vbox.box-flex1,
- .box-flex1 {
- /* Old browsers */
- -webkit-box-flex: 1;
- -moz-box-flex: 1;
- box-flex: 1;
- /* Modern browsers */
- flex: 1;
- }
- .hbox.box-flex,
- .vbox.box-flex,
- .box-flex {
- /* Old browsers */
- /* Old browsers */
- -webkit-box-flex: 1;
- -moz-box-flex: 1;
- box-flex: 1;
- /* Modern browsers */
- flex: 1;
- }
- .hbox.box-flex2,
- .vbox.box-flex2,
- .box-flex2 {
- /* Old browsers */
- -webkit-box-flex: 2;
- -moz-box-flex: 2;
- box-flex: 2;
- /* Modern browsers */
- flex: 2;
- }
- .box-group1 {
- /* Deprecated */
- -webkit-box-flex-group: 1;
- -moz-box-flex-group: 1;
- box-flex-group: 1;
- }
- .box-group2 {
- /* Deprecated */
- -webkit-box-flex-group: 2;
- -moz-box-flex-group: 2;
- box-flex-group: 2;
- }
- .hbox.start,
- .vbox.start,
- .start {
- /* Old browsers */
- -webkit-box-pack: start;
- -moz-box-pack: start;
- box-pack: start;
- /* Modern browsers */
- justify-content: flex-start;
- }
- .hbox.end,
- .vbox.end,
- .end {
- /* Old browsers */
- -webkit-box-pack: end;
- -moz-box-pack: end;
- box-pack: end;
- /* Modern browsers */
- justify-content: flex-end;
- }
- .hbox.center,
- .vbox.center,
- .center {
- /* Old browsers */
- -webkit-box-pack: center;
- -moz-box-pack: center;
- box-pack: center;
- /* Modern browsers */
- justify-content: center;
- }
- .hbox.baseline,
- .vbox.baseline,
- .baseline {
- /* Old browsers */
- -webkit-box-pack: baseline;
- -moz-box-pack: baseline;
- box-pack: baseline;
- /* Modern browsers */
- justify-content: baseline;
- }
- .hbox.stretch,
- .vbox.stretch,
- .stretch {
- /* Old browsers */
- -webkit-box-pack: stretch;
- -moz-box-pack: stretch;
- box-pack: stretch;
- /* Modern browsers */
- justify-content: stretch;
- }
- .hbox.align-start,
- .vbox.align-start,
- .align-start {
- /* Old browsers */
- -webkit-box-align: start;
- -moz-box-align: start;
- box-align: start;
- /* Modern browsers */
- align-items: flex-start;
- }
- .hbox.align-end,
- .vbox.align-end,
- .align-end {
- /* Old browsers */
- -webkit-box-align: end;
- -moz-box-align: end;
- box-align: end;
- /* Modern browsers */
- align-items: flex-end;
- }
- .hbox.align-center,
- .vbox.align-center,
- .align-center {
- /* Old browsers */
- -webkit-box-align: center;
- -moz-box-align: center;
- box-align: center;
- /* Modern browsers */
- align-items: center;
- }
- .hbox.align-baseline,
- .vbox.align-baseline,
- .align-baseline {
- /* Old browsers */
- -webkit-box-align: baseline;
- -moz-box-align: baseline;
- box-align: baseline;
- /* Modern browsers */
- align-items: baseline;
- }
- .hbox.align-stretch,
- .vbox.align-stretch,
- .align-stretch {
- /* Old browsers */
- -webkit-box-align: stretch;
- -moz-box-align: stretch;
- box-align: stretch;
- /* Modern browsers */
- align-items: stretch;
- }
- div.error {
- margin: 2em;
- text-align: center;
- }
- div.error > h1 {
- font-size: 500%;
- line-height: normal;
- }
- div.error > p {
- font-size: 200%;
- line-height: normal;
- }
- div.traceback-wrapper {
- text-align: left;
- max-width: 800px;
- margin: auto;
- }
- /**
- * Primary styles
- *
- * Author: Jupyter Development Team
- */
- body {
- background-color: #fff;
- /* This makes sure that the body covers the entire window and needs to
- be in a different element than the display: box in wrapper below */
- position: absolute;
- left: 0px;
- right: 0px;
- top: 0px;
- bottom: 0px;
- overflow: visible;
- }
- body > #header {
- /* Initially hidden to prevent FLOUC */
- display: none;
- background-color: #fff;
- /* Display over codemirror */
- position: relative;
- z-index: 100;
- }
- body > #header #header-container {
- padding-bottom: 5px;
- padding-top: 5px;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- }
- body > #header .header-bar {
- width: 100%;
- height: 1px;
- background: #e7e7e7;
- margin-bottom: -1px;
- }
- @media print {
- body > #header {
- display: none !important;
- }
- }
- #header-spacer {
- width: 100%;
- visibility: hidden;
- }
- @media print {
- #header-spacer {
- display: none;
- }
- }
- #ipython_notebook {
- padding-left: 0px;
- padding-top: 1px;
- padding-bottom: 1px;
- }
- @media (max-width: 991px) {
- #ipython_notebook {
- margin-left: 10px;
- }
- }
- [dir="rtl"] #ipython_notebook {
- float: right !important;
- }
- #noscript {
- width: auto;
- padding-top: 16px;
- padding-bottom: 16px;
- text-align: center;
- font-size: 22px;
- color: red;
- font-weight: bold;
- }
- #ipython_notebook img {
- height: 28px;
- }
- #site {
- width: 100%;
- display: none;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- overflow: auto;
- }
- @media print {
- #site {
- height: auto !important;
- }
- }
- /* Smaller buttons */
- .ui-button .ui-button-text {
- padding: 0.2em 0.8em;
- font-size: 77%;
- }
- input.ui-button {
- padding: 0.3em 0.9em;
- }
- span#login_widget {
- float: right;
- }
- span#login_widget > .button,
- #logout {
- color: #333;
- background-color: #fff;
- border-color: #ccc;
- }
- span#login_widget > .button:focus,
- #logout:focus,
- span#login_widget > .button.focus,
- #logout.focus {
- color: #333;
- background-color: #e6e6e6;
- border-color: #8c8c8c;
- }
- span#login_widget > .button:hover,
- #logout:hover {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- span#login_widget > .button:active,
- #logout:active,
- span#login_widget > .button.active,
- #logout.active,
- .open > .dropdown-togglespan#login_widget > .button,
- .open > .dropdown-toggle#logout {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- span#login_widget > .button:active:hover,
- #logout:active:hover,
- span#login_widget > .button.active:hover,
- #logout.active:hover,
- .open > .dropdown-togglespan#login_widget > .button:hover,
- .open > .dropdown-toggle#logout:hover,
- span#login_widget > .button:active:focus,
- #logout:active:focus,
- span#login_widget > .button.active:focus,
- #logout.active:focus,
- .open > .dropdown-togglespan#login_widget > .button:focus,
- .open > .dropdown-toggle#logout:focus,
- span#login_widget > .button:active.focus,
- #logout:active.focus,
- span#login_widget > .button.active.focus,
- #logout.active.focus,
- .open > .dropdown-togglespan#login_widget > .button.focus,
- .open > .dropdown-toggle#logout.focus {
- color: #333;
- background-color: #d4d4d4;
- border-color: #8c8c8c;
- }
- span#login_widget > .button:active,
- #logout:active,
- span#login_widget > .button.active,
- #logout.active,
- .open > .dropdown-togglespan#login_widget > .button,
- .open > .dropdown-toggle#logout {
- background-image: none;
- }
- span#login_widget > .button.disabled:hover,
- #logout.disabled:hover,
- span#login_widget > .button[disabled]:hover,
- #logout[disabled]:hover,
- fieldset[disabled] span#login_widget > .button:hover,
- fieldset[disabled] #logout:hover,
- span#login_widget > .button.disabled:focus,
- #logout.disabled:focus,
- span#login_widget > .button[disabled]:focus,
- #logout[disabled]:focus,
- fieldset[disabled] span#login_widget > .button:focus,
- fieldset[disabled] #logout:focus,
- span#login_widget > .button.disabled.focus,
- #logout.disabled.focus,
- span#login_widget > .button[disabled].focus,
- #logout[disabled].focus,
- fieldset[disabled] span#login_widget > .button.focus,
- fieldset[disabled] #logout.focus {
- background-color: #fff;
- border-color: #ccc;
- }
- span#login_widget > .button .badge,
- #logout .badge {
- color: #fff;
- background-color: #333;
- }
- .nav-header {
- text-transform: none;
- }
- #header > span {
- margin-top: 10px;
- }
- .modal_stretch .modal-dialog {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- min-height: 80vh;
- }
- .modal_stretch .modal-dialog .modal-body {
- max-height: calc(100vh - 200px);
- overflow: auto;
- flex: 1;
- }
- @media (min-width: 768px) {
- .modal .modal-dialog {
- width: 700px;
- }
- }
- @media (min-width: 768px) {
- select.form-control {
- margin-left: 12px;
- margin-right: 12px;
- }
- }
- /*!
- *
- * IPython auth
- *
- */
- .center-nav {
- display: inline-block;
- margin-bottom: -4px;
- }
- /*!
- *
- * IPython tree view
- *
- */
- /* We need an invisible input field on top of the sentense*/
- /* "Drag file onto the list ..." */
- .alternate_upload {
- background-color: none;
- display: inline;
- }
- .alternate_upload.form {
- padding: 0;
- margin: 0;
- }
- .alternate_upload input.fileinput {
- text-align: center;
- vertical-align: middle;
- display: inline;
- opacity: 0;
- z-index: 2;
- width: 12ex;
- margin-right: -12ex;
- }
- .alternate_upload .btn-upload {
- height: 22px;
- }
- /**
- * Primary styles
- *
- * Author: Jupyter Development Team
- */
- [dir="rtl"] #tabs li {
- float: right;
- }
- ul#tabs {
- margin-bottom: 4px;
- }
- [dir="rtl"] ul#tabs {
- margin-right: 0px;
- }
- ul#tabs a {
- padding-top: 6px;
- padding-bottom: 4px;
- }
- ul.breadcrumb a:focus,
- ul.breadcrumb a:hover {
- text-decoration: none;
- }
- ul.breadcrumb i.icon-home {
- font-size: 16px;
- margin-right: 4px;
- }
- ul.breadcrumb span {
- color: #5e5e5e;
- }
- .list_toolbar {
- padding: 4px 0 4px 0;
- vertical-align: middle;
- }
- .list_toolbar .tree-buttons {
- padding-top: 1px;
- }
- [dir="rtl"] .list_toolbar .tree-buttons {
- float: left !important;
- }
- [dir="rtl"] .list_toolbar .pull-right {
- padding-top: 1px;
- float: left !important;
- }
- [dir="rtl"] .list_toolbar .pull-left {
- float: right !important;
- }
- .dynamic-buttons {
- padding-top: 3px;
- display: inline-block;
- }
- .list_toolbar [class*="span"] {
- min-height: 24px;
- }
- .list_header {
- font-weight: bold;
- background-color: #EEE;
- }
- .list_placeholder {
- font-weight: bold;
- padding-top: 4px;
- padding-bottom: 4px;
- padding-left: 7px;
- padding-right: 7px;
- }
- .list_container {
- margin-top: 4px;
- margin-bottom: 20px;
- border: 1px solid #ddd;
- border-radius: 2px;
- }
- .list_container > div {
- border-bottom: 1px solid #ddd;
- }
- .list_container > div:hover .list-item {
- background-color: red;
- }
- .list_container > div:last-child {
- border: none;
- }
- .list_item:hover .list_item {
- background-color: #ddd;
- }
- .list_item a {
- text-decoration: none;
- }
- .list_item:hover {
- background-color: #fafafa;
- }
- .list_header > div,
- .list_item > div {
- padding-top: 4px;
- padding-bottom: 4px;
- padding-left: 7px;
- padding-right: 7px;
- line-height: 22px;
- }
- .list_header > div input,
- .list_item > div input {
- margin-right: 7px;
- margin-left: 14px;
- vertical-align: baseline;
- line-height: 22px;
- position: relative;
- top: -1px;
- }
- .list_header > div .item_link,
- .list_item > div .item_link {
- margin-left: -1px;
- vertical-align: baseline;
- line-height: 22px;
- }
- .new-file input[type=checkbox] {
- visibility: hidden;
- }
- .item_name {
- line-height: 22px;
- height: 24px;
- }
- .item_icon {
- font-size: 14px;
- color: #5e5e5e;
- margin-right: 7px;
- margin-left: 7px;
- line-height: 22px;
- vertical-align: baseline;
- }
- .item_buttons {
- line-height: 1em;
- margin-left: -5px;
- }
- .item_buttons .btn,
- .item_buttons .btn-group,
- .item_buttons .input-group {
- float: left;
- }
- .item_buttons > .btn,
- .item_buttons > .btn-group,
- .item_buttons > .input-group {
- margin-left: 5px;
- }
- .item_buttons .btn {
- min-width: 13ex;
- }
- .item_buttons .running-indicator {
- padding-top: 4px;
- color: #5cb85c;
- }
- .item_buttons .kernel-name {
- padding-top: 4px;
- color: #5bc0de;
- margin-right: 7px;
- float: left;
- }
- .toolbar_info {
- height: 24px;
- line-height: 24px;
- }
- .list_item input:not([type=checkbox]) {
- padding-top: 3px;
- padding-bottom: 3px;
- height: 22px;
- line-height: 14px;
- margin: 0px;
- }
- .highlight_text {
- color: blue;
- }
- #project_name {
- display: inline-block;
- padding-left: 7px;
- margin-left: -2px;
- }
- #project_name > .breadcrumb {
- padding: 0px;
- margin-bottom: 0px;
- background-color: transparent;
- font-weight: bold;
- }
- #tree-selector {
- padding-right: 0px;
- }
- [dir="rtl"] #tree-selector a {
- float: right;
- }
- #button-select-all {
- min-width: 50px;
- }
- #select-all {
- margin-left: 7px;
- margin-right: 2px;
- }
- .menu_icon {
- margin-right: 2px;
- }
- .tab-content .row {
- margin-left: 0px;
- margin-right: 0px;
- }
- .folder_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f114";
- }
- .folder_icon:before.pull-left {
- margin-right: .3em;
- }
- .folder_icon:before.pull-right {
- margin-left: .3em;
- }
- .notebook_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f02d";
- position: relative;
- top: -1px;
- }
- .notebook_icon:before.pull-left {
- margin-right: .3em;
- }
- .notebook_icon:before.pull-right {
- margin-left: .3em;
- }
- .running_notebook_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f02d";
- position: relative;
- top: -1px;
- color: #5cb85c;
- }
- .running_notebook_icon:before.pull-left {
- margin-right: .3em;
- }
- .running_notebook_icon:before.pull-right {
- margin-left: .3em;
- }
- .file_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f016";
- position: relative;
- top: -2px;
- }
- .file_icon:before.pull-left {
- margin-right: .3em;
- }
- .file_icon:before.pull-right {
- margin-left: .3em;
- }
- #notebook_toolbar .pull-right {
- padding-top: 0px;
- margin-right: -1px;
- }
- ul#new-menu {
- left: auto;
- right: 0;
- }
- [dir="rtl"] #new-menu {
- text-align: right;
- }
- .kernel-menu-icon {
- padding-right: 12px;
- width: 24px;
- content: "\f096";
- }
- .kernel-menu-icon:before {
- content: "\f096";
- }
- .kernel-menu-icon-current:before {
- content: "\f00c";
- }
- #tab_content {
- padding-top: 20px;
- }
- #running .panel-group .panel {
- margin-top: 3px;
- margin-bottom: 1em;
- }
- #running .panel-group .panel .panel-heading {
- background-color: #EEE;
- padding-top: 4px;
- padding-bottom: 4px;
- padding-left: 7px;
- padding-right: 7px;
- line-height: 22px;
- }
- #running .panel-group .panel .panel-heading a:focus,
- #running .panel-group .panel .panel-heading a:hover {
- text-decoration: none;
- }
- #running .panel-group .panel .panel-body {
- padding: 0px;
- }
- #running .panel-group .panel .panel-body .list_container {
- margin-top: 0px;
- margin-bottom: 0px;
- border: 0px;
- border-radius: 0px;
- }
- #running .panel-group .panel .panel-body .list_container .list_item {
- border-bottom: 1px solid #ddd;
- }
- #running .panel-group .panel .panel-body .list_container .list_item:last-child {
- border-bottom: 0px;
- }
- [dir="rtl"] #running .col-sm-8 {
- float: right !important;
- }
- .delete-button {
- display: none;
- }
- .duplicate-button {
- display: none;
- }
- .rename-button {
- display: none;
- }
- .shutdown-button {
- display: none;
- }
- .dynamic-instructions {
- display: inline-block;
- padding-top: 4px;
- }
- /*!
- *
- * IPython text editor webapp
- *
- */
- .selected-keymap i.fa {
- padding: 0px 5px;
- }
- .selected-keymap i.fa:before {
- content: "\f00c";
- }
- #mode-menu {
- overflow: auto;
- max-height: 20em;
- }
- .edit_app #header {
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- }
- .edit_app #menubar .navbar {
- /* Use a negative 1 bottom margin, so the border overlaps the border of the
- header */
- margin-bottom: -1px;
- }
- .dirty-indicator {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- width: 20px;
- }
- .dirty-indicator.pull-left {
- margin-right: .3em;
- }
- .dirty-indicator.pull-right {
- margin-left: .3em;
- }
- .dirty-indicator-dirty {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- width: 20px;
- }
- .dirty-indicator-dirty.pull-left {
- margin-right: .3em;
- }
- .dirty-indicator-dirty.pull-right {
- margin-left: .3em;
- }
- .dirty-indicator-clean {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- width: 20px;
- }
- .dirty-indicator-clean.pull-left {
- margin-right: .3em;
- }
- .dirty-indicator-clean.pull-right {
- margin-left: .3em;
- }
- .dirty-indicator-clean:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f00c";
- }
- .dirty-indicator-clean:before.pull-left {
- margin-right: .3em;
- }
- .dirty-indicator-clean:before.pull-right {
- margin-left: .3em;
- }
- #filename {
- font-size: 16pt;
- display: table;
- padding: 0px 5px;
- }
- #current-mode {
- padding-left: 5px;
- padding-right: 5px;
- }
- #texteditor-backdrop {
- padding-top: 20px;
- padding-bottom: 20px;
- }
- @media not print {
- #texteditor-backdrop {
- background-color: #EEE;
- }
- }
- @media print {
- #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
- #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
- background-color: #fff;
- }
- }
- @media not print {
- #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
- #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
- background-color: #fff;
- }
- }
- @media not print {
- #texteditor-backdrop #texteditor-container {
- padding: 0px;
- background-color: #fff;
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- }
- }
- /*!
- *
- * IPython notebook
- *
- */
- /* CSS font colors for translated ANSI colors. */
- .ansibold {
- font-weight: bold;
- }
- /* use dark versions for foreground, to improve visibility */
- .ansiblack {
- color: black;
- }
- .ansired {
- color: darkred;
- }
- .ansigreen {
- color: darkgreen;
- }
- .ansiyellow {
- color: #c4a000;
- }
- .ansiblue {
- color: darkblue;
- }
- .ansipurple {
- color: darkviolet;
- }
- .ansicyan {
- color: steelblue;
- }
- .ansigray {
- color: gray;
- }
- /* and light for background, for the same reason */
- .ansibgblack {
- background-color: black;
- }
- .ansibgred {
- background-color: red;
- }
- .ansibggreen {
- background-color: green;
- }
- .ansibgyellow {
- background-color: yellow;
- }
- .ansibgblue {
- background-color: blue;
- }
- .ansibgpurple {
- background-color: magenta;
- }
- .ansibgcyan {
- background-color: cyan;
- }
- .ansibggray {
- background-color: gray;
- }
- div.cell {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- border-radius: 2px;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- border-width: 1px;
- border-style: solid;
- border-color: transparent;
- width: 100%;
- padding: 5px;
- /* This acts as a spacer between cells, that is outside the border */
- margin: 0px;
- outline: none;
- border-left-width: 1px;
- padding-left: 5px;
- background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
- }
- div.cell.jupyter-soft-selected {
- border-left-color: #90CAF9;
- border-left-color: #E3F2FD;
- border-left-width: 1px;
- padding-left: 5px;
- border-right-color: #E3F2FD;
- border-right-width: 1px;
- background: #E3F2FD;
- }
- @media print {
- div.cell.jupyter-soft-selected {
- border-color: transparent;
- }
- }
- div.cell.selected {
- border-color: #ababab;
- border-left-width: 0px;
- padding-left: 6px;
- background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
- }
- @media print {
- div.cell.selected {
- border-color: transparent;
- }
- }
- div.cell.selected.jupyter-soft-selected {
- border-left-width: 0;
- padding-left: 6px;
- background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
- }
- .edit_mode div.cell.selected {
- border-color: #66BB6A;
- border-left-width: 0px;
- padding-left: 6px;
- background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
- }
- @media print {
- .edit_mode div.cell.selected {
- border-color: transparent;
- }
- }
- .prompt {
- /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
- min-width: 14ex;
- /* This padding is tuned to match the padding on the CodeMirror editor. */
- padding: 0.4em;
- margin: 0px;
- font-family: monospace;
- text-align: right;
- /* This has to match that of the the CodeMirror class line-height below */
- line-height: 1.21429em;
- /* Don't highlight prompt number selection */
- -webkit-touch-callout: none;
- -webkit-user-select: none;
- -khtml-user-select: none;
- -moz-user-select: none;
- -ms-user-select: none;
- user-select: none;
- /* Use default cursor */
- cursor: default;
- }
- @media (max-width: 540px) {
- .prompt {
- text-align: left;
- }
- }
- div.inner_cell {
- min-width: 0;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- /* Old browsers */
- -webkit-box-flex: 1;
- -moz-box-flex: 1;
- box-flex: 1;
- /* Modern browsers */
- flex: 1;
- }
- /* input_area and input_prompt must match in top border and margin for alignment */
- div.input_area {
- border: 1px solid #cfcfcf;
- border-radius: 2px;
- background: #f7f7f7;
- line-height: 1.21429em;
- }
- /* This is needed so that empty prompt areas can collapse to zero height when there
- is no content in the output_subarea and the prompt. The main purpose of this is
- to make sure that empty JavaScript output_subareas have no height. */
- div.prompt:empty {
- padding-top: 0;
- padding-bottom: 0;
- }
- div.unrecognized_cell {
- padding: 5px 5px 5px 0px;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- }
- div.unrecognized_cell .inner_cell {
- border-radius: 2px;
- padding: 5px;
- font-weight: bold;
- color: red;
- border: 1px solid #cfcfcf;
- background: #eaeaea;
- }
- div.unrecognized_cell .inner_cell a {
- color: inherit;
- text-decoration: none;
- }
- div.unrecognized_cell .inner_cell a:hover {
- color: inherit;
- text-decoration: none;
- }
- @media (max-width: 540px) {
- div.unrecognized_cell > div.prompt {
- display: none;
- }
- }
- div.code_cell {
- /* avoid page breaking on code cells when printing */
- }
- @media print {
- div.code_cell {
- page-break-inside: avoid;
- }
- }
- /* any special styling for code cells that are currently running goes here */
- div.input {
- page-break-inside: avoid;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- }
- @media (max-width: 540px) {
- div.input {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- }
- }
- /* input_area and input_prompt must match in top border and margin for alignment */
- div.input_prompt {
- color: #303F9F;
- border-top: 1px solid transparent;
- }
- div.input_area > div.highlight {
- margin: 0.4em;
- border: none;
- padding: 0px;
- background-color: transparent;
- }
- div.input_area > div.highlight > pre {
- margin: 0px;
- border: none;
- padding: 0px;
- background-color: transparent;
- }
- /* The following gets added to the <head> if it is detected that the user has a
- * monospace font with inconsistent normal/bold/italic height. See
- * notebookmain.js. Such fonts will have keywords vertically offset with
- * respect to the rest of the text. The user should select a better font.
- * See: https://github.com/ipython/ipython/issues/1503
- *
- * .CodeMirror span {
- * vertical-align: bottom;
- * }
- */
- .CodeMirror {
- line-height: 1.21429em;
- /* Changed from 1em to our global default */
- font-size: 14px;
- height: auto;
- /* Changed to auto to autogrow */
- background: none;
- /* Changed from white to allow our bg to show through */
- }
- .CodeMirror-scroll {
- /* The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
- /* We have found that if it is visible, vertical scrollbars appear with font size changes.*/
- overflow-y: hidden;
- overflow-x: auto;
- }
- .CodeMirror-lines {
- /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
- /* we have set a different line-height and want this to scale with that. */
- padding: 0.4em;
- }
- .CodeMirror-linenumber {
- padding: 0 8px 0 4px;
- }
- .CodeMirror-gutters {
- border-bottom-left-radius: 2px;
- border-top-left-radius: 2px;
- }
- .CodeMirror pre {
- /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
- /* .CodeMirror-lines */
- padding: 0;
- border: 0;
- border-radius: 0;
- }
- /*
- Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
- Adapted from GitHub theme
- */
- .highlight-base {
- color: #000;
- }
- .highlight-variable {
- color: #000;
- }
- .highlight-variable-2 {
- color: #1a1a1a;
- }
- .highlight-variable-3 {
- color: #333333;
- }
- .highlight-string {
- color: #BA2121;
- }
- .highlight-comment {
- color: #408080;
- font-style: italic;
- }
- .highlight-number {
- color: #080;
- }
- .highlight-atom {
- color: #88F;
- }
- .highlight-keyword {
- color: #008000;
- font-weight: bold;
- }
- .highlight-builtin {
- color: #008000;
- }
- .highlight-error {
- color: #f00;
- }
- .highlight-operator {
- color: #AA22FF;
- font-weight: bold;
- }
- .highlight-meta {
- color: #AA22FF;
- }
- /* previously not defined, copying from default codemirror */
- .highlight-def {
- color: #00f;
- }
- .highlight-string-2 {
- color: #f50;
- }
- .highlight-qualifier {
- color: #555;
- }
- .highlight-bracket {
- color: #997;
- }
- .highlight-tag {
- color: #170;
- }
- .highlight-attribute {
- color: #00c;
- }
- .highlight-header {
- color: blue;
- }
- .highlight-quote {
- color: #090;
- }
- .highlight-link {
- color: #00c;
- }
- /* apply the same style to codemirror */
- .cm-s-ipython span.cm-keyword {
- color: #008000;
- font-weight: bold;
- }
- .cm-s-ipython span.cm-atom {
- color: #88F;
- }
- .cm-s-ipython span.cm-number {
- color: #080;
- }
- .cm-s-ipython span.cm-def {
- color: #00f;
- }
- .cm-s-ipython span.cm-variable {
- color: #000;
- }
- .cm-s-ipython span.cm-operator {
- color: #AA22FF;
- font-weight: bold;
- }
- .cm-s-ipython span.cm-variable-2 {
- color: #1a1a1a;
- }
- .cm-s-ipython span.cm-variable-3 {
- color: #333333;
- }
- .cm-s-ipython span.cm-comment {
- color: #408080;
- font-style: italic;
- }
- .cm-s-ipython span.cm-string {
- color: #BA2121;
- }
- .cm-s-ipython span.cm-string-2 {
- color: #f50;
- }
- .cm-s-ipython span.cm-meta {
- color: #AA22FF;
- }
- .cm-s-ipython span.cm-qualifier {
- color: #555;
- }
- .cm-s-ipython span.cm-builtin {
- color: #008000;
- }
- .cm-s-ipython span.cm-bracket {
- color: #997;
- }
- .cm-s-ipython span.cm-tag {
- color: #170;
- }
- .cm-s-ipython span.cm-attribute {
- color: #00c;
- }
- .cm-s-ipython span.cm-header {
- color: blue;
- }
- .cm-s-ipython span.cm-quote {
- color: #090;
- }
- .cm-s-ipython span.cm-link {
- color: #00c;
- }
- .cm-s-ipython span.cm-error {
- color: #f00;
- }
- .cm-s-ipython span.cm-tab {
- background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
- background-position: right;
- background-repeat: no-repeat;
- }
- div.output_wrapper {
- /* this position must be relative to enable descendents to be absolute within it */
- position: relative;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- z-index: 1;
- }
- /* class for the output area when it should be height-limited */
- div.output_scroll {
- /* ideally, this would be max-height, but FF barfs all over that */
- height: 24em;
- /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
- width: 100%;
- overflow: auto;
- border-radius: 2px;
- -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
- box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
- display: block;
- }
- /* output div while it is collapsed */
- div.output_collapsed {
- margin: 0px;
- padding: 0px;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- }
- div.out_prompt_overlay {
- height: 100%;
- padding: 0px 0.4em;
- position: absolute;
- border-radius: 2px;
- }
- div.out_prompt_overlay:hover {
- /* use inner shadow to get border that is computed the same on WebKit/FF */
- -webkit-box-shadow: inset 0 0 1px #000;
- box-shadow: inset 0 0 1px #000;
- background: rgba(240, 240, 240, 0.5);
- }
- div.output_prompt {
- color: #D84315;
- }
- /* This class is the outer container of all output sections. */
- div.output_area {
- padding: 0px;
- page-break-inside: avoid;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- }
- div.output_area .MathJax_Display {
- text-align: left !important;
- }
- div.output_area .rendered_html table {
- margin-left: 0;
- margin-right: 0;
- }
- div.output_area .rendered_html img {
- margin-left: 0;
- margin-right: 0;
- }
- div.output_area img,
- div.output_area svg {
- max-width: 100%;
- height: auto;
- }
- div.output_area img.unconfined,
- div.output_area svg.unconfined {
- max-width: none;
- }
- /* This is needed to protect the pre formating from global settings such
- as that of bootstrap */
- .output {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- }
- @media (max-width: 540px) {
- div.output_area {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: vertical;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: vertical;
- -moz-box-align: stretch;
- display: box;
- box-orient: vertical;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: column;
- align-items: stretch;
- }
- }
- div.output_area pre {
- margin: 0;
- padding: 0;
- border: 0;
- vertical-align: baseline;
- color: black;
- background-color: transparent;
- border-radius: 0;
- }
- /* This class is for the output subarea inside the output_area and after
- the prompt div. */
- div.output_subarea {
- overflow-x: auto;
- padding: 0.4em;
- /* Old browsers */
- -webkit-box-flex: 1;
- -moz-box-flex: 1;
- box-flex: 1;
- /* Modern browsers */
- flex: 1;
- max-width: calc(100% - 14ex);
- }
- div.output_scroll div.output_subarea {
- overflow-x: visible;
- }
- /* The rest of the output_* classes are for special styling of the different
- output types */
- /* all text output has this class: */
- div.output_text {
- text-align: left;
- color: #000;
- /* This has to match that of the the CodeMirror class line-height below */
- line-height: 1.21429em;
- }
- /* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
- div.output_stderr {
- background: #fdd;
- /* very light red background for stderr */
- }
- div.output_latex {
- text-align: left;
- }
- /* Empty output_javascript divs should have no height */
- div.output_javascript:empty {
- padding: 0;
- }
- .js-error {
- color: darkred;
- }
- /* raw_input styles */
- div.raw_input_container {
- line-height: 1.21429em;
- padding-top: 5px;
- }
- pre.raw_input_prompt {
- /* nothing needed here. */
- }
- input.raw_input {
- font-family: monospace;
- font-size: inherit;
- color: inherit;
- width: auto;
- /* make sure input baseline aligns with prompt */
- vertical-align: baseline;
- /* padding + margin = 0.5em between prompt and cursor */
- padding: 0em 0.25em;
- margin: 0em 0.25em;
- }
- input.raw_input:focus {
- box-shadow: none;
- }
- p.p-space {
- margin-bottom: 10px;
- }
- div.output_unrecognized {
- padding: 5px;
- font-weight: bold;
- color: red;
- }
- div.output_unrecognized a {
- color: inherit;
- text-decoration: none;
- }
- div.output_unrecognized a:hover {
- color: inherit;
- text-decoration: none;
- }
- .rendered_html {
- color: #000;
- /* any extras will just be numbers: */
- }
- .rendered_html em {
- font-style: italic;
- }
- .rendered_html strong {
- font-weight: bold;
- }
- .rendered_html u {
- text-decoration: underline;
- }
- .rendered_html :link {
- text-decoration: underline;
- }
- .rendered_html :visited {
- text-decoration: underline;
- }
- .rendered_html h1 {
- font-size: 185.7%;
- margin: 1.08em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- }
- .rendered_html h2 {
- font-size: 157.1%;
- margin: 1.27em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- }
- .rendered_html h3 {
- font-size: 128.6%;
- margin: 1.55em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- }
- .rendered_html h4 {
- font-size: 100%;
- margin: 2em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- }
- .rendered_html h5 {
- font-size: 100%;
- margin: 2em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- font-style: italic;
- }
- .rendered_html h6 {
- font-size: 100%;
- margin: 2em 0 0 0;
- font-weight: bold;
- line-height: 1.0;
- font-style: italic;
- }
- .rendered_html h1:first-child {
- margin-top: 0.538em;
- }
- .rendered_html h2:first-child {
- margin-top: 0.636em;
- }
- .rendered_html h3:first-child {
- margin-top: 0.777em;
- }
- .rendered_html h4:first-child {
- margin-top: 1em;
- }
- .rendered_html h5:first-child {
- margin-top: 1em;
- }
- .rendered_html h6:first-child {
- margin-top: 1em;
- }
- .rendered_html ul {
- list-style: disc;
- margin: 0em 2em;
- padding-left: 0px;
- }
- .rendered_html ul ul {
- list-style: square;
- margin: 0em 2em;
- }
- .rendered_html ul ul ul {
- list-style: circle;
- margin: 0em 2em;
- }
- .rendered_html ol {
- list-style: decimal;
- margin: 0em 2em;
- padding-left: 0px;
- }
- .rendered_html ol ol {
- list-style: upper-alpha;
- margin: 0em 2em;
- }
- .rendered_html ol ol ol {
- list-style: lower-alpha;
- margin: 0em 2em;
- }
- .rendered_html ol ol ol ol {
- list-style: lower-roman;
- margin: 0em 2em;
- }
- .rendered_html ol ol ol ol ol {
- list-style: decimal;
- margin: 0em 2em;
- }
- .rendered_html * + ul {
- margin-top: 1em;
- }
- .rendered_html * + ol {
- margin-top: 1em;
- }
- .rendered_html hr {
- color: black;
- background-color: black;
- }
- .rendered_html pre {
- margin: 1em 2em;
- }
- .rendered_html pre,
- .rendered_html code {
- border: 0;
- background-color: #fff;
- color: #000;
- font-size: 100%;
- padding: 0px;
- }
- .rendered_html blockquote {
- margin: 1em 2em;
- }
- .rendered_html table {
- margin-left: auto;
- margin-right: auto;
- border: 1px solid black;
- border-collapse: collapse;
- }
- .rendered_html tr,
- .rendered_html th,
- .rendered_html td {
- border: 1px solid black;
- border-collapse: collapse;
- margin: 1em 2em;
- }
- .rendered_html td,
- .rendered_html th {
- text-align: left;
- vertical-align: middle;
- padding: 4px;
- }
- .rendered_html th {
- font-weight: bold;
- }
- .rendered_html * + table {
- margin-top: 1em;
- }
- .rendered_html p {
- text-align: left;
- }
- .rendered_html * + p {
- margin-top: 1em;
- }
- .rendered_html img {
- display: block;
- margin-left: auto;
- margin-right: auto;
- }
- .rendered_html * + img {
- margin-top: 1em;
- }
- .rendered_html img,
- .rendered_html svg {
- max-width: 100%;
- height: auto;
- }
- .rendered_html img.unconfined,
- .rendered_html svg.unconfined {
- max-width: none;
- }
- div.text_cell {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- }
- @media (max-width: 540px) {
- div.text_cell > div.prompt {
- display: none;
- }
- }
- div.text_cell_render {
- /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
- outline: none;
- resize: none;
- width: inherit;
- border-style: none;
- padding: 0.5em 0.5em 0.5em 0.4em;
- color: #000;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- }
- a.anchor-link:link {
- text-decoration: none;
- padding: 0px 20px;
- visibility: hidden;
- }
- h1:hover .anchor-link,
- h2:hover .anchor-link,
- h3:hover .anchor-link,
- h4:hover .anchor-link,
- h5:hover .anchor-link,
- h6:hover .anchor-link {
- visibility: visible;
- }
- .text_cell.rendered .input_area {
- display: none;
- }
- .text_cell.rendered .rendered_html {
- overflow-x: auto;
- overflow-y: hidden;
- }
- .text_cell.unrendered .text_cell_render {
- display: none;
- }
- .cm-header-1,
- .cm-header-2,
- .cm-header-3,
- .cm-header-4,
- .cm-header-5,
- .cm-header-6 {
- font-weight: bold;
- font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
- }
- .cm-header-1 {
- font-size: 185.7%;
- }
- .cm-header-2 {
- font-size: 157.1%;
- }
- .cm-header-3 {
- font-size: 128.6%;
- }
- .cm-header-4 {
- font-size: 110%;
- }
- .cm-header-5 {
- font-size: 100%;
- font-style: italic;
- }
- .cm-header-6 {
- font-size: 100%;
- font-style: italic;
- }
- /*!
- *
- * IPython notebook webapp
- *
- */
- @media (max-width: 767px) {
- .notebook_app {
- padding-left: 0px;
- padding-right: 0px;
- }
- }
- #ipython-main-app {
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- height: 100%;
- }
- div#notebook_panel {
- margin: 0px;
- padding: 0px;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- height: 100%;
- }
- div#notebook {
- font-size: 14px;
- line-height: 20px;
- overflow-y: hidden;
- overflow-x: auto;
- width: 100%;
- /* This spaces the page away from the edge of the notebook area */
- padding-top: 20px;
- margin: 0px;
- outline: none;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- min-height: 100%;
- }
- @media not print {
- #notebook-container {
- padding: 15px;
- background-color: #fff;
- min-height: 0;
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- }
- }
- @media print {
- #notebook-container {
- width: 100%;
- }
- }
- div.ui-widget-content {
- border: 1px solid #ababab;
- outline: none;
- }
- pre.dialog {
- background-color: #f7f7f7;
- border: 1px solid #ddd;
- border-radius: 2px;
- padding: 0.4em;
- padding-left: 2em;
- }
- p.dialog {
- padding: 0.2em;
- }
- /* Word-wrap output correctly. This is the CSS3 spelling, though Firefox seems
- to not honor it correctly. Webkit browsers (Chrome, rekonq, Safari) do.
- */
- pre,
- code,
- kbd,
- samp {
- white-space: pre-wrap;
- }
- #fonttest {
- font-family: monospace;
- }
- p {
- margin-bottom: 0;
- }
- .end_space {
- min-height: 100px;
- transition: height .2s ease;
- }
- .notebook_app > #header {
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- }
- @media not print {
- .notebook_app {
- background-color: #EEE;
- }
- }
- kbd {
- border-style: solid;
- border-width: 1px;
- box-shadow: none;
- margin: 2px;
- padding-left: 2px;
- padding-right: 2px;
- padding-top: 1px;
- padding-bottom: 1px;
- }
- /* CSS for the cell toolbar */
- .celltoolbar {
- border: thin solid #CFCFCF;
- border-bottom: none;
- background: #EEE;
- border-radius: 2px 2px 0px 0px;
- width: 100%;
- height: 29px;
- padding-right: 4px;
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- /* Old browsers */
- -webkit-box-pack: end;
- -moz-box-pack: end;
- box-pack: end;
- /* Modern browsers */
- justify-content: flex-end;
- display: -webkit-flex;
- }
- @media print {
- .celltoolbar {
- display: none;
- }
- }
- .ctb_hideshow {
- display: none;
- vertical-align: bottom;
- }
- /* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
- Cell toolbars are only shown when the ctb_global_show class is also set.
- */
- .ctb_global_show .ctb_show.ctb_hideshow {
- display: block;
- }
- .ctb_global_show .ctb_show + .input_area,
- .ctb_global_show .ctb_show + div.text_cell_input,
- .ctb_global_show .ctb_show ~ div.text_cell_render {
- border-top-right-radius: 0px;
- border-top-left-radius: 0px;
- }
- .ctb_global_show .ctb_show ~ div.text_cell_render {
- border: 1px solid #cfcfcf;
- }
- .celltoolbar {
- font-size: 87%;
- padding-top: 3px;
- }
- .celltoolbar select {
- display: block;
- width: 100%;
- height: 32px;
- padding: 6px 12px;
- font-size: 13px;
- line-height: 1.42857143;
- color: #555555;
- background-color: #fff;
- background-image: none;
- border: 1px solid #ccc;
- border-radius: 2px;
- -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
- -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
- height: 30px;
- padding: 5px 10px;
- font-size: 12px;
- line-height: 1.5;
- border-radius: 1px;
- width: inherit;
- font-size: inherit;
- height: 22px;
- padding: 0px;
- display: inline-block;
- }
- .celltoolbar select:focus {
- border-color: #66afe9;
- outline: 0;
- -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
- box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
- }
- .celltoolbar select::-moz-placeholder {
- color: #999;
- opacity: 1;
- }
- .celltoolbar select:-ms-input-placeholder {
- color: #999;
- }
- .celltoolbar select::-webkit-input-placeholder {
- color: #999;
- }
- .celltoolbar select::-ms-expand {
- border: 0;
- background-color: transparent;
- }
- .celltoolbar select[disabled],
- .celltoolbar select[readonly],
- fieldset[disabled] .celltoolbar select {
- background-color: #eeeeee;
- opacity: 1;
- }
- .celltoolbar select[disabled],
- fieldset[disabled] .celltoolbar select {
- cursor: not-allowed;
- }
- textarea.celltoolbar select {
- height: auto;
- }
- select.celltoolbar select {
- height: 30px;
- line-height: 30px;
- }
- textarea.celltoolbar select,
- select[multiple].celltoolbar select {
- height: auto;
- }
- .celltoolbar label {
- margin-left: 5px;
- margin-right: 5px;
- }
- .completions {
- position: absolute;
- z-index: 110;
- overflow: hidden;
- border: 1px solid #ababab;
- border-radius: 2px;
- -webkit-box-shadow: 0px 6px 10px -1px #adadad;
- box-shadow: 0px 6px 10px -1px #adadad;
- line-height: 1;
- }
- .completions select {
- background: white;
- outline: none;
- border: none;
- padding: 0px;
- margin: 0px;
- overflow: auto;
- font-family: monospace;
- font-size: 110%;
- color: #000;
- width: auto;
- }
- .completions select option.context {
- color: #286090;
- }
- #kernel_logo_widget {
- float: right !important;
- float: right;
- }
- #kernel_logo_widget .current_kernel_logo {
- display: none;
- margin-top: -1px;
- margin-bottom: -1px;
- width: 32px;
- height: 32px;
- }
- #menubar {
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- margin-top: 1px;
- }
- #menubar .navbar {
- border-top: 1px;
- border-radius: 0px 0px 2px 2px;
- margin-bottom: 0px;
- }
- #menubar .navbar-toggle {
- float: left;
- padding-top: 7px;
- padding-bottom: 7px;
- border: none;
- }
- #menubar .navbar-collapse {
- clear: left;
- }
- .nav-wrapper {
- border-bottom: 1px solid #e7e7e7;
- }
- i.menu-icon {
- padding-top: 4px;
- }
- ul#help_menu li a {
- overflow: hidden;
- padding-right: 2.2em;
- }
- ul#help_menu li a i {
- margin-right: -1.2em;
- }
- .dropdown-submenu {
- position: relative;
- }
- .dropdown-submenu > .dropdown-menu {
- top: 0;
- left: 100%;
- margin-top: -6px;
- margin-left: -1px;
- }
- .dropdown-submenu:hover > .dropdown-menu {
- display: block;
- }
- .dropdown-submenu > a:after {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- display: block;
- content: "\f0da";
- float: right;
- color: #333333;
- margin-top: 2px;
- margin-right: -10px;
- }
- .dropdown-submenu > a:after.pull-left {
- margin-right: .3em;
- }
- .dropdown-submenu > a:after.pull-right {
- margin-left: .3em;
- }
- .dropdown-submenu:hover > a:after {
- color: #262626;
- }
- .dropdown-submenu.pull-left {
- float: none;
- }
- .dropdown-submenu.pull-left > .dropdown-menu {
- left: -100%;
- margin-left: 10px;
- }
- #notification_area {
- float: right !important;
- float: right;
- z-index: 10;
- }
- .indicator_area {
- float: right !important;
- float: right;
- color: #777;
- margin-left: 5px;
- margin-right: 5px;
- width: 11px;
- z-index: 10;
- text-align: center;
- width: auto;
- }
- #kernel_indicator {
- float: right !important;
- float: right;
- color: #777;
- margin-left: 5px;
- margin-right: 5px;
- width: 11px;
- z-index: 10;
- text-align: center;
- width: auto;
- border-left: 1px solid;
- }
- #kernel_indicator .kernel_indicator_name {
- padding-left: 5px;
- padding-right: 5px;
- }
- #modal_indicator {
- float: right !important;
- float: right;
- color: #777;
- margin-left: 5px;
- margin-right: 5px;
- width: 11px;
- z-index: 10;
- text-align: center;
- width: auto;
- }
- #readonly-indicator {
- float: right !important;
- float: right;
- color: #777;
- margin-left: 5px;
- margin-right: 5px;
- width: 11px;
- z-index: 10;
- text-align: center;
- width: auto;
- margin-top: 2px;
- margin-bottom: 0px;
- margin-left: 0px;
- margin-right: 0px;
- display: none;
- }
- .modal_indicator:before {
- width: 1.28571429em;
- text-align: center;
- }
- .edit_mode .modal_indicator:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f040";
- }
- .edit_mode .modal_indicator:before.pull-left {
- margin-right: .3em;
- }
- .edit_mode .modal_indicator:before.pull-right {
- margin-left: .3em;
- }
- .command_mode .modal_indicator:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: ' ';
- }
- .command_mode .modal_indicator:before.pull-left {
- margin-right: .3em;
- }
- .command_mode .modal_indicator:before.pull-right {
- margin-left: .3em;
- }
- .kernel_idle_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f10c";
- }
- .kernel_idle_icon:before.pull-left {
- margin-right: .3em;
- }
- .kernel_idle_icon:before.pull-right {
- margin-left: .3em;
- }
- .kernel_busy_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f111";
- }
- .kernel_busy_icon:before.pull-left {
- margin-right: .3em;
- }
- .kernel_busy_icon:before.pull-right {
- margin-left: .3em;
- }
- .kernel_dead_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f1e2";
- }
- .kernel_dead_icon:before.pull-left {
- margin-right: .3em;
- }
- .kernel_dead_icon:before.pull-right {
- margin-left: .3em;
- }
- .kernel_disconnected_icon:before {
- display: inline-block;
- font: normal normal normal 14px/1 FontAwesome;
- font-size: inherit;
- text-rendering: auto;
- -webkit-font-smoothing: antialiased;
- -moz-osx-font-smoothing: grayscale;
- content: "\f127";
- }
- .kernel_disconnected_icon:before.pull-left {
- margin-right: .3em;
- }
- .kernel_disconnected_icon:before.pull-right {
- margin-left: .3em;
- }
- .notification_widget {
- color: #777;
- z-index: 10;
- background: rgba(240, 240, 240, 0.5);
- margin-right: 4px;
- color: #333;
- background-color: #fff;
- border-color: #ccc;
- }
- .notification_widget:focus,
- .notification_widget.focus {
- color: #333;
- background-color: #e6e6e6;
- border-color: #8c8c8c;
- }
- .notification_widget:hover {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- .notification_widget:active,
- .notification_widget.active,
- .open > .dropdown-toggle.notification_widget {
- color: #333;
- background-color: #e6e6e6;
- border-color: #adadad;
- }
- .notification_widget:active:hover,
- .notification_widget.active:hover,
- .open > .dropdown-toggle.notification_widget:hover,
- .notification_widget:active:focus,
- .notification_widget.active:focus,
- .open > .dropdown-toggle.notification_widget:focus,
- .notification_widget:active.focus,
- .notification_widget.active.focus,
- .open > .dropdown-toggle.notification_widget.focus {
- color: #333;
- background-color: #d4d4d4;
- border-color: #8c8c8c;
- }
- .notification_widget:active,
- .notification_widget.active,
- .open > .dropdown-toggle.notification_widget {
- background-image: none;
- }
- .notification_widget.disabled:hover,
- .notification_widget[disabled]:hover,
- fieldset[disabled] .notification_widget:hover,
- .notification_widget.disabled:focus,
- .notification_widget[disabled]:focus,
- fieldset[disabled] .notification_widget:focus,
- .notification_widget.disabled.focus,
- .notification_widget[disabled].focus,
- fieldset[disabled] .notification_widget.focus {
- background-color: #fff;
- border-color: #ccc;
- }
- .notification_widget .badge {
- color: #fff;
- background-color: #333;
- }
- .notification_widget.warning {
- color: #fff;
- background-color: #f0ad4e;
- border-color: #eea236;
- }
- .notification_widget.warning:focus,
- .notification_widget.warning.focus {
- color: #fff;
- background-color: #ec971f;
- border-color: #985f0d;
- }
- .notification_widget.warning:hover {
- color: #fff;
- background-color: #ec971f;
- border-color: #d58512;
- }
- .notification_widget.warning:active,
- .notification_widget.warning.active,
- .open > .dropdown-toggle.notification_widget.warning {
- color: #fff;
- background-color: #ec971f;
- border-color: #d58512;
- }
- .notification_widget.warning:active:hover,
- .notification_widget.warning.active:hover,
- .open > .dropdown-toggle.notification_widget.warning:hover,
- .notification_widget.warning:active:focus,
- .notification_widget.warning.active:focus,
- .open > .dropdown-toggle.notification_widget.warning:focus,
- .notification_widget.warning:active.focus,
- .notification_widget.warning.active.focus,
- .open > .dropdown-toggle.notification_widget.warning.focus {
- color: #fff;
- background-color: #d58512;
- border-color: #985f0d;
- }
- .notification_widget.warning:active,
- .notification_widget.warning.active,
- .open > .dropdown-toggle.notification_widget.warning {
- background-image: none;
- }
- .notification_widget.warning.disabled:hover,
- .notification_widget.warning[disabled]:hover,
- fieldset[disabled] .notification_widget.warning:hover,
- .notification_widget.warning.disabled:focus,
- .notification_widget.warning[disabled]:focus,
- fieldset[disabled] .notification_widget.warning:focus,
- .notification_widget.warning.disabled.focus,
- .notification_widget.warning[disabled].focus,
- fieldset[disabled] .notification_widget.warning.focus {
- background-color: #f0ad4e;
- border-color: #eea236;
- }
- .notification_widget.warning .badge {
- color: #f0ad4e;
- background-color: #fff;
- }
- .notification_widget.success {
- color: #fff;
- background-color: #5cb85c;
- border-color: #4cae4c;
- }
- .notification_widget.success:focus,
- .notification_widget.success.focus {
- color: #fff;
- background-color: #449d44;
- border-color: #255625;
- }
- .notification_widget.success:hover {
- color: #fff;
- background-color: #449d44;
- border-color: #398439;
- }
- .notification_widget.success:active,
- .notification_widget.success.active,
- .open > .dropdown-toggle.notification_widget.success {
- color: #fff;
- background-color: #449d44;
- border-color: #398439;
- }
- .notification_widget.success:active:hover,
- .notification_widget.success.active:hover,
- .open > .dropdown-toggle.notification_widget.success:hover,
- .notification_widget.success:active:focus,
- .notification_widget.success.active:focus,
- .open > .dropdown-toggle.notification_widget.success:focus,
- .notification_widget.success:active.focus,
- .notification_widget.success.active.focus,
- .open > .dropdown-toggle.notification_widget.success.focus {
- color: #fff;
- background-color: #398439;
- border-color: #255625;
- }
- .notification_widget.success:active,
- .notification_widget.success.active,
- .open > .dropdown-toggle.notification_widget.success {
- background-image: none;
- }
- .notification_widget.success.disabled:hover,
- .notification_widget.success[disabled]:hover,
- fieldset[disabled] .notification_widget.success:hover,
- .notification_widget.success.disabled:focus,
- .notification_widget.success[disabled]:focus,
- fieldset[disabled] .notification_widget.success:focus,
- .notification_widget.success.disabled.focus,
- .notification_widget.success[disabled].focus,
- fieldset[disabled] .notification_widget.success.focus {
- background-color: #5cb85c;
- border-color: #4cae4c;
- }
- .notification_widget.success .badge {
- color: #5cb85c;
- background-color: #fff;
- }
- .notification_widget.info {
- color: #fff;
- background-color: #5bc0de;
- border-color: #46b8da;
- }
- .notification_widget.info:focus,
- .notification_widget.info.focus {
- color: #fff;
- background-color: #31b0d5;
- border-color: #1b6d85;
- }
- .notification_widget.info:hover {
- color: #fff;
- background-color: #31b0d5;
- border-color: #269abc;
- }
- .notification_widget.info:active,
- .notification_widget.info.active,
- .open > .dropdown-toggle.notification_widget.info {
- color: #fff;
- background-color: #31b0d5;
- border-color: #269abc;
- }
- .notification_widget.info:active:hover,
- .notification_widget.info.active:hover,
- .open > .dropdown-toggle.notification_widget.info:hover,
- .notification_widget.info:active:focus,
- .notification_widget.info.active:focus,
- .open > .dropdown-toggle.notification_widget.info:focus,
- .notification_widget.info:active.focus,
- .notification_widget.info.active.focus,
- .open > .dropdown-toggle.notification_widget.info.focus {
- color: #fff;
- background-color: #269abc;
- border-color: #1b6d85;
- }
- .notification_widget.info:active,
- .notification_widget.info.active,
- .open > .dropdown-toggle.notification_widget.info {
- background-image: none;
- }
- .notification_widget.info.disabled:hover,
- .notification_widget.info[disabled]:hover,
- fieldset[disabled] .notification_widget.info:hover,
- .notification_widget.info.disabled:focus,
- .notification_widget.info[disabled]:focus,
- fieldset[disabled] .notification_widget.info:focus,
- .notification_widget.info.disabled.focus,
- .notification_widget.info[disabled].focus,
- fieldset[disabled] .notification_widget.info.focus {
- background-color: #5bc0de;
- border-color: #46b8da;
- }
- .notification_widget.info .badge {
- color: #5bc0de;
- background-color: #fff;
- }
- .notification_widget.danger {
- color: #fff;
- background-color: #d9534f;
- border-color: #d43f3a;
- }
- .notification_widget.danger:focus,
- .notification_widget.danger.focus {
- color: #fff;
- background-color: #c9302c;
- border-color: #761c19;
- }
- .notification_widget.danger:hover {
- color: #fff;
- background-color: #c9302c;
- border-color: #ac2925;
- }
- .notification_widget.danger:active,
- .notification_widget.danger.active,
- .open > .dropdown-toggle.notification_widget.danger {
- color: #fff;
- background-color: #c9302c;
- border-color: #ac2925;
- }
- .notification_widget.danger:active:hover,
- .notification_widget.danger.active:hover,
- .open > .dropdown-toggle.notification_widget.danger:hover,
- .notification_widget.danger:active:focus,
- .notification_widget.danger.active:focus,
- .open > .dropdown-toggle.notification_widget.danger:focus,
- .notification_widget.danger:active.focus,
- .notification_widget.danger.active.focus,
- .open > .dropdown-toggle.notification_widget.danger.focus {
- color: #fff;
- background-color: #ac2925;
- border-color: #761c19;
- }
- .notification_widget.danger:active,
- .notification_widget.danger.active,
- .open > .dropdown-toggle.notification_widget.danger {
- background-image: none;
- }
- .notification_widget.danger.disabled:hover,
- .notification_widget.danger[disabled]:hover,
- fieldset[disabled] .notification_widget.danger:hover,
- .notification_widget.danger.disabled:focus,
- .notification_widget.danger[disabled]:focus,
- fieldset[disabled] .notification_widget.danger:focus,
- .notification_widget.danger.disabled.focus,
- .notification_widget.danger[disabled].focus,
- fieldset[disabled] .notification_widget.danger.focus {
- background-color: #d9534f;
- border-color: #d43f3a;
- }
- .notification_widget.danger .badge {
- color: #d9534f;
- background-color: #fff;
- }
- div#pager {
- background-color: #fff;
- font-size: 14px;
- line-height: 20px;
- overflow: hidden;
- display: none;
- position: fixed;
- bottom: 0px;
- width: 100%;
- max-height: 50%;
- padding-top: 8px;
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- /* Display over codemirror */
- z-index: 100;
- /* Hack which prevents jquery ui resizable from changing top. */
- top: auto !important;
- }
- div#pager pre {
- line-height: 1.21429em;
- color: #000;
- background-color: #f7f7f7;
- padding: 0.4em;
- }
- div#pager #pager-button-area {
- position: absolute;
- top: 8px;
- right: 20px;
- }
- div#pager #pager-contents {
- position: relative;
- overflow: auto;
- width: 100%;
- height: 100%;
- }
- div#pager #pager-contents #pager-container {
- position: relative;
- padding: 15px 0px;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- }
- div#pager .ui-resizable-handle {
- top: 0px;
- height: 8px;
- background: #f7f7f7;
- border-top: 1px solid #cfcfcf;
- border-bottom: 1px solid #cfcfcf;
- /* This injects handle bars (a short, wide = symbol) for
- the resize handle. */
- }
- div#pager .ui-resizable-handle::after {
- content: '';
- top: 2px;
- left: 50%;
- height: 3px;
- width: 30px;
- margin-left: -15px;
- position: absolute;
- border-top: 1px solid #cfcfcf;
- }
- .quickhelp {
- /* Old browsers */
- display: -webkit-box;
- -webkit-box-orient: horizontal;
- -webkit-box-align: stretch;
- display: -moz-box;
- -moz-box-orient: horizontal;
- -moz-box-align: stretch;
- display: box;
- box-orient: horizontal;
- box-align: stretch;
- /* Modern browsers */
- display: flex;
- flex-direction: row;
- align-items: stretch;
- line-height: 1.8em;
- }
- .shortcut_key {
- display: inline-block;
- width: 21ex;
- text-align: right;
- font-family: monospace;
- }
- .shortcut_descr {
- display: inline-block;
- /* Old browsers */
- -webkit-box-flex: 1;
- -moz-box-flex: 1;
- box-flex: 1;
- /* Modern browsers */
- flex: 1;
- }
- span.save_widget {
- margin-top: 6px;
- }
- span.save_widget span.filename {
- height: 1em;
- line-height: 1em;
- padding: 3px;
- margin-left: 16px;
- border: none;
- font-size: 146.5%;
- border-radius: 2px;
- }
- span.save_widget span.filename:hover {
- background-color: #e6e6e6;
- }
- span.checkpoint_status,
- span.autosave_status {
- font-size: small;
- }
- @media (max-width: 767px) {
- span.save_widget {
- font-size: small;
- }
- span.checkpoint_status,
- span.autosave_status {
- display: none;
- }
- }
- @media (min-width: 768px) and (max-width: 991px) {
- span.checkpoint_status {
- display: none;
- }
- span.autosave_status {
- font-size: x-small;
- }
- }
- .toolbar {
- padding: 0px;
- margin-left: -5px;
- margin-top: 2px;
- margin-bottom: 5px;
- box-sizing: border-box;
- -moz-box-sizing: border-box;
- -webkit-box-sizing: border-box;
- }
- .toolbar select,
- .toolbar label {
- width: auto;
- vertical-align: middle;
- margin-right: 2px;
- margin-bottom: 0px;
- display: inline;
- font-size: 92%;
- margin-left: 0.3em;
- margin-right: 0.3em;
- padding: 0px;
- padding-top: 3px;
- }
- .toolbar .btn {
- padding: 2px 8px;
- }
- .toolbar .btn-group {
- margin-top: 0px;
- margin-left: 5px;
- }
- #maintoolbar {
- margin-bottom: -3px;
- margin-top: -8px;
- border: 0px;
- min-height: 27px;
- margin-left: 0px;
- padding-top: 11px;
- padding-bottom: 3px;
- }
- #maintoolbar .navbar-text {
- float: none;
- vertical-align: middle;
- text-align: right;
- margin-left: 5px;
- margin-right: 0px;
- margin-top: 0px;
- }
- .select-xs {
- height: 24px;
- }
- .pulse,
- .dropdown-menu > li > a.pulse,
- li.pulse > a.dropdown-toggle,
- li.pulse.open > a.dropdown-toggle {
- background-color: #F37626;
- color: white;
- }
- /**
- * Primary styles
- *
- * Author: Jupyter Development Team
- */
- /** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
- * of chance of beeing generated from the ../less/[samename].less file, you can
- * try to get back the less file by reverting somme commit in history
- **/
- /*
- * We'll try to get something pretty, so we
- * have some strange css to have the scroll bar on
- * the left with fix button on the top right of the tooltip
- */
- @-moz-keyframes fadeOut {
- from {
- opacity: 1;
- }
- to {
- opacity: 0;
- }
- }
- @-webkit-keyframes fadeOut {
- from {
- opacity: 1;
- }
- to {
- opacity: 0;
- }
- }
- @-moz-keyframes fadeIn {
- from {
- opacity: 0;
- }
- to {
- opacity: 1;
- }
- }
- @-webkit-keyframes fadeIn {
- from {
- opacity: 0;
- }
- to {
- opacity: 1;
- }
- }
- /*properties of tooltip after "expand"*/
- .bigtooltip {
- overflow: auto;
- height: 200px;
- -webkit-transition-property: height;
- -webkit-transition-duration: 500ms;
- -moz-transition-property: height;
- -moz-transition-duration: 500ms;
- transition-property: height;
- transition-duration: 500ms;
- }
- /*properties of tooltip before "expand"*/
- .smalltooltip {
- -webkit-transition-property: height;
- -webkit-transition-duration: 500ms;
- -moz-transition-property: height;
- -moz-transition-duration: 500ms;
- transition-property: height;
- transition-duration: 500ms;
- text-overflow: ellipsis;
- overflow: hidden;
- height: 80px;
- }
- .tooltipbuttons {
- position: absolute;
- padding-right: 15px;
- top: 0px;
- right: 0px;
- }
- .tooltiptext {
- /*avoid the button to overlap on some docstring*/
- padding-right: 30px;
- }
- .ipython_tooltip {
- max-width: 700px;
- /*fade-in animation when inserted*/
- -webkit-animation: fadeOut 400ms;
- -moz-animation: fadeOut 400ms;
- animation: fadeOut 400ms;
- -webkit-animation: fadeIn 400ms;
- -moz-animation: fadeIn 400ms;
- animation: fadeIn 400ms;
- vertical-align: middle;
- background-color: #f7f7f7;
- overflow: visible;
- border: #ababab 1px solid;
- outline: none;
- padding: 3px;
- margin: 0px;
- padding-left: 7px;
- font-family: monospace;
- min-height: 50px;
- -moz-box-shadow: 0px 6px 10px -1px #adadad;
- -webkit-box-shadow: 0px 6px 10px -1px #adadad;
- box-shadow: 0px 6px 10px -1px #adadad;
- border-radius: 2px;
- position: absolute;
- z-index: 1000;
- }
- .ipython_tooltip a {
- float: right;
- }
- .ipython_tooltip .tooltiptext pre {
- border: 0;
- border-radius: 0;
- font-size: 100%;
- background-color: #f7f7f7;
- }
- .pretooltiparrow {
- left: 0px;
- margin: 0px;
- top: -16px;
- width: 40px;
- height: 16px;
- overflow: hidden;
- position: absolute;
- }
- .pretooltiparrow:before {
- background-color: #f7f7f7;
- border: 1px #ababab solid;
- z-index: 11;
- content: "";
- position: absolute;
- left: 15px;
- top: 10px;
- width: 25px;
- height: 25px;
- -webkit-transform: rotate(45deg);
- -moz-transform: rotate(45deg);
- -ms-transform: rotate(45deg);
- -o-transform: rotate(45deg);
- }
- ul.typeahead-list i {
- margin-left: -10px;
- width: 18px;
- }
- ul.typeahead-list {
- max-height: 80vh;
- overflow: auto;
- }
- ul.typeahead-list > li > a {
- /** Firefox bug **/
- /* see https://github.com/jupyter/notebook/issues/559 */
- white-space: normal;
- }
- .cmd-palette .modal-body {
- padding: 7px;
- }
- .cmd-palette form {
- background: white;
- }
- .cmd-palette input {
- outline: none;
- }
- .no-shortcut {
- display: none;
- }
- .command-shortcut:before {
- content: "(command)";
- padding-right: 3px;
- color: #777777;
- }
- .edit-shortcut:before {
- content: "(edit)";
- padding-right: 3px;
- color: #777777;
- }
- #find-and-replace #replace-preview .match,
- #find-and-replace #replace-preview .insert {
- background-color: #BBDEFB;
- border-color: #90CAF9;
- border-style: solid;
- border-width: 1px;
- border-radius: 0px;
- }
- #find-and-replace #replace-preview .replace .match {
- background-color: #FFCDD2;
- border-color: #EF9A9A;
- border-radius: 0px;
- }
- #find-and-replace #replace-preview .replace .insert {
- background-color: #C8E6C9;
- border-color: #A5D6A7;
- border-radius: 0px;
- }
- #find-and-replace #replace-preview {
- max-height: 60vh;
- overflow: auto;
- }
- #find-and-replace #replace-preview pre {
- padding: 5px 10px;
- }
- .terminal-app {
- background: #EEE;
- }
- .terminal-app #header {
- background: #fff;
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
- }
- .terminal-app .terminal {
- width: 100%;
- float: left;
- font-family: monospace;
- color: white;
- background: black;
- padding: 0.4em;
- border-radius: 2px;
- -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
- box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
- }
- .terminal-app .terminal,
- .terminal-app .terminal dummy-screen {
- line-height: 1em;
- font-size: 14px;
- }
- .terminal-app .terminal .xterm-rows {
- padding: 10px;
- }
- .terminal-app .terminal-cursor {
- color: black;
- background: white;
- }
- .terminal-app #terminado-container {
- margin-top: 20px;
- }
- /*# sourceMappingURL=style.min.css.map */
- </style>
- <style type="text/css">
- .highlight .hll { background-color: #ffffcc }
- .highlight { background: #f8f8f8; }
- .highlight .c { color: #408080; font-style: italic } /* Comment */
- .highlight .err { border: 1px solid #FF0000 } /* Error */
- .highlight .k { color: #008000; font-weight: bold } /* Keyword */
- .highlight .o { color: #666666 } /* Operator */
- .highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
- .highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
- .highlight .cp { color: #BC7A00 } /* Comment.Preproc */
- .highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
- .highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
- .highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
- .highlight .gd { color: #A00000 } /* Generic.Deleted */
- .highlight .ge { font-style: italic } /* Generic.Emph */
- .highlight .gr { color: #FF0000 } /* Generic.Error */
- .highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
- .highlight .gi { color: #00A000 } /* Generic.Inserted */
- .highlight .go { color: #888888 } /* Generic.Output */
- .highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
- .highlight .gs { font-weight: bold } /* Generic.Strong */
- .highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
- .highlight .gt { color: #0044DD } /* Generic.Traceback */
- .highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
- .highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
- .highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
- .highlight .kp { color: #008000 } /* Keyword.Pseudo */
- .highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
- .highlight .kt { color: #B00040 } /* Keyword.Type */
- .highlight .m { color: #666666 } /* Literal.Number */
- .highlight .s { color: #BA2121 } /* Literal.String */
- .highlight .na { color: #7D9029 } /* Name.Attribute */
- .highlight .nb { color: #008000 } /* Name.Builtin */
- .highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
- .highlight .no { color: #880000 } /* Name.Constant */
- .highlight .nd { color: #AA22FF } /* Name.Decorator */
- .highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
- .highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
- .highlight .nf { color: #0000FF } /* Name.Function */
- .highlight .nl { color: #A0A000 } /* Name.Label */
- .highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
- .highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
- .highlight .nv { color: #19177C } /* Name.Variable */
- .highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
- .highlight .w { color: #bbbbbb } /* Text.Whitespace */
- .highlight .mb { color: #666666 } /* Literal.Number.Bin */
- .highlight .mf { color: #666666 } /* Literal.Number.Float */
- .highlight .mh { color: #666666 } /* Literal.Number.Hex */
- .highlight .mi { color: #666666 } /* Literal.Number.Integer */
- .highlight .mo { color: #666666 } /* Literal.Number.Oct */
- .highlight .sa { color: #BA2121 } /* Literal.String.Affix */
- .highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
- .highlight .sc { color: #BA2121 } /* Literal.String.Char */
- .highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
- .highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
- .highlight .s2 { color: #BA2121 } /* Literal.String.Double */
- .highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
- .highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
- .highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
- .highlight .sx { color: #008000 } /* Literal.String.Other */
- .highlight .sr { color: #BB6688 } /* Literal.String.Regex */
- .highlight .s1 { color: #BA2121 } /* Literal.String.Single */
- .highlight .ss { color: #19177C } /* Literal.String.Symbol */
- .highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
- .highlight .fm { color: #0000FF } /* Name.Function.Magic */
- .highlight .vc { color: #19177C } /* Name.Variable.Class */
- .highlight .vg { color: #19177C } /* Name.Variable.Global */
- .highlight .vi { color: #19177C } /* Name.Variable.Instance */
- .highlight .vm { color: #19177C } /* Name.Variable.Magic */
- .highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
- </style>
- <style type="text/css">
-
- /* Temporary definitions which will become obsolete with Notebook release 5.0 */
- .ansi-black-fg { color: #3E424D; }
- .ansi-black-bg { background-color: #3E424D; }
- .ansi-black-intense-fg { color: #282C36; }
- .ansi-black-intense-bg { background-color: #282C36; }
- .ansi-red-fg { color: #E75C58; }
- .ansi-red-bg { background-color: #E75C58; }
- .ansi-red-intense-fg { color: #B22B31; }
- .ansi-red-intense-bg { background-color: #B22B31; }
- .ansi-green-fg { color: #00A250; }
- .ansi-green-bg { background-color: #00A250; }
- .ansi-green-intense-fg { color: #007427; }
- .ansi-green-intense-bg { background-color: #007427; }
- .ansi-yellow-fg { color: #DDB62B; }
- .ansi-yellow-bg { background-color: #DDB62B; }
- .ansi-yellow-intense-fg { color: #B27D12; }
- .ansi-yellow-intense-bg { background-color: #B27D12; }
- .ansi-blue-fg { color: #208FFB; }
- .ansi-blue-bg { background-color: #208FFB; }
- .ansi-blue-intense-fg { color: #0065CA; }
- .ansi-blue-intense-bg { background-color: #0065CA; }
- .ansi-magenta-fg { color: #D160C4; }
- .ansi-magenta-bg { background-color: #D160C4; }
- .ansi-magenta-intense-fg { color: #A03196; }
- .ansi-magenta-intense-bg { background-color: #A03196; }
- .ansi-cyan-fg { color: #60C6C8; }
- .ansi-cyan-bg { background-color: #60C6C8; }
- .ansi-cyan-intense-fg { color: #258F8F; }
- .ansi-cyan-intense-bg { background-color: #258F8F; }
- .ansi-white-fg { color: #C5C1B4; }
- .ansi-white-bg { background-color: #C5C1B4; }
- .ansi-white-intense-fg { color: #A1A6B2; }
- .ansi-white-intense-bg { background-color: #A1A6B2; }
- .ansi-bold { font-weight: bold; }
- </style>
- <style type="text/css">
- /* Overrides of notebook CSS for static HTML export */
- body {
- overflow: visible;
- padding: 8px;
- }
- div#notebook {
- overflow: visible;
- border-top: none;
- }@media print {
- div.cell {
- display: block;
- page-break-inside: avoid;
- }
- div.output_wrapper {
- display: block;
- page-break-inside: avoid;
- }
- div.output {
- display: block;
- page-break-inside: avoid;
- }
- }
- </style>
- <!-- Custom stylesheet, it must be in the same directory as the html file -->
- <link rel="stylesheet" href="custom.css">
- <!-- Loading mathjax macro -->
- <!-- Load mathjax -->
- <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
- <!-- MathJax configuration -->
- <script type="text/x-mathjax-config">
- MathJax.Hub.Config({
- tex2jax: {
- inlineMath: [ ['$','$'], ["\\(","\\)"] ],
- displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
- processEscapes: true,
- processEnvironments: true
- },
- // Center justify equations in code and markdown cells. Elsewhere
- // we use CSS to left justify single line equations in code cells.
- displayAlign: 'center',
- "HTML-CSS": {
- styles: {'.MathJax_Display': {"margin": 0}},
- linebreaks: { automatic: true }
- }
- });
- </script>
- <!-- End of mathjax configuration --></head>
- <body>
- <div tabindex="-1" id="notebook" class="border-box-sizing">
- <div class="container" id="notebook-container">
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h1 id="Artificial-Intelligence-Nanodegree">Artificial Intelligence Nanodegree<a class="anchor-link" href="#Artificial-Intelligence-Nanodegree">¶</a></h1><h2 id="Convolutional-Neural-Networks">Convolutional Neural Networks<a class="anchor-link" href="#Convolutional-Neural-Networks">¶</a></h2><h2 id="Project:-Write-an-Algorithm-for-a-Dog-Identification-App">Project: Write an Algorithm for a Dog Identification App<a class="anchor-link" href="#Project:-Write-an-Algorithm-for-a-Dog-Identification-App">¶</a></h2><hr>
- <p>In this notebook, some template code has already been provided for you, and you will need to implement additional functionality to successfully complete this project. You will not need to modify the included code beyond what is requested. Sections that begin with <strong>'(IMPLEMENTATION)'</strong> in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section, and the specifics of the implementation are marked in the code block with a 'TODO' statement. Please be sure to read the instructions carefully!</p>
- <blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations, you need to finalize your work by exporting the iPython Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to \n",
- "<strong>File -> Download as -> HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
- </blockquote>
- <p>In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a <strong>'Question X'</strong> header. Carefully read each question and provide thorough answers in the following text boxes that begin with <strong>'Answer:'</strong>. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.</p>
- <blockquote><p><strong>Note:</strong> Code and Markdown cells can be executed using the <strong>Shift + Enter</strong> keyboard shortcut. Markdown cells can be edited by double-clicking the cell to enter edit mode.</p>
- </blockquote>
- <p>The rubric contains <em>optional</em> "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. If you decide to pursue the "Stand Out Suggestions", you should include the code in this IPython notebook.</p>
- <hr>
- <h3 id="Why-We're-Here">Why We're Here<a class="anchor-link" href="#Why-We're-Here">¶</a></h3><p>In this notebook, you will make the first steps towards developing an algorithm that could be used as part of a mobile or web app. At the end of this project, your code will accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling. The image below displays potential sample output of your finished project (... but we expect that each student's algorithm will behave differently!).</p>
- <p><img src="images/sample_dog_output.png" alt="Sample Dog Output"></p>
- <p>In this real-world setting, you will need to piece together a series of models to perform different tasks; for instance, the algorithm that detects humans in an image will be different from the CNN that infers dog breed. There are many points of possible failure, and no perfect algorithm exists. Your imperfect solution will nonetheless create a fun user experience!</p>
- <h3 id="The-Road-Ahead">The Road Ahead<a class="anchor-link" href="#The-Road-Ahead">¶</a></h3><p>We break the notebook into separate steps. Feel free to use the links below to navigate the notebook.</p>
- <ul>
- <li><a href="#step0">Step 0</a>: Import Datasets</li>
- <li><a href="#step1">Step 1</a>: Detect Humans</li>
- <li><a href="#step2">Step 2</a>: Detect Dogs</li>
- <li><a href="#step3">Step 3</a>: Create a CNN to Classify Dog Breeds (from Scratch)</li>
- <li><a href="#step4">Step 4</a>: Use a CNN to Classify Dog Breeds (using Transfer Learning)</li>
- <li><a href="#step5">Step 5</a>: Create a CNN to Classify Dog Breeds (using Transfer Learning)</li>
- <li><a href="#step6">Step 6</a>: Write your Algorithm</li>
- <li><a href="#step7">Step 7</a>: Test Your Algorithm</li>
- </ul>
- <hr>
- <p><a id='step0'></a></p>
- <h2 id="Step-0:-Import-Datasets">Step 0: Import Datasets<a class="anchor-link" href="#Step-0:-Import-Datasets">¶</a></h2><h3 id="Import-Dog-Dataset">Import Dog Dataset<a class="anchor-link" href="#Import-Dog-Dataset">¶</a></h3><p>In the code cell below, we import a dataset of dog images. We populate a few variables through the use of the <code>load_files</code> function from the scikit-learn library:</p>
- <ul>
- <li><code>train_files</code>, <code>valid_files</code>, <code>test_files</code> - numpy arrays containing file paths to images</li>
- <li><code>train_targets</code>, <code>valid_targets</code>, <code>test_targets</code> - numpy arrays containing onehot-encoded classification labels </li>
- <li><code>dog_names</code> - list of string-valued dog breed names for translating labels</li>
- </ul>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [58]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="k">import</span> <span class="n">load_files</span>
- <span class="kn">from</span> <span class="nn">keras.utils</span> <span class="k">import</span> <span class="n">np_utils</span>
- <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
- <span class="kn">from</span> <span class="nn">glob</span> <span class="k">import</span> <span class="n">glob</span>
- <span class="c1"># Define function to load train, test, and validation datasets</span>
- <span class="k">def</span> <span class="nf">load_dataset</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
- <span class="n">data</span> <span class="o">=</span> <span class="n">load_files</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
- <span class="n">dog_files</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s1">'filenames'</span><span class="p">])</span>
- <span class="n">dog_targets</span> <span class="o">=</span> <span class="n">np_utils</span><span class="o">.</span><span class="n">to_categorical</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="s1">'target'</span><span class="p">]),</span> <span class="mi">133</span><span class="p">)</span>
- <span class="k">return</span> <span class="n">dog_files</span><span class="p">,</span> <span class="n">dog_targets</span>
- <span class="c1"># Load train, test, and validation datasets</span>
- <span class="n">train_files</span><span class="p">,</span> <span class="n">train_targets</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">(</span><span class="s1">'/data/dog_images/train'</span><span class="p">)</span>
- <span class="n">valid_files</span><span class="p">,</span> <span class="n">valid_targets</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">(</span><span class="s1">'/data/dog_images/valid'</span><span class="p">)</span>
- <span class="n">test_files</span><span class="p">,</span> <span class="n">test_targets</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">(</span><span class="s1">'/data/dog_images/test'</span><span class="p">)</span>
- <span class="c1"># Load list of dog names</span>
- <span class="n">dog_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span><span class="p">[</span><span class="mi">20</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">glob</span><span class="p">(</span><span class="s2">"/data/dog_images/train/*/"</span><span class="p">))]</span>
- <span class="c1"># Print statistics about the dataset</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%d</span><span class="s1"> total dog categories.'</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">dog_names</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%s</span><span class="s1"> total dog images.</span><span class="se">\n</span><span class="s1">'</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">hstack</span><span class="p">([</span><span class="n">train_files</span><span class="p">,</span> <span class="n">valid_files</span><span class="p">,</span> <span class="n">test_files</span><span class="p">])))</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%d</span><span class="s1"> training dog images.'</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_files</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%d</span><span class="s1"> validation dog images.'</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">valid_files</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%d</span><span class="s1"> test dog images.'</span><span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">test_files</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>There are 133 total dog categories.
- There are 8351 total dog images.
- There are 6680 training dog images.
- There are 835 validation dog images.
- There are 836 test dog images.
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Import-Human-Dataset">Import Human Dataset<a class="anchor-link" href="#Import-Human-Dataset">¶</a></h3><p>In the code cell below, we import a dataset of human images, where the file paths are stored in the numpy array <code>human_files</code>.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [59]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">random</span>
- <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">8675309</span><span class="p">)</span>
- <span class="c1"># Load filenames in shuffled human dataset</span>
- <span class="n">human_files</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">glob</span><span class="p">(</span><span class="s2">"/data/lfw/*/*"</span><span class="p">))</span>
- <span class="n">random</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">human_files</span><span class="p">)</span>
- <span class="c1"># Print statistics about the dataset</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'There are </span><span class="si">%d</span><span class="s1"> total human images.'</span> <span class="o">%</span> <span class="nb">len</span><span class="p">(</span><span class="n">human_files</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>There are 13233 total human images.
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step1'></a></p>
- <h2 id="Step-1:-Detect-Humans">Step 1: Detect Humans<a class="anchor-link" href="#Step-1:-Detect-Humans">¶</a></h2><p>We use OpenCV's implementation of <a href="http://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html">Haar feature-based cascade classifiers</a> to detect human faces in images. OpenCV provides many pre-trained face detectors, stored as XML files on <a href="https://github.com/opencv/opencv/tree/master/data/haarcascades">GitHub</a>. We have downloaded one of these detectors and stored it in the <code>haarcascades</code> directory.</p>
- <p>In the next code cell, we demonstrate how to use this detector to find human faces in a sample image.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [60]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">cv2</span>
- <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
- <span class="o">%</span><span class="k">matplotlib</span> inline
- <span class="c1"># Extract pre-trained face detector</span>
- <span class="n">face_cascade</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">CascadeClassifier</span><span class="p">(</span><span class="s1">'haarcascades/haarcascade_frontalface_alt.xml'</span><span class="p">)</span>
- <span class="c1"># Load color (BGR) image</span>
- <span class="n">img</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">human_files</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span>
- <span class="c1"># Convert BGR image to grayscale</span>
- <span class="n">gray</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_BGR2GRAY</span><span class="p">)</span>
- <span class="c1"># Find faces in image</span>
- <span class="n">faces</span> <span class="o">=</span> <span class="n">face_cascade</span><span class="o">.</span><span class="n">detectMultiScale</span><span class="p">(</span><span class="n">gray</span><span class="p">)</span>
- <span class="c1"># Print number of faces detected in the image</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Number of faces detected:'</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">faces</span><span class="p">))</span>
- <span class="c1"># Get bounding box for each detected face</span>
- <span class="k">for</span> <span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">,</span><span class="n">w</span><span class="p">,</span><span class="n">h</span><span class="p">)</span> <span class="ow">in</span> <span class="n">faces</span><span class="p">:</span>
- <span class="c1"># add bounding box to color image</span>
- <span class="n">cv2</span><span class="o">.</span><span class="n">rectangle</span><span class="p">(</span><span class="n">img</span><span class="p">,(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">),(</span><span class="n">x</span><span class="o">+</span><span class="n">w</span><span class="p">,</span><span class="n">y</span><span class="o">+</span><span class="n">h</span><span class="p">),(</span><span class="mi">255</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">),</span><span class="mi">2</span><span class="p">)</span>
-
- <span class="c1"># Convert BGR image to RGB for plotting</span>
- <span class="n">cv_rgb</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_BGR2RGB</span><span class="p">)</span>
- <span class="c1"># Display the image, along with bounding box</span>
- <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">cv_rgb</span><span class="p">)</span>
- <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Number of faces detected: 1
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAQsAAAD8CAYAAABgtYFHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzsvdmTJFl23vc79153jz232qu7unu6ZzBLYzbMgmVAgYQwJGAghg8ktJkRNAM5euE750+ADHqhmcxknAeaSJNJBAEIIkwPEiFQEM20AEMsHBEDzNZ7dXWtucXmfpejh+sRGZmd1V3VtUz1dHxmaZkRGRHpGeH383PP+c53RFVZY4011ng3mB/0AayxxhrvD6zJYo011rgnrMlijTXWuCesyWKNNda4J6zJYo011rgnrMlijTXWuCc8MrIQkb8hIt8Wke+JyNce1d9ZY401Hg/kUegsRMQC3wF+DngD+Abwn6nqtx76H1tjjTUeCx5VZPEF4Huq+pKqNsC/AL7yiP7WGmus8RjgHtHrXgZeX7n9BvDFuz1YRNYy0jXWePS4papn3+uTHxVZyCn3HSMEEfkq8NVH9PfXWGONt+PVB3nyoyKLN4CnV24/Bby5+gBV/TrwdVhHFmus8X7Ao8pZfAP4sIg8JyIl8J8Cv/uI/tYaa6zxGPBIIgtVDSLyD4H/DbDAP1XVP38Uf2uNNdZ4PHgkpdP7Poj1NmSNNR4H/lhVP/den7xWcK6xxhr3hDVZ/JBCJBekjDn6iFd/XmON+8X67PkhxWJ7qZqW9y12eyL5a4017gePqnS6xhOC1ZRUSvq2+9ZY416xJosfUiwih6JwGGMIIaCqqCopHT1mNcJI6e2v8ziO8TSsCe3JwxNBFtZaRqPBD/owfmiQUsIYgzGGXq9HURTEGIkx0jQNTdOgqojI8guOti6PC/IObPEkVOl+2LC7u/9Az38iyAKU9Lgvaz/kCCHgXI4qqqoixkgIgRgjwPL9Xl2w77R4HwXWZPH+whNCFo//RP1hhjFmSQbW2iVpAFRVRQgBEVkuyB9UZPFOWJ8PTx6eGLJY4+3QE+vlpHTtbsuprmuKosAYg3MOjBCCRyyoJFQSGF0mBpKm5bbk7cgkIyJETicTs3L34hhXX0lEUDIZLf4nVV0+1hiDiJBSWpLcusz75GH9ibxPcK8aVyUvtEVEYa1FFDQlQgjLrUiMkZTSfUUT5i4PTe8SBCwSq6oKbUXGWrv83eI4RGSZa1njycM6sngf4G5E8U7LfBFVLK7amoTU5ivgKMw/9l31xGu+fdGeRhjvRBZLMlqJWowxFEVBE48iiZMJ13UO68nDmiyeYLzXjhlr7TKkn8/nFEWRr9ri0FQfy1GsRhZG5PjWpv2VqpI0rVROzPE8hySStDsbyce9eNW0IAFY5klE82OMMafmTVJK65zFE4g1WTzBWCyX++UMESHGSF3XxBiXIX9KCSW+bYEuF+bJLYkk9JSw4bSE6N22KIvHrlZfUkp470+tyMBxElnjycGaLN4HEN5OGItE4WnRx2oeoAl+GRGoRoqiuDtZcJwActSgoObYFmGZnGwfa1bW+snjcc6R2nzJIicBLEu4q39/TRBPNtZk8T7EapVkEfavIqGIbbcKIaEagbzIYwhHz1UFjvIUVsxKdCErDJUQsSukklCV5TbGmLtvGZxzS6IAjkU5J0lqcd96C/JkYk0W7zPcSznVOdNWO5R8ITd5S7PoRD3xjMWit06Iy8SitjmMlbJmzFGANYZk216TJJjTciDtoi/LEoCmaUgpEWNcvt5qRQSOyqXrCOPJxJos3gdYLJ2TRLGKk78y5ihKUE1obMukKeGK8tjV25qchAyNx61GCUnIUYWQVHHWgBpQsAoWAyaTRt6e5CNJwrFti4jkEu4Kqayjh/cf1mTxPsFJojhWamxvZ52V4psGKzkisCKAIMaiqhSFQ2NCUvsaqdVAAKUVCptPiaSyzHskBAMYsSiLfMhKviMpIkclVEObZxGIISx7VU4e+xrvL6zJ4gnGyYhitTAhxmBSW+5MirQ5BKtCryzzNiREiAkjgkWxxlDgGHYGVEWBc47COpxzOCv4+RxpcwwhRlKCqO3WwRaEqARNy7Ksb4VdwVqSKpGs0FQgkQOb8XicyWFFpQlrOff7EWuyeMJxGlHAYrHlqGDxK4ugKGE+wxlLZQy2JYTKFThj6VYV5zY3EYVQN4QQMElxxlLaEgUChigCFoImguSopEZxgBpHIuEQIpGaLAU3qiTJx7wgj7uRwjq6eP9hTRZPME4jCmVFf7FIKCrYBNpuSWyCfrdDp6zoFCVVUVIVltI6NEQKFUTBGUe0WbkpCVKKpNhWKlQRY3PEEgMhKg4hKUQiksAlMBj84uAkH1tc1V+024+0ksQ8KQZb4/2BNVm8j7C6vDJJtF8pf1tUPLa3thgNhnTLCmcFJ2b5ZSvD/GCMUSicpWgFXN57rICmCCEnNQ0JSQl8zIRkXa6oxoS2vWgGyQnUlICjyCKXZBUxR9WW1YTnqs5ijfcH1mTxGKDt2yy0fRDS7ulbmTTkhbeICqS9PW+Th8aCE4NITi6G6NGkDIsCEwKEQBdh1OnR63TZ2RhRVVVuVddASgEWCxtA4vIK36SIxggidJyh8WCc4GMgRiWmiE8x5y4kkTC5IGJAxOWF38yIkoiqpDZvkWShnWijoXbLEReeoEaOs99DwGrbPRyVYNfbnYeDNVk8Jhxr2da8VhKZFO7WiGWQLK7SmJvAJF/xS+OwVom+oWMKRht9NnsDhlWX0rpcClXQFEAVQy5dWjE0TUNhLAbBoAgCbVnTiGCMQnx7E9dSLKV5m5K3FRE1NkcSulB8sqyuwPGf4Tg/yNsKvg8fa6J4eFiTxWPAIqI4LqBKGFg2YJ1EEhCTk4a58SqhSbEmRxkpBAa2ZHM44Pxoi41eD6dCChGHokTiYnsigklgDRRiwIJoNsgxkhMNTgxGNLeIq8GoA1WsCK6VjUMbDaUc4SQBYsp/rfWqSByVYpMq+hgIYYF1HuTRYk0WjwUpby04IoxFeVHaTs3Yyq5VjsJziQFNSqUGq2ASFAqFUS5feIqd4YCOK7AxQhOQFDEK0QectRRklaQriqyWTEqtkRggpYDhSHqdomeu7WJHSPGoDKq5ZZSZb3JIZAziDCllX4xcPckkEclbkZzBUIyxd31XHvXiXkcVDxdrsngckITqCZG1ZvJQsdmBauFaZTSTiggExSJYVUwIFGIYFRUb/R7nRhv0CotTwVryNgBFVDFVh5QCKQkWoRCT8xUCDgEDFttuLSzERFAI2s4ZabUQcRElqOawJOZKh6C5NKqJqAk1hsQikgA1ucKCkUdCCO9Ujl39eU0WDxdrsngMyAm+lLOCx3DitiQWcmkLFNagMVFZS+W69IuC7cGAzcGQrhiKBE4UKyBGSMkQU6RXFcRoaBadnqrQGvaKQGEdaiQnVUWImp21TFJSq+iMmvMScRHoGItYg2oitAnP1DZ/RaNLoljmX0zOSCyyH+tptu9/rMniMWCRl0iSMCsEkWCZ+VRpl9XKFdEZIfpIUTi2+wM2ez02un36VYVGj41Au2hFQVAKZ0khIkYorM1OWTY3lunSxNdlaz0FiYmUFklLg4+KjwnvYyYKa9BW+k1rBBxiJLY5CzFyZHSzQhQ/yMEf69zFo8GaLB4LlCTHr7SoaXMB2ZZysc6klWaL5JxFZQ1bgxFnNzfZ7A2oxEDwaCuiMuTEp0gr/W49IxKavSRgqaMIrRHOvKnb7YWgMRHConfDEFKkCZ550yClw6gwa2rUGqJphxS1Sk3JfzTft2K6sVisuWLyaLYCq2XSVbOck0Sx9sp4eFiTxWPAqufE8pRtxUuaEixatlGczWVNTQmahtHGBme3NulYh8SItVDYgpBqED26gC9KlDGBywShLXHEmIgp5xdSVGLKDlgpxTaiaCMfc7Socjk0b0d0IeFevEZKSz2FaQuwJ907YbGgH+17u4pVY+B1vuLhY00WjwF2EZ8vcxZmKeUOKeGMoQRcVGyMlEYojOXKxUtsjzbYLLqkxmPnDR4IKdLrdknSKiol5qpKuzJDVJqQ6DjA5MJtFMEWJbVvqH048uQ0gmn9L6bNlFmoaYInEkkxi6py8jLhkxIV1NiletRHJUk6kqAbWSZTs/T74b+fdxNbvZvz1xoPhjVZPAas6ij0RFKzsBaNAZeUQoUSGJYVo16fi6NtyqLAtUYxpbNoSkR/fFFYKfLtdNRzURQFiZzzWE4ia70qmhiynqIN5Q1C3XiaFI+2GDYnS0PUvAWJaanENFmokXtI0DZFkbcnizzu0m/rnUw4HgJObkfgeISxxsPDmiweA8xKRJFl3lkUpZKwYoiApETHOjY7HXY2N9gajNioiqy+VMWJtElMk7UL2RFvWf40ConcAGacpSwt3nuaGBAsxmQJ98IeT5MQJOJ9xNrEvKmZp0Bcai3yVqYOEaOWgKA2q0Wy6EqXik2j5P+h/S8XzW0JRbi7zuK94l4ii0Ur/Lol/uFhTRaPAbbNaiZpZd5tclNabYQTQymWYbfHha1tzoxGVEVBmTwaI4VmMtDVYTwIUY4bytAqK0lCYSpCmJFSoixLLEqY5UQnmhOgvvHM5w1lWeK9Z+prjLMYY7OIK+YFZozBikGNyTmMNorIgu2ctpXUirjaSCUutJuPcI2+GwGsI4uHiwciCxF5BTgkX1iCqn5ORLaB3wCeBV4BfllVdx/sMN/fWCkUnECWbReFpRLDsNtha2PEoNsnNQ0SE7HxqEmIyVEGIuiiXNm+qFGWmgcNkZlvcM5R1x6M0nUOIyBzYT6fk8iLvq49s9ls2QUaQqB0FuMMtigoNBJVcFUJMVd0sg7jSPRkRfDp6L9breo8jsW6+ncWx7QmiUeDhxFZ/FVVvbVy+2vA76vqr4nI19rb/+gh/J0nBu/ohblyni4e1rgcFotVos/5ggIwSQlNTSeWPHv2AmdGm/S0QOYRFwRfR8Awi4GyslDkzlPn8hYDDEazQU3SSDKQnLRt5x7nHLN5w3TagDHEoJjCMZ4f0gSPFkLtmrzYLdRVQzmoqHWGtQ21zIg24GdKt9uja3vMg0ITScaSTNZgWDEkJCs5jaAYlNj2noRj74kuSpmYBxqipKrEGI/muXK05VjNV6y3Hw8Pj2Ib8hXgZ9qf/xnwB/yQkMW75epOnvxLsZK2fefatpubLMNO3lPa7GR17uxZhlUFtSeFSL/TxcdWD9EuAtc2gS1mmYpYNKzOLBWctVSFYzatsUWZxwQ2DWoUW1kmB2Oa6JnMZ4g1YISqKrBFRWm7bJ/ZQkTwKXJwcICf1zRNwBqDMVC5Au0aojhCTDQxt79Lm8Vd9LrAYqHePa56UJw0BV4liTVhPHw8KFko8K9FRIF/oqpfB86r6jUAVb0mIudOe6KIfBX4avvzAx7G48Vpk8IXWDReHWs7b/ULNiYKEcTnBda3hu3BiHObmwzKkjSbQSuQmk0jlbVL6/wY8oK11qAxZgPdNrGYW8sttp2cfufOjZyorGuSQOM9TWrwyeM10mjNaHvAxvYWm1s7bO2c5emnn0Yl8b1XX2a0uQEWdnd3OTw8JPlEM/fs3drPxBGUugl5JKFCCJGIQUhtL23MjXOynIO8eOfa9+jBBh+fJIXFWIG1hd+jxYOSxU+p6pstIfyeiPzlvT6xJZavAzhn3xebzNV28qWyWY//fpUoFr0SprXLt7lEQPINvaJiZzjkwuY2O4MRxntSzHJtUYi+gSrP3HDGHk0aV5ZJyxBSJq62ZOq9X84bDSHSNA1eIUo2t2miJ1nlzLmzPHXlac5duIBYR1l02Dq7xWg04pvf/hbd1GPQH1J2O8hsirMFVbeLswV17bl9a5fx+BBrHWXlmMQ5qCDELM9S0yo7pSXWlYWqpr1pWNGzvmcstiOrtxcq1nUJ9eHigSheVd9sv98Afgf4AnBdRC4CtN9vPOhBPklYjRiMshzyu7i9wIIoVLI7VDaOyfLsyho2ul0u7exwZjikBCox9MqS0tg8k0PM8sRf7MmlvV+UbG3XzgIxmjUWxKMhPmqEst/FlIa6aahTQ6MRHxs+9MJzfOgjz/PUs08xGPXxBA4mBySByWxGHTwUFikcyQimUyKFZbA14tyFs/T6HWL0LTksBGExd6wu/v/2in86HjyyOPl3YoxrYnjEeM+fmoj0RWS4+Bn4MvAfgN8FfqV92K8A/+pBD/L9gLeNEFzIuQVC8lgrEAMOGHU6bA8GnB1t0DUW4wMmZeWmaZ0ujGEpplJVdGHrD1gRQtNgNDt6w3Eh0iJn4KoSRKhTgyfShJqpn3HxymVsp2AWGuaxhkKIBm7t7eI6ZRZhWUFLC5WjM+zT3RxhCsfmzhZnz59hc2dIp1/gU0PehWZiMKLL/EVeuCvl3Qckibvh2P+uR3Ne18TxcPEg25DzwO+0e0EH/A+q+r+KyDeAfykivwq8BvydBz/MJw9G304QC5y8WzQrKoMqDqVfddjo9RiUHcJ4gmiCmDtPjeQkZUqJ+XwOgBPyFsMYNBZoTJAUW+ToI7akEltttVhLbDx+NuNwMqb2Df1+hUa4ePEpnn3hea7fvMHB5JCZbxgMN6h6FRjDuUsX6Y4GdAZD5inRrRs2trbpVR3emLzMYHPAuXSB8WzCZDJhMn8TMYDm9npan4ylzd4jEFqsmv+eTGie/FrnKh4e3jNZqOpLwKdOuf828LMPclBPMo5tNVYaxBadnqq5MUxElipH23aKmpgYDnvsDEd0jMFPJjjNqktLbiQzxhDkSAy1yEVsbm6SYmR/fx8nho2NDeraY8uizV+ErNYUQVzWRuzu7TFralxZ0nhPZ9Dn4598kfNPXaIa9rl5+xaHkykHB2MGYqjrmsvPXmEePMYWFFWXsxcvsTkakkJg+/xZxvMZIXk+8alPcOfWTfYP7zALc3COWZOb10SEEDxlWWYf0BYPqy5yspN0aQZ8wjF8TRQPF48mLvwhxclkJhyVCaOm5VCdxaDgbIormBRRHxh2u2wPhgy7HbquzNuOpIjGvOdPR9O+YowUZUlRlseukAvDmqZpckk0xOUs0UVFICEcHB4ynk4w1hI1MWnm9IcDnvnQc8x9w9a5Mzz7wgtcePppeqMNksB4OqMoO7iiQo3gyoJ+v4+KIUXo9nscTicko1y+cplnXniWnQtnSFl3jnFuORf1dHFUOvH94eJkKXX1a40Hx1rufR84Ji5iqYZeOloLcjT7s72GOhGGpsRPay6fu8DTZ84zcgVFSnSNRUpBEbz3pBSIrRRbBYqyQEQ4mE2OLbzCOurZnBiVWmrUC3XTEEJCjbC7u0eICYyj6JRMpp7zT1/iV//Lf8CLn/kEv/9//QGXnr5C1ekhtqIabhBCYjTcoq4DsVGSgY3+FmfPnuXWzet4lKo/onOlYjjsU3ZLDm9N6Gz0aFLEhwCuYuprEIt1xdL1+9hSbTtUH0U24Z1IYZ2/eHCsyeI+sGyUWnxfrQi2D8jaK2VRDBYBq3mSV7/sUJpcGpWkJBKlGNQZfMrlRmsstpVzL+z1clgfSDEb5DZNs4wmYozM5w2z+Rw1lqIoqMou0ddII4wnM5roOXv2HJ/89Kdoouf8pctcuHiZg8MJh9MZmqDq9uhXBddv36GwJUVVsjXaYnu0RZg2fP/N79CphHPnzqBG+f5LL/HGm69TdsqcxNWUm1oXcnTJ/4Nhdbt2lMPIjfMPN7BdE8KjxZos3iNOjhZMmhun8rbiyLVKREiTOZXNjWIOgyybviKp9a80rVRarEGMyaa3Kb+uaeXdqR1E7JOn0+kgkh22QwiEEMCCcy67YqWYzWmMobQlVadDrzvg2hsvM6/b3xuLGIsrqzy2MCQun7vI1s421lrG4zGvfPv7/Nmf/SmT8ZiP/MiziMLu7TtcvXqVxjeMNnKVhJAw1lIUhoTLepMQj9VCjn9f4/2GNVncB04OBEqy4ttgTHararcji8cbzT6X/W6fXqebr7QrQ3yitsM9zFHSLmpCUp5MnmLM9nhNThSWZbl8fgghL/qFjV1KuXt0OiVaS0rQ6/coTC4nzn2DMYa9vT1m3/ke1hY4V4IpuXHjFhvVJpfPX6DxkauvXuWtt95ib28PrQPbww32b92htJZoAleefpqiU1CHBlcUpFlzREBi8lAkWJrgPMlYb1/uDWuyuE8YXclVrN7fmtlqK8BajCNMmj0rep0OlSuIIWBiwhqDCPnxtCesZsu7pPl+hUwWJnteWGspbUEKOZqYzWriwm07RnwK1E2TtyfkcmvP9lELMWYiOxiPmU7nvPbmNcqqx7PPfojhcIubN+5wcHDAtatvcePWTd58802cc1y8cIFPfPRjHBzscXB4m8Ggj62Esl8hTnjt9VdxzqGqeXtkS4xtT6sfsHHvvWJNFveGNVncB+42ZjAJxPYKXxqwRjA+kHzAIkgJ/X4XGyLdZBkUFU6Fpq4pqoqgiXkKZGsbm4VWArNJjbWGsjCkTpGdtVNCnCMlwavPIz5CxCSlSLmjNRYd5ge7nBl2Kaxy2EzpuQT1DPUNYgz9wYii08HHmBvJHLx1401efuv79EcbXHjuIs8+82F2zlwmNJa3rt1Bb98m6Zzaj9m/cYeQDjncP2C40+VgPmU612z+GyOlzWVTwecRBwKKBSmIalEsyWZ5OppLxEYEoymLutQDuiIXN0tbwqUT+kPAaU1oa5yONVk8RGibe4i+QVQoigJtAjubW/S7PZxzuLSY0QG2MG2p1eBM+1Fovk+AwlhE2tbrlRJtCglrXH4dk6eBGYmQcmdoxFCWZe5STdlcJ/jEZDLh7NmzvL57m56xDDY2MOKYTqdMJhNijHQ6Hc6fP8/HPvoJzp65RFLHndtTqo5l7g8ZT3ap612m89tgZhyO7wAGYwyVMzQIJpmlkrIwZIFWzn7m+SKaxysaTblzts3x/KCwJol7w5os7gMnT6lFDiN7SmgeSqyaOy1jotMp2Bht8JGnLvM//uEf/SAO+Qivwz/5vR/sIbwfsLW1+YM+hCcWa1HWQ4JRKJxDY6BjCwqBUiw729t0bfGDPrw11nhgrCOLB0JrY932dECudBjnKIuSYbfH1mBAudJ9+bWf/hmIoW0313boT4MTlxOFKZF8IEWIyaOqzGNNEgUxhKjUITKb1tRNXFYdrBWqIr8GxtI0DYU1uMrR6VXUqWH70gX+9n/xn/Ctay/z+vVruG7FaHsL4yy3b99GJweI7dKp+nR6fTa3dojRU/Ud129cZTy9QUoN/W511Kuiwm/89/+Wq9duYE2FdRWqrZFFCljjs4s4bfs++fhUDLVv0CStifCRH4VqBFmRievivX73nMVpycqTPSQnH7e7u3e/H/wHEmuyuB+szCs95gil2UYuNp6y7QPpdvvsbIyorKPwfvkSmgLGGohpqc1YnMwx5sWvMWZT3ZQQJwSfaEKDVyUhNCExaxpizJ6YRtNSQB1Soup2iL6hdBWldThjUVMwOxzzW7/xLxldOcfgzAbb584y2h5xMBlzdXYIzZRbt2+ytXWWs65gMjkkmcjeZIzSgDTsH9wmNF2sLZhOGm7duM10PMNExVohzOd4H3DOUpWO0uR8RpI87yQGT/CehGJdmUmQlEcGiOU0KfhqD859f2R3cQC/G9bNZ3fHmizuFycGHC8sXIxCDIHCWtJ0Rnfo2ByMsJqozNHbvPCnUJsbxDCteAtZ9oQYbRdYAiuWZKBJiUYjSYWEpSZixIGRdpBP67ydlLLtNXHOYQ0QEyLKbDJmd3rA5pWzjPo99ndv8ub11zHO4JxQdCt6fc9oc8iZczsAVL2S2VyomwOq7iYiSrfsEmrhcO82hwdzmsksWwaiCAlnYWs0ZGdrgzM7I1SVEALT+YzxdM68bvAxMZnVBGldy40sZ4y8jRfUrGg/H45pzhr3jzVZPAQYwFlH7UO29e/1GPX6VNbgEkjwxx7vnMsLu2myq3aKmFZolbvPE04MTYoUYmlSZBYampha+/9EMhYfAhoTzmRfT+dc3hrg2dwa4FyujoTYEFBMadAQslXem28y8TNcVTDcGKDRowQuX77E01ee4+y5S2ANBwd3ODj07O8fcubskE5Rc+v6Hp1qSKcYYbRH9JFUQ9VzXDhzlu3tbS5cOMeZnW2sBubzOfOmZjKbcTCecHt3l8PJFO8N4iOe1syHI0Pf08aNvFOEcdLZ+6Q35/1idfbIGhlrsnhI0LYa4lB6RcGgU1FZCyHizPEzP7QzRqMmDLnvIzTZyTsP6DFIiExjwKoynteMm4YmKYvrt/cR9dlOxiCtTX8CEiEmyn4/y74bjwo0KVLPIvv1hI39fc5cPsdgc8jET9pZIpHB5gjnOjTNnPH4AKzhzp07uS8lwSvffx1fB5pZIswbDnen3HprF6tw8fw2zzz3HM88e4WdnR0qZ0nRMxkfYCRbCpZGqCx0nCUUhlAWWfYeszt5Dh3aIUhqchS3xCJfcfr7/05bh9NyFov738m3c43jWJPFe8YJK/uoOBUGZYdnL1zk4sYGHbFghTidLR+WUOZNs2xF9z7P76jnHuOKbNhplISyW9cosDebMQ8B37pgpQT13NOzBV1rcdZgLRiJFEYIoebgYI+iqIgKk9mcaeNJzhCM5d9/8y/48+9+l4uXL/ChD3+IS09dBBkxrac899zTHI4n+DDDmQ57e3tcv36Tb37zm7z8nZcoxRE9SJKlNuRXf+VXeOaZpym7JbP5hKapmU/H7O9PscFjg6dIEaxAr4M1yqhfcntvxqGdccgM0wheBSUdRRf64MW6k4v+XiKNNVGcjjVZ3Bfu7vyUW9MT/W6PYb+LM4bUNFSuwJZHpdPY9nt474ne40yxrCrU3uPb3pCEMA2JRGSWIo0mAtpOP4fYjhg0TrLrtySsKAZLWTmcOA6nE4xkm398Yu9gDJ2C8WyOTgCxlJ0eIhbnDFoKL730MnXTMNzcwhjD1avX+Pa3v8uffuNbDLt95iExm0wZDQZ84hMf58WPf4znnrlCt1fRhBqSR9RjJFKatpITPSl6SPkYC2dAHVVhqQtHpyyJKUBKhGwa9p5wMko46dW5eMzJmahv+5RlURwsAAAgAElEQVTXIwROxZosHgJEj0LafqdL6XL/hoSItXZpuLvAsmM1go8ejTniaEJgHiJ1DHgSswRBA9Pg8eRti0KrBMuzOowxGJuD9Gx7I4gaprM583mNsZC8MvMRnwSLY7S5QzLK7d199r/550wPp1y8dJ7O1ogQ7zAaDYDE9es3+c53vsOf/ek3GQ6H7L11yPbWBp988ZN87IUX+NBzV9ja2qLf7eKbGT7MSMGDepxAWeZKjEERzeVlK1Bag1HbDgjKX2Vh0SBtE11qFZ/3Vwk56aC1fL/vYrH3blHGujJyHGuyeEjQmBvIiqLIcz9DamdnSC6VtkgpIWahLQjMpzWoEnykiQEfI/PoCVGZA1Ej8xiJKRFNS0oGCizGZV1F4QSXsnlvYYQmJWazGa7ooK19f8KwuX0GqUpuz/ep/Ry1hlFvk8lkzh/94R+zdek8SRr6/S5Vr2I6nfPKK29Q1xDmY55++gof/8hH+NSLn+DDz19he9THGDjcHxOtII3mZGpooPW3MO0kkfa/z8OVjCFZEM23rRiMUYwBkaOu3eV7uySMd9+W3G3x38+iX0cWp2NNFg8JeU5o7tdYZNEXNnerkYWPAYtdlklzcjELrUJM1MFTh4CPAa0qYsqu2Gkxp7w1vXGSI5aicBTOUCRDoZHCCo1P9Ho9VBzJFHSNo3IVxbDP1AdG5Sb9YY+bd27y5ptvURQWIfHm7i6dnqXxkQh0OjCdgHMw7G7yN3/xK3zswy+wtTHAEQihxkge8GOCAAknYJzD+5qUQuu10eQkKbkVP2k4tWqxiNDezfLiblf8d4oSVh+/zkm8N3wgycIllsOATnaSyooN3EJ1CPlxZVDECrXmJFxhLaSIRE+HwE6/ZKcLwyJQGEtlhMIp89395eublPAh4n3Ep0idAjHBQQrMRJlZZSZCY4W5TSARaQIOpVClTEKhiW5VMnCO0uRFajsOI44mNBRhg2JQcDhrsJ0uojDzniYI0hmwtdHj5Zdf5s7+mF5vBx8axuMxVW+TWFsqm23+6t2GrX6P7a0NPvfZT/Plv/JjBF8jqaZwlvk0cTgeU1hBYoNLUGpJDAFCbn6z1mLLgo7NW4wmeExUSmOoTIIKGh8wvkFsFm0lcajY/Nmoad22UnZB5+5X/LuRyML4ePGYd3qNd/vdBxkfSLJ4zzDSdpZaaEVUlnZBqFKYXJkQkbwV0UhIxydmzX1D4wMhpKzM9PkxXiNBlQDtFdhkgRZKIYbCyLLfxIphczDEAVsbIyQ1zA738SnS71YUmyNu7e1x5tJFRts77E/nNNev0wgMel3EWgajEZN6yqyeoxoZboxIKkwnEyDRrTo8+/QVfvTFj/MjLzzPC88/R6/XYz5T5pMxk/GY6D1FUUAKLEubK/kBay1lWS5dxzV6DJJjJBHKsoOJysx5jAmIpKVADRYGydl+717yFqdFD4v7TuYnTuoyTr7OOvp4Oz6QZHHXWv1dzo+ldR6LkDlP8TYJJCWMRoadiq3+kH7ZwaaI+qyLICnij164qT1Tn3MSSYVQWLzCbBaZpMA8RWqNhJTAOhClYwwdga4xlEAhhsrn6MXUgW6nQ2fkiN4jAjdpOPPR53nq2eexVcVbf/lt2Bhw8fw5Ot0+k2bO5Nob7E4PsVbolBVSOur9CR/7kY/ymU/9KD/xxS/y0Rc+TOEM08MDNAXqyRQ0j040IjRNO7jZx3ZRZtVHiguzHcG5km6pzGlIETQ1aFBiigwGA0JUJrXHzRqsKJaAplwiPnrX0rEsxr0s45ML/p20Fnd7/hrH8YEki/cKFRCxtFZWR6MEm0DV69AtHCZFUl2jPrTjBrOPwwLzxlP7XPUIgA+JOiUmvqERiGKy54Pk55qUcEYZFCWDoqBjDE4FJ8K5s+fyNHSxjEYjmmbOwcEBg4vn2X76Kf7vP/tjXKfHX/8bv8DHP/Up/uzf/3/8xm/9JteuXWMyOcQWBaVz1L5m3tR89hM/yld/9e/zoStP0+1U2AQxNHSLEl8n5j6gmonBFQViTHbH0qz9qKo81NkYgzQm53GKDoIF45YkC/NsPNz6b3Q6HUb9iHUeHxK+Dq0L+P3pLFaHD8HpkcZpuZI17g0fWLK4m+vV3U6dbE5tljohUTJhoBTWsNkbMKi6mJSt8RZEIauJD2DeBKbeM/Men5QohnnIWoocSeSGKlUwUTFJsZqQFLFqcRgKEbY2cs/FcDikKDs0MWA6PZ67eJk3+o4/+da3cL0O//nf/bs889yH+H/+8Bv83r/5N1y/cYPdvT1Gw34ejZgCH/3ox/mpn/hxPv/ip/j0iz9KVTrwgRiyr2Yd81YohYgrsqFw1JD7OZwlhdAmcktMSwoiFmtzYtPaAuwRWaR29MF0WiPO0e12UVui0ymHsznS+FM+gXvHadPKVn+3+pi7NZqttyFvxweWLOA9+EwbIYRE6QrQCN7jTCaKnY0NRp0O+Agh5agAIWlOaC7gk1LHyDwlGrKFfiOKF0FQokobwQg2KVaEyjpKFRxQmpxY9aGhHIyY+UCwAdepiAJ35lO++fobvPjJT/F3/vYvs3P2Ir/5m7/Nb/327zCdTvE+b1v83HNmZ4vPfvazfOknfpwXX3yRc6MtSJHD/QMkRgoMJikOwRQlw34fV5ZEDTTBo8HjY0LEINZhTA4xTErYlBBrKaNC01Bi0CSEqBQBUjT4lLtV85yRVixlji/g+/mM7hYpnOwZWf3+Tq8Fa9JYxQeSLE6LKlbzFSddvJfPwxBjgy0qlERqAkVVMux2GJQdKmsIsxnEiNrszu29Zzw/8mZoUiIoeBECwqSpCSiBXJqRth/CkKselXX0q5J+KfTLgmG3R6esmM0bpCpQA7FyTKPnrRu32D884HaR+Ju/+EuIK/j1X/91/t2/+xP29g6IjacoSna2tnnuyjN88Quf5yd//Ce4dOlCvrr7Bj+pkSRUrqRyjljPCUmp53NEDaSEInS7fUpVmIwJIS4rDiEEjLE4V6CqFFUkkZWrNiWKGHHOE2MiIjTBkxDqEGm8z9GOkK342g7fkzmmu+WWVsniXvMSazK4d3wgyeJueMctSAtrLaSEhERpLP2qw7DqUlmTRwkqmFZfEULCh5QTnS0mdcNcYB4TsxhIVohkuffiGBbHUYmlX1R0nKF0ll6vR7fbwxQOVzhujPcp+gMOxge89NrrTJua8xcv8bM/+XlCCPzPv/0/8X/83v9Op9Njsz9kv95jVPX4Wz//S/z1n/tZXvjQ83mgsm8okmHWRJwrc6QQA9qSQFEUxNAQfcQVBWXpMNaiKT8eV5Jaosi1Z4uSiCSMLTA2ISYb2tQxvx/J5G5a7yOz2mOso+xUuKpE6iZv5cRgncW3jXfGtJWmeHoFI6W01LacViJdJZL7Mehdi7QyPrBksXqanIwqVrGshAiQAkYMEgJWE8NOxfmNIRc2N3AxUqiiKRFi3l7UTaD2DRNXLl9vLwRqo8xFaZyhTiEPIZas/ygUKuOorGGUDEZgONyg1y+RwjIxEEm8cecmY2O59car1KqMNrb42Ic/yQsf+TA/cuV5/vF/9V9z9bWrnBtuMugN+fxnP8+nP/0ZvvBjX+TZK89R1zW+rqlsQTkYZfWpWJr5lKb21HVDMELHOWxZgW+YHwSkiGx1N7BFyXg6pVNA6mexmYsRrWuadrvhU+RgPmE2r5lMZty8eZNbt26xt7fH/v4+bx3eydsOTBauWcd0VmeVa7swffKoygoBB8q7JD4X4xhOiuJOyr0XvSF5dMPbpeEno5OTW5cPajTygSWL9wpnJEcQKVLZDr2iomMLTGjy1TTkReJDykKoxjNeef40eiKGZG07jSzPNi2QVlMhdIyhMpZu1aF0lmQEtQ7b7VDHwN50zEGIvLF3m42dHS6eu0C332O0ucFgMODqq69y89pbjHp9nr3yHJ/73Bf4+S//AtvbOzhxTA4m9Pt9Rv0RKSXquib4QFGUhKZBxWbXKiMEQKMiJs8G0ZT1EUVR4ZsIEYIk8J4mzPAx4UnZGSsmbty+ze3dXfb3D7l+/ToHBwfM53MODw+ZpfnSpTzGSKQh+LZ13+Zqi7Tak6VQTvVtIeBiES8W/2LBL0hjoflYXfx3E3CdjETWUcURPpBkcdp1YfVUkLs1l8aEWkMKHmsc3U5Jt1NSOIP6mEuqtOVVAxhLspbJ/Ci7n0QIxhBEUWPbTyDlxCCGAqEAKlU6ZYErC8pOAaVjEiOHsyk3D8fcPDzg7OXL9AZDBqMh/X6fwhoO9nb5P/+Xf832aIOf/tJ/xF/7mZ/lhRc+wuZwE02t+5Yp8D6gCraosEWHqA0pNMxnNd7nhKwYAyaXd8VZTFvtAIM1Bc4UBMn5mblvqH1DHTw+RA4m2eTmj/7kT7lz5w6Hkwnj8RRoRywmpVN0WgLKjuhKwhmLVcGnhBibx0DGBJqby06ODFhdxIuI5GTuQkSyZWH7+0VkARz7efU1F2RzklQ+qFEFfEDJ4m44uQU5CRHFGhBVnDF0qw4dmw1crBhE8skVYqJuy6NNiO0AoYxkLAElSv6urtVqxJCrCCKUmqXdVbdDSgFTlsx84Ob+LnfGh0xDoNrYZPPMWbwPzGYzUlNz560GX8+xYvhbv/QVPvuZz/HCcy/Q7w+YTCYUrgMYOlWfJiTqmLIICogKhSuPrsY2t9ZbFIlZodnp9hFj8E2kcBGDQaPSaB6jmGL+3w8nY1557TVefvU1XnntjVYlmlWqqMmiK2PpdPKUeINdzhlJSI50ag/krt2oCVWTiYO7RwXLz7HNbZxsSz8ZUdxNvfluFZMPajfqmizuA7YVHCFC5YosrS5dzmUgoHms4Nx7prVn0jTU3lPL0dscJBvb+NazIiXNJIQstRmVy4lNYwwhKQezCXvTMTf27lCrUg4GXLryDP/hL/+Sc2fOsj0acfPWLcJ8xs7WNl/43Of58pe/zJmdcySfCCHQ6XQwUhBCYn98iBiHdSWBgIjNIwdTg7W5imGsYp1DUyCqoiTKTkUKkbpuKF25vPrO5nMOx2Pu7O9x8/YtXr/6Bt956WVev3qVw9kkLy5bYFyZqx1GKMuKK089RVmW2be0ndNazz139ve4cfN2jgSszUOSlKyGXfk8Ti5Ya+3y/tV+kEU3cAhhOQhqYZD8TjmLk7dPJkY/aISxJov7wCJ55oCizDmFTlnhfENK2dwlxsXc0fw9KtTxaBuSW83bBBuKDwFn21ohijNQWkenLAjJIyLs7u9z+3CfJnkGW9tsnjvHWzduIORJ5zqvqZzlxY9/gp/8whf5zCc/x2AwoJ7NcDYnVxf79hASrihQMWANhSsJKTJvaur5eLmgRPLCi5rwsVWjWovGvKhzdSILrebzOXfu3OG1q2/w8quv8NJrr3Przm1mdd1GBrpcsEVVsrm5yZmdszx/6fyScLz31HXNfNYAsL9/SN00R/mGcORgfrcAcLXjF443kC22IfezrVglhw8aMZyGdyULEfmnwC8CN1T1xfa+beA3gGeBV4BfVtVdye/oPwZ+AZgCf09V/+TRHHrGg7C8ALY9t5LkgceLblQ9+TgFZyzSBDaN44wrGCpUscE5YWw9M/XckAZvlLm11KZkHgONHImyapdIkjAKlYduUpxXSgy2LKl7PQ6HfZpuBxOUg4MDbtzZo6hKts+do9PpMN7bZ7q/z1anw3Q64cLzL/ClL/0VPvPJT3Hp0iW6ZkDdwHA4oKyqfBUVxRSRbrdkXk+JMWKNxRoHGknSsK8NUx1jJbYNbYJxUHYSvm6IIeFD9t/YO5i1g55r9m5e49VXXuG7r77Ka29d59qdmxxMJzQxQPI45+hUjn6/w/nzFzh//jyDwYhhTMS6wdcNLihdsYwFZlWJKRxN9K2hj835ipRzD9KOfTz2Wdqsx5CFd4jkdv7FtiWkSNK2+qFZMHfXBGd7ThnJ9gKnNaN9EHMX9xJZ/HfAfwP885X7vgb8vqr+moh8rb39j4CfBz7cfn0R+G/b748M74UkFmYq99SQxFEuwwqQEjtbO5zbOUO3KvF1nYVVGpj5hsl0Rh2hDkrdJJqYaGQ1oeayq5UkbAJr8tZj0B9QVSXGWSbNnP3pGE2G2WxC0e1y7vxZrM3DgA4ODuj1OvyDv/f3efHjn+Dy5csUxpFSoqoqRAr6/SznnswmzOsp8/mcpmmYTCbs7+8TY6RXdRgM8gzWGCOzxuNM7pYtHIxGQ7qdDgBFUbB/uMd8OqPxNb6e40PNZDLhj77xDb7z0stcvXmTw9mMOiZUoBCh3+vTKR2dsqIqOrg6Mrlxh8mNPa77SfbZsC5XVVq1a4iRJAkRlibEIrKyJTndV/Nureim7eA9lgxFT81hL15D2zK4cvpWZPHaHyS8K1mo6r8VkWdP3P0V4Gfan/8Z8AdksvgK8M81v5v/r4hsishFVb32sA54FasnwEnN/7uassq727WtEsWiFwSNdLtdulWJUZYO2kHytqMJiTpBHZWa7CcZTvtDbZNJjB5hcaXMPROzpmZe54ljxsLOcJvJdMatmzewCM898ww/+eM/wc//3JepipIQYuu25ZmNJwRNvPTSIddv3eT27dvs7e1x685tdnd3c2XAe6y1DIdDdra26Ha7bQJQOXd2J9vclTlqqHsDkg8YDOPxmKap8c2cyeSQ6WzMwd4es3oOJm8XDOSJ7kVBp1MiIULyaACSRc2cJuQ8yu2DG5Akb+eKEld1EGMJmiiKAhfymIQQW7ctyUIvcKiuLtYjgribcvPU5jLh7a5cq+fNSpRx2uuffN4PO3m815zF+QUBqOo1ETnX3n8ZeH3lcW+09z1UsjitGei9hoXv1FC2ShQCiEaMtXSrAmeEFAOp7fsIIeFjrjDUSalVsoxblHjsJMpXLtFESooThzWSNQ0p4lPAh1xdqCWwM9pi3tRE7+l0Onz0+Q/z0z/1U/zHf+1n6VddZrMZ2i6+69evc/XqVb7/xiuMZ2N2d3eZTCbUdc14MmE8HuO9p1NVOGfo9XrcGI3oVR2stXQqx/7+BoNen62trWysG6Gua5xxS7Jo/JzZ9JDDwwN29+9wMBkzredYaxkMBvRiXjzWQMeVbAz7jEYj+r0hnU6HGBMHkzF79QHz6Yw4mzKZzjFugi1Kks0y8KiBkBJJ03KgEshyxtDRAs0OpAvfkOPnRGqJxR6LDpafszl+AqwKwhYir+Vj36E68kHAw05wnvZunvpOishXga+2P9/bi59oFCqKYnl7kZi7lw9uMfn8nqILPSIOg1AVhk5V4oxBm5qU8gnaLOzwklKr0iSyUzdkPUUL1exxoSoYVZzLprY+RkiBEGMuFRph1B8y2Bjyyre/y5mdLb742R/jr/70X+HHPvNZzuzs4OsZ88mUa9eu8fLLr3D16lX29/e5Pb5FCIHxeMx4Nm0t7vJ+3VmhKARjshlNPZuQQo2I4GtLv1cSC0cznzI9HEOE6CPWFEync2azCT7MaZo5TfB475nHerlQC+sImhO9EhKbO1s8dfki25t5pmrTBG7f2WW8f5At/12BbzxNPUNroSw9UpTt6+VoB5XlSXTy810SA8cvIotIafWUPLmVuJfS6N2SoavK0LedMz+kPSfvlSyuL7YXInIRuNHe/wbw9MrjngLePO0FVPXrwNcBnLPv+s6eFNvAUals8fv7+YAWhLE8nhO/N3qcKBY/V8ZR2nwixkX1QxPBR0LKsy+8Kl7AIyRR4qruR7MeI3tt5atd1KyiVMk+FkjK5rUmMjncZTjo8OJHf4Qvfu7TfOTDz7E96pPqmreuXeOtt27wvZe+z6uvvM6t3Tt5+pc/oGlye/mCRItORdVGFFXb5GWMoSotzuX3sSoMw36XbrcCoJ7NKV0HZ0usLXC2RHWKJsG0ysvsqZnLwVETIURSyCTYrSqef/55Lpw/S1EU7B3sszc+5Pb+HncO9rntJ3nIUErEEBDjcnk0RHKLe44k1ASMcXk4ombx2iKPcfz8WH2jE6wkMXOJ+t7yDifPs7vhh5EQ3gnvlSx+F/gV4Nfa7/9q5f5/KCL/gpzY3H+Y+YrTNPoPuk+8m1hzgQVRAEjS1s7eIKQs746RJgQCeeZoEkNUIZpWR6Esbe1XXpXsYg2qko1tNWKtwRT5pBcRUjPncD7nS5//cX7mSz/Nh557BkdifHhAM5vz3e99m2/9xV9w7cbNvI3oFzSpYVj1uHlzghXBVUVrMFPR6/XY2NgAcr7HGZsJpMiLrFtYBM1jDBw4V1KVXaqqS+E6SMqGNnMDPkDTzAHDbFYzmU5pmgDGUhYl/V6PQa/7/7P3JjGWZel93+9M9943RERGZEZWZmXW1F3d7Ca7WwJlWga8EG3BOwMCF4atjQFbsLyQ4Y1X9kYGBO08bAwYkGHD8MIytDQMAQYMCSJIiBApkqJIkeyhuqYcKjPmN9zpDF585973IjIyu7obqq7MrAMkMoYXL268d893vuE/MLuxSzKa48U5Hz98yJOnT7lYLlmtV6z7buu9leZlHyJd24DSUiIkjc5BdfyHGlsJ25nF5ZM+Xtn0l5ufw71zXaYy3huvWTD4SevzjE7/PtLMvKWU+hT420iQ+AdKqb8BfAz8B/nh/xAZm/4QGZ3+Jz/vBV7X3d4OEgP2YZsH8HmyjOuyimeo0Fceb3Lg0AbatiFkY2NPou09bUziR4oIvEg4kQxk++/RWkOUIBEzNiARCKHHaYdzBlKk1ImydPzqX/g2d27fYFZanIXV4piHDx/zu7/7O6zqNbMdgXyjDQfeU58dMSkdk8mE3Rs3KCt3qWQbsCClla8boyXYWEPfBybVhPl8j/lkxqSYMKlm7O0esDvbxRjNk6ceSBRFRYqwWEkvJCrRtjKFo5rP2Nndow2epw8e8PT4CZ8dHbNsGnwQsZ+dPTEyWq8b1us1ne8oy5KUIAzerykKTyUq+jgonMdnDokhs9jcB5ZtA2XtrJSeVw6Yq89ztQR50aj0amB5XgB6VdbnmYb89ed8669e89gE/K2f96K213Vv5vb/w8c/TYZxtXEJLx6jDo8vjGVWVPiuxXcdMXb0MbDqW5Y+sEqKOih6BV7kKEnPSWmjkoyjCS3KJEpjJIOJPakVENedW1N+9Vd/lb/8F79L8oF6ccqP/uyP+Zd//MesVjXvfP19vvWdv8KdN+8SEZxBWZZ0T0/4wQc/Yr1e8/TpU06OT2hb6SsUhePOnTtMnLikaQXzasJkMsFay5t372GMo6qmzGd7WFPhfeL27dukpDBW0XUdxyefEbzCe7g4W1A3HbaqSFqjq4rpjRvs3b7FP/vjP+Lk9JjJbMpbX3uXH/z4A85Ozwgx8a17b/P222/z4PFjfvTBByyXS5qmFYPnIK+Z05oQA73vQBm0NWxnDUoltBiUoLUZuR7PZJ/KklM5ORVSGj+99F7nEi3FlAP79Zv/6jj1VZ+EwEuG4HxRxL6uHn3uY1/w7edNRwB0UJTOjZlAJOGJMiJVokuBivnGlaaIUfKYrT9Crk+J/WCM0rHvfKQ04Kyhso7KWb777W/y3lv3MSnS9C2ffvop3//hDzg5PeJr73+Tf+ff/Svs7O3jQ6TpWjofWS9XXJyfsVgs+OSTT/j04QOUUsxmM6y17OzsMp1OKYoCcpajrIwri+xFYq3DWktROMqyJHg5zZ0tKMtyzFJkUylSiBnLkHDWUFQlIUVOLha0fYd1BXv7BxwcHLD75Ijj43NiDITeU5Ylk0nFdFKRYuDC92I8ZGXTW2vpiaguEXQi4UnpckDYvLTb7/3Qv5CSJeUpx6VehVKo52A2InKSXD2Uth939Wee9/mrsr70weK6cdewfp6I/rP8lIoJqx0RuSkDiS4GPELL7pOgHsXeQuDbSYmU/eUl47zBdMcYS+zWJG0ojOXm3i6HNw/4xte/xv037wKRvm/57Olj6rrmna+9x/e+9z12d3epmwbvg+hith1HR0d8+sGH/OBHP+T0VPgVh3feYGdnh5QS8/mcmCHUg1R/kQPgALs2xmAUKCJGJ8pJgSKgiFitMRqIieA9MQTJOJSh7T2uBGdLVnXL2cWSe/feoq5r1uslH/7oQ9YXK0wEa0oqa2jXK55+9oizsxOqqqKwmnq15PDGASkpXFVKM9pqQkq0fZcnJYpEQmHzuHOwIhhKCPLnY3Pjc8G3r47jn1d+XL0vX9UAsb2+9MECnp9R/KzNqKu9iOdlE2OrLE9OrLYUNhsZa40nGxQrhU9SIUvWkANZCjnd3T6FpKWalFgTphSwtkQFsEYzqQreOLzFN7/2Hjs7O+zt7ZEULNcr+j5w8/Yh3/3ud7n/9lvU65a2lSZhCInjJ094+OkjfvzRhzRdx8Gt2+zu7rK3f4Ou62jbmtOzM0IIzGczyrJkPp8zm81QMaEMdF1HWRUCgIotfS+3SIyi9dn7lhB66bfESIxeUJUKkhdOSYwxi9gE/r2/+huslyt+7/d+j0cPHlBiOJjs0vc9i4sT0qc956dHhL6lV4IeNQpmU6GvlxPRFlVOAnO3qCFs9RIQJuuQJQ3v7nhvDFmI3vRrtu+X+IJgoJRkTc9bz8s6XtWg8aUPFv86X/ifREm/upxz2YpQExCRmy54AV6llCX8jYxGlRpHLYrLwB7p3udfrqURaq1ld3eXN2/f4p237vH+e19jPpff1XWei9Waajbl9htvcOfuPSaTGcuLFaH31Muap0+PefDJpxwdHXG+WPDOe++SUqKuaz59+IDT01NAAFZaw3w6lCU73LhxA2sMN6oZ850ZRemYVhMgkejxXrxSus7TdWJKhBK2rFIKnU2ADJKdXJxd0HQtBwf73Lt7n7Ze8dnHn0IbODs5pcCy8AsW52fUbY01mtm0ZN3UKCLznQm3DvZQSmOLgp6IXRua0LNuVvj+ss96IlxCwSqlBMQFxEHT9ArAangvrq7hfhuh41f6EtdlG69qcLi6vvTB4kXrair405QlP018zdAAACAASURBVG2gGFZKKvt3imRe27Z4JSmyT/L9RBrTYGLakJvYOrXkM6wVBSprLTdv7nPv3j3u3X2TN27fZr7jhNPhe7z3zHd2eOONu5RlKdTwdcN6seT4+JQHnzzk8cNHnJ8v2LmzT9N0PDn6jLquAXjw6BHrtYjP7MxmLKYLvPdMqwkHBwc457i9cwNtZEojkG8xXo6pYzKZ0XcbnobWEiCG/s/A6uy6jrpp6YPnzp07/JN/9I/xfc+Djz7EKEtsA4Uy7FQzqDqi0iglvQmjNLYqKLXl8PBw7KfUfQdWYfuOxXpJU68/94Z93ga/DrczPM+2II66hm8yfPy85vvw/K/aeqmDxYtm5C9aUelcelw5afJ4VD4Rr86w9ZS99dShpugr2qWmax0pQBd7ApGIJ5g+n7YGokZFg7WXf08KkYT4feqQIAb292e8eesWb9+7y+03blJOHCYFysISk6JwU5HCm+8R+shydU7frnly8pQPPvyQTx58RtP22GlBi+XTTx7y5MkRF8sFMUZWyxqlZdOcLY/Z391lWjja+pSLiwus0Zwe3MXu7JJcyWynY3c3YnuPJhA7i0FDaNC6w9lAoCWqhnI+oV0swUf6eok2jmnluDj7jB//ODIpHUo39G3HfAoajbUz2jRl3a7pQ0dRaqamwDnHjd0dbt0sIWmKomC5VqR2SaUMYTKhDee0Ao0lYLGlYEFi9BgDKQW8bzcbXwHI9GdAsg5NWu/9pfcGLYF//FScVoFESnEL33EZs/EikNersl7qYPGzrs/jm3ndajo5MaMTtGIg0SNmv56sRTngP6TZPnqADGs2mdJ1XXZPzwEp9NzcP+Ab3/gG3/rWN9mbTTEKiqLEaYUykfv37+NcCWiapmN1cc4HH3zAJw8f8eTpEat1Q9MGmtMTLn78IUU15ezsjLfuv8N7773Hw4cP+YM/+ANijPzyr/wSd24f0rcNT5885vT4iK5vWCx69uYTLIF5VeKM5mD3BrPZPF+zIEILY6mqiklZURYFk8mEEBPGtfjIqFlx9+4bHN7aQ6VA8p5CG1SApq7pmjajPicoq7CFTGKm00pKo709+qYlJIXVEP0uddsQu44nZYlvOwJJAmDOaCCSrIgIjSe/VmhlMNaOzvXbWp3PW0PDV8fLuItNNhte+Uzi6notg8VPWs/zQu36ni7IIDRZDUGTggJt8b4lakEdJvRmjq+4VCvv7++zWq1YrRcZHCWYitlsQlUU441cVhXOynO3fct0Os/9Enm+i4sLVqsVdV2zWq04O1+wqhv6LvDO+9/i137t1/j9f/FHtG3L7u4up6enUu4Yw+HhIffv3ycFz3w24dbBTbzviFFzcnREZQ37Ozvs7+zQT2YkH0haOC0qT1IKaynLchzJKpXl7MaUPZBSxFhFaUqUdwKdD4nCGMx8F1RAWYMrLbYwDNaIRSlZVSBBCuIgr6BLER17Cmep215O+axelvQGixsZvFITOgmcni1z6us2/9W1KbWub3C+DtOPq+u1DBZDZvG8oPC81cdE03s8kaAQVmlizDJSkskISRLXiEaRLqW6rjCYVlzWY99hjCIpYYAao+TELArczlw2oDGSMlvR/+77npQS3svJl3ygXq1ZnJ8T0UxnU77x/vv8+q//On0f+K3f+i0+/ugjnnz2Gc5anDbszOaUzrFY13SNiNPszuYoa/j4ww9ommZkX8rv8mh6tLZCiS9LmqJiPp2yN9/BWj1uPGsNGknv27bFKs3u7i6VNZiIBB4v5YFTEZ+i4FEKgzICpbdWE70Hrem8R8WAJWBSxBrFZFKyaluCF58QbZQEaqXIaQVGOZEDVArUZTFfeH4vY1tNS2st7+BWqbF5/KuPq7i6XstgMazr0JtXA8j2WFVpTRc8fRID4z4m2ujpk4ik8AwHRBCcekuD88mTJ/i2Gze9RpMMVEUx1tHDWDKQsKagLCegzbhxY0hMp1POz8+5uLjAe2lIGif8j+Pjpzz49FNIAWMUi7Nz6uWKvfkOisjF6Rmxazk9Oebp06cQPJPJhJs3b/LeO+9y/+4dDm/ewmrxMfXekwLM5yXOTUgp0XUd02rCfD4XV3WtKaxDGY0gSxQx9DRNTdcUVNMZhRNvkGTEjGlSOLq+xyePMwICs048RPp1gw6JvoPkvWQlJCbWMilKDEoylxTH7E0ZjcpZnCQdgmrVSrIWnQPAkOlt0wTG9+vKph+mItuPuw7W/TpwSl7rYPGT1lX8RdKKru9FbFdDQ6CLguRM2oyPH5W48udmi6J+enQsp6rVWKNJKVBY4TFEHwQ3QMYDpIjRHjeZkZS4ltlCAkZRTYhRbtLZfIorCyIarS2PHnzCb/7jf8RqtWI+m9C2LZOqwBoRBn744BOqoqTrW3SKzHZ22NvZFVvDd97i1s19duc7o0mPNYbgRQpQuCuOoiioqoppNWOaexc+yIb1UVgx3nu6tmW1WIDvSZOpeKwohTOOSVmKSlfy2KLAukwYY1PuWCWq3jZfR1WWGFtLP2hrShFCxBrxYBk3bu4XRSXBa9TDyLydpJ49HC5NQpQaMTLPjl5fzYDwovVaBgshOG+W4tm3/jqglg+JuutpfEAlEeXtgzBOxdB389jhJpRMYVMvDyNCY+Tx0QdcaQm9p2lrfNejpkitnDUnTVIobTBGU+afqaqe9957TzKMswvW2ZNUrt1xcX7CarViOp0RfcfOrCT0hrZtmU0n7ExnMj1Qmv2DPfb397lzeIf5dMLOzg77+/sU1uK9z0FndzxhNWCVxhiLc26EgCd6lNICNvNSInVNS6MTNonOqHLi3xqdQusJBIhhA5aKuXGofMIoocEbPUDQJeOyNn/dBBntWo0ngNEbSYEcJBKglYbwbGYwlBrba5A9eLbsuJxlvKLJwwvXaxksftZlnMX3nlXX4LQRWrqSVDeSiEmSZTmMBvjx5RuuKApS9KjML5lOK7RW+E5Gi30vgjLeeyauQmvpU6gESlv6PjNGywnvv/8+h4eHnJ2ec7a4YLlcs25qIpq6rmmbNdbA3nzKrKpkAkNkPplSliWFE4r63nyH+XzO3s4NDg/3mU5KqmpCYQ0pCP/DGIfWVrxNgcnEszNt6JuW3Z0ZR0eG9XpNiIP/R6Sua7yfU7o5ZSkaGSELBEUf6MoJKGlQeh/xXnAcMQqsHIQc5pyj8z0Kg+8lAxs2ex89Vkmm08eItXlDZ+SsvP4Ckruq7n2dwdC2Buf2uorleVGweFUnI69lsLja377ufR9AW5cyjMyneHp+JpyKwqF1Rdc0IycBNiVIHH9sU4YE35F8YHdvj8PbN3FWavLQe/q2JvmeFLzQ391Gxj/GSAy9oCj7wLSasHOzYm9nj3t3RL26rluW6zXnF8eklFitVnLyRrZOxARBTueqqtiZzdndE8i301P29naELt/1dG1LUVTs7e6hlMEkjTVShjgnOIgY4f4bdzk/Oef89IKua7FlQQqwXCxYXVQsCkdlHbvVlNlkjtUalTQhSR/IuBKV0qipWpaW9UIEfOqupWlkbJtSGuUHx78lc3QwGmvJhLYeQkRrQ0q5fDBKnM+yTB+AQmHV5YDhQydTEE3mvejLrx1D4Hj9UovXMlgM67q3e7vXAJeRnjHJaeZDD30/ovsSG/j2dSXNpd+ZhPZcVo69nTlKJ4g9Sm/Qg1dPN6M1ShuIEnicK4U1GgMx611aWzCZaEgal5Fl88kUIJ/Y0tArioLCXu47VFVFURQYVWJtISVSEej7EmNczgo0vhc5QJWGCYAi+MRsWnFjd4ed2YSu64i9BwWlK0ZUp+9j7rEYnC3EXUwltDVop0cMxPA3ex8JIaG2HOhjjLnBK0rgISlSjOgQUEqjnd00I0fY9sahDDYj0RHWrZ4tQ4b+xPDYbV3O4TmG63md1msZLH7aken4c8MGzjqTsRPtyme1PPWVn9v8QiGkyXhR+hcR4ww6tNLgHDv1Hu+FJKbcRNisSW7egZ+S0sB7sDgrsndaWXZ2J5Kit924CTeiQSKq64xFaxG9kR6AA1QWwlEY5VBKNo6xhZzSsQej0dZiojBWrS2wSjPJWUq9bll1DSlEVGHxPowlRh+kORu0zT2YhFHyenQZlzIEBGHmXhbgVUpGqxJQDVpD2jJsslqPDWLJNxQKO75HaIVOG0ZpjFFGq1trgN8Pv5f0LMt04KC8buu1DBY/aT3PGHm8iYwmIak/kGX2rvw80nyPXF/Deu9xRhzJJ1VBszjF+07AUd4TvRVH86Sg70jGCdgLPZ52TmvKcpJPQJtPOoU1sunctBiv2RmbKeiB2WSeT1s9BgytxexYG/C+p+nlOqwptvQrNUoZrC1QKlGVIppDSlilmU9n1Dsd/XlgsVoSl55pZVFh2HDCCk1JrIOslpNfqYRVZM1N0ClitMZoTdLI40g4o7BOk3RuTloD1oJxJLMhkmlN7h9lVipqLCdQG3PlF6E4r2Irth87lCEv6k28iuPT1zJYXJdZfB4IuFKGqIbadVCPljXQ2HV6tiey3Uiz1kKuf+fzOfP5jPms5MivRxzF5qYUCvj2SWdMFsqNicIMJUuWwc/QaKUkGIlZs86TAwsEptMS54qRmTlMFqRXUKINNE0NREIecYrtoaf34mZubRAglpWSoijE1Ghvr8PHRBc866am6xp8N4gGS4pvTSG/UzuUauSUz9lUYayoZsSIRrKOlAOZlGkRnRJ9H+i9JyFjVawR5GxKKJ0nHNsNyZhIw/dzljEoYV1d4QrS8yfBwl+n9VoGi+vW57IFyBusD91oqqNg7M4/K3Ij62qwCH2P1pqdnR0O9m8wm5Wszo62JOE2vYvh5McYjC1wTrAJ0QdBRRpDSiJ1F3TmPBDxXT82VodgkRJYZVBR5fLC5B6FAL6MMYiyuM6/J49iM3gpBAFTeS94jpRkPLkzndHt9/gIPiaatmW5XAIx62i0oz+qMloc2rUR6n7wxJgh2iRQkZRBaVprrEoYpUQ/M5coA7fGK4MrUg4MihgCZmskqhQQXjzmvJodhBAu9S2el0G8jvHjtQwWz8P7X1rp2Y3fZ8/SYVOnGMeaFgaPVH3pOTTkkWV+jujpfYMyO9y6dYuvf+09dOw5/+wzFIl13XO26tAu5RO4onTSMzDGUBUFZTWl7/txrKiUYlLJ32SMoe0aZvMd2rana32uzQuK6c64kQaVrKoqR86JLUq6pkYbSPRoJady8D2x68UnxVh88tBZ6CKVqrizf4+JnjJ3U3aco9QBowJPjo84Xq45OluR1BOMLqlchbOa+XROEypC7wmxF8KcztB4lWhDT9N1oA0+GXpVkhQ0fUfjRUXclSXFpCQaaH2PVpYYpHwxTqDa2CgG1MGPzcyIZCC2cM8iNo0ZG9RKa7zJRtHD9zNJjfDTSSK8Cuu1DBZf9Lqkg5BRhSEEptMpu7u7NMtFhlbn0zcJHiPmhuZ2hmGczU24IWPI1GsiVksAcGVB13mSagipRcVIUVTjVMMZlacqjjIL+iilBEfSZq2IrA0afMAHj+8zcStp2UzKYAtLGRNlUVFUU2YxsGprdusbnK/WnJyfyTQkeC6WC54cPWV3d858Ps0jaY0ymsIW0sxMcqoPUPgYpVwIIQlwK0VCiAQ/jErza2EcgQ6Fy/IAMmkZX/UECgNJlNkHLY4hW9pel5CaaotPMvBF8s8lLmclL5J/fFXWV8HiC1iXUIDKkJQdwVd78x1U8Ozs7LC8OGe1WLOcLLh5cICOl3sYm/RaJinOlYLBCKB0wjqHdQWFm+FKD6bEWMGAWDtIAlqsyo/XBucsNpcr0mPoCX1H6FvR2Yye5APBZ8aH0RhXUJQTQJCl2llcWVAEGelOJtL4NMaMo+cueE4XFxydPGU2n2AKS1UUeaJi8X1L34uKl/cetEUpT4yiSBZCkMlKH2n7DpJGaYsy2WFdWaKSsW4kYZKIJ8skKm2CQNJoZdFaEWP77OY2wpwdSpBxjJ2/PeJutILwrIbFZur06gWPr4LFF7CupqpKKeq65cGDRyilqcopt27dptCGoydPWC1r1os1flCqigltpE+glUUpjbUGZwUVOUwHBuxE1ArlSqa6xJVTwTdky0SjobQOrRI6K3olH4jRs1qciaNZs8Z3Q5YTGaq2qprKv3JKMZlIlqFysMgZirMlk4nAyWeTOXA8jikvVks+efwQZQ3RwNtv3INcXgWfN1nSWzqZihgTwSd8lIyiD5HOBxhIazEKb0Yr+k7KPacN2srrRRJB4ascvzg2qa/pR2hFUkJv5wrrFBhp+M8LCK8qC/WrYPEFrG1UsUwtEl3X84Mf/IDFasXOZMK0rAizGUeIPH3TNEBB24cxEAhEWzZlCCmDhUwOHhbnCrR19ClhjMOVFuMqiAnfR0Lfo1QSAJYGUiT5nraraduW9XIhMoHdVkNSqVHfsigqXDnBVRXOlkQULoEtK3TTCCIzX2tVVcxmMzA6Ty4sPnS0TxvJBErL/TfeJCWZnvgMyEpaAlBKnpgSnY/0QTKKzge61tOHhHUiauNlWgwMuIirviHCTt0GZo0bOY+ct9fIGVF51LoFxU3yw5fG5NcFhats1FclcHwVLL6AtT0N8d5jtEJHy0efPOCjjz7he7/8beFcJOF0VK7g4nyBcQfjhh2k+4d0OuYRpVJxHEWSxOlMacFDaGUEIaoVqEBK5GzCQAoQZWrS1Q31ek3X1LTreuwZKJWfSwvwS8admt5HtEk4Z3HlhN0be2KYHIOMkLXNeAzphXR9T8hj4Lrt+OwIJvMpIQTxV4nDJjXoPPpU2gI9KQWCT3Q+0PaBuuuEdm4tyjpg8GHRWGdFjXsLRBWQ72kEbPaMBN5VfogWAeJBAyP4dFmmYADhRUbYOHD5OXm1gsSwvgoWX/CKMVK4EmNguVzyu7/7z7l/5y7aivnw0FvzfT/aDIYgyM4QgsjHJYUrK/ouABGtLMlmL5NMOFPakmIQ1mUyQvO2QBB9CkKXXdRr1us19WpJ14q/RwxhBGkpJze91dIb8N6TvGQ0tiwoi5KdvT1OT4+BzWYZdCyDj3TeQwpoDZ33nC8XHJ+d4UOgKAoUCm0GgZo09mQwmqTEQ7YPia73wvglX9vAAlUyuRj2bkpJhIe06IUopbLKl0GpAUsRr1X8BkaBZQWkJMJFSSuRZc3Nzm1Q/6UG9is8IfkqWHwBK/pNx90UpbClUwRl+Se/+Vvs7+7xH/7GX+PeHVHuvjg75+jJYzxP6LqOW7cOx4mITCkEMTqZ7EigyKdYCAGnNSk4tNGYwXVcW4xRFM7RNy06tPQh0K5W1KsF9WpJ3zWslhd0bStCNsWUyUTKDaXkpO/qhs50uLIkBJcbkpqu69DOsrO7m/HsBnN6zKrt6IM0K43N/QVEgHi1rPn440/Zv7HLjd1dXKHwXp4vJOlv9D4RlMajWPUdT88XnF4s0EWJcVZ6OElc7GVaAcYN5YbUJ8YYQowYvfE+FWKeIoRnCWFDoBgqEG3NOB2KKkrmkglt2ppR7/N1AG99FSy+iKUup6sxprEkWNUNf/b9H2LLiomzfO3r3+Dk+CmTyYTHjz5ivVxSr5ZYpSmM8DAGFulsuiOewSER8cSkSMkKIEsZKQeMIeVxn1YSUEwe3cpEpsWHThCauU+xPa6V8gBC7JnM5iRliCGwrpfCvwg9i+U5db1GWUM5mbBsatZNzcVygQ8J7QygidGjkiifq6g4Pz/FGkVZGFQq8MFveCBGEzopX7oYWCzXnC8X9HlkrKz8s1m6MCLj1etOdSkDNSpdpqkPpc/2kkwjbrgjAzfEalSQhmtMKRPhuITOuk4t61UKIF8Fi1/QSgqImqIq+eiTjwUeXSd2dneoqoq9vT3OzySzWC6XGKUpiwJn9ch7CLHHgLBegyJohdcdoRd3duM0CYXvO1IU0FPXNWiT6HtpYg5lTt93Y3ayTakfTsy+6znrj4lkN/OUcQ6FY7Fa0DQN3guy8uLigqfHx5xenNMFLyWM98IQ1aIDqjF0bUtdr1mvC1QMhNgLryMHrD4G1k1L53va6OliIig2WRZgjRnh7TF5EgaTW5ApPxalICoR9FcKZZz0cp733mxlCZ3vcWYDiU9akYIEDMPzy40XNT5f1jLlq2DxBaxtGLnccBkJqAXxeXx6xvd/8CO+/u47TELElQV79oA7d+7w5PFnrBbLrFFZjFwOjaJvGmIRBXCkDSlC6BVGVaQQiUqmDL6XxmNpB68MEdcJUWwI+76j6WravqNwjslkMhoZLZen1OuW09NTTs/PsaZgOp8xn8+ZzMUCsemkKdo0DafnJzx8/IjHTz7jYrGQksv7PL5UlNYxLSqqoiKEQFs3LJdLUmhJGZRljJHrDoHOi6K6CO8q/JZ+pvBfpLcxvLZWwVBaaDZfH0BU46ZPSXQ7roKyrAU1NJEjtH1WB0emSt5DjKLIJYSVz12CvOxNz6+CxS9gKeQ0zB00lNH89m//NvfevMN6rZnPxOX8zu1D2npNXa8onZgmO21GGbsQe0wwYLOFoBJuhdUKfI8PEZ+RkMNJ7JwjNG2+kKEcaWVk6j0HBwfM53OIitPTUx4+fMjR0xM++ugjjLGUE9G/mM/n7N24we7uLnZS0HUNF4szHn32mI8ffMxnR09Z1WuiMpDHweIVWzItK2aFaG2EEGjXKzQlRoE3GuccQsFPdL6nzmPZaJS4vVubm5MenZSUVSplQ+dthbJBvDehlEOpy+SwIau6urY39EBZ3240azIKFEVUiRQvlyIvCggva1YBXwWLX8gaTjoNoBWFrvj9f/GHfO+7v8I3vv41cTonsbu7y8HBAQ8++YTVaiXpt4GUdqmqSpCWxmCDIhpGX48YekIWmlHaYrQGlYT+HgI+9qDEoCeqgSuRqKYTbty4QVVVNGsJHk3T0LRrDg4OuH//PkVR0PYddV3TtQ3LBWhvOT0/5/FnD/n04QOeHD0V31JrcLjciFQUxlC6itJVTIpJ9voK9H1Ct2C1IhLpOkOPpemll7JuG5pO0JYxiZuYsZY2+PH1HDxLtCYreG1UvofXRTZq2upHPLupYxYb3nYu816QpAOt3wwyvldMk68LBFe/9lVm8dV64XreDZOAkDUoTk/O+Rd/9EfcfeM2SimapqEwhtlsRgiBuq5HsFPhZLNW0w5l7BZXwhFMwCVD0gZttEC5M8W863t83xF9t2nM5RO5LMuxvLCmwPdxtAcQ3VDF3bt3mc/neO85uxDbw67rODu54OjoiEePHnF0dERd12K6XExYdwHnSnRSODRlVukSnooAsbz30EaCVnS+QynFeesJyo7O9CEEfDai3i4lhnJhkNhLKaHZKFtd5XBcfV8GEt2wjDGjs7ogSjPlXUuwMEoLPyQE0qDzsZVNvIow72F9FSx+ivUMhX0gVV1aW47p+eOY3Oa7ijwdiUQlIzlPxLjI7/zLf843v/dtbr1zj8ODAyoKbs+m/OjjD4m9Z7Fe0DRr2r2GGHom5QQTNdo6rHFEp0kq0qpjZtN9YvB0jZfxZu4phNjjY0NMXvQtE8TpnHL3BtNyh2j36JXBzWfcmd3h8K1A7OV692ZTUgo09ZrDWyLU03Udf/jnf0hd19y6eZuqqnjj9i3atmFVrzk+OyVE0cPUtsiQ9IpoPIu+gz4T4npRL48h0NUNPnmULuhixLcd6+WCZi1CyZ2RoFOYDVdGAyFzQZLe6A0MOAuVdTJEQUvKNRIMalzD8j5PZDCggjwmbCYoIUV6HzaiwlmweVAUB2Ejmy3B5iGTHD5/WddXweIXuTIUedBMWK1q/vz7P+Tg4IDqO99hMi0wZUnrA5OqRIVI6D3aGi6WC3b3arR1FKkixohBaO199NkWUY9sSR88MXU5TRc2acwktSFjqcopylhSVGgjo9ciQSwiKQSBYcdIzBgEgVInqtKxM5tTWEM83JfGaL3i7OIcrTWL1VquzzhcUeCsUMNXPmQUp8aa7CjvPU3X5Owhbkoe32fnty1zIJV7E4MvqdUoNiNfgEHSUGXMReLqWPNy1rHtXJZIl8hiA7hr+/PEph80YC5gg954eUPDs+snBgul1P8G/PvAk5TSd/LX/lvgPwOe5of9Nymlf5i/918DfwPpH/+XKaX/91/Ddb9U63r9DHEvMcYSgkdpTd97/uz7PwBgvWr43i+9BzHxwccf8+79+2IMFAR3EDs/9jHSTFFoBVGjc9ocQp83imygED0xhtzzGBCMUDpH4SpKV2JdCcpkn1CGiEDI0aHpWohCzIoJ+iDwbR0SlTU4M6UoLNoZ6rpmWlU0TUPpLui9Z5DkiyBaG70gUlNKuMIwKROkSNv3TKxFaZUh3u3oMRu3ew5ZqIckI1GjN8FifO3VIH4cxgxjWCmJePKl92qL2ZuSwOS3BX4TW/2PdLnEiVm2WUyNrsdavMwIz8+TWfzvwP8E/B9Xvv4/ppT+u+0vKKV+GfiPgF8B3gT+P6XUN9PVXO81XlfVw2129zbGEZPms8dPWS1rHj18yg///C4GxZ/+qz/BuZJ7d++gjKLz0pFfrJdgNK4qKSiI9ISUcGaysUfUNm8oT6LPehB9/p2GsiwoXEVRVELdtoU0CgEyA1RwjrKxUlT0QQyWoiCWsEbhjMZEcNYwnUyZVRPK0nF6eopKSkR7QwA0TSt8lC5EMW1qGpHpu7FL6SxoI0hKJbL/Xb5e2IxAlRFJPW2zi1lKDCXg9oYcs5CwpfKdkjQnQ3zm6B/8ShQIPkOJ4lZM8VJTVOuNcdH2U1wdo77MZcfV9RODRUrpN5VS737O5/trwP+VUmqBHyulfgj8m8A//Zmv8BVcm96HHqX8tTK4qiDFyNliwWKx5IMP/lQwFTHy9vEJ+zdvsjOp6GMUJ/G+wzRrZv0M4ww2ObQelLl8rt1FwyFETwwtkUTb1oDO+pmFUM6LkpAMRZbv3yAdDYaA9wlrLG3o6UKL73u0NVSzKbNJb0NqIAAAIABJREFUSfSdeIZow7QqsYWjrBzOWKzS9CnQt56IIniP7zx9DDRtx8ViyaAdsb+3g9GWspzQe7/hx8RIUjKHUCZLDbJhk4ofyLPw7ZSG1/eKLeGYQVy/mYdNbrazihwIrpMcGDQvknzhmet4FdbP07P4L5RS/zHwe8B/lVI6Be4Bv7P1mE/z155ZSqm/CfzN/PHPcRlf/qWfkfDdLO+96HrGJPaEVYXzgYuLC3rtUSownxQ8fPKUvRs30HfewMfA4a2baGvoQseqWRGjF3yCmhFDT1mWmOSICkKGc/vQicVAaFFkhawkhYpKoK3Cx158PnKjTysFCnH6Qohexmh0VWCzGndVVTRNTQh+NO0JvadZC/W96zr6pmO9rkV7IsrfvVyvWa8bUfVKYpJ0Y3fOfDZjNpuxXK2BLe6F5BXYjLPwMZBCECBVXlmCIsOxN+xTg9n0GVIag83VnoUx5pkMYih7Lpco1wvcjKxTozayi69I3PhZg8X/DPwdJHz+HeC/B/5Trr7ysq59qVJKfw/4ewDWmlfk5fzp1zC+61pP8GIWZIsys0cNKURChMdHR9y6dYvDw0PZLMYKnDumDKjqKK3DWk3wPc6ZrAKeR459Q99nH5KURrjzMJZUyhOS8EXEdtBjbUHpsumQUrRNQ4oRZRVOieBu13Xifp7p6CkF0cZYr3ly9JSnT49oO9GgqNsO34s/7MnJGSerxdiotFrQpYWruHHjgMm0oO16zKgrkf8pRIVcazrfjpMQY6T5qpRsZqOH8arckjrpz1USDGPZsdGZ1KVMZFjC8A3Dm5j5N2nMLEaGKowGVMBoqfgyrp8pWKSUPhs+Vkr9L8D/kz/9FHhr66H3gYc/89W9Ius6k+Xxe1H+aSsakau6BgR2HHUQRqkrWTU9f/L976ON4S987zucXCyYvnGIy9lAjKI7uWpWTIodTs+OcFvK3UNWoKzBaFHC7ru1SOf1Hq0tve7weUIhG6bD96JiVRUlZanwbU+zXnJ8fs56saRtW06PHokTWW4ihhB4enzEw0ePiEmGleeLC45Pzlk1dSa8CaEsIXB1pzUGTfQyTp5P56xXtZDmQpbD0xqVcRAhZz7kk98WDkK65L4GyATGOenhsAFjJcQe4CpFXduCFAIx9pAQ7k3OLIbXZcxWModGJP/8pa/FFKUMDJebnNvzl2006fD5l3n9TMFCKXU3pfQof/obwB/nj/9v4P9USv0PSIPzG8A/+7mv8iVfST2/DNHZtpB8Kg3w42Es573P0w3PYrXm6PSU09NT3K0DQoyU1lEWVijUMXt0uDAGCDCgEjHILIE8qhQRXIXXnuA8xjha1gxSc9YKn1OAThCi4uT4hIuzc87Pz6mXK7qmzQIxIaMcRYin6zoWiwXL5QqP4uTsgrOLBSnB3u4+2hqi0tSPHxGCHf9mjZDdhs039Ct8GJzXDMq4cWMy9i425LNtgZuNexvj1OVqeXH1lL/anExajXT0lEe1Q6KwDe0eMg+bM6HhHR+c3LdLkaQGkYGXa32e0enfB34duKWU+hT428CvK6X+IvI6fAj85wAppT9RSv0D4F8BHvhbX01CXryE4yCCLrA5EZVSo4WAuKiLfP1yueTHH37Mwd6NvMlKymICSTaYweB9h3MCgFIIpd0ajTaKpllnPkggBmlg9r3I6J/XJ+zv7zOdTikKaSb6XoBXTx9d8NGPP6ZerkhBJil6C0XZNN348eJiydnxGavFEqzj5s2bvPXOu0ymMxarmo8++ZTHT588s3ltIeC1rutYLJcs1yvqtqEPHh8VioTRItsXSGOp1Xl5nYY+gtZ6BFIN5cSlKcbWuq5ZOSwp0eT9GAh8lzglW9dvlR7Thu3nGJGmV4Bb1xXnX/a26OeZhvz1a778v77g8X8X+Ls/z0W9autFN8BQjw89hE1afJkhSQYQrddrHj9+TPftbxFCpI8DqMkBTWZsdkynU4yxwjjNY1JrBD25Wi1o29zEzJaEArtusFpjlCK2PYvFCUdHR5ydnbFarFmcLdAoppOJ+J1iCDFweiTQ7wHLcHFxwXrdULqKt99/n/nOHto5Vk3L6fmCvu8pjGUFdEGCjJzIkaYV9mmfes4WF6y7lj4G+qSxSkabQhPfQLpDCKMOhTEuB+AMI0cCSUgbnY7hdY8h8oySr86ao1FGpr7vcqNXj7t5DEJ58xvUJbDY88qJqKSsubpeFjbqVwjOL3glJfTmQVj2eTdJSgltspWfBpX0WGYAnJyc8O69OzkYgLIqK2IZ/IiAHE5+kNGkeHxcXFzQtjVd048pv/eBGAP1SnxD2rZltVqzWCxYr9f41lMYEQyOXRgbjzFGVqua0EcGlmfhHG+9eY+9vT1u3L6Nso5FXXN8csbibEGzriW7if2I4NRaE5WYBYXY04SW08UFbd8RFEStwBlMVYyvT4yy2TevYRrLkeExIYSNMVBen4cZOjY6wybjG6cyOYMxozjQZXLakCGkK8+ZLzHfB2y50X/5AwV8FSy+kHVtg3PoYwxM0a3yA3K9HGLu8OcbMzE+9pNPHvC9b39rQ51OJqfgFufsyJCUKYXYAIy4CSVuXSH0rFYrFosV6/Wai4szqmo6XofNXqnTssJOHLPJHKtshjzL97XWTCZTKaViEncx59jZ22M6n3G+WrKqG85PTjk7ORUJPi2NzEhCW0NZOspJhTYGHwM+9PS152K1oPV9xlVYirJktjOnqiq6rsM5I41hhrKtJQSZ0Jjs8aqUgZAh6plePr7GW5yNYYUhIOTmqbZ2xHkwTEiMZF+jpN7WqPXqW31dGBjHq7xcoK2vgsUvYF1lJEgAGKwR5eYfTulBVNZaAUwBLJcrHuepBUG69DFkY2atKW2Zm30Woy0xZiRmEA3Jsizp+4q2bQkhsF4vubi4QKXEG7cOmc1mo1+J9340N96d7Ik/SFa7MsZhlGZVLxGHdulvFKWV3xECKUiTtm1bmqZBIQbI0oAE5wqm0ynldIJWCu8bQuhZtw1120hzUxu0FSOjcjLJr08ipIjakv631uaAEdCuyHgMSyJANpgeMo9hqnF1GrLdRxnKvzGLQcqIgTcyNHVTJpZdChRf8snGz7Je2mBxtRH1ZV7ObzW80sZvE0BpTQBR5Ca3JhAQUVIVwXvWi4ieGGzh6IisQ4syJd//+GO+88vf4sHJU/Z35ty5dZOL1Rn7u/t0nccYhdGCf1BWicuX1lTzXaK29D6xblp2bwTKSYUtJty+fx+nRTPTaiP4hNws7OsuGx03rEPIxkVJ7AN7AX2F4Fm3a/q+p/M956sli9WSo7Nzzs5POD45oel6ptOC+exuPsHFrjGEwOqiZrGoWa1rehRBOTAFs9kuOzs7GGc5rxeklChMQfBiQpSS2EGWWsakngBWEfAE01O4aZ4YyQYPcZgYXbl3tCJ0fpzQOGMz92Qwh45jnyKSR8BZEHmwREwpYQYflNxrGuHnpJGfMvBMhpUy2vbLul6aYPEyE3DS1Sba51gD8lJpJUK9VmOzcrUOApR6+vQpi8VdJkVB3/e0XSdpfAZUScaRsFZGf4Nc3IhEtIZyMmVXa+AG0+mM3d1dea1jysQsAzFycnRM4Ry71RSVRNF7vV7Tti113rzjRvQdbXY67/qG5eqCs/MjLi7OadoVSluqwjDbv4FSiqbv6LJYsPRLOqIYBGCMpphMmM5m2LJAKSGdKUSDI8WIz2Az2IwoNYMqt+h+qiTaIZIgCInvumZk9OHy4RPTiHJNAxpzCDLxClFsq/lpks6RP4yP2cZovIzrpQgWVzOHl+0F377eYb6vtwhlz4MDx5QwSpFUxCdPSLmPYGBVrzk6Oebx48e8+87bdL7n7OyMG3s7Mm0oZGMoJaAnkzQpRtq2JVc6WGuZTCZMp1Ocs0znM6bVREoWLxs3eI/3icM3bnH0+AkXF2cwTFecZVZW+EVuknaRrl+zWkkPpG5bnhw/Ybla0/Yd852K3f0ZZXYr64xMYlbrNUenUqaEEDHaYVXCk9BFyWQ2pawKUpJ+hC3spimakniOBORv0xpnLElBCP3YI9FZAGjAXyhlZBx9JbPo23Yck8YYib0IDauYRt/WgQcykMlCimP2NdyrcQwkVzKHLcj58Fwvy/rSB4uX6cX8adbIfnzBms4qSal9h7MQo6GLgRQ7Quipu5qj0xNuH97CJE/0PfOdKSoyYjTQFrzH+yhq3l7sCxNgbEE1laBRliVlKdgMHQJBe6L3mViZaH3PbHdGOS3pGoFzn5+d0Dctte+yR2r+lzkhYnCcKCaOcl5iCifcEmepKkelC/oUCanAXIiBUd8FSe+VhhTFZb2Q6+qiOLqbKKl6FxtUVhkPuYcw8EZUQhS9g/R/ks59h5hQuTFLDgiX3peEPEbnBmZUqKTH7EKKhzSOe6OWvolAv8W7RMVNRnFp2pFE3vDae/oFwL0vy/rSB4tXYW3fHNc5YI2P43Ljc92u0QmMFb9Q73ucUThnePOtN7l16xbaGE7PT3DmFtNqwuJixe5sThc6wRyMICI/ksNCkvTbOScqVU7jigLrig1xymg0FoOgTLUGnCGEIKQyFYkEGqt4+Olj6mU9NkyJAr+2hWPmZthSlMmVAZ8EkVpNJpyvOhZ1g0YEeJTSUrq0nmQNnoRJG9EaiDgn9HWl9Ii1sNaiVRKaekr4TsoSay3zapLRlJJxRCVZkdOGgKKP/aX3wCotVgoq5pLDYHL5EXOPhvwvxI3PidZ6HNEGwjMlx2Uy3LP3xcuwvgoWX/C6Wru+6IZpmjVWaWxZyibViv2DA+4c3uKbv/QNqlLhm4ajkxNu7O5hnOVitWRaVjkwiNepBKi0Sa1j5okY6QmYrIpljJz8Ohm0lvGhU4qUM496tSYCriyYkEgKjLMc3r7NarrMdopC2hr+vrJyaCcw7Eig61pR6C4KfEzil5JZrn0M9CHm5q8mRJn4tG1LGz1BRSazqcDCUaQ8HtZJGsUxZxQ+ZPxGBrZpoPeCt9D58cIITc9kd13bispYLiNMtOP7dFXkN8aYx8uSJW4fA2KVmK4pOaRf8jKulzpYvCyR2WxTqLeuWUaFopI1SM5vf382ETzBrcMDvvbO29y/d5eDg30R8Y09Tz97wMPHj1AhcvPmTe7du8d0t2RZr+ljYjJJFDYDiIwVnkQwhNBv2fQl4VgoqNuAUZtaOw4AEaXo+gS2oDAF0UFUDUWyJN1ycEtzcAshgg2jSWRkWtdr+r4lJg8BnHHYlEax2xhF8ev8/Jym7cUQWUNI4hbWNB3rx5+BUaRMTrZFNf491siItDDFCKRSIaJCxDctyrnMTBVGbdd1WO3yqLd/pl+0Pl+g1BBE4qVgsb0kGCjC1Y0/BErNCIaTn99+0CZgjM97pQ139TD5MoC3Xupg8bKs7XTUGPGxGoVmc9rfdt3YnR/Kg9V6weHhIf/2v/WXefPuXebzKSF46mZF37cY5yiqkovTMxarNcpo9vb3uXhynGv4iDGRypXYbDCklZZeQm70AZuNg2hvppSykEweCyqNsyW+y9BxwLgJ1XSXGCNtt8ooUC+WgyHgO+mPQG7yJZ0zFzVmN4K96GRqk4StKvJ5aZTPQ4nE/wAESypSX6y2Xj87NiwHfIjONHCtNZpEYSydF4yHisKLkZIpjfob40oBsrivThGlN9oVl9mhmaT3zJstXxcf1asZhCKNQeJKsLg6Rv0SHoRf+mDxZYioP++6ehNcxyEoy3Izi8906H/jL/0l7t+/z9fee0+MgOp15nD4jdCtdTRty/lyQUiKopqys59YnJ1TVTIebTuR0xO+iGFde+g1yQoRSxsjfYh+0xjVhgzsMmM6P8CaVVIiwZc3ad1cjCI3nVkLXT1GdK8ZjkyjFFo7IoY+tMQQaZuepu7ovMj0+SgmxynraiqlUFo2ZkwJouhBOGtHPIJKEH0ipZ6L/hznHE4PjcuIzQ5nSfcopehanyc3HtAkt1FeBzLGBDFBRn63UkP5OL6jWwFjS4FrvE1DnoIMP/DsiPbSff05mptfhj3wpQ8W8GzAeNkwFyOlGkYl6m0xFa019XoNSnHz5k3effdd3nzzTe7e3sd7z+//7u9xdPSEalLy9tv3OTi8JV6gweNjpPOetunofWBdN9x54zbHxyes1nXGKgi4aqC7F0Uxjv8gorKmhrOGummkaejK7AwWc2mfqMoJsjmGOl2u33QFRiesCnRbBj/agHOWGAMG+Xu99yLN10b6qGi9p2572q6nD/ncHYhb4zLoNOhvJiJ63IdK20sISxVFlCYGwW30RDF2LwIpqrGXY5RAo65mFkOmt+kr5Y28LZyaFbYEYDf0MfQlj5LL7NatPsWV0enwNcafvaxxsfn6L369FMECnn3BvgyR9vOuPmyChTQTNy7lQzq+s7PDG3fucHh4yGQyYVWv+ae//aecnZ0R2oa6XlFNStq25vDsjPfef48Y2Rgbh0jrA+t1gzo07N24wfHREW3bcuvgJtpp6rqWTV9Vcl19T5MnGEopzDw3OLUoXqVBcEaB0YaqqhCGqgj3xphyKl+QTCIaP24EozQ4R4wOTSTl/of3Ae8DTdPS9Z6uD6zWDeumxsckLNCU/VtBdD5ySWSyZmbycnIrI2VGZHOqpyCq3yomDEk0MJRCJY/WYAqLtWKi1HWeGC5PQ0Lvc/mTqe3DNy4JUgyqW2ELcTlkBxuuyvjwrcbmNqpzKEW2JyqDJuuXcb00weJlXlfl2Ib/h3JjNpuxvy9ZxMOHDzeHWL3k4vSMwkm3fVJWvHF4m/tvvzWCjZLStH1gtRbgU9KKp8en3HvrbapqytMnjzk6OWY2mTIphlInO6P3/RjIjDas1xcy4lQp+47I1KIoKoF+ay1ZRlQ525Ab3ufNOwRAqxXRaUwytF3edCoSg2hVtHVH1/SsVx2LZcNivaZpOrwxoAwhRqxAEhi22YDGVGgxQ1ZSkoidYPZBzb2YlAKohLOWonAURUFZFpTlRNzRlGG1qlksVvj+cgmwIfTl92srSKgRRTdkGxquQLRVpumnrQi23ZcY1Lrkd+S+it68dgNxcLs/8mUpxb8KFl/Aum7eDohnZsZBdF0HSgRv6rah73tuTcoMmJLO/8HBAfv7+1RVxbJejs/X9z3n5+f8/+y92Y9le5bf9fkNezpjzJFz3qH63q6u7rLbqO320HYLZJCNhCUk4AWEEdgv8IDEAxZ/gZ+Q/ICQWuIBIySMhCXTwjJGNNBY8uw2Xa66dW9V3SHHiIzhzHv+/X48rN85EZlV1a7utruyqmtLqYyMjDhx4py9117ru75DuanRJmFTlbgQOLlzitWGsxfPWK/X6CF417PZrHcnoTGi3AwhsKnWoIY7YhNqe8U6wESCmMf1cpF6D33nKVcVSnsC/U6B6b0jBGFAOtftvraPAKh3MF+tWS5X1HVNHzwhaPyNx1SkaQfwCh9igpgDrQIxrCC6fst3iCuW4AhaCXejKHJGgyHHxynD4ZjEZmhtaZqWzVr8Nc52JpG37vKxsdn6bCqlpECF77HyjgVjWzJ2fIrAax3JDrBVW5Me2ObXbouF69/eEfv3abG4PU9+b3Dp+1nh7fwTgzzObQqwUmpno7brIBSYW0QcHe+Kzjka1zIcFqBhtrqk6zo8mjTNyEY5Y5WjTMakSPnSe4957733KIZDLldzJknBq82CrvY0ZcOFe8XZsy94dPeE4fEJ33rxDOUD0/GE9//gV+mblvnlFavlgs1igetbEq1EIZqku/Fodr1iOBwyGozF4q6VlSNJT+9q8cQMcucMfYgU6iWu83RtTd/W9GVFWcmGRBlD33Wsq1JS3ZWnNo6Fr/j81ZKLeY1TI7JMUTUNASF0OdeRpIFhUaCCo6lLfBc3J9qI5sVk+AhwJllO8IHOOYwJeBVItCIfaoqxJh9DUCVtqMnMmPHegPF0CuZ1zML3QnpzrcP5DmskslG2RNFPRPldYZL3WVih/tZ5sANg3zDolQKd3hTqW4Y8sna+Oe9ue2jcDjr6YR2/T4vFP//4fhZncrO4OcFu26X5W5ZqSim2ePrt1CtJ5dKy/dAFm82KYlgwKka0bYsyCdPpHpPJhDshZbWc83MffInpZEhdVmyqil4FVqslXfBRKKWp65rrxZymbcm9F+1FVbNYLOjbjr3JiOPTU/I8pVqtqPqOLkSz2VSwhtRm0UOzZxXW6Gi7b23KIPNYle4Mhl0vM79rO5xvabuapmkIrqftO1mLtg02SajahrKS7sEFz6aU57XZrGRzokDH1e6Nx0NkWqYGqwzWKJoSmqrGJAkh9MJsbV282DxaK2wwaBNQOmaoKr2LBdBakyQZg2KA62E+n7NYLF57f5Mk2fmiKm0ZpKlI0UNPH7EMucABdLQWUPE9VjfErTiOfPeZdLPufdO5a+v49SbA+bYcv0+LxQ/AoAsa9UZ3EW51JLep2bfNbfztu0gsEm13A6KdnJyQplZOSiM0au8d2iqG4xHD4Ri0tPyDTc9kPOQP/cGf5+zlM87Pz6m6hnRQsFyvaXSgrmsZS5Yd19dzyqZm0HXkWYYaFHjvWa7Fym4yGpClOSd37zKf56yXc6q6oek7IYXFbUEb6dJaa4ospyiG9J0ns7FY9MLh6DvpOpTucV0nkYnOy2P0XZSKBzZVSet6kiwFD3XXMlsu4uglXAatxTLPeWFZaKWwWpMnKXmWgOspNQTv6GF3Zzb0BCPAplcQgviZBtfjeuLo1NP3gFHkuSFNU+abFWdnZ1xezl97j7eFZ/dvIxsTYwq03gLK8THDjQx9O77cjBDqtRvHrgAEIngcXisKgl91O9Dz9vETzOJH4XjTW+C3GCW3b+hO+6GV0JLjSb09Do4OKTJJArORBm2MxiRxxWkTurZHB3BdzcO7D/jwgw9oqzWL2Yy6rqGXVeR6vaJpGorhmLquma+WVE1L1TYMwzCqSZNI2lozm83Ym0w43t+jGAxYjUbMZjM2yxVlXeO7/rWT3hojYCaaLBUl6nYDI0XDCVfKd3S+23Et6rqSAqkUZV3RdD1oRds5rhdznr14zrMXzwnaY7Nk556dKL2T2HuvyIuUosgYFBlWK9JELuTr5ZrEatLUisW/2m5mXLxDi1weJZumrE1wbcBmBuUVvuupNhvm19eUq/L1tzxeyNuU9dQarM0YDofkhaS1NZ0oZFerVdxEfbcn9Q7UVjejigDL0Pc3q/PbnUWIEYlvnldvy/GTYvG7OLa1fts6b7sKAchu5tEsK5hfy9euViv6NmU4HJKR0DQ94/EIawzrzYaqaug6IV0Vq4YkSdifTDncP2D26pLZ1TWLusJbS7Wp6HtHMSiYGS2A4WrFtOtidKEizTKK4RitLXVZcRULznQ8YjTdJy0KrpJLrq6uaNp6xwExxmA6R9P2LJdL8jynyAYopaPpzQ0T02goyw3r9Xqn8/BeFKPL9YagoO47Lq9nfP7kCWevLijLEpMVmFQ2IDoRk56203jfkVjNsEgYFJnEIWpFogNaBZquJ0TbvNoovBMg0miNx8kmIwTiHhIVwFoJgFYRRG6aRjCiN3NDIjN06/1hVCAxiP9GnuMVFD7FDQckiYlmQB1N1+0yV0IIBBWB0e9xhwm43dNT/vaIqna08LepSGyP35/F4vZ48dtyJoq7cvXG2p0bYEuCcPRr4JW7dec5P38pKH2Wk2aW4TBnvRHmYdu2bNYVZSniqsfZhDsnp7RNjatbgu+pyzVnF5fY0YBluRYDm0GB87Bar5mv1jzUMk40xlEUBcPxiCzLsGkKWvH8yTMuY8LZ3mTM5OCQfDRmfXnBYrGg6xvapsPfsu4rioLxUMYVEyXess30bFZLqqqSSAEtArCqqqjblldXV9Eir+VyPuN6tsCHwORgny7qNoKCoIR16UKP0kFsBNOENDMYE82GswSlhqyrGtBUTUtiLFUfk9gTyUNRbAXicVxBYXVCYi0aI6te/72NaPI8x1i1KypdW2EN4oulAyaGNXkdSO0N+zMoBdxQ9r1jtzLm1nPZblVujyE37FDRw7ytx+/PYnH7+OdYmd0+naQ+fO9Nyq51tzZKqG+o21W12X1d24o1XV1t0BrWazk50zQVULASvCBJUg4ODviZD3+acrVmtVrRNW30W3D4vqfelCTDYjfP1nXL5ZWY4lZ1i7EisvLKoIwl9Z6DNGO92rBeLXl5ccm6rNnbmzAeDjFHByhrKMtS1plNi6fGh8DVfMZqtdoVitsZoH3d7FiqOrE0dcdsMWe9XvP84hWrTUUXNR82S8kSwWwGA+F9+KDog6dre7qukZHDGrLUUqQJidWYyEUoMstyvYFYXPTEElbgnKhkQ/DiuYlHBUWIAUh9JzwPryTseKu/eRMLODzaj3d4KXj9Mj6f1DLIpbg1XYurOrq+IUQJfZ5uX49Ix9+eGrfPrVg4tLIEddt270fj+LEtFtt0rNtvSAgheiPcqugxMHd3fA+V3259tTu5bnCJ21+TWIuxYr7rnL/RgNxCw73vBQsIniTJ4lwta8xEKyZHB5wen/Duu+/zqJhgrOLy4pzF/Jrz85eA54Of/hBvNVcfN/Ra0XuHtQmzxZKPPvmYn/7Zr7A3PcAYS9N2aJMwHE8wiVjt3X/vPfpGbPGWixlfvDyjrWoKHXj33XfZOzne/X/XNoQQqDYl+J62Fhv/uq6pmg06wKYsd52Fj+NJ2bSUVYVOE6aDAfmgwKMp4/fbNGF6MGaz2dB7eV/qqsX3DeV6QZZm7E0GHB3vY5RG4SkiwWpdNnRONj69h3ywoO88y02J91ZGHBRGJzRVwxqFO5rSlD0q8+STgslEsTc9oKx7uLUQOTk5om1lRBkNMmbdhkBPVa5IrOLRO4/F+Gc5Zz6/JssK0qygKNLd9sMYQ9n3aG1ey051ztH1beRXbM874aPI9uXt9d+EH+NicVviexuN3lFvg7Srt78uhCCp4bxOujFzmTSrAAAgAElEQVQSMxUJQzfoNz5mRChJGVd4+v52voRkaehbM8tisfzBfoH/K/793/z2fu+/93flz4/D8Y2P/8U91ne++MG+znuH1aATg9aGe/fuUFUVxhgGo4LhsGAymbAuN3zx9JlI3pOEEOxrfhfbc24rxtu6m+eDYkfKgi0LduuypXmbA/x+rIvF7bXW9vitEqMIARO7EQmniTLi+HjbLmSbLbHVD2glqd1yskQqbxCjFWsNWaKY/cv+hX9y/As5gutQKmCNrHOD1kz39zg6OuLBgwccHh4yHI9QRvPRx59EGwAxD/YeFJqm72ibFu9lrIKEJDGMRoPINn39BgVvJ6D55vF29z2/i+P2i/8mv35r4S4y4pvcidsaDsPN7nyLkN+MLh7C6y7Q8uNEQJUmhmKQsbc/4c7dE9595x3+rX/zX/u9+LV/cvwujj/8r/wcINsdjQPvGE8n7O/vc3Jywt27d9k/PODLX/4yf/JP/kkGgwHOddR1vQN3jY0mvr4hyxMGw1yo48qTpDemwVsB4G578iOAX/zYdxa3P96ZzWCRccLFz28ZgNvNxa3kKnXjYxBa8UTYApjy8W1U3WOs6DhGxYDj40NOTk74ys/8NPP5nH//3/u3yQcFz58/56NPPsb7nkeP7/PlL3/IIBMl6OnxHb785Z/h/fffx1+tGBY5f/2v/Q/cuXPC/Qd3uVrMWdcNLy4v+X/+4T9mNl9itaFcbZhfz8izjPvvvst/8hf+AtmgYDAck+aZ8Doymav7eNdTRDJQF3NPnaPabMTGrqqp61KS0nu5Qz64cyKGwNHDs3ct6/UaV7c4F9PPPbgAXd/T9D19FE61veSIOOduaNG+o6k7mq6lLCs2mw1XlzO++OILfuqD9/nKV77Cwd4evWu5urri8tU5ZVkyGu2htMF5GE33SIoBKM31bMXVxSUvXpwxu7qmrctdMtl4PGZvb0+o7JMxaMv19TUXF7IBmkxHKLUnmpKt/WDvyIoBzns2VU3bdxwVQx49eoe79x137twRIDgGPYlQLcH1nrxvefDgLoeHhxIKdXbGarXCJhLxIExY//oWTb3pqPV2HT+2xeLN4/abskXS8exmRBXUjQN0xCa2uOQWckishbjx4FaR8IhK0/W90Hy9I+QZRVFwdHjIIM/49vkrzi+v2KwrNtUa1zaUTcl8PufTTz/lD/zcVzDG8PL8RczjqHk8PWKQizDs/sN7VF1FsGAyw6YtCcqTphYVNME7CB7XtqzmC8rNhjzP0UrtnKMg6g8SjeoNru8Jwe3WvKHrKIZD8sEAP+6py4rVakVdblAqcHZxgbkApQOJ0aSZ0JaDcxiTyKZDGXxQooptJae0944s5LhIOuq88Ei6qowK1kCX9KRJTpZlGGMYDsZy5w6e9aoUoVxdoYxQ5VGapu3JiwKbZYRITR9Nxhx3Dt87rp0jOAdoyrLGmA1121HWDcoY1us1ddsQosHuVgCnlMFEHd26FNLWyDlsmrN3cMBoMtnZB0qim2hmxmO127DcvXfMO+8+4O7d+5L2pj3hRU9ZNfIztBcpviKqTuF7kDffquPHtli8aZaz/bd0FoZoxhR9El+3ONMBdOwejLpRBGaZ5IBucys8UVvhWjabJlrOKVonm4SqXFNVG+qyoqpLXjx9RucdAUgzi8lGVNWGZ88qvvqzP4O1lqZZce2usNby8OFDXr06Y7I/QScWemE69n2DR0RTXdeho4eCQdF3Hcvlkvl8zniyt7t77WL2FGRZIlb7yqOdnAIqSCixSaxQp73HJJIrYq3GFQW+q7i+vuLy5RlluWZ/f58H9+9SJDn5cECeDTCJpXeBsqmxVc2q3EQA2GISi3O98Be8o+w6QioKVuc8wUkymdaaPJcYhNVqxWqxoK5rjJHZfzAYyJYnkdc/iWSmNBU6Ovuyfej7nnK9JjhPXTe46I2RFnmMV5R173A4ZDDISdJbHhpIvGKaSmSkxDnKebLVkzRNA8pIpGPsKJVS5HnO48cPefz4IXt7e0DPnTsnDIcFv/m1r2PMDbgJMsKKlkgK29t6vDXF4s3AnW1jv9tmxK8JQZyStNaYWz6Gt/n5QBwnxMO+94EQV1rByBvqeo/DEUIXtxWyEtU4lFaMhgXDUcGoGJDG4tDGIBnnOpQyKB9oak9dK5zJMFZaY+c65suSb332hFfXCz794lX0gVQcTI8i668hSwxVU1OWPfPrhqODESfTu9y7c5df/Pk/yqhu+N9+/e/yla/+AhfLJdlgwGpVc70oGeZj/HpDOZuDMjRNR+2dvHD1hidPPufw+IAkNwTVM7Bjmr6J62SLTix5bLedc4QoPqvbjo5OJOEqI81SUiAEz3J2wdGoYHrvhPnVJS9fPOMffePrvHv/Poccs59lFDbHKU+ejCjGY8zK7FidBIXz0HeB0XBMeiIirdVyjdeGul9QNY6gUmbXa9rqKeVmzXhYkKVDEtUxLsZYMrxOwPRUmxpjUorhkCKXdHe84+7pHRKlef70OWVZ0gbFuqpJkoTQNLi2QxEwRvHowV2KgXh2hOiytXXQWq1WpGnKcr3iYjYjf/Gcr3/7O5yfn/P1zz5lkOVMDvdJjIbQopUiTeFnP/gSR0cH3H9wl+vzJxzup/yJP/Yn8N2aJ09fcnl5hcWCFsp6zBEg6O99Saq3oO14a4rF9ztuc+dhC1bKJsK7m83GmwYzKhJ0lJJfcXuHFVdIwSR8cFHAZMmylDy1OyR8OByQp9u7hfzsRJtYmJzYvMU7ZppCVXaRVxHBUqV3NvavXp1xuLdPUQiBShynFEErqqbGWstqteH0+ES0HkXBcrlkdn7BarWiqirSNKWuWvneRTSZsSkETe/8jrqsrKGqGxaLBavVinwwwKaZaCgiL0QMbtQNVqMUXm0NbbaF10SsRsa0vpcs0c1qiQ7I+nA13hG46rqmLGu6ztF3Loq6Al71gpdYGw18lQQeNT1OO4hZoSCRiJvNRkhrZUWWJq8xYZMsi6NJDFXWCcG73R1/K4az1go4OR5zfHzE9fWMxfmr6DUqNn+djwY5QfQozkmhkVH15v3rXY9znqbr8ChmiyXL5ZL1puLe6T2yLCOxmq5pacoKjGIwGGBtynpd8s++9g2++OILPPDo4WO+9FMfslrXbNY1VdvFUfcGSO9/gln8zo/bHYPzN0YkXgVM/P/b24pd2rWRQBwVvAiVtLTfw2EhBiyd0KeHgwGjwYDxeMhoWOBct2MKys93O0MXpQTp9krLnZcb1qa1FtN2EqdnTUyvEsamNenuJGqrGmMMnQt0dYs1CUmScHFxwbsPH9B1HScnRyRG8fLlSzarNU1ZMdofs2o3KEO0lQu7i7BvO7wTvYZCTvKLiwuurq4YjsckWY5NEjCid9gWLa00WlspqjrgtMzrygRMXAt7r0WUFUlOW2JbYnOKoiBPsx3OIExJMfLpg4wBdVeKriQf3oQaGSN0aGR74L3EElZlI9qZqC3RWpPkecQBHDbJhIodJHowKI3yNy7pSolDuGwcxAR5Op3ifeDZ+asoP5eiJFkj7MyPfTTRMVqyVFAKnEZrQ1VVLFcbLq5m5PlTFst1BLmlo+uaQNs0QmzLU6xNuX/vAevNis+fXpEVQ+q65tmzF0z3jtjb2+fyYkHVrHYFuu8dQYE2P6F7/46PrahJaY1vYq7kljux7ToU0ZnoZgWltUbp7SZDBEjWKNLEYIMj9JpEZzy4c8pgKDNsZmOB0dL2Od/hHDtmnUZs7LxPcH0vd0ot/hZpZum6BBd6jNEoLW7YWmu0Fa2GNUYuWDRpmrP1kfS+5+XzF8zfe5fpeMJoNKLvJU/DOaEd20KKSllXhKBwrSOxGWma44OmTT1d5Binacp8Pufq6oqDoxOK4Yg0y0hUgosGLsYYbMze2CaEK1Kc1ygt8/lWAbrthur1kiTJMMrTNhV4xXg85s6deyQ2AzRdH4OAe8FTri+vAEjSnNFoxP7+EUVR0LWOVd0KHuLCThpfR+q4NlIA8izFRmk4SkamJM2wWoM2uOBpoxblO599znpV0tS15LtG4hxIYTXG0Md1pU4s1hj6XgKcuz7FmD66hqnderN1Isdv2xbjRNG62VRRXq9vzjnnwHu6riD4Oa3zeBRd69jbOyDLMoajEUpZ+g6qpqPrJMDamGSXnep+lDsLpdRD4K8CdxAk8FdCCH9FKXUA/DXgHeBz4N8NIcyUzAV/BfizQAn8+RDCP/mdPsEt4cVYKyduH0B/dzScPFlAy6jhYiydMZICrpXCxD+jQcYwRurdOTm4cSEKnizmcbq+FZPZW2vVgCXg0CqjN4ZOOZEbo6JmQokuIUiLnyTyM5LU0LmWNB2SJjlN05EkGVluYutdsV7NePH8jMOfmYLvmV9fUW5WpFazmF/jcOwdHewMabbiNB0DirIso+k7vANjNJtNxWK+YrPZMG1bXCwQyopXRqINQSeRjryNLDQo3YsFnnforiOEiuCsFMNqQ1EUaDxtLYrY4+NjTk5OaJuetu0h5pIIqY0de/Hy8gUKzYNHHcdHp6KFWfZsypq2c6AMdS0sx213KF1eTppa+q6JUn+5ODNr8VphlKUtSxbLGV/72teiAY+8LnmSMxnJViUrcunAQh8Tz0T8pZSkuCdtgtFbNmWK0oHOO9JUOpu6rqmbjrbqb0yE43ZHFmqK0Hs265JqU/Hi+Rn37t/h+PSUq6tLRuMpjx494tmLc9AWrQ3WpmiTEHB4t+XtvL3krB+ks+iB/yKE8E+UUmPgHyul/g/gzwP/ZwjhLyul/hLwl4D/EvgzwE/FP38E+G/j3//c400l541r0hskq0BMdHjdrmx7Ucv3SQfSty1JapiORhwcHDAejxnaG58JE5fbSoVdcpg2CqNTjFG7ll9eiEgT14AOeC0hvmrrrBQA5+npSZRFpZLGba10OcUgR6mO5XqDD0q0IeidQvH502d8+N5jhsWAxGgWixl5nnJ9fU3jW7BE3CHevePzMuYGke+85JpWVcVisZD1YDTIUVoLqNn1dLrDmESKXMQFrE3R1uFdQEdh2JY05B3k+QDXt2jfkaWpdAqTKcPhEEIFaLR2uDhGJElCZjNCUCRJxcWrS66uZty5e5/33/8p0jRnNjsXP8yNrEf7vt+NK977aGGn8U4cp5xzZKmMWm3TE4yKAGrHZrWWLY5JcG0XHcwmKKWYTCbMZjPo5fXqvSN0YTeKdN6RBo8JkgVrQsxNSZLIzvQsliLo01qT2gTnPFobtNUYFF3EtPCBqqkJaKaTfdbrNYPBkHv37nM1W8dzL0Hpjq3b1hbv0vZHeAwJIbwEXsaPV0qpj4D7wJ8Dfjl+2X8P/N9IsfhzwF8Ncib/PaXUnlLqbnyc39YR4NYMGqRbUAHUVpr13QrQrdzXGEPwPRjYn4y5c3rKwYG0g2nfRtq2F5Wjtbt5VmzxAxiNw+LjXVewPiVOTkGo4AaF04EQxNF6F5+3a02F2LOpNmRJhjKGPDeMR1OcC6RphveBwWDEeGBpGwkXPtibUpVrZvMrlNZ0fc1i0dP5XohV2uB9H3UHsk5FK5ImEf6CFwet2WzGbDbj8PCQoih2hLFdfkfToOJsb61FaSPJ4NGwRfcGa0SG3bcNxkgAcV/3lJuKtmox+wZtEpLEY222SybzMUtUKUWiDZPJhOVixXe+/QXPn50zny/5hT/+xzDGsl5f8+rVK65m17ubQpYl2Ci2stbStRJ1qEL0wuwcddOImM95hsWALEsoy5qtJZ9zjvVaLs67d+9RlmvatkYbg3f9rih08WMXbpLQQsRBmqZiOBxydHTA4eEhl1dXtG0fDZKbOL7d3HxCvJncv3+fNE0j3RvKuqZqGj755BMWiyWr9Zq6bknTHKVCXNF6iUN4S4/fFmahlHoH+Hng7wOn2wIQQniplDqJX3YfeHrr257Fz/2WxeLNzMntoa2iaWQboGO83s4zgJt0L623u/U2ItSWPMuZ7o15//FjbNRu9HVJQifhc8YwnI7i3C4WbDqCgEopCJ40KjWVUqhe4RzgenrlMUaRovFOMxkNUErGCk9AWbPb0FhrccEzn8/Jc7H97zrHcrmiKHK08hzvH5PQc/fwANqWv/Nrv8aLl18wmU4xeYLXjqvrC7xWHBwcYPOELDdUbSknZd9hk4DqArSWpu158eKMwWDAaDTagZoKSJME7xydb3cBwCEEEURpjSPglUYnKYk22N7SonCNp2oqZpczvva1r3N1dcEv/uFfYG/vABO9HXxQ5JGP0vc9e3t7grnUCcPhmKOjI7717c/43//W3+b43iPu3bvHp995wmeffiEy8qgWLoqCIk9JtET+aQ2JkbFus9nI12QJyojTVlk33Dk54fPPP0d52Za1raNkzXg85A/9/B/g+vqSy8tLhqMBVd8KoU0pluWGJMuwWYLymuB7rLcYApPRABMBX200D+4eoZSh6064mi1ZrVasVxJl0NQ1Vd2Qpim/+jd/lV/6pV/i+PiQsqn44tkT5nOx8CuKnP39fZbLJd5DF0HhJNUoZb8n7XsL+P4wjx+4WCilRsD/AvznIYTlbyF8+V7/8V2/vVLqLwJ/MX78fR4p2sPHghCCF4FWBDO7tiPLUpQRxDrLE8ajPbIsYW88YTAUG3gtrow3+o0ImG47iRA7ke1KEWSLgQ+vvUnysyU+TwHBe2n7vdvd5VUca0JwqBjxJx2Ej1kfCYlOEDzM4b2QjCbjEWlwPLh/n+VixstnT7FJImSsxGITS+06XOeouxs3qslkhNYW59d4ZXE+pas7eieWcut1uRtHrLX4Qb7DBLabe9l6QK5SVGyDb2exohV916KsRSnN9XzGsxfPWc4XXF1es65KsjQnsxnGSDp7nudi/nvZYq1l05eRyCakpTTNub6e8+DBI/I8xzmJNAgx8/S1c8LfbMS6riExuXSXIRBCjwqWNLUUMQJyF86swmtdY2ItaTTc2Vodeu+xiXRmSmt0YnfbkC1xTVhTPUolEVMX3chkVJBZQ5FmzJYLuq4hwjacnZ1xdvaCu3dPuXv3LvP5nNn8GtdLp+r6lr7rMPH5KR0ERH1jDNm9Dm+B0OwHKhZKqQQpFP9jCOGvx0+fb8cLpdRd4FX8/DPg4a1vfwC8ePMxQwi/AvwKgLXm+/Zer9mhv/F/WWKxWmOtZjw8IBuIV2JiZEZNrSVLEhKlhF+hNam1WOV2BUCncvJgNNoKQUYpCScOIdBV3Q5E1BqUMgTEj8IYjdHgHFhrdidl37vXWlOjEwhy90hNBjkkiaEoMlzfkicFoyJnUqT81Hvv0lcNvutJi5x8UBDyhCTPaIFNM2O5XAIamyZMJpOdS1aaphI0FOndfe9Zr9dcXV1xeHhIkhiGt8xybt4LtTOi3QKH27Q0gOAVaZbTR8OW6+s5Zy9fsVrO+eLZc7705Q9RccNTFAUgxVYpacG11ngF1tywM621PH/5ki9/5SscHByRZRnL5RylFGkq+IuJvAilxLx3+9pmKSgrXAgftx3WGI6Ojhg8eSo+pURMZ5ss5ra+lzcf+1jskzwTd7PEkuU5iZUxzfduVzAF35LkAKUUzirquiWxoib18eckaytck77n6dOnHB0dobR0l6PhGGMyVsvN7vxyfY9SgneZ79M4iEbpR6BYxO3Gfwd8FEL4r2/91/8K/IfAX45//41bn//PlFL/EwJsLn4neMV3h8Xe3F1CXBEWqTz90XDEvft36J0T63hrGeQ5PqLyeZbJRgQxqNHxXem6jjyx0QrOy1otMhrTGJibZClt3ewAQOdCvNlEw1VjsCEmZVkFJqC8cDLkrhwEuOJmTedcR5YohoOUzaYjzSxFYjnY3+Nob8r1xSsGWY62MBiOua7WXK9Kzq8vubySVWSeFxweHjIaTZjN5/EOmcZid3PW1XXN4lqwi+GwEIqyl7la6xvr/RDkzpamqTAZI14QQiBoyUft24qyari4uma53rBabXj6/BnL9UoKRfBkSUZBIXyGSJcOIUgkY96KiXCWY9OMs7Nz1us1kyjwOj/3YnJTTHZErO17LuS3VNzCIg6CNhA8QcvzPz48FC5L24ogK/JufBCKuetkk9GHPjqv33hOoDUmTcgHBcYoXFnSOQFbk0Twk3g9SHdptGzM0PS95KkOBjlplglDt+94+fKctv37u23be+8VaJUTgtx0xEVLxqwQpAvqb532txnJt4WRP6zjB+ks/jjwHwBfU0r90/i5/wopEv+zUuo/Bp4A/078v7+JrE2/jaxO/6PfzRO8vQ1xXsaQ3RZAwWAw4M7pMdPRkPlqKfhnCKit8YhIK1HBC+FGKVQEorQRGnia5ZhEXgo5uT3rxZKr1YrpaIzrBLRLY+ewU5wqeaO996BvJVdtO5GYUk4MJ1aqpu9bqnINRSFzeWY52J9gLIwHBa7rqdYblHMU4ylOGT7+5Ds8ffmCi+srqqbFWEueZfzyn/pXOTw55PmLM0IQZmRqM1qrYksfaJrI5pwvqI8OaGK2qbmF/ajeSUZoCHR9C6QYpJgksUVvGnHMms1mnJ2d7cx5ry5nLOYrRsMJVVVF/Fk6szS1jMdj+uCjbsNjbLK7MK6vr5nNZkyn0x04HHzAGL1zOXPO4Y0mNbKVMErTx+2RMqCweAWuDwwGA4osZaHErQykM+2dE11ML12jDx5rrCgxvCbJUmyaYNMEE1mjpm0xfhvfmGKUltfUebxSsTgM6FpH3zeECKqmmZgxz2YL8HBxdiFAslKUq5LEDlgsVqzmK3TQZFkSOxxx8H2zKOw+fgvkqD/INuTv8P2Xv99l0hC3IP/p7/J5vfGYN2IoY6SFT63lcH/CdDplfzLGeU+WRDJR21IDg1ySwPu2IzH6Vmut0EaTpQUqMewfHnB4fBxTw2FvMuHzTz/j+bMXmKBjS3zzfN5Mkeq6RpiVbMHMsDPtlYsSaXEjCNi2LdYa9iZDUltweDChX6/Is4S2qXB9T55ltCbj6fOXfPvTJ5xfXVI1rZgFq57lsuL6es69ew+4uLhivS5Ba8bjMV3bUZayRtwWi8ViQbXZsFlJsI+0+GZHzlJKYawmOE9Hi3MmqmtfD8O5urri+csXLNdrsiRBGU3nt1sHg1ZW3L77Hly/44Qs1xuur69ZLBbMFis2VUXd9pRlKXfUuDLVJmE6nXLnzh1WyzldtOHzStN3XohskUpOBGwTY1AWdJqK4W7chGit6fpe/Cba5mY8cV5YqXHcygYFaZGTJpmwb5V0GVaB0QlWxwCk4HC+ly2YCzE6QUuRGg7onKeLrcHh4bGYGW9WeA9VVfHZZ09JbC7/LhtZVasU58XLk8A2V3l7LX1/PO+HcLy9Erd47O7gIaBRZFnGwd4ed+7c4cHdexwfHJIkCd71pFbuPoPBAK1FFViXFYnRqBCj9pzss4PS2DRDW8tkb4/7Dx9w9/490jwjyTIePnzIcDxitlzICBKBse2fqHTfzbM7GvTWsfpWR+Sd3Pm2XUnXtfTRi3FvMiRNE4yCyXBEvSnZLJckScK3v/0pX//6RwxHUw4PTygGQ7I0J7Ep1lhevjijqVuKfEBdNVRVTQjs5vxtcSxLATnn8znz+Xznl7ltwaULSF9L43K+361B+14u+qZtubi+4vr6mrbtyPOc6XQfay1lU8v4FlWay+WSs7MzglYkNqVtW1zw4vpd1zRNt6Nn13VN56Xb2d/f58MPP+SDDz5gf38/vmZbUFCeyzaPRQd246qxiixJRb5O3O5Y+b6tdqUuq51Piev6qKwVyXue57KWNkao3Lubi1j27/QnyoqWxQt2c315yXK+oG2EBCgU9YJHDx9z5/Qu+3tHFMUQpYyse+sW70BrAYuFGrDVLW21R2+nEc7bQ/cOcicQ81mROZs46yVJglGB4TDjvXceMRmPGOYFSZJSVRVJYsl1wcHREaenp0z397i+vOKjjz6iLktU3TAZjRkVA9brNcYFjAqUixV7x4cUWca7j99hPJ3w7Nkz/s6v/7985cMP+cU/8of5jX/0j2nrhnQ4xBhN0AglWhlhYQ4UyliarkVphc00ofYQZMNQt4GgO5SDpuspEkvXdHTOow567j84ZGxTwt4R0/EBn37+khfPL/jii5f8zX/4D1gul/ypP/XLzD97QlnNMSbbnbifPnnJvc+f8q//mT/Lr/7q3+D8/Iyrq0uK/B5G5bhWaNN9CFy/uuIzK7mmy/k1zjkme2IS6whYm2KxDNKMVN8S3zlxHtVGcfHqjE8++Sar1ZI0t5zcPeHxew+ZjAZoFEZ7ys1KWvRsQKoyjvfu4uucg0lPOdXQF6yXjrZ0lP2aptowGKa40JIOU+6/c58/+st/lNOTI3rdsq7muLplMB7RNQ3GKAaJET4EsUvEE1SC8zBfVHinQSWoJAUaTGqoqg1BidLYBY+yFmMsxXDIcLTHYDgmz0ZkNgMf0H1Lsy6p+zWqKEjTlDxJcVro4mme4YEXry5YzNegDYPRhMl0j5O793jvnQ+x1jKfz/nmN7/JetGikXHFh57W1RilsNrSa3F0R2uU1oTtFu6WyOz7dRlvqrX/ZR5vT7EgKke3YjFuCFZ934OG6f6UceQMmAjAyVydcHLvDn/g53+e09NTxtMJq9WKn/u5n6Mu1/za3/rbbDYbDCrqK0pxNAqy059MJpyennJycsIgL/j808/o+54PP/yQ5WzON/7Z1yMYWkT0/ea4ETGJpmC7tjMR+Vc+4FVcxTqPShVFUTAZFExH452Fvow6akeWevHixY6Q9vTpU66vr/Fxht6eOM45nj9/zh/5xV/g5OSEV6/OpdUOVXxuYSdSWpcl2XzOZrORApsVwlzsOrQ1pOnrgOKNcnd7pxMfh+vra/q+ZzQayAi4v89gMMAoHcOCietKw6avOD8/Z7laAmL0IphBvwMtm6YiBNHD5HnG6emp8GSShNPTU56N91i0lzv8xWqDs4Idpch2yz8AACAASURBVFlG7x2td1iT7GIahXV68ztsx5xtlKHWmjRPSLJUQMmoG5H1ud1hVF3X0dubrtHaFKUc0EfNTkNTx9Ew3ug2mw0vX77kN37jN7h37x7D4ZDxeEye57vRqe1bUqvJhwNxjK88XS9GPlXb3bjS3wotSsz35l/8Xh5vRbF4XX6udujx9k3quwatU6bTKXmekWiD8x2bzYbJZMLjx4+59+gB77zzDrD1skDWeL6nGA53AbxplpIGmY/7Hc3W7zwmtm25c47Dw0Pu37/PsydP5bnoG8/O7fPdrdWMzKuidI0qWA/O9yiTELZ8DScFKs9ztvF6fjhgfzqJF09N01bMZjNhm6YpZ2dnlGWJjryNEAImitOur69JkoQPP/yQL774XLwb2lY0MsrgI3DZti3L5ZKrqyuRvOe1EIFsDA4amUiVvykYt9O6lFLM50tmswVCn97j4OBgxw5NjLTnCkWSZ+RJjnOOs5cXNF3PvXv38EExn8/lok80VS3Pf7I/YTAocN6yvz+NVPGU0fEw6k4aVFAQNDbJCEpA1947nI+2+tbw/PnzXbQA3IwOShmSLEUnFr/xOy6DtVZ0I6nFGkViVCTvdbRNQ1OV+CzdnaM7Gzyks6mblrYX3xQhaomMve5avvnJR7x6dcZoNKKua2GOaiFgGc2OTWusJXGpsJUjB+jGJuBHbxvye3DIRejDjTfFloQVnCc1llG0YBdCVUAFxf7+Pu+++y4/9dMfEozi888/F/6/jp4Gwe0ujsFggDHCsHTO7fQHSinKsuTZs2csFguePXvG2dkZh9M9vvXJt5nNZoxGI9br9e5C3WEXKEzQOOWjojHsvBVVLELOOeiEzNV3PVWnyMZjsiyLBQjKas3poWwqtpbxKC9K2CzbmcFuZ3BRX0qep7GK8/OX3L9/j4cPH7Jczanq/sY8CIQSraBuGs7OLyjrljz+rDTJ46ai33UGsCUDaUS41eMjZ0N0JgX70z329/fZ3z8kzway/YlYwPY9lOds0K7n+PiQJEtZlUu++cnHLJcLUJ7Fckbv7jMZjynrDYPBAKUEm1IBGSmvrnj18ozNeoNSmiLPcSHQVg0YTTEY0vc9z5692G0etBbNzZafoBPZPKBFB7S1LCiyhMzKH03AdQ1tVdJVJa7r0NYSlKLtfXSyiuZKPfRe4Z3GBU/fS6EoEkk+67qGF2fP4xq/IM9T9idj6RAh+nSws/TDaJwGg9lFK5po2KS13r2uP8zjrQA4t6QTadNef0rOdwyHQpEej4akVnb+gzxjMpnwzjvvcHp6yvPnz/n1X/91Pv30UwCOjg744MMPefz4MW0v4blJkrwmPttW8cViwXe+9S1+8zd/k29961tkSUJd13z00Ue8Or/A2gQbNxnb0WeXicmNp4bVNxTv7QrRGEPXtLv22GrDdDplOhmhtaw4Ly9f0XUNi8WMst4wn892hQxkhblbJfput/bc/tyPP/6Ytm157733ODw8BDyd7/BKEri2XULbivHter3eAY1bF6u2bnYekDeFYtvtyXZhGwQ8HA53I8je3t7Oz2JLmy/LksV6Id1QIn4Z8+UM76VoHB0fUHcCiM7nMzabDVmW7Ipjnuesyg3Pnz/H+4CxCYv5kk1ZRsZsoCdg8hRbZLSu5+XZK15dXYrewxhMxF2k85OtTTEc7DrB4bDgYG8qdnpGtD14T7OpqMsS3/fYeI6IEZAS0Ziy+GCoG0ffBTENQtE5MSX2QQSJXnlMatjbm3Dv/h1O7xwzHBVSHIKjyNOdCVLnHZ4QJezq9S7m1jn2wz7eis5CKV67+MSMxKECFFnO0eE+B9OJ7PwBvEMbs3NVKsuSyWTCwcEBe3FTcni4z+npKVoJRrBarfDek+c5PTfzeFs3XF/OdoKj6XTK0b17PPv8CU1Z7fQUWZbRNy1a3xIMRamydLtimpInKa3tdxfPze+oGAwy9qdTjvb3UCqwXq5YugajhCNQVeJwfXl9hTYGo9wOA5GthIt7/wStRafSdR1nZ2ecn59zenrK/fv3ubj+nH7dxs2GOGB5Feg6h2pqrq+vGY/HtE2/E+ltZeVy6NdOzu3cv1gsICaBjcdjxqMpg8EAjBWVZ2Q3tl1H13W0bR29MxRX15dcz+a8evWKuqspBhnVfMNms+H6+pLh8CH7+6JgzfOc2WzGq7NXdE0r2EBs97N8hNcGnWiGwyFN1/Ls+Uu+89lnbMpSsCMPXm11JjJGTKdjTu+e8OryXDgzacpkKh1eYjQ6ena6tsN1HVZrgk3k8RRoY7FJhusVdbVhta7ovcZYMUX2XY13smFpXcd0OGA4GHBwuM90MqatG/IiIUuE+DUaj3AK1lUvhWwgRDVnO7mpeY+6lQy/Db/6YR5vRbEIQWa5NLXi2NT1KAWjQc7jRw94/OA+fdeSJQngcV1P01ZMpycUoyGj0YiD7oB/40//acqm3BGAtJK5frleYbQmHxTCuosz/K79cw69MUKm6edsViXVRkDQEE+iNE0xyB3adl0EOt1u7DDaYBIbsyQCvWdntT8aDmjKSiz125qLV2cY5UkTxXg0ILWKZblCOST1ajQiLwq+eP6Upql2IrA0TTg4kAu0aRouLs8JwTEcDthsNqSZ5YMPPuDscsPHH1+jPfjg4+rXCgjnPP/0//saeTGkGIx2XhjbYObhcLi7s+1cx5Smdz1PnjxBa82jR4/40pe+xKNHjziY7on5biMdSp7n2BjMrFSg8x2DJOf5yxecv3rJy5fnDIc577//DovfuEZrePnsOe+++5ivfvWr7O+LpPvjjz5htVrxtX/6NTarNSdHRxTpgOM79+lDy6rc8PTTT/nk29/iyZMndC7ggibPBrRthzaGDEuSWKqqwunAV776s9gs4ez5M7Iso0gTssSigqfebOi7jsxmpNrQYtA6QdmU3kFftaw3PfPlmvl8TVW3eJWS5Ibe99A7lA00fUdfex49POHo6IjpeIL2gTTJef/9x1y+OqdzUsibvqWsNugi5+D4iOF0j8qkzGLSvXduR3vfUs9/mMdbUSzgZiSw2shs6Hum0zGHh/uCM/Qdndki7SK8sVm6A6m6V2dsNiteXV1yenrK4eEhXddRVZVsETIBReWiuJn/9PYG6oNsTIzBakNmEwkEcEDQuP5WlADb7icK0MhjsTO7GZOup+lrvA/0cQYdFTldU5GojOGoYDIuGBQ5y+Wcq9kl09E+q3JDWuQSytu25GmK73tU8IwGQ/YmE0ajgThprWYMixwVAr5v6eqGw8NDDvanqMDugpfuIWHr3LVYLHjx4gUPHjwghEBZrZnujfGR2XkbYNuOOl3dMZvNOD4+5v7de7J1Gg7F3CYyI5WCtq1pqloozM5RNxV95xgOC4oiA8SBTDYUYGykOfeeuqyYKwl/ms/nPHnyjOvra/K84ODoGO/hajZn3Wx48eI5nz35jOvra6q2w+iEwWgIQTEdTuk6AcDpHYPhVFzW65LRaMDRkbh1HR+J8dF6tiJ4j1WyWnadJMd3nWxVNlVHWVaUm5q2k06ycyInd9E+0CsITkDXNM/iNB3EzXxrBKQ0J3eOeX72kt53FIMByXrDqpQOeRxp9VubRufDDSFO//C5F29HsQgB7zq0srRdS2I0g+GQ4WBAok0U4mwBM0tiLDboHQ4gbbLm6dOnrFYrmqZhNpvh2o71es3edMzFxcUORxiYJBrUhmh3F0cgJ/RvF6ALNzqArZCJ2FkISzFB64CYl3Rxbk8EyOx7qnoTDWpFIFQUBffv32WQpxitsNqjNHSuRcWK5YLMvXXbQDSP3d7dtdYMBjnj8ZDBYEBdl9gkGsTc8vIIwfHOO4/4+te/HoHSgDLbOVgKwPb1ubq6iqDxKI4ggeD9bk53zuG6nmCEBVlVFSeHBxwfH3NwcECaWinkbRe7K1FraiOvZY8nTyyLpqHrHVlqyXPhxkjBkPFOAnoynAusVnLhPH32gm9/6zscHR3x8N5DNmXL+fk53/j6N3Has1jNqesKYw2jdIzWliwdkKY5o9FEGKvVhq7v8bgdyD0ZjkjMDYGrrRspkhiUUbJBArRKCb7n/EJWxW3nYlJ7EkFjI2ZJPtD3NwrdgJjfbIvuFkMZRK/Sw5MjatfRuSA3jGbEpq1Zr9cMxxVFJMdZa0Vqj4yaRv3w4cW3o1jE7irRhrbvSPIBR4f77O9PxdC1dySJRVnBAWyS4JzGJAbwNF3NYjbnG9/4xi7fYZDlgk90sptXQR7fOYejI8Sgod5HJ6g0ee1OmqRmF85z+07b9y7qK6RQGGPIgqYPHhd9JPu2iW24ktl4JDP+weEeiRa/BE0PMZzIRIq4I9B0HXXXMiiG5GkWHafl5JuMxkzHE9mKuF44B127M9npu4a+63hw9x5H+3ucn1/QhkhuQ++2M94rLi4uePHiBXfvnWLMkbiK5/K7bdWzBI+xW7xiTr0pGT1+xMmJFIs8T2nbOoJx0VEs3BQv4VYo+r6lbbpdF1hVldwxlUYFEegVxZCm6egjo/PlyzPG0z3u3XtA2bR8/PHHbJYbSQDD4UJPXqQMhmOSXLCFJD7O/v4hxiiqasV6vabrRA+j8SRZQpJOYmRAwHVdFJ4FrLKRKwOt82yqlr5bRYMbg04sSSIKWhMtA53vcGxXtIIPiU/nhjwREHM0LhhHez+TJmzamrPzV9gk4eDggGVZUZcVruswcbOUJAnK32BJNjE/6SwAYuQwWotXRZHlHB8csjee4IOj6xrSVFpendjdRW3TqE3oOvHTvHMHYwx37tzhnUePyYuUT75ZYlCcHh1LtQ7guoY+eFQQUdHWRt8Yg0lFzNSpDq9uAZReUtGd8yglRQqIiVqe5XJJ1/UsFvOovVASlTcasT+dRAq6wvlOzICVR+NRWpFYMZ6VbBSND5DmBak1qCh6SpOU8WjAMPpRSHcihrQaBUG6gL7tGA4N9+/dYb1e0y9WO5D2ttfDer3m/Pyc1WoFyFglr4MjBHODxcStzOWrC9q2Ji9EKJWnQiIDMEZWiMF5fJAWXhJloeua3ajXtx3WCDaklFDT27bl8PCQyXAkj6UMTSNxiF/60ju0rePb3/mMi8trQjT2xSpsljMYDcgGBSb5/9t7sxjLsuw879vDme4cQ05RmVWZVVlV3a1mNdktNylTaHiAB/GF9pNpA7YMC5YfZNiG7QdKeiGgJxuWDRs2BNCQAMk2LKs9wDRgiaINiaNIsZtsdndVd2UNOY+RMdz5THtvP6x9bmQ1q4pFsVkZBccCLiLy5r0R+544Z5211/oH2dcXeY8sKxgO+8IcpeHxw4dSgaiTPkyWpKgA69ggD20QxZOgqErHYrFiNl8xm68xA4FlC48mASXub0FJItVOiylVAKUk6YdWiGtaSxN2MBySZhlBQd7LGE8mPNrfZ11X9AZDtkZj7j96RLla09MnehtN+KCeyvOOU5EsABSeuhKZ/GG/YDQakBcZy7mwG/M8x+gEoxOatqVuPTknknBbW1u89NJLPH36FK01o9GIt7//Ft///vfp9XqkNmE+n1P0ClTIqetaxnBtoHymEuhGVq7xWCsNptQIg7RpmojyE7GWtqxZLOVuN10sqKqKdVmilKJIU4b9HoNhnzRLsElU+zaCz/Be4dqGXi+Oz1wrIrlGAEedx0W3zTJWpjppmtK2J5obwEbIBSLLsqm59uJLUtKXDatyLQgBJVspYwxNIxgU4XkIdTwEt6FkC7JUtCJmsym3bt2KTVYp3zvhoLquydIUJ5AMdOsRZVJJGE1dA55EK+qmEoMmYDGbx/6OYW/vBYqih7bSjLx//yEXLlwgsRnvvXuDg4MDXHRJCyJ9RJ7nDIdjBqM+SfR30daSaEuaJxT9bXQCy9WCVbU8aQ76EPUzZe2u8dGfVOD469WK46MZ09mKdVXT74k7nTYWOi5H9Bmx1tA04mOzwd5Ixt9MMeTCT0AJa9prxc7F84yePmExX1L0B8JncZ7ZwRGZMpu/6Ql50vx+QaDnEKckWchBreuK3W0Zgfb7/Y2GQPeH7S7WTgF6Z2eHC1Fbc7Va8dprr3Hp0iXquub+vTt885vf5HD/KePhCGVESSlPU3QUI2m8i0zGIFiMzZTEkD8jwNJRpZ0L1K4V/89ITlqvZS/flYjdflPUoEQbwlrZSigdhCKvDar1BMxmTNZpIGAsHmgDDHo90pgwkth0xTkMCnyLRtwQVHD4piVY+VqtV5zb3eHqlcsCP370RMhKSncYJWGCzmY8ePCA4+Njzp07FyHJbiPL38Ggj4+Pefe9G4zGAyajEUUvQ6lAXTeU1Uo0QhBqvlcKvSnHHVVscIboZxKiifB8PseYhK2tLba3dlEYnAs8frzPu+++y5/+ya/xznvvc+feXRSasqowJmEw6LOqViRpHh3Ox6RFRsDR1JLcdWLIi4KRHzEcD5gtZDuXJekG8OeegX57RKVrMV8xn62Yz9esypqAwXmNiSNU59loTwQNrWvo9D67y9g7Q3Ceupam6GKxIC1yBrYXldhgNBmze/4cq2g+rQKkNmG1XLLI8xNN1Gdg9y4mjecZpyJZhBAo0pTgat544w0uXTiP8yKKamJzbjqdcnR0JGpQVcNgMMDcfJ97D+5vtBm//vWvszWeUNVr2krwFxrFermkidZ15Wq9YRoaa0isgLvE4FZMcNtWmJodCKnD6HuvqGMFkmUZw0GKjvTusFxiioK6rmJlII+AF40WHFonwmnRkFgoYpXknKNxFVnZYJOENC/wIdDv9ymKAqWCEOTGI+mpGCIwq0UpkRTsxGGccwIqq1tefeU63sNysebp4ZHIByaWtnVoa1islrz51lucO3eO3d1ttre3N0phSolgzfHxMb/8y/+A3/3d3+VrX/sab7zxBqPRSJJ3W21GpY1Gpj51hDbjqcsSg2LVNNSVYBjKsqStW9ERvfuEn/jxf5rz5y9SljU33nuXt99+mxf2rvCtb3+HmzdvQlAsVwvSNN/8bbK8x2Syxfb2LqOtAf1+D5RnNp+T5z3wgbxIGY0vUQwyJlsD7ty5wxe/+EX6RY+mEjOjuqwwGO7ff8xstmC1rHDBoEhQWtzQ61qOsZg6C2JWJyJkNJ9P6eU5O7tb9PIC3wah4R9OOXx6IF4rZcVqtZItCJ68KKjbmot7e9g04/GDx6RZ4KUrl3n/HUEgd0C3Xq8X8So1WZJ+AH7/POJUJAulNKuyISv6DId9alfG7rzHe81wMJG7eVWCgl5/RJrlZEHTN9Jkc85RGMPB40eb6iNEsFcwsA4Ny0pk3vq6R6hbkqDoF+JuReuwKJGlizoEVVPH9SkcgUIZepne0KDLugJXolVLkUuFgIueHo3cRY3SUpp6KaCNFUEeAUs5cGBIUFgSI9sRrVpCWJMpwyjPaXCMhj3SzLKuGoKHJOvhgkU5sf9LjCX4BhMc7bwG3xJaj3Et2tXQVihtCQSRAQyaIu/hasfB/lMO9g+5dhVIgLgfb9o1jx7f4cbbb7IuZwwGBdp46nqFUYrlciF3uyDH3weHTQ0hCAI2zQeYpMGaQGsrCIq6FoIWynPh0oTBMMP5igcPHvLgwQO0SXj55Vf5h7/8qxAS4ZHYaBBUN3jVkPeETDjoj+j3hiSJoGrTZEVVzuL2TASUiyxhb2+Pb966y717d7h27RVWZcV0UeJaw9HRlEeHi4jIFGCdUoEmOBwO72s0hswkJEZG9iYo8FAoRa41k17OaDyQREuOYsXBTAyW+v0+Rid4p9DBkuuAdjAseqgtj1vWPHr0BKOiSJIPtOuKBGnAqqDRsepSH5iIxKbqppn8x9/XOBXJops2nDt3DmP1RhOi82tQSuTuu+lC3u8J8zSJalQhZb1cyF3XGpJOi7LrP/BB75HO7DaLcnvOOXE6X683gijGGAqdo8yJyE3aQaDNCcLRx/U7J9RnAGXN5nc+O0np/k1HmAsKH124g9cb4pyJAsR5LqV2G5pNn0BEgS3rdRn5DydkuBBChEO3m3Jba70BXbU+cjYC0ahJY6Lu6NOnT5nNZhSFSO/lec5sNuPNN9/k7t27G+xKkiRysUdzIvndojUhbm7mA59XeisGk/RZzJeEIGPMqqnZ3t7ekPZu377NgwcPeONLPxZFY+S1eZ5uyvFGNZtRZFdJZbkocmkTmC7CZusoAkORsAes1xVPnx4yHG4RvGK1WlOWNcfTuWwv4t+ps4LoJlDeNSiVkxorep4BtAqkqcWogjzLyLOUPM1IrcE1A1aLJU0j4+bpdCr+qwcHmFT0Qq5evcpoNKJtZDu2XC4Z9sdRsIcTThEflNZ73nEqkgVEebyLF4HOK6QWWz1CVIcStGVa5AwGkizqusK2rYwelcYFcf+u18JJICaaJJZwdVtFGzw2dOWjg4MN47RDMGZZRhEBR2IpJ388SweMibgFnmHMGo1FEyKoqEtyHdVY2TgS8PJ5pHehyTI5uRfzNctyzXAwZjKZiNy9SphMxnjlyWOf4ESAh9iobDaQ7a5PALAql2A0o/GAvct7rOuG/YMjBJuuZRSoNb2I4pzNZszmx7xw+RJlKUnvyZMn3Lhxg7ZtOb8jPY22bUWotl9sSF/elfi289pQYGRy0FHq5fjWmx6BMtCsGvYu7QlzNorybG9vc/nyZW7cuHEi918UKKUkkce7aJIa0jQhyxPyPCXLUrSRflHp1qh4wSmlsCYlSxVZVnDwdArhNkmSslyuqUrHarVmg3KHTUXbHed+0aOXp2S5FUXuuqbFkWjF7s4k2hIWZInCe0Ovn9MfiGhx0zTMpguWi+gvYhJQnqOjKdvb2zjnePzgIet1w2gwEcBgs6JtkxOYt4YQPgi/f15xKpKFAnbPbTMajaKyUxWVqPvxpIOsKEhnc0aTMaPxWBpAqZCrOpMYm0hjqG7KKJUvd7zGtZvRYNu2aHdCYW6qOl5AJ+KySimyJEHHJpPxXkBaWkBL3oshjSSMsPFf1daSJwlNEx3DlDxE81KduHTT3TH0BhfSNA1+taLIpU8hTc+WrJeRZIJPUNZgvINw4kLWlHEL8AzfJShPG1o0CeOtLa6iWDcNtQ9M56uNA5lSIsufZXJyz2YzGUlH0Za33nqLx4/32d7e5trVlzdToPV6TWYTbNKBkSzWgtYiOYdWhCD8kE7FejqdMlvNN1VBVa3Z3t5msVhw48YNUJ4vfvEL1HXJrVu3cK4hLVLyviQot3YErVDWkCRWcDCJbBuMVSgjautVVUEI0RxJ0zSCtN3ZPs+7h+9z//4jesUA78E5T9t4lEowRkiMzQbKT+QOlTRJQmJlVJ1khiTNyBLL1lgmXWmaRmPqQJGKDUUHMqvLBhcaXCtTl7zf4/Bgxmol/ZyyrDfbizS1VHWgdTVNYz9wY/jIZBH0h4hb//HE6UgWWrO3t0eepzTNktVqxuXLl7l48aJ4SqBwbeDp4SFJlpFmcfS1EiCUtQnWCeW7wVO2YuDTlOLwBR8s51IjuhCJMZg835TwJs63N2IoEWrbwAk1vmPH6pgM4niraVrSeAHXtXBJOhNep1q8ESyJjSCrzoKRCLxJ05SglTQAW9G5UEaTFSn9fkHez0miqLBrT/wwxM4wnkgqGi3jyIpc9DuKhG2zw9WmIc36/N533sIHFcFSonbdbVU6ST1jDPfu3eOtt95Ca83Vl1/h+vXrsRsvlUkIgeCjUM5mi6VonZcqI6JjveuquDo2ZxUdDLooCm7fusuTJ4/Z23uBfr/P2+/cYFUuSfKUwaDPYNCPVUWIbF/ZntrMbmwh0dEESgdR8m715sZgVYo1GXk2wjstTeyQkGc9jDbUwZOmiUD6o+hyh7uRzwjB12QmZzAoKPKEvLAkRmO0mB8pRBLAaElSG+3XVmD+zku1aYyOidXia+mJKNVtqRLSzKJXsrVrXS0WEsAJyI2P+PenE6ciWVhr2d3dxVrFfLZktVqRZpbxZIiNbuPaGIKNwixaSze+rNBGKMFlhDCvViuBE8e9vNKB0WgUxVnk/f0kO+k5NC2hbaOLlcJGbH63b9UaUqXFQV2r2MgL6OCf6UOoCEM3seegEMJbTU2gKNINdFcrtQFIdRBhHY132h8AiCW9lDRY0jwVJGsQb4+6ESanjYhWImhno91oFc61tM7RtC1JnnHuwnmwGe/cvM1sugDAeU9Zy9asKPr0ix6LxYymcdy5c4fFYsGVK1e4fv06W+MJy/kUa9Ko15lho9N504jgbGgDTdOiCVL+W8/RckpVVRsVqqaRinFvb4/pVPAbg8GAqy+/zGq14O7du6xWC7Z2z7G1O2E8HhMOZZunvIw5k7j9sNZEpitxQiRYFO+IzuctaV6QZQXBa6zJ8G7Nai3ubYnNCDSgjMC0Y3Q9A6UDO1sTRqMRO9tjRqMBvdyitMe1wjJt2xrXCkxcawvBowgMBgPqupXKBbGGDF7Rlh6diYNeB0oDyIp8wwvpFNIwp2P70cWpSBZpmnLv3j2sVRQ5vHL9Gi9fv85oNOLJkydUTUue9RC8SiDLE2ymSJJdHjx4wK3bt5lOj/DeU/QK9i6cYzKZbA50mpgNz0NrTWhamrJivV6LhVxQBO2xWmNymdNjBNYLYXMiuUhB1kpho6qSpgPiQLUusdpwfntHsP6jXIRrEKSld45gLVZLMiIqb6VpjvOB4B1lBz1OLUE5jBUwl/fSl0hSSXrLhcCyu5l87VpWTYWuEwrVkPUzaB2z9RxVl+TFkJ3dXa5eu8bv/M63UZGNOpvN2N/f5/r1lyXJNi2z2ZwLFy7wM//av7ERHFqv1/TzAoITgWGTQPBUZROPR4YyUFeiHWKMJUmiU1tUXe8UvLa3t9ne3eHv/eIvc+WlF3n55ZeZLRf82q//OqtyTX884MWrL3Du3Dl0krIslwQd8EpIW8YG8jwjLyw2NRgbm6gmQWFo64q016NatswOnqKU5snjY4p8TNvXTOdz1rbFDgusSsEDAgAAIABJREFUFS0OEZwpcd6Bakmsot8fcOncLpPJmK3tIVlqaNo1bVNCaFChwrdRqNdmItSUZLx2/SqvfflLfOO3v8WNG+8yn60IQeNbaJrOYjOh18+jWpamKAqG4z6rldwspXdSS4Xju6r4DO5NZ2BbVSv+uX/2T/Hqa9cYTSb44BgMBoTlamMU05nVuuDZ3z9i/+AJq9WC4WS8kZNPenKXTpJE5uJRe9NElWibpmhr8ApyJz4ddTTnab3DxfQgU5jIISCQG5kElGW1wex3k4jOo9MYQ1vV5EkqQidW+hJKE4FdDqPixMecKG851xIIopvRttRRfTtJDUUuoihSnQj0eI1sr7z30gCOZDibJrQ4JuMhuiwptGW1rsl7BUkqJ2Wn4l2ul5Sl4uhIBGiaRvgbOzs7YiKdi1jMcrkkaRP0cEBwDaaDIUcZuKYuI5dEnMGc6zgy9Qa6DHK3d07wGzdv38IkCZ/73OdovON73/8+i9UShzRFd3a3GW1NNspXxipCFftJWUp/UEhV5QPBR6MfZdFojMmoljVP51OWi5JqLaZD1ib0en3KstoopnWWlc7JxEkwIrIlyFMR7qnqNTAUTpBvcG3LajUHX8cmbo7Wmslki0sXL7O1tcM6SXn1tTnHxzPK9X2qytE0tUz8jKasFsxmM7IsYTCcYK1YCnQgPa1Pts2dQtvzjlOTLLpm2N7eHi+++CKzxYKn+/uMhmPq1kUVphKPkJ2ePn3K4dGUoijY2t2hrmuOpscbtGe/X5zAgJU4WG1YnB60tZgsJXcFnoBp7cZKIDFGphqd0pTVMsb2Po62XEwa5Qck0FAiWBK0SN9txnG+xXAyAvSCA8R+yEhM6Tg+DZ4mNBv3tU4IRSY8etMo7C5E531stsq0Je/n0YbQomzKcDJmuRCUqHMNWgtZrK5rlss5B3Eq1DSOJDNkaUGSpniPbDl0Ql0taUqFrytC8BCbtt4YlHe4bjIUE5t3UNct3oOKIrsd9d8Yy+UXX6RuHe+89w6Hh4dkmfRgBqM+/eGQLEs3MPxnLxabnGy7tDZYbfHesTXeIkv6PLz3kJv37rD/6JC6dliTkoSkG2bLtiXeqbu/pXcOnVrGo2iU3TYbiYPRaMRisWA8HFBVa7zr+jaKNM3Jsx7j7S3Onb/AzoVdxqMJYd1y8fwFXnrxMovZgv0nR9gs4UtfeoPhqM+TJw94/+a7UTzaMBgMwMhovBt7e9+JH8FpELU7FckCiCV1nAzUjnK1IrMpd+/e5eHDx0IWSkQPoWpq9vf32d45x2g0oigK3r19U8q7XsFwPBSti84LI8jJ4X2LD54QkOmB0ZgsJcVhfSIz8zyXC7NtNhWF+FNI81ArpCopPyh91nrZq4qlYbSng9joq7BBqpVuP9ypaHUjsrquCc94jPrWYVIRgrVKy/pb6ZcohdCgI31+05+JzVmnPUWvJy5X2pIniqzIOTxacHB0QOMdNtjIiZC77OPHD6kjjF4rwTAobfG+3YgJEWHlXkmDEgyI899Gko8f2PsLu9SglcEmKVpbHtx/xM33b/OFL/84i9WSW3fuMF8u6A172FQg4OPJkMRmEUrvPoBX6TQzO/k/sZV0YtNQlTx5fMDDe09Yr0sMBp1qVDRFFrFcoekvFzPSLOOlFy9LBYNsEXSAxknD8srVq2iteP3VV/jSl36E3/hHv8pv/9ZvMhjmWKMZFEO2d3a4cuUK2zvnKIqCLM+x7Zrz53e5fv0689mS5XLNcrGmVyRcu3aF4SjjeHpA9Xi98W3pxKLlhnTSg+qIgM87TkWy6GT/29ZvaMwHh/vUdc3tmzf57W/+Lt57LlzcI+/3GI+HpDZhPBqQ51Lu19V6Qy/XWkyDhRQlCM0QROQXkK1G8DR4gtUYb7FKkRUFWZoJRLsxuLqhbRraELveQaoNZUVNOlhNMBZlWkLwsq3QKuohxOan8pv+RwgBHx+dY5YxBh/AWoePiFMAbRw2yr8bpUXmTSe0vkUFTS/LN+C1sq6gVPRcXyqWVOz4oosvRosU/v7+Pvfv32cwGNDLUlzbsFg0hOBYLOc8frQvFV7bRv9O8T9Jk4yyLDfHVtYsZLEQxKHeiW/k5uTegMSaNmp+VqRpjsKwv3/AdDqnKhvu3nsgXJ+4lRoMBmyf26bX623gzc+qdsm2RraVVll00BgStLYcHO5z9+5Dnjw8iNMpqYyaqmWUa7LU0lrNoFcIbb4uKYosaqVkBN9idWA8HFFkgkL98lf+KZbLOcPRCJv2+Pznvsiv/eqv8/T2Q169fpVef8TlK1fZe2GPJJOktVwvEQnAlO3tCXsvXGR/f5/1esmDh3e4fOUCk8mQF1/aI8nkMzfRL0cMuDUhNHSCyX9ghE+n6jgVyYIInkkSvRkldV4Pw+EQ37QczeY4F7hw8SIXzu0wHo/p5QVBIVLxqvO7kImBtRqTaLQVYo8OgWAEPutoaYLHxRMwWEEymjwVQJEWqbmyLHErJyhJpWhdC8QL3wgEvHEtq1q6/R6ovZPqA42NCSLJUrQRVGcn9huA1nk6CpKWGdwHRrxaiVu78tIwtCbgGidoSd/5qipcLSO/tMjpjwakhZXf1YnNmoT5csmDR4+YLua8tPcSF3Z3qMo1Vb2kqgVpeOPGDb7y1R8nYFHKkkYh3i5BuEamDp0wb8csDU6SaYiK423b4lq36essl2vKdU2SpUznC44OZ2xNdnn3/fe4dfcOrXMoIypR5y5eYHd3VzAHVfMBdKpGkrBWJyhbsQBMWK1Lvv/muzx+vM9iscaQUJUlzglTNs8t3jfgo3m2UTilKIpMPpPRZEmfLBnzyrVr7O5uc/vmLQ6OpgyGvWhgNOPCpSu8/vkf4Vd+9R9S9EYMhltMts7hlKGO/KOuX9a2LWlm2NnZ4uKlXY6OD1gsjzg63ufll6/y+uuvcuHSecq1MKCztOsndXq0zwhDP/+WxelIFiEEFosF5y9IEqiqCmtSUaoOovmYP3nK06NDfFRvqssKMxFil2trGXNGFF9n6HKCPwhR1VseHf6haqOhS8QKeCBYhbUJibFiT2gVbS3NRiIzVfuAahowmlYF6uBIg8IpucN28HQd1b3SbrTZVQ7mxDu0GyuGuE159q5sdULQTsatSqYvrRYxINe2G2CWrsVuL89z+sMBzjbUrawvIBfX0dERT5482ZCTRqMRvQu7BCru3L7Fo0cPyEyPe3cfcNEJSrXwYLOUoE1kkp5oQpyMfzVtewJi6rZZ3cM7sDYlzw1lXXHn9l1mswXXrr/Cm+/fYj6fkxUpWZoz2dlmb29PRt1J8oFk0Y2eVTQD9a0TzoYtUEEzPZxz/95j5vMlrvY0dUtVNWRJSi8vMFpRlRWtdyQGhsMe29vbfO4LnydPM1brBThPuV4ynR4x6GV413Dz5m0uXjwvOBuTEILipauvUnzjd8mLMTbts1xXzFZLUJ7t7Ylgg4KOzU/L1vaICxfO8fD+XeaLYw6P9nnJ7zHZGtIb9Dg6Omb/IPrERETvyfSjuwl+Shfjx8SpSBZpmvK1r/0zfPkrb3Dp4hjwXLhwgdVySVs7zu2cZzQYs3Uk0vO+8TRlxb07t1FGVKoSLfP7wWhIXhQkaRJHfIamlhO3rWvquqZshO5etw1JlqJ0pFdrAYh5rXDak/V7DCZjCEJhxsn4cr1qSKdzgrF4a8n6ItJbxN8HHqxCJRYdTZJCUOi63twRg5XXplEqsJutd5wSrTV1WUricwGHwypNnuQoHFW9YjAYsG5rlvVKRpORoWhzy6osyfMedeMo64p333+P926+T1VVXHz1Ar1+wd7FC/zIG5/n9q33+P5b3+W7336Pr3/96/zYV77C66+/zoWLewwnYzmJjcZEj7y2bQm+RhNIjN4oUXnnCDgSY8D6DRx9PB7z8PE+t27e5uDgiJdeusbWZIfF6i0mWzvoFF577TovvniFre0xo8kIgoCjqqqKsn0nKuPdxaSjC9xyUfLk8SGpyRn1LauwxKiE1GZMp0esF0usHrG1tcXe3h5JmjKdznnp5Wt89atf5caNG9x+/xhrDKF1vPmdb/Po/j36/R4P9mv6AxEverJ/xHrdoEzBtVc+z7p0PH5yyN2HD3j99VdBOd69+S6vf/51dibn4rjb0evlXN67wOHTF/jGN/8xN96B7Z0Bo/EWzsPBwRGLVUWaZ+JeVqQbt3u54floa3imZ8Fg2Oerf+oNzu1u07YNratRKsMmCUWvhzaQZpbMGoo0QQdFs25Y+nKjTaiDJtOavE0ofEpoDSpJhOxkpDFYa0VtoKWlCQ0i0+JIbRrdvxJMHHOqJNBQ0bhK6Oa5RiFq301T0mSBJvE462iN4C+8sYwGkfwWvTiddygtVYCxot5UeXHoxCoa4zEWahfwKoAHZS0aCwFUZvEKmqp6hrwWKN2adStmw3mSk6gUWyfYKkV50ZS0yuK1YTafcbB/RLlao3ygXxQMJ0O0lQro8kvXaFrPo8dH3Lt/i16ekmropSlWBcxoiEoSSFUkWzUYrchtInD6RvpNxmjSrKBpHG0jqFWdJazWFdP5jMNjMWw6f+k87793i3K9IM9ge7RNmjj6PU2vn2ANrFctCkuaFrhgaJzDmETczbN+VBRzWO2hrTncf4jRKbVXWNOjqZeEtqKXJphMsdcbcG5rm+3tEct2TeYDx7N7vP19xaWL51mue7QBwnCAbTKOyxkZFjvYYrZ2JHnKrVuPWUzfYX48ZTAYcFhX1M7iA1S1YjKe4KqHPLq1z+RHBwRVkSYO5R2DQcr58xPZli3WPHj0FG9Ej7QzsCoSTZJ6khRcWBEQAJ8IRut4IzrxdPm0i41TkSwSm2waWoPBAOcbUQ6aLZ4Rc3UbLIPWJ2rbz5a+3QgMEDcnOvWiIGNPRP4sOL+Ro0ttQhq3HVaLsrc2gG8BRVACigkqCFwXGUcGBzgfR5viFpamqfhoyDs3DcH1ei4Nyo3xUCKMWWPwdYvqEJvaxFGg3DkTJVsLX9YfKMVD8JjEQl1HglxL4zzzlfiYFkFm9W3borymXK1YzuYE58QAOULFOwUmYwy7u7t85Stf4Rd/8Zd4/PhhFO/JeVVrFqslk8mEPDPgm9iMdjRB9D07rEInCtxVSU0tSfTw8JBbt24xnU65/NJVZrMZ8/l808web4kV4mAwOLElMNLfeXbitNH5hM1ItW1bFsuZcH6MuIx530Ipjm472wN6hWFr0GcwHgkfJi2EXbte0SzXjIs+W8MRy6ZhVZUyJcsNtl+wt3WRtmpZLOa0rsGmFq8Cq2qNzRStbymrZXSuKzBJwny52GCCMIZWSfNy2BvE80HQxkku/BHnfGTXCk1dKRGa9MF16WLTw3iecSqShYrjrK6ZJpexNKbEy1Mg1N0JorWm9iVtZ4LbOoKLjEGj8SEw3t0WOnFEWAYnfiOuaaNOgGh/RndPAfe4gFcuIubChgtitEIHvdFZzI2M7hKTYG1KauRnJsaS5z1sNCJKjNwN2tFASvdW+g/GGLI8Jy16DOyWTC1iGDqymaKpKrIip6xFat5E4JUPsfFlNKpjxjrhk9SuJamhbRqMshibMZ/PmU6nm2NXFMIYLYp8o+qd9wqRsksMh4eHG+ZsmudcunRJqPEU2G68G3sSaWKpFtXG4BlO+CWdGE/bttStCBbt7u7y3rs3efLkCUmaiEZpdDZLi3yzxeiSXYdj2cgdumYDqS+KAt+0zGYzqqrEe9nbaw1FkTEcFAx7FnwlxynKCXrEEaypWvxiTXO8oDqeM69XlFXFeHvChfMXuX7tOs16m5s3b3Kw/5TGyzZr3azBazJj6emCYOB4MeNcvYUyisVCFOYTazcSAsCGMr8qK46PZyR5sVFU68Bv3oFWdtOnUNFHVZ0CHc5TkSw6i3mloHU1bVuTGplIuLbeNAOVOtEkBDn4OE+Is3wC1OuSpTEbh2qbaCyKxgd83dCWFZaTLJ1qQxrv5kZprLKRaxA1M7XGdC5kUchGY9BOeCXtuqJciYJ4rWvqskJlGYmJhr1K0+sNKcsSlYFVMk1J8pyi15PKQfEMIlQSWQB87KU4ZNxKBBOFgND103TzKCN8vSxLmHqUN7RZy3BoWMzmzKczQbA6v0kWvSKnrFYsl0vBfqSWq1evcu/2PabTI27edGS9gjQTWPV41IsEPHDKoeOoujP/baITWVO31FVD7VoOnh7x+PE+0+MZ4/EWTdOwWq1IspS0l21EjYuiiCNDh/dmU2J3VPMO2Zin6YbtCl4g+/M5nkDbNmhtGU8GTMaXOLc7wVVLnjy6x2y1pGhGjHo92SKWNbp0KFdz960bPHz6iFloWBpPpRTpsM/cl1wY9Rn0c9arDK1EfV4dadZVSVUFiiYnywzzcsHdR/dYz+esVzOOj4+ZjMfYyCzOE9ENHQ0nLFZPmM1mYv48GtHrCWGtXK1oW/FTVcoiVHkDQaNUh+J8fknjVCQLgbZC41qyvCAEmQ60rt6Al07EcFoMltRovAevNS7qJmitMWhC61jNhSylBNcIjUO7gGo9CkEYKiUsUKssiU6wRmOjTJ6KO0YVAsoJlNNHBe350TGz4ymL4wXz6YLlbC78jrLFGsOw16ctsk15nnrZGnnv8VGjIUkzQoDFYnmCwfBiBq3DiZ1jBx4LWuEjv6QTb+30PrvtxPx4yvHBIT2lUN7iikBqc9aLJW1Vg9Ib0Bgg0vZemI11LZYCV65cYXZ8zPRYZPTv3LnD9vY2xlr2Lp0D/AYPorzHOUkQbeNoG4d3XYPWRpGdEyGf8fYWR4dTpvMZZVlz/sIug9GQ4XAomqvWih4GbLadoj9yQtp71hlusVhwdHjEar0QNfVxwXi0xe72NlvjEYN+zuH+Q548DqzqioPDQ1DSa1kcHOKnc7RNaTKF8iXjrT42U+yXKw5mxxzMp1wdQC/XKOVofE2jHLqQ8XowjpKKohjQtA13H93HVSXKtTx9+pTxSBTdKicizoPBgPF4zOOnByxmC5raM1xXkrh7AzLbyRtoqS5wMv3ZUNSfb3VxKpJF5GpHTclOZUn2pxv0oA9yF25aQhqJXW0roKm6obA5SYRAq6Boy4oyYv6VDpvtivKBpqlp4jh0lS5ok/aDXXbYVBUdRl+pjj7ecnx0zHK+pCkbjNdYndBUDcEFVvPVprfgnLBWD2dz8jxnuZqjlPipdkIyaWo3I1AZ9/oT4FPXB9goO0f4ePxqjMEoRWotiTYsqzXr5YrhTj8muZPeTJamtBFz0MGYe70cm4q0P8DjRw+YbI25du0a3//eDblrHx1z48YNjFFcv/4i/Twj+IAJDhU8VdOio3Fwl/Da1ouYcdXwne98h4cPHrFz7jzndsXAOs9lejSaDJlMJjIB6PUwUdjYxy2QEO1OhGi686HT3GiahulUDJjbtubSC5d44YXLjEZD2rqkrldUzZoQGnbOnWe5XPL22+/QLNe00yXDAGb3PJNxRlANoTBgLApPVZfM1gvOn58wm2/x4PF9ZvM5rVYUk4yEFI/ohpShBhrWi6k0l1VgenwsxLzaMZ8uROJQJ/T7Q/q9AcezOet1hbIrmjrQlI7RaCTIXC2GVSB8JeDjR6fKfyrArD8wWSilrgB/C7iIEOl/PoTwXyulfg74d4H9+NK/FEL4v+N7/iLw5wAH/AchhF/8uN8RQhCyjhI1KB1HRamVPa3Rcocd9AoZDSaGqlyLcZCxGAsJmtwkWCOApExbfOOomwWrcomP5kBVVVI1ddxjK2zjSZIIPlL2A/gMYwyJ1ZteCrGHkaucKjRYr9EOjDfgIVUJOmh8I6jBxKQYk7I7HnN4eAiIpuR7+7fpFRnnz5/HlTV5llH0LY1rBUgUXPx9htoYiiTDKk2IehPWGHA1aItF088KkpHGNJ5BmmNaBXVLGyrKxRrlPEWWc3h4jFFWiHO1KEtneYrNUgrleeGFF/iNX/t1Ll+6zI/+2Bt859tvMp9PWb2z4OnTR3z+C6/x2vWrdBAAnVh08DK5UCoeRznJF6uSsqzZf/KUrZ1drr58nQcPHvDezVssl0t2zp3jtdde4/yFHSY7Mpr0Sn5OXde0rt4gcjulaw0MBgO0FguIqqrYPzxgWa7oDwa89vlr9Pt9nG9pXI1JHVmuGO+M+Bf++Z9md2uXr/8vf4e//3/9PXazPrWDB3cfcm58nVy3rKsKTMMgNegA0/sPufve96jXK5LMY9tA6Rta1bJqa7CG9XzOwf4TBmlKYgPWB6y2/MZv/AZvv/022+NtvvC5P8GVvcusVw2vXHuF+bJkubrJdL6gcWDVilXeI7OFKLWlnsTmKGoIdgP3/gCZrBO8+ZSEb+CTVRYt8J+EEH5HKTUEvqmU+qX4f/9VCOG/ePbFSqkvAD8D/AlgD/h/lFKvhRAcHxHS1a7pTGs6ll3H7y/yHrP5lDzPqUvpD0iJKvgKEk2aJHHMFEijmZD2IZoJicHNarGkXC1pkSqlyAoSI4YzOhiKKITjvd8I4XQTjW4/Lc2EyBtpHHXZsF6Ke3eW5BiTxGpAjGtEUbwiMSm9XspyLXobi/mKprzLqDdgPOwzzDK0F2i3IsTmFuBDFMyR3k7rIhLDC1pSB3HHCo1YA5SLJb1Rb9OfmB9PKbKCfl5wEI6AyE+pRcW7a0I2jSLNBT7+6NEjdnfPsffCRW7fuisTh8UC76UCa+tqAxRzMQnLxEL2NyI4JEIzFy/ucXHvEuuyZDqfsVjMUCaR6qrfo+j3RROjrVGGE7yJc2Jw3GmJGjkvOmm+5XJJHdmjAJOdCb1RgdIQygabAIgSN4j5cj/vc/Wll5lMtjh4/ISgc4w10hTOE0pfk2DJewNG1oJK+N5b36VsGx5PD1mowGG9kvF73PplRUKWakLE0GQ6QUXW7Wy64Ee+8CNsbW2hMPR6Cb3egPF4izx/zHJVgfO03d/ERTyPXAVobTHRRe95K3vDJ0gWIYSHwMP4/Vwp9T3ghY95y08DfzuEUAE3lVLvAl8F/tHH/Z6PEiXdcD0w+Lg16Lr6yjtQYSNTp7sx07PvF8rCiWtUkKmC0VpOrNARxcTIVyslDaVOp8ILcatrOsrP1Oig5GfKM5v+QQfX7SDriU25sneJF154gdbA06dPODo64s6tm9x6/ybr6Zx2NWLSExJVqg3aCq+jbVz87LKWxgeZ2oRAnqa0HnKbEJoWozQmxDXHNYlP6wlDtRO5fVZMV9YsIjLlasF4POboaErTNOSpjDFnsxlZT6jz3YWslcJp8Wft+iday+m0XEqj9enTp1SNAOEOD4+YTqfoRJL/s4pkQBQUOrl7ynrDyXFMEnBseljEnlOSJBSFTBW0Bq09QYu/qwonif7Rg4e8cu06u7u7XLi4h1+3WOdZr9Zk/R6TCyO2e5p14pk3NQ8fH3A8XbIebGN6GT60JHlKohMaJdwiH5w0vU2E77ctlQblRCphPByyNd6mn/di8hMNkmFP/GqXqzUuuqx16mhFUfD7exPdv59vwlB/GJ68Uuoq8CvAF4H/GPi3gRnwDaT6OFJK/bfAb4YQ/sf4nr8O/N0Qwv/6Az/rzwN/Pv7zdeAAePpH+CyfZuzy2VkrfLbW+1laK3y21vt6CGH4T/rmT9zgVEoNgP8N+I9CCDOl1F8D/gpyw/0rwF8F/h0+HDny+zJSCOHngZ9/5ud/I4TwJ/9wy38+8VlaK3y21vtZWit8ttarlPrGH+X9n6iFqpRKkETxP4UQ/neAEMLjEIILIXjgv0e2GgD3gCvPvP0y8OCPssizOIuzeP7xByYLJRvcvw58L4TwXz7z/KVnXvavAt+N3/8C8DNKqUwpdQ14FfjHP7wln8VZnMXziE+yDflJ4N8EvqOU+lZ87i8B/7pS6keRLcYt4N8DCCG8qZT6O8BbyCTlL3zcJOSZ+Pk/+CWnJj5La4XP1no/S2uFz9Z6/0hr/UM1OM/iLM7i/7/x/NkpZ3EWZ/GZiOeeLJRS/7JS6m2l1LtKqZ993uv5sFBK3VJKfUcp9a2uo6yU2lZK/ZJS6p34des5re1vKKWeKKW++8xzH7o2JfHfxGP9baXUl0/Jen9OKXU/Ht9vKaV+6pn/+4txvW8rpf6lT3mtV5RS/0Ap9T2l1JtKqf8wPn/qju/HrPWHd2yfVRD+tB+AAd4DXgZS4PeALzzPNX3EOm8Buz/w3H8O/Gz8/meB/+w5re1rwJeB7/5BawN+Cvi7yHj7J4DfOiXr/TngP/2Q134hnhMZcC2eK+ZTXOsl4Mvx+yFwI67p1B3fj1nrD+3YPu/K4qvAuyGE90MINfC3EQToZyF+Gvib8fu/Cfwrz2MRIYRfAQ5/4OmPWttPA38rSPwmMPmBqdYfe3zEej8qNmjgEMJNoEMDfyoRQngYQvid+P0c6NDLp+74fsxaPyr+0Mf2eSeLF4C7z/z7Hh//AZ9XBODvK6W+GZGnABeCQOGJX88/t9X9/viotZ3m4/3vx9L9bzyzpTs1643o5R8DfotTfnx/YK3wQzq2zztZfCK05ymInwwhfBn4M8BfUEp97Xkv6J8wTuvx/mvAK8CPIjykvxqfPxXr/UH08se99EOe+1TX+yFr/aEd2+edLD4TaM8QwoP49QnwfyDl2uOuxIxfnzy/Ff6++Ki1ncrjHU4xGvjD0Muc0uP7x420ft7J4reBV5VS15RSKUJt/4XnvKYPhFKqr4Saj1KqD/yLCFr1F4A/G1/2Z4H/8/ms8EPjo9b2C8C/Fbv2PwFMu3L6ecZpRQN/FHqZU3h8PxWk9afVrf2YLu5PIZ3b94C//LzX8yHrexnpGv8e8Ga3RmAH+H+Bd+LX7ee0vv8ZKS8b5G7x5z5qbUjp+d/FY/0d4E+ekvX+D3E9344n8aVnXv+X43rfBv7Mp7zWP42U5t8GvhUfP3Uaj+/HrPWHdmzPEJxncRZn8YnieW9DzuIszuIzEmfJ4izO4iw+UZwli7M4i7P4RHGWLM4joBm1AAAAMUlEQVTiLM7iE8VZsjiLsziLTxRnyeIszuIsPlGcJYuzOIuz+ERxlizO4izO4hPF/we3OBIyHE9wpwAAAABJRU5ErkJggg==
- "
- >
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <p>Before using any of the face detectors, it is standard procedure to convert the images to grayscale. The <code>detectMultiScale</code> function executes the classifier stored in <code>face_cascade</code> and takes the grayscale image as a parameter.</p>
- <p>In the above code, <code>faces</code> is a numpy array of detected faces, where each row corresponds to a detected face. Each detected face is a 1D array with four entries that specifies the bounding box of the detected face. The first two entries in the array (extracted in the above code as <code>x</code> and <code>y</code>) specify the horizontal and vertical positions of the top left corner of the bounding box. The last two entries in the array (extracted here as <code>w</code> and <code>h</code>) specify the width and height of the box.</p>
- <h3 id="Write-a-Human-Face-Detector">Write a Human Face Detector<a class="anchor-link" href="#Write-a-Human-Face-Detector">¶</a></h3><p>We can use this procedure to write a function that returns <code>True</code> if a human face is detected in an image and <code>False</code> otherwise. This function, aptly named <code>face_detector</code>, takes a string-valued file path to an image as input and appears in the code block below.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [61]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Returns "True" if face is detected in image stored at img_path</span>
- <span class="k">def</span> <span class="nf">face_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="n">img</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">img_path</span><span class="p">)</span>
- <span class="n">gray</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_BGR2GRAY</span><span class="p">)</span>
- <span class="n">faces</span> <span class="o">=</span> <span class="n">face_cascade</span><span class="o">.</span><span class="n">detectMultiScale</span><span class="p">(</span><span class="n">gray</span><span class="p">)</span>
- <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">faces</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Assess-the-Human-Face-Detector">(IMPLEMENTATION) Assess the Human Face Detector<a class="anchor-link" href="#(IMPLEMENTATION)-Assess-the-Human-Face-Detector">¶</a></h3><p><strong>Question 1:</strong> Use the code cell below to test the performance of the <code>face_detector</code> function.</p>
- <ul>
- <li>What percentage of the first 100 images in <code>human_files</code> have a detected human face? </li>
- <li>What percentage of the first 100 images in <code>dog_files</code> have a detected human face? </li>
- </ul>
- <p>Ideally, we would like 100% of human images with a detected face and 0% of dog images with a detected face. You will see that our algorithm falls short of this goal, but still gives acceptable performance. We extract the file paths for the first 100 images from each of the datasets and store them in the numpy arrays <code>human_files_short</code> and <code>dog_files_short</code>.</p>
- <p><strong>Answer:</strong></p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [62]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">human_files_short</span> <span class="o">=</span> <span class="n">human_files</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span>
- <span class="n">dog_files_short</span> <span class="o">=</span> <span class="n">train_files</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span>
- <span class="c1"># Do NOT modify the code above this line.</span>
- <span class="c1">## TODO: Test the performance of the face_detector algorithm </span>
- <span class="c1">## on the images in human_files_short and dog_files_short.</span>
- <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
- <span class="k">for</span> <span class="n">img_path</span> <span class="ow">in</span> <span class="n">human_files_short</span><span class="p">:</span>
- <span class="k">if</span> <span class="n">face_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
- <span class="n">human_face_percentage</span> <span class="o">=</span> <span class="mi">100</span><span class="o">*</span><span class="n">count</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">human_files_short</span><span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Faces detected in human files: </span><span class="si">{}</span><span class="s1">%'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">human_face_percentage</span><span class="p">))</span>
- <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
- <span class="k">for</span> <span class="n">img_path</span> <span class="ow">in</span> <span class="n">dog_files_short</span><span class="p">:</span>
- <span class="k">if</span> <span class="n">face_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
- <span class="n">dog_face_percentage</span> <span class="o">=</span> <span class="mi">100</span><span class="o">*</span><span class="n">count</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">dog_files_short</span><span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Faces detected in dog files: </span><span class="si">{}</span><span class="s1">%'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">dog_face_percentage</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Faces detected in human files: 100.0%
- Faces detected in dog files: 11.0%
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <p><strong>Question 2:</strong> This algorithmic choice necessitates that we communicate to the user that we accept human images only when they provide a clear view of a face (otherwise, we risk having unneccessarily frustrated users!). In your opinion, is this a reasonable expectation to pose on the user? If not, can you think of a way to detect humans in images that does not necessitate an image with a clearly presented face?</p>
- <p><strong>Answer:</strong></p>
- <p>We suggest the face detector from OpenCV as a potential way to detect human images in your algorithm, but you are free to explore other approaches, especially approaches that make use of deep learning :). Please use the code cell below to design and test your own face detection algorithm. If you decide to pursue this <em>optional</em> task, report performance on each of the datasets.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [63]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## (Optional) TODO: Report the performance of another </span>
- <span class="c1">## face detection algorithm on the LFW dataset</span>
- <span class="c1">### Feel free to use as many code cells as needed.</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step2'></a></p>
- <h2 id="Step-2:-Detect-Dogs">Step 2: Detect Dogs<a class="anchor-link" href="#Step-2:-Detect-Dogs">¶</a></h2><p>In this section, we use a pre-trained <a href="http://ethereon.github.io/netscope/#/gist/db945b393d40bfa26006">ResNet-50</a> model to detect dogs in images. Our first line of code downloads the ResNet-50 model, along with weights that have been trained on <a href="http://www.image-net.org/">ImageNet</a>, a very large, very popular dataset used for image classification and other vision tasks. ImageNet contains over 10 million URLs, each linking to an image containing an object from one of <a href="https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a">1000 categories</a>. Given an image, this pre-trained ResNet-50 model returns a prediction (derived from the available categories in ImageNet) for the object that is contained in the image.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [65]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.applications.resnet50</span> <span class="k">import</span> <span class="n">ResNet50</span>
- <span class="c1"># Define ResNet50 model</span>
- <span class="n">ResNet50_model</span> <span class="o">=</span> <span class="n">ResNet50</span><span class="p">(</span><span class="n">weights</span><span class="o">=</span><span class="s1">'imagenet'</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Pre-process-the-Data">Pre-process the Data<a class="anchor-link" href="#Pre-process-the-Data">¶</a></h3><p>When using TensorFlow as backend, Keras CNNs require a 4D array (which we'll also refer to as a 4D tensor) as input, with shape</p>
- <p>$$
- (\text{nb_samples}, \text{rows}, \text{columns}, \text{channels}),
- $$</p>
- <p>where <code>nb_samples</code> corresponds to the total number of images (or samples), and <code>rows</code>, <code>columns</code>, and <code>channels</code> correspond to the number of rows, columns, and channels for each image, respectively.</p>
- <p>The <code>path_to_tensor</code> function below takes a string-valued file path to a color image as input and returns a 4D tensor suitable for supplying to a Keras CNN. The function first loads the image and resizes it to a square image that is $224 \times 224$ pixels. Next, the image is converted to an array, which is then resized to a 4D tensor. In this case, since we are working with color images, each image has three channels. Likewise, since we are processing a single image (or sample), the returned tensor will always have shape</p>
- <p>$$
- (1, 224, 224, 3).
- $$</p>
- <p>The <code>paths_to_tensor</code> function takes a numpy array of string-valued image paths as input and returns a 4D tensor with shape</p>
- <p>$$
- (\text{nb_samples}, 224, 224, 3).
- $$</p>
- <p>Here, <code>nb_samples</code> is the number of samples, or number of images, in the supplied array of image paths. It is best to think of <code>nb_samples</code> as the number of 3D tensors (where each 3D tensor corresponds to a different image) in your dataset!</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [66]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.preprocessing</span> <span class="k">import</span> <span class="n">image</span>
- <span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
- <span class="k">def</span> <span class="nf">path_to_tensor</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="c1"># Loads RGB image as PIL.Image.Image type</span>
- <span class="n">img</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">load_img</span><span class="p">(</span><span class="n">img_path</span><span class="p">,</span> <span class="n">target_size</span><span class="o">=</span><span class="p">(</span><span class="mi">224</span><span class="p">,</span> <span class="mi">224</span><span class="p">))</span>
- <span class="c1"># Convert PIL.Image.Image type to 3D tensor with shape (224, 224, 3)</span>
- <span class="n">x</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">img_to_array</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
- <span class="c1"># Convert 3D tensor to 4D tensor with shape (1, 224, 224, 3) and return 4D tensor</span>
- <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
- <span class="k">def</span> <span class="nf">paths_to_tensor</span><span class="p">(</span><span class="n">img_paths</span><span class="p">):</span>
- <span class="n">list_of_tensors</span> <span class="o">=</span> <span class="p">[</span><span class="n">path_to_tensor</span><span class="p">(</span><span class="n">img_path</span><span class="p">)</span> <span class="k">for</span> <span class="n">img_path</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">img_paths</span><span class="p">)]</span>
- <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">(</span><span class="n">list_of_tensors</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Making-Predictions-with-ResNet-50">Making Predictions with ResNet-50<a class="anchor-link" href="#Making-Predictions-with-ResNet-50">¶</a></h3><p>Getting the 4D tensor ready for ResNet-50, and for any other pre-trained model in Keras, requires some additional processing. First, the RGB image is converted to BGR by reordering the channels. All pre-trained models have the additional normalization step that the mean pixel (expressed in RGB as $[103.939, 116.779, 123.68]$ and calculated from all pixels in all images in ImageNet) must be subtracted from every pixel in each image. This is implemented in the imported function <code>preprocess_input</code>. If you're curious, you can check the code for <code>preprocess_input</code> <a href="https://github.com/fchollet/keras/blob/master/keras/applications/imagenet_utils.py">here</a>.</p>
- <p>Now that we have a way to format our image for supplying to ResNet-50, we are now ready to use the model to extract the predictions. This is accomplished with the <code>predict</code> method, which returns an array whose $i$-th entry is the model's predicted probability that the image belongs to the $i$-th ImageNet category. This is implemented in the <code>ResNet50_predict_labels</code> function below.</p>
- <p>By taking the argmax of the predicted probability vector, we obtain an integer corresponding to the model's predicted object class, which we can identify with an object category through the use of this <a href="https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a">dictionary</a>.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [67]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.applications.resnet50</span> <span class="k">import</span> <span class="n">preprocess_input</span><span class="p">,</span> <span class="n">decode_predictions</span>
- <span class="k">def</span> <span class="nf">ResNet50_predict_labels</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="c1"># Returns prediction vector for image located at img_path</span>
- <span class="n">img</span> <span class="o">=</span> <span class="n">preprocess_input</span><span class="p">(</span><span class="n">path_to_tensor</span><span class="p">(</span><span class="n">img_path</span><span class="p">))</span>
- <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">ResNet50_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">img</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Write-a-Dog-Detector">Write a Dog Detector<a class="anchor-link" href="#Write-a-Dog-Detector">¶</a></h3><p>While looking at the <a href="https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a">dictionary</a>, you will notice that the categories corresponding to dogs appear in an uninterrupted sequence and correspond to dictionary keys 151-268, inclusive, to include all categories from <code>'Chihuahua'</code> to <code>'Mexican hairless'</code>. Thus, in order to check to see if an image is predicted to contain a dog by the pre-trained ResNet-50 model, we need only check if the <code>ResNet50_predict_labels</code> function above returns a value between 151 and 268 (inclusive).</p>
- <p>We use these ideas to complete the <code>dog_detector</code> function below, which returns <code>True</code> if a dog is detected in an image (and <code>False</code> if not).</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [68]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Returns "True" if a dog is detected in the image stored at img_path</span>
- <span class="k">def</span> <span class="nf">dog_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="n">prediction</span> <span class="o">=</span> <span class="n">ResNet50_predict_labels</span><span class="p">(</span><span class="n">img_path</span><span class="p">)</span>
- <span class="k">return</span> <span class="p">((</span><span class="n">prediction</span> <span class="o"><=</span> <span class="mi">268</span><span class="p">)</span> <span class="o">&</span> <span class="p">(</span><span class="n">prediction</span> <span class="o">>=</span> <span class="mi">151</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Assess-the-Dog-Detector">(IMPLEMENTATION) Assess the Dog Detector<a class="anchor-link" href="#(IMPLEMENTATION)-Assess-the-Dog-Detector">¶</a></h3><p><strong>Question 3:</strong> Use the code cell below to test the performance of your <code>dog_detector</code> function.</p>
- <ul>
- <li>What percentage of the images in <code>human_files_short</code> have a detected dog? </li>
- <li>What percentage of the images in <code>dog_files_short</code> have a detected dog?</li>
- </ul>
- <p><strong>Answer:</strong></p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [69]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Test the performance of the dog_detector function</span>
- <span class="c1">### on the images in human_files_short and dog_files_short.</span>
- <span class="k">def</span> <span class="nf">dog_detector_performance_test</span><span class="p">(</span><span class="n">image_array</span><span class="p">):</span>
- <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
- <span class="n">total</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">image_array</span><span class="p">)</span>
- <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">image_array</span><span class="p">:</span>
- <span class="n">count</span> <span class="o">+=</span> <span class="n">dog_detector</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
- <span class="k">return</span> <span class="n">count</span><span class="o">/</span><span class="n">total</span><span class="o">*</span><span class="mi">100</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'The accuracy of detecting dog in "human_files_short" is </span><span class="si">%.2f%%</span><span class="s1">.'</span> \
- <span class="o">%</span> <span class="n">dog_detector_performance_test</span><span class="p">(</span><span class="n">human_files_short</span><span class="p">)</span> <span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'The accuracy of detecting dog in "dog_files_short" is </span><span class="si">%.2f%%</span><span class="s1">.'</span> \
- <span class="o">%</span> <span class="n">dog_detector_performance_test</span><span class="p">(</span><span class="n">dog_files_short</span><span class="p">)</span> <span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>The accuracy of detecting dog in "human_files_short" is 0.00%.
- The accuracy of detecting dog in "dog_files_short" is 100.00%.
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step3'></a></p>
- <h2 id="Step-3:-Create-a-CNN-to-Classify-Dog-Breeds-(from-Scratch)">Step 3: Create a CNN to Classify Dog Breeds (from Scratch)<a class="anchor-link" href="#Step-3:-Create-a-CNN-to-Classify-Dog-Breeds-(from-Scratch)">¶</a></h2><p>Now that we have functions for detecting humans and dogs in images, we need a way to predict breed from images. In this step, you will create a CNN that classifies dog breeds. You must create your CNN <em>from scratch</em> (so, you can't use transfer learning <em>yet</em>!), and you must attain a test accuracy of at least 1%. In Step 5 of this notebook, you will have the opportunity to use transfer learning to create a CNN that attains greatly improved accuracy.</p>
- <p>Be careful with adding too many trainable layers! More parameters means longer training, which means you are more likely to need a GPU to accelerate the training process. Thankfully, Keras provides a handy estimate of the time that each epoch is likely to take; you can extrapolate this estimate to figure out how long it will take for your algorithm to train.</p>
- <p>We mention that the task of assigning breed to dogs from images is considered exceptionally challenging. To see why, consider that <em>even a human</em> would have great difficulty in distinguishing between a Brittany and a Welsh Springer Spaniel.</p>
- <table>
- <thead><tr>
- <th>Brittany</th>
- <th>Welsh Springer Spaniel</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <td><img src="images/Brittany_02625.jpg" width="100"></td>
- <td><img src="images/Welsh_springer_spaniel_08203.jpg" width="200"></td>
- </tr>
- </tbody>
- </table>
- <p>It is not difficult to find other dog breed pairs with minimal inter-class variation (for instance, Curly-Coated Retrievers and American Water Spaniels).</p>
- <table>
- <thead><tr>
- <th>Curly-Coated Retriever</th>
- <th>American Water Spaniel</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <td><img src="images/Curly-coated_retriever_03896.jpg" width="200"></td>
- <td><img src="images/American_water_spaniel_00648.jpg" width="200"></td>
- </tr>
- </tbody>
- </table>
- <p>Likewise, recall that labradors come in yellow, chocolate, and black. Your vision-based algorithm will have to conquer this high intra-class variation to determine how to classify all of these different shades as the same breed.</p>
- <table>
- <thead><tr>
- <th>Yellow Labrador</th>
- <th>Chocolate Labrador</th>
- <th>Black Labrador</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <td><img src="images/Labrador_retriever_06457.jpg" width="150"></td>
- <td><img src="images/Labrador_retriever_06455.jpg" width="240"></td>
- <td><img src="images/Labrador_retriever_06449.jpg" width="220"></td>
- </tr>
- </tbody>
- </table>
- <p>We also mention that random chance presents an exceptionally low bar: setting aside the fact that the classes are slightly imabalanced, a random guess will provide a correct answer roughly 1 in 133 times, which corresponds to an accuracy of less than 1%.</p>
- <p>Remember that the practice is far ahead of the theory in deep learning. Experiment with many different architectures, and trust your intuition. And, of course, have fun!</p>
- <h3 id="Pre-process-the-Data">Pre-process the Data<a class="anchor-link" href="#Pre-process-the-Data">¶</a></h3><p>We rescale the images by dividing every pixel in every image by 255.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [70]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">ImageFile</span>
- <span class="n">ImageFile</span><span class="o">.</span><span class="n">LOAD_TRUNCATED_IMAGES</span> <span class="o">=</span> <span class="kc">True</span>
- <span class="c1"># pre-process the data for Keras</span>
- <span class="n">train_tensors</span> <span class="o">=</span> <span class="n">paths_to_tensor</span><span class="p">(</span><span class="n">train_files</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">'float32'</span><span class="p">)</span><span class="o">/</span><span class="mi">255</span>
- <span class="n">valid_tensors</span> <span class="o">=</span> <span class="n">paths_to_tensor</span><span class="p">(</span><span class="n">valid_files</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">'float32'</span><span class="p">)</span><span class="o">/</span><span class="mi">255</span>
- <span class="n">test_tensors</span> <span class="o">=</span> <span class="n">paths_to_tensor</span><span class="p">(</span><span class="n">test_files</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">'float32'</span><span class="p">)</span><span class="o">/</span><span class="mi">255</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stderr output_text">
- <pre>100%|██████████| 6680/6680 [01:11<00:00, 93.40it/s]
- 100%|██████████| 835/835 [00:11<00:00, 75.73it/s]
- 100%|██████████| 836/836 [00:09<00:00, 85.81it/s]
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Model-Architecture">(IMPLEMENTATION) Model Architecture<a class="anchor-link" href="#(IMPLEMENTATION)-Model-Architecture">¶</a></h3><p>Create a CNN to classify dog breed. At the end of your code cell block, summarize the layers of your model by executing the line:</p>
- <pre><code> model.summary()
- </code></pre>
- <p>We have imported some Python modules to get you started, but feel free to import as many modules as you need. If you end up getting stuck, here's a hint that specifies a model that trains relatively fast on CPU and attains >1% test accuracy in 5 epochs:</p>
- <p><img src="images/sample_cnn.png" alt="Sample CNN"></p>
- <p><strong>Question 4:</strong> Outline the steps you took to get to your final CNN architecture and your reasoning at each step. If you chose to use the hinted architecture above, describe why you think that CNN architecture should work well for the image classification task.</p>
- <p><strong>Answer:</strong> The architecture used for the classification problem is described as follows.</p>
- <ul>
- <li><em>Convolution layers</em> that detect regional patterns in the image using filters. <em>Four Convolution layers</em> are used to make image array deeper as it passes through the network and identifying more complicated patterns. These layers use 'ReLu' activation function to deal with the vanishing gradient problem.</li>
- </ul>
- <ul>
- <li><em>Four Max Pooling layers</em> follow each convolution layer <em>to decrease the spatial dimensions</em> (i.e., reduce the dimensionality of the image array).</li>
- </ul>
- <ul>
- <li><em>Two dropout layers</em> to <em>avoid overfitting</em>. </li>
- </ul>
- <ul>
- <li>A <em>Global Average Pooling (GAP) layer</em> is used <em>for dimensionality reduction</em>. </li>
- </ul>
- <ul>
- <li>A fully connected layer with '<em>softmax activation</em>' function is used to return probability for each output node.</li>
- </ul>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [71]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Conv2D</span><span class="p">,</span> <span class="n">MaxPooling2D</span><span class="p">,</span> <span class="n">GlobalAveragePooling2D</span>
- <span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Dropout</span><span class="p">,</span> <span class="n">Flatten</span><span class="p">,</span> <span class="n">Dense</span>
- <span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Sequential</span>
- <span class="n">model</span> <span class="o">=</span> <span class="n">Sequential</span><span class="p">()</span>
- <span class="c1">### TODO: Define your architecture.</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Conv2D</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'relu'</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="s1">'same'</span><span class="p">,</span> <span class="n">input_shape</span><span class="o">=</span><span class="p">(</span><span class="mi">224</span><span class="p">,</span> <span class="mi">224</span><span class="p">,</span> <span class="mi">3</span><span class="p">)))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">MaxPooling2D</span><span class="p">(</span><span class="n">pool_size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Conv2D</span><span class="p">(</span><span class="mi">32</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'relu'</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="s1">'same'</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">MaxPooling2D</span><span class="p">(</span><span class="n">pool_size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.2</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Conv2D</span><span class="p">(</span><span class="mi">64</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'relu'</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="s1">'same'</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">MaxPooling2D</span><span class="p">(</span><span class="n">pool_size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.2</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Conv2D</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'relu'</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="s1">'same'</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">MaxPooling2D</span><span class="p">(</span><span class="n">pool_size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.2</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">GlobalAveragePooling2D</span><span class="p">())</span>
- <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="mi">133</span><span class="p">,</span> <span class="n">activation</span> <span class="o">=</span> <span class="s1">'softmax'</span><span class="p">))</span>
- <span class="n">model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>_________________________________________________________________
- Layer (type) Output Shape Param #
- =================================================================
- conv2d_5 (Conv2D) (None, 224, 224, 16) 208
- _________________________________________________________________
- max_pooling2d_13 (MaxPooling (None, 112, 112, 16) 0
- _________________________________________________________________
- conv2d_6 (Conv2D) (None, 112, 112, 32) 2080
- _________________________________________________________________
- max_pooling2d_14 (MaxPooling (None, 56, 56, 32) 0
- _________________________________________________________________
- dropout_4 (Dropout) (None, 56, 56, 32) 0
- _________________________________________________________________
- conv2d_7 (Conv2D) (None, 56, 56, 64) 8256
- _________________________________________________________________
- max_pooling2d_15 (MaxPooling (None, 28, 28, 64) 0
- _________________________________________________________________
- dropout_5 (Dropout) (None, 28, 28, 64) 0
- _________________________________________________________________
- conv2d_8 (Conv2D) (None, 28, 28, 128) 32896
- _________________________________________________________________
- max_pooling2d_16 (MaxPooling (None, 14, 14, 128) 0
- _________________________________________________________________
- dropout_6 (Dropout) (None, 14, 14, 128) 0
- _________________________________________________________________
- global_average_pooling2d_4 ( (None, 128) 0
- _________________________________________________________________
- dense_4 (Dense) (None, 133) 17157
- =================================================================
- Total params: 60,597
- Trainable params: 60,597
- Non-trainable params: 0
- _________________________________________________________________
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Compile-the-Model">Compile the Model<a class="anchor-link" href="#Compile-the-Model">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [72]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">optimizer</span><span class="o">=</span><span class="s1">'rmsprop'</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'categorical_crossentropy'</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">])</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Train-the-Model">(IMPLEMENTATION) Train the Model<a class="anchor-link" href="#(IMPLEMENTATION)-Train-the-Model">¶</a></h3><p>Train your model in the code cell below. Use model checkpointing to save the model that attains the best validation loss.</p>
- <p>You are welcome to <a href="https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html">augment the training data</a>, but this is not a requirement.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [73]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.callbacks</span> <span class="k">import</span> <span class="n">ModelCheckpoint</span>
- <span class="c1">### TODO: specify the number of epochs that you would like to use to train the model.</span>
- <span class="n">epochs</span> <span class="o">=</span> <span class="mi">10</span>
- <span class="c1">### Do NOT modify the code below this line.</span>
- <span class="n">checkpointer</span> <span class="o">=</span> <span class="n">ModelCheckpoint</span><span class="p">(</span><span class="n">filepath</span><span class="o">=</span><span class="s1">'saved_models/weights.best.from_scratch.hdf5'</span><span class="p">,</span>
- <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">save_best_only</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
- <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_tensors</span><span class="p">,</span> <span class="n">train_targets</span><span class="p">,</span>
- <span class="n">validation_data</span><span class="o">=</span><span class="p">(</span><span class="n">valid_tensors</span><span class="p">,</span> <span class="n">valid_targets</span><span class="p">),</span>
- <span class="n">epochs</span><span class="o">=</span><span class="n">epochs</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">checkpointer</span><span class="p">],</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Train on 6680 samples, validate on 835 samples
- Epoch 1/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.8799 - acc: 0.0093Epoch 00001: val_loss improved from inf to 4.85909, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 32s 5ms/step - loss: 4.8798 - acc: 0.0093 - val_loss: 4.8591 - val_acc: 0.0144
- Epoch 2/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.8317 - acc: 0.0161Epoch 00002: val_loss improved from 4.85909 to 4.79839, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.8315 - acc: 0.0162 - val_loss: 4.7984 - val_acc: 0.0180
- Epoch 3/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.7731 - acc: 0.0180Epoch 00003: val_loss improved from 4.79839 to 4.76546, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.7725 - acc: 0.0180 - val_loss: 4.7655 - val_acc: 0.0192
- Epoch 4/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.7241 - acc: 0.0210Epoch 00004: val_loss improved from 4.76546 to 4.71545, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.7236 - acc: 0.0211 - val_loss: 4.7154 - val_acc: 0.0335
- Epoch 5/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.6697 - acc: 0.0311Epoch 00005: val_loss improved from 4.71545 to 4.68986, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.6703 - acc: 0.0310 - val_loss: 4.6899 - val_acc: 0.0311
- Epoch 6/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.6185 - acc: 0.0303Epoch 00006: val_loss improved from 4.68986 to 4.63581, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.6182 - acc: 0.0304 - val_loss: 4.6358 - val_acc: 0.0347
- Epoch 7/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.5489 - acc: 0.0416Epoch 00007: val_loss improved from 4.63581 to 4.62179, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.5494 - acc: 0.0415 - val_loss: 4.6218 - val_acc: 0.0419
- Epoch 8/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.5005 - acc: 0.0456Epoch 00008: val_loss improved from 4.62179 to 4.56871, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.4993 - acc: 0.0458 - val_loss: 4.5687 - val_acc: 0.0395
- Epoch 9/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.4515 - acc: 0.0483Epoch 00009: val_loss improved from 4.56871 to 4.54942, saving model to saved_models/weights.best.from_scratch.hdf5
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.4518 - acc: 0.0484 - val_loss: 4.5494 - val_acc: 0.0539
- Epoch 10/10
- 6660/6680 [============================>.] - ETA: 0s - loss: 4.3985 - acc: 0.0524Epoch 00010: val_loss did not improve
- 6680/6680 [==============================] - 25s 4ms/step - loss: 4.3977 - acc: 0.0524 - val_loss: 4.5597 - val_acc: 0.0419
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt output_prompt">Out[73]:</div>
- <div class="output_text output_subarea output_execute_result">
- <pre><keras.callbacks.History at 0x7f7cee8ac6d8></pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Load-the-Model-with-the-Best-Validation-Loss">Load the Model with the Best Validation Loss<a class="anchor-link" href="#Load-the-Model-with-the-Best-Validation-Loss">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [74]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="s1">'saved_models/weights.best.from_scratch.hdf5'</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Test-the-Model">Test the Model<a class="anchor-link" href="#Test-the-Model">¶</a></h3><p>Try out your model on the test dataset of dog images. Ensure that your test accuracy is greater than 1%.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [75]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Get index of predicted dog breed for each image in test set</span>
- <span class="n">dog_breed_predictions</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">tensor</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)))</span> <span class="k">for</span> <span class="n">tensor</span> <span class="ow">in</span> <span class="n">test_tensors</span><span class="p">]</span>
- <span class="c1"># Report test accuracy</span>
- <span class="n">test_accuracy</span> <span class="o">=</span> <span class="mi">100</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dog_breed_predictions</span><span class="p">)</span><span class="o">==</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">test_targets</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">dog_breed_predictions</span><span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Test accuracy: </span><span class="si">%.4f%%</span><span class="s1">'</span> <span class="o">%</span> <span class="n">test_accuracy</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Test accuracy: 5.2632%
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step4'></a></p>
- <h2 id="Step-4:-Use-a-CNN-to-Classify-Dog-Breeds">Step 4: Use a CNN to Classify Dog Breeds<a class="anchor-link" href="#Step-4:-Use-a-CNN-to-Classify-Dog-Breeds">¶</a></h2><p>To reduce training time without sacrificing accuracy, we show you how to train a CNN using transfer learning. In the following step, you will get a chance to use transfer learning to train your own CNN.</p>
- <h3 id="Obtain-Bottleneck-Features">Obtain Bottleneck Features<a class="anchor-link" href="#Obtain-Bottleneck-Features">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [76]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">bottleneck_features</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s1">'/data/bottleneck_features/DogVGG16Data.npz'</span><span class="p">)</span>
- <span class="n">train_VGG16</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'train'</span><span class="p">]</span>
- <span class="n">valid_VGG16</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'valid'</span><span class="p">]</span>
- <span class="n">test_VGG16</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'test'</span><span class="p">]</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Model-Architecture">Model Architecture<a class="anchor-link" href="#Model-Architecture">¶</a></h3><p>The model uses the the pre-trained VGG-16 model as a fixed feature extractor, where the last convolutional output of VGG-16 is fed as input to our model. We only add a global average pooling layer and a fully connected layer, where the latter contains one node for each dog category and is equipped with a softmax.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [77]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">VGG16_model</span> <span class="o">=</span> <span class="n">Sequential</span><span class="p">()</span>
- <span class="n">VGG16_model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">GlobalAveragePooling2D</span><span class="p">(</span><span class="n">input_shape</span><span class="o">=</span><span class="n">train_VGG16</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:]))</span>
- <span class="n">VGG16_model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="mi">133</span><span class="p">,</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">))</span>
- <span class="n">VGG16_model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>_________________________________________________________________
- Layer (type) Output Shape Param #
- =================================================================
- global_average_pooling2d_5 ( (None, 512) 0
- _________________________________________________________________
- dense_5 (Dense) (None, 133) 68229
- =================================================================
- Total params: 68,229
- Trainable params: 68,229
- Non-trainable params: 0
- _________________________________________________________________
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Compile-the-Model">Compile the Model<a class="anchor-link" href="#Compile-the-Model">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [78]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">VGG16_model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="s1">'categorical_crossentropy'</span><span class="p">,</span> <span class="n">optimizer</span><span class="o">=</span><span class="s1">'rmsprop'</span><span class="p">,</span> <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">])</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Train-the-Model">Train the Model<a class="anchor-link" href="#Train-the-Model">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [79]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">checkpointer</span> <span class="o">=</span> <span class="n">ModelCheckpoint</span><span class="p">(</span><span class="n">filepath</span><span class="o">=</span><span class="s1">'saved_models/weights.best.VGG16.hdf5'</span><span class="p">,</span>
- <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">save_best_only</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
- <span class="n">VGG16_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_VGG16</span><span class="p">,</span> <span class="n">train_targets</span><span class="p">,</span>
- <span class="n">validation_data</span><span class="o">=</span><span class="p">(</span><span class="n">valid_VGG16</span><span class="p">,</span> <span class="n">valid_targets</span><span class="p">),</span>
- <span class="n">epochs</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">checkpointer</span><span class="p">],</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Train on 6680 samples, validate on 835 samples
- Epoch 1/20
- 6580/6680 [============================>.] - ETA: 0s - loss: 12.7794 - acc: 0.1140Epoch 00001: val_loss improved from inf to 11.64069, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 5s 679us/step - loss: 12.7763 - acc: 0.1142 - val_loss: 11.6407 - val_acc: 0.1832
- Epoch 2/20
- 6620/6680 [============================>.] - ETA: 0s - loss: 11.2368 - acc: 0.2393Epoch 00002: val_loss improved from 11.64069 to 11.15474, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 287us/step - loss: 11.2388 - acc: 0.2392 - val_loss: 11.1547 - val_acc: 0.2527
- Epoch 3/20
- 6660/6680 [============================>.] - ETA: 0s - loss: 10.8508 - acc: 0.2839Epoch 00003: val_loss improved from 11.15474 to 10.89021, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 274us/step - loss: 10.8449 - acc: 0.2844 - val_loss: 10.8902 - val_acc: 0.2635
- Epoch 4/20
- 6640/6680 [============================>.] - ETA: 0s - loss: 10.4611 - acc: 0.3130Epoch 00004: val_loss improved from 10.89021 to 10.49600, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 272us/step - loss: 10.4566 - acc: 0.3132 - val_loss: 10.4960 - val_acc: 0.2958
- Epoch 5/20
- 6660/6680 [============================>.] - ETA: 0s - loss: 10.1769 - acc: 0.3348Epoch 00005: val_loss improved from 10.49600 to 10.31862, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 273us/step - loss: 10.1641 - acc: 0.3353 - val_loss: 10.3186 - val_acc: 0.2934
- Epoch 6/20
- 6620/6680 [============================>.] - ETA: 0s - loss: 9.9007 - acc: 0.3569Epoch 00006: val_loss improved from 10.31862 to 10.12106, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 274us/step - loss: 9.8947 - acc: 0.3572 - val_loss: 10.1211 - val_acc: 0.3126
- Epoch 7/20
- 6480/6680 [============================>.] - ETA: 0s - loss: 9.6728 - acc: 0.3725Epoch 00007: val_loss improved from 10.12106 to 9.92301, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 286us/step - loss: 9.6677 - acc: 0.3729 - val_loss: 9.9230 - val_acc: 0.3246
- Epoch 8/20
- 6660/6680 [============================>.] - ETA: 0s - loss: 9.5323 - acc: 0.3919Epoch 00008: val_loss improved from 9.92301 to 9.81311, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 287us/step - loss: 9.5261 - acc: 0.3921 - val_loss: 9.8131 - val_acc: 0.3317
- Epoch 9/20
- 6620/6680 [============================>.] - ETA: 0s - loss: 9.4018 - acc: 0.4023Epoch 00009: val_loss improved from 9.81311 to 9.76238, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 289us/step - loss: 9.4021 - acc: 0.4022 - val_loss: 9.7624 - val_acc: 0.3317
- Epoch 10/20
- 6640/6680 [============================>.] - ETA: 0s - loss: 9.3459 - acc: 0.4101Epoch 00010: val_loss improved from 9.76238 to 9.61726, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 288us/step - loss: 9.3406 - acc: 0.4105 - val_loss: 9.6173 - val_acc: 0.3461
- Epoch 11/20
- 6580/6680 [============================>.] - ETA: 0s - loss: 9.2954 - acc: 0.4140Epoch 00011: val_loss improved from 9.61726 to 9.57953, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 280us/step - loss: 9.2847 - acc: 0.4147 - val_loss: 9.5795 - val_acc: 0.3557
- Epoch 12/20
- 6480/6680 [============================>.] - ETA: 0s - loss: 9.1424 - acc: 0.4188Epoch 00012: val_loss improved from 9.57953 to 9.42498, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 277us/step - loss: 9.1372 - acc: 0.4195 - val_loss: 9.4250 - val_acc: 0.3593
- Epoch 13/20
- 6580/6680 [============================>.] - ETA: 0s - loss: 8.9372 - acc: 0.4331Epoch 00013: val_loss improved from 9.42498 to 9.26422, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 274us/step - loss: 8.9438 - acc: 0.4328 - val_loss: 9.2642 - val_acc: 0.3749
- Epoch 14/20
- 6600/6680 [============================>.] - ETA: 0s - loss: 8.8360 - acc: 0.4417Epoch 00014: val_loss improved from 9.26422 to 9.15274, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 278us/step - loss: 8.8466 - acc: 0.4410 - val_loss: 9.1527 - val_acc: 0.3725
- Epoch 15/20
- 6540/6680 [============================>.] - ETA: 0s - loss: 8.7744 - acc: 0.4450Epoch 00015: val_loss improved from 9.15274 to 9.07872, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 276us/step - loss: 8.7489 - acc: 0.4461 - val_loss: 9.0787 - val_acc: 0.3772
- Epoch 16/20
- 6620/6680 [============================>.] - ETA: 0s - loss: 8.5544 - acc: 0.4556Epoch 00016: val_loss improved from 9.07872 to 8.89981, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 275us/step - loss: 8.5532 - acc: 0.4557 - val_loss: 8.8998 - val_acc: 0.3892
- Epoch 17/20
- 6600/6680 [============================>.] - ETA: 0s - loss: 8.4860 - acc: 0.4647Epoch 00017: val_loss improved from 8.89981 to 8.88511, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 274us/step - loss: 8.4667 - acc: 0.4659 - val_loss: 8.8851 - val_acc: 0.3952
- Epoch 18/20
- 6500/6680 [============================>.] - ETA: 0s - loss: 8.4646 - acc: 0.4686Epoch 00018: val_loss improved from 8.88511 to 8.86300, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 275us/step - loss: 8.4514 - acc: 0.4696 - val_loss: 8.8630 - val_acc: 0.3988
- Epoch 19/20
- 6560/6680 [============================>.] - ETA: 0s - loss: 8.4499 - acc: 0.4710Epoch 00019: val_loss improved from 8.86300 to 8.83430, saving model to saved_models/weights.best.VGG16.hdf5
- 6680/6680 [==============================] - 2s 274us/step - loss: 8.4466 - acc: 0.4710 - val_loss: 8.8343 - val_acc: 0.4036
- Epoch 20/20
- 6500/6680 [============================>.] - ETA: 0s - loss: 8.4583 - acc: 0.4723Epoch 00020: val_loss did not improve
- 6680/6680 [==============================] - 2s 274us/step - loss: 8.4355 - acc: 0.4738 - val_loss: 8.8923 - val_acc: 0.3988
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt output_prompt">Out[79]:</div>
- <div class="output_text output_subarea output_execute_result">
- <pre><keras.callbacks.History at 0x7f7cee66edd8></pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Load-the-Model-with-the-Best-Validation-Loss">Load the Model with the Best Validation Loss<a class="anchor-link" href="#Load-the-Model-with-the-Best-Validation-Loss">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [80]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="n">VGG16_model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="s1">'saved_models/weights.best.VGG16.hdf5'</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Test-the-Model">Test the Model<a class="anchor-link" href="#Test-the-Model">¶</a></h3><p>Now, we can use the CNN to test how well it identifies breed within our test dataset of dog images. We print the test accuracy below.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [40]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Get index of predicted dog breed for each image in test set</span>
- <span class="n">VGG16_predictions</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">VGG16_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">feature</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)))</span> <span class="k">for</span> <span class="n">feature</span> <span class="ow">in</span> <span class="n">test_VGG16</span><span class="p">]</span>
- <span class="c1"># Report test accuracy</span>
- <span class="n">test_accuracy</span> <span class="o">=</span> <span class="mi">100</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">VGG16_predictions</span><span class="p">)</span><span class="o">==</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">test_targets</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">VGG16_predictions</span><span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Test accuracy: </span><span class="si">%.4f%%</span><span class="s1">'</span> <span class="o">%</span> <span class="n">test_accuracy</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Test accuracy: 37.0813%
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="Predict-Dog-Breed-with-the-Model">Predict Dog Breed with the Model<a class="anchor-link" href="#Predict-Dog-Breed-with-the-Model">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [81]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">extract_bottleneck_features</span> <span class="k">import</span> <span class="o">*</span>
- <span class="k">def</span> <span class="nf">VGG16_predict_breed</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="c1"># Extract bottleneck features</span>
- <span class="n">bottleneck_feature</span> <span class="o">=</span> <span class="n">extract_VGG16</span><span class="p">(</span><span class="n">path_to_tensor</span><span class="p">(</span><span class="n">img_path</span><span class="p">))</span>
- <span class="c1"># Obtain predicted vector</span>
- <span class="n">predicted_vector</span> <span class="o">=</span> <span class="n">VGG16_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">bottleneck_feature</span><span class="p">)</span>
- <span class="c1"># Return dog breed that is predicted by the model</span>
- <span class="k">return</span> <span class="n">dog_names</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">predicted_vector</span><span class="p">)]</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step5'></a></p>
- <h2 id="Step-5:-Create-a-CNN-to-Classify-Dog-Breeds-(using-Transfer-Learning)">Step 5: Create a CNN to Classify Dog Breeds (using Transfer Learning)<a class="anchor-link" href="#Step-5:-Create-a-CNN-to-Classify-Dog-Breeds-(using-Transfer-Learning)">¶</a></h2><p>You will now use transfer learning to create a CNN that can identify dog breed from images. Your CNN must attain at least 60% accuracy on the test set.</p>
- <p>In Step 4, we used transfer learning to create a CNN using VGG-16 bottleneck features. In this section, you must use the bottleneck features from a different pre-trained model. To make things easier for you, we have pre-computed the features for all of the networks that are currently available in Keras. These are already in the workspace, at /data/bottleneck_features. If you wish to download them on a different machine, they can be found at:</p>
- <ul>
- <li><a href="https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/DogVGG19Data.npz">VGG-19</a> bottleneck features</li>
- <li><a href="https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/DogResnet50Data.npz">ResNet-50</a> bottleneck features</li>
- <li><a href="https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/DogInceptionV3Data.npz">Inception</a> bottleneck features</li>
- <li><a href="https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/DogXceptionData.npz">Xception</a> bottleneck features</li>
- </ul>
- <p>The files are encoded as such:</p>
- <pre><code>Dog{network}Data.npz
- </code></pre>
- <p>where <code>{network}</code>, in the above filename, can be one of <code>VGG19</code>, <code>Resnet50</code>, <code>InceptionV3</code>, or <code>Xception</code>.</p>
- <p>The above architectures are downloaded and stored for you in the <code>/data/bottleneck_features/</code> folder.</p>
- <p>This means the following will be in the <code>/data/bottleneck_features/</code> folder:</p>
- <p><code>DogVGG19Data.npz</code>
- <code>DogResnet50Data.npz</code>
- <code>DogInceptionV3Data.npz</code>
- <code>DogXceptionData.npz</code></p>
- <h3 id="(IMPLEMENTATION)-Obtain-Bottleneck-Features">(IMPLEMENTATION) Obtain Bottleneck Features<a class="anchor-link" href="#(IMPLEMENTATION)-Obtain-Bottleneck-Features">¶</a></h3><p>In the code block below, extract the bottleneck features corresponding to the train, test, and validation sets by running the following:</p>
- <pre><code>bottleneck_features = np.load('/data/bottleneck_features/Dog{network}Data.npz')
- train_{network} = bottleneck_features['train']
- valid_{network} = bottleneck_features['valid']
- test_{network} = bottleneck_features['test']</code></pre>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [82]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Obtain bottleneck features from another pre-trained CNN.</span>
- <span class="kn">import</span> <span class="nn">requests</span>
- <span class="n">source</span> <span class="o">=</span> <span class="n">requests</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/DogResnet50Data.npz"</span><span class="p">)</span>
- <span class="n">bottleneck_features</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s1">'/data/bottleneck_features/DogResnet50Data.npz'</span><span class="p">)</span>
- <span class="n">train_Resnet50</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'train'</span><span class="p">]</span>
- <span class="n">valid_Resnet50</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'valid'</span><span class="p">]</span>
- <span class="n">test_Resnet50</span> <span class="o">=</span> <span class="n">bottleneck_features</span><span class="p">[</span><span class="s1">'test'</span><span class="p">]</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">train_Resnet50</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>(6680, 1, 1, 2048)
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Model-Architecture">(IMPLEMENTATION) Model Architecture<a class="anchor-link" href="#(IMPLEMENTATION)-Model-Architecture">¶</a></h3><p>Create a CNN to classify dog breed. At the end of your code cell block, summarize the layers of your model by executing the line:</p>
- <pre><code> <your model's name>.summary()
- </code></pre>
- <p><strong>Question 5:</strong> Outline the steps you took to get to your final CNN architecture and your reasoning at each step. Describe why you think the architecture is suitable for the current problem.</p>
- <p><strong>Answer:</strong> Classifying dog breed problem requires a large number of filters to discover more patterns in the image. CNN should be deep enough to discover these patterns. For a deeper network, we have to add more layers, but at some point, the performance declines due to vanishing gradient problem. <strong>ResNet architecture</strong> is the best to overcome this problem, unlike VGG.</p>
- <p>With the aid of <em>transfer learning</em> using the weights in <em>pre-trained ResNet</em>, images are passed through the <em>ResNet network to the last max pooling layer to get a new data set</em>.</p>
- <p>Finally, <em>creating our network with two layers only</em>; the input layer that uses the images passed through the ResNet and an output layer consisting of a fully connected layer with softmax to get the object in the image.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [83]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Define your architecture.</span>
- <span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Dense</span><span class="p">,</span> <span class="n">GlobalAveragePooling2D</span>
- <span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Sequential</span>
- <span class="n">Resnet50_model</span> <span class="o">=</span> <span class="n">Sequential</span><span class="p">()</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">GlobalAveragePooling2D</span><span class="p">(</span><span class="n">input_shape</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2048</span><span class="p">)))</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="mi">133</span><span class="p">,</span> <span class="n">activation</span><span class="o">=</span><span class="s1">'softmax'</span><span class="p">))</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>_________________________________________________________________
- Layer (type) Output Shape Param #
- =================================================================
- global_average_pooling2d_6 ( (None, 2048) 0
- _________________________________________________________________
- dense_6 (Dense) (None, 133) 272517
- =================================================================
- Total params: 272,517
- Trainable params: 272,517
- Non-trainable params: 0
- _________________________________________________________________
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Compile-the-Model">(IMPLEMENTATION) Compile the Model<a class="anchor-link" href="#(IMPLEMENTATION)-Compile-the-Model">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [84]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Compile the model.</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="s1">'categorical_crossentropy'</span><span class="p">,</span> <span class="n">optimizer</span><span class="o">=</span><span class="s1">'rmsprop'</span><span class="p">,</span>
- <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">])</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Train-the-Model">(IMPLEMENTATION) Train the Model<a class="anchor-link" href="#(IMPLEMENTATION)-Train-the-Model">¶</a></h3><p>Train your model in the code cell below. Use model checkpointing to save the model that attains the best validation loss.</p>
- <p>You are welcome to <a href="https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html">augment the training data</a>, but this is not a requirement.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [85]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Train the model.</span>
- <span class="kn">from</span> <span class="nn">keras.callbacks</span> <span class="k">import</span> <span class="n">ModelCheckpoint</span>
- <span class="n">checkpointer</span> <span class="o">=</span> <span class="n">ModelCheckpoint</span><span class="p">(</span><span class="n">filepath</span><span class="o">=</span><span class="s1">'saved_models/weights.best.Resnet50_model.hdf5'</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
- <span class="n">save_best_only</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_Resnet50</span><span class="p">,</span> <span class="n">train_targets</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">validation_data</span><span class="o">=</span><span class="p">(</span><span class="n">valid_Resnet50</span><span class="p">,</span> <span class="n">valid_targets</span><span class="p">),</span>
- <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">checkpointer</span><span class="p">],</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Train on 6680 samples, validate on 835 samples
- Epoch 1/50
- 6528/6680 [============================>.] - ETA: 0s - loss: 1.8017 - acc: 0.5694Epoch 00001: val_loss improved from inf to 0.88200, saving model to saved_models/weights.best.Resnet50_model.hdf5
- 6680/6680 [==============================] - 4s 591us/step - loss: 1.7781 - acc: 0.5740 - val_loss: 0.8820 - val_acc: 0.7222
- Epoch 2/50
- 6560/6680 [============================>.] - ETA: 0s - loss: 0.4538 - acc: 0.8602Epoch 00002: val_loss improved from 0.88200 to 0.65110, saving model to saved_models/weights.best.Resnet50_model.hdf5
- 6680/6680 [==============================] - 1s 175us/step - loss: 0.4518 - acc: 0.8608 - val_loss: 0.6511 - val_acc: 0.7856
- Epoch 3/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.2640 - acc: 0.9200Epoch 00003: val_loss improved from 0.65110 to 0.63688, saving model to saved_models/weights.best.Resnet50_model.hdf5
- 6680/6680 [==============================] - 1s 173us/step - loss: 0.2638 - acc: 0.9196 - val_loss: 0.6369 - val_acc: 0.8000
- Epoch 4/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.1651 - acc: 0.9520Epoch 00004: val_loss improved from 0.63688 to 0.63438, saving model to saved_models/weights.best.Resnet50_model.hdf5
- 6680/6680 [==============================] - 1s 172us/step - loss: 0.1650 - acc: 0.9521 - val_loss: 0.6344 - val_acc: 0.8120
- Epoch 5/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.1145 - acc: 0.9667Epoch 00005: val_loss did not improve
- 6680/6680 [==============================] - 1s 170us/step - loss: 0.1142 - acc: 0.9666 - val_loss: 0.6352 - val_acc: 0.8120
- Epoch 6/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.0765 - acc: 0.9812Epoch 00006: val_loss improved from 0.63438 to 0.60124, saving model to saved_models/weights.best.Resnet50_model.hdf5
- 6680/6680 [==============================] - 1s 174us/step - loss: 0.0768 - acc: 0.9810 - val_loss: 0.6012 - val_acc: 0.8323
- Epoch 7/50
- 6400/6680 [===========================>..] - ETA: 0s - loss: 0.0517 - acc: 0.9862Epoch 00007: val_loss did not improve
- 6680/6680 [==============================] - 1s 171us/step - loss: 0.0528 - acc: 0.9859 - val_loss: 0.6148 - val_acc: 0.8287
- Epoch 8/50
- 6592/6680 [============================>.] - ETA: 0s - loss: 0.0386 - acc: 0.9903Epoch 00008: val_loss did not improve
- 6680/6680 [==============================] - 1s 167us/step - loss: 0.0391 - acc: 0.9903 - val_loss: 0.6066 - val_acc: 0.8431
- Epoch 9/50
- 6464/6680 [============================>.] - ETA: 0s - loss: 0.0256 - acc: 0.9932Epoch 00009: val_loss did not improve
- 6680/6680 [==============================] - 1s 169us/step - loss: 0.0270 - acc: 0.9925 - val_loss: 0.6670 - val_acc: 0.8216
- Epoch 10/50
- 6496/6680 [============================>.] - ETA: 0s - loss: 0.0186 - acc: 0.9974Epoch 00010: val_loss did not improve
- 6680/6680 [==============================] - 1s 167us/step - loss: 0.0192 - acc: 0.9972 - val_loss: 0.6619 - val_acc: 0.8132
- Epoch 11/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.0147 - acc: 0.9965Epoch 00011: val_loss did not improve
- 6680/6680 [==============================] - 1s 163us/step - loss: 0.0152 - acc: 0.9964 - val_loss: 0.6870 - val_acc: 0.8311
- Epoch 12/50
- 6560/6680 [============================>.] - ETA: 0s - loss: 0.0123 - acc: 0.9973Epoch 00012: val_loss did not improve
- 6680/6680 [==============================] - 1s 166us/step - loss: 0.0122 - acc: 0.9973 - val_loss: 0.7316 - val_acc: 0.8311
- Epoch 13/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0107 - acc: 0.9974Epoch 00013: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0107 - acc: 0.9975 - val_loss: 0.7301 - val_acc: 0.8240
- Epoch 14/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.0088 - acc: 0.9978Epoch 00014: val_loss did not improve
- 6680/6680 [==============================] - 1s 163us/step - loss: 0.0090 - acc: 0.9975 - val_loss: 0.7383 - val_acc: 0.8323
- Epoch 15/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0072 - acc: 0.9983Epoch 00015: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0072 - acc: 0.9984 - val_loss: 0.7782 - val_acc: 0.8263
- Epoch 16/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0072 - acc: 0.9977Epoch 00016: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0071 - acc: 0.9978 - val_loss: 0.7851 - val_acc: 0.8228
- Epoch 17/50
- 6592/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9989Epoch 00017: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0051 - acc: 0.9990 - val_loss: 0.7970 - val_acc: 0.8204
- Epoch 18/50
- 6528/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9986Epoch 00018: val_loss did not improve
- 6680/6680 [==============================] - 1s 167us/step - loss: 0.0050 - acc: 0.9987 - val_loss: 0.8221 - val_acc: 0.8180
- Epoch 19/50
- 6560/6680 [============================>.] - ETA: 0s - loss: 0.0050 - acc: 0.9985Epoch 00019: val_loss did not improve
- 6680/6680 [==============================] - 1s 167us/step - loss: 0.0049 - acc: 0.9985 - val_loss: 0.8122 - val_acc: 0.8395
- Epoch 20/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.0053 - acc: 0.9983Epoch 00020: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0053 - acc: 0.9982 - val_loss: 0.8829 - val_acc: 0.8180
- Epoch 21/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9985Epoch 00021: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0047 - acc: 0.9985 - val_loss: 0.9122 - val_acc: 0.8335
- Epoch 22/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00022: val_loss did not improve
- 6680/6680 [==============================] - 1s 163us/step - loss: 0.0049 - acc: 0.9987 - val_loss: 0.8550 - val_acc: 0.8359
- Epoch 23/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.0049 - acc: 0.9986Epoch 00023: val_loss did not improve
- 6680/6680 [==============================] - 1s 163us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 0.8820 - val_acc: 0.8371
- Epoch 24/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9986Epoch 00024: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0042 - acc: 0.9987 - val_loss: 0.9261 - val_acc: 0.8263
- Epoch 25/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.0046 - acc: 0.9984Epoch 00025: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0044 - acc: 0.9985 - val_loss: 0.9235 - val_acc: 0.8228
- Epoch 26/50
- 6336/6680 [===========================>..] - ETA: 0s - loss: 0.0058 - acc: 0.9987Epoch 00026: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0055 - acc: 0.9988 - val_loss: 0.9407 - val_acc: 0.8263
- Epoch 27/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00027: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 0.9739 - val_acc: 0.8240
- Epoch 28/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0053 - acc: 0.9986Epoch 00028: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0053 - acc: 0.9987 - val_loss: 0.9882 - val_acc: 0.8251
- Epoch 29/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9988Epoch 00029: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.0021 - val_acc: 0.8263
- Epoch 30/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.0040 - acc: 0.9986Epoch 00030: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0038 - acc: 0.9987 - val_loss: 0.9961 - val_acc: 0.8299
- Epoch 31/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9985Epoch 00031: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0038 - acc: 0.9985 - val_loss: 0.9994 - val_acc: 0.8275
- Epoch 32/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0040 - acc: 0.9988Epoch 00032: val_loss did not improve
- 6680/6680 [==============================] - 1s 171us/step - loss: 0.0039 - acc: 0.9988 - val_loss: 1.0456 - val_acc: 0.8216
- Epoch 33/50
- 6528/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9989Epoch 00033: val_loss did not improve
- 6680/6680 [==============================] - 1s 173us/step - loss: 0.0042 - acc: 0.9990 - val_loss: 1.0431 - val_acc: 0.8335
- Epoch 34/50
- 6592/6680 [============================>.] - ETA: 0s - loss: 0.0042 - acc: 0.9985Epoch 00034: val_loss did not improve
- 6680/6680 [==============================] - 1s 172us/step - loss: 0.0041 - acc: 0.9985 - val_loss: 1.0770 - val_acc: 0.8251
- Epoch 35/50
- 6592/6680 [============================>.] - ETA: 0s - loss: 0.0047 - acc: 0.9986Epoch 00035: val_loss did not improve
- 6680/6680 [==============================] - 1s 172us/step - loss: 0.0047 - acc: 0.9987 - val_loss: 1.0552 - val_acc: 0.8299
- Epoch 36/50
- 6528/6680 [============================>.] - ETA: 0s - loss: 0.0041 - acc: 0.9985Epoch 00036: val_loss did not improve
- 6680/6680 [==============================] - 1s 175us/step - loss: 0.0040 - acc: 0.9985 - val_loss: 1.0564 - val_acc: 0.8275
- Epoch 37/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9988Epoch 00037: val_loss did not improve
- 6680/6680 [==============================] - 1s 171us/step - loss: 0.0043 - acc: 0.9988 - val_loss: 1.0788 - val_acc: 0.8216
- Epoch 38/50
- 6400/6680 [===========================>..] - ETA: 0s - loss: 0.0050 - acc: 0.9989Epoch 00038: val_loss did not improve
- 6680/6680 [==============================] - 1s 171us/step - loss: 0.0048 - acc: 0.9990 - val_loss: 1.0695 - val_acc: 0.8359
- Epoch 39/50
- 6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9989Epoch 00039: val_loss did not improve
- 6680/6680 [==============================] - 1s 169us/step - loss: 0.0047 - acc: 0.9988 - val_loss: 1.1195 - val_acc: 0.8335
- Epoch 40/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.0035 - acc: 0.9986Epoch 00040: val_loss did not improve
- 6680/6680 [==============================] - 1s 171us/step - loss: 0.0039 - acc: 0.9985 - val_loss: 1.0888 - val_acc: 0.8311
- Epoch 41/50
- 6464/6680 [============================>.] - ETA: 0s - loss: 0.0056 - acc: 0.9988Epoch 00041: val_loss did not improve
- 6680/6680 [==============================] - 1s 170us/step - loss: 0.0054 - acc: 0.9988 - val_loss: 1.0891 - val_acc: 0.8275
- Epoch 42/50
- 6400/6680 [===========================>..] - ETA: 0s - loss: 0.0053 - acc: 0.9986Epoch 00042: val_loss did not improve
- 6680/6680 [==============================] - 1s 170us/step - loss: 0.0051 - acc: 0.9987 - val_loss: 1.1164 - val_acc: 0.8347
- Epoch 43/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0051 - acc: 0.9988Epoch 00043: val_loss did not improve
- 6680/6680 [==============================] - 1s 172us/step - loss: 0.0051 - acc: 0.9988 - val_loss: 1.1107 - val_acc: 0.8287
- Epoch 44/50
- 6464/6680 [============================>.] - ETA: 0s - loss: 0.0045 - acc: 0.9986Epoch 00044: val_loss did not improve
- 6680/6680 [==============================] - 1s 168us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1243 - val_acc: 0.8275
- Epoch 45/50
- 6656/6680 [============================>.] - ETA: 0s - loss: 0.0044 - acc: 0.9986Epoch 00045: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0044 - acc: 0.9987 - val_loss: 1.1468 - val_acc: 0.8311
- Epoch 46/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0038 - acc: 0.9986Epoch 00046: val_loss did not improve
- 6680/6680 [==============================] - 1s 166us/step - loss: 0.0038 - acc: 0.9987 - val_loss: 1.1387 - val_acc: 0.8287
- Epoch 47/50
- 6368/6680 [===========================>..] - ETA: 0s - loss: 0.0045 - acc: 0.9987Epoch 00047: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0042 - acc: 0.9988 - val_loss: 1.1349 - val_acc: 0.8311
- Epoch 48/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9986Epoch 00048: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0049 - acc: 0.9985 - val_loss: 1.1403 - val_acc: 0.8323
- Epoch 49/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0054 - acc: 0.9985Epoch 00049: val_loss did not improve
- 6680/6680 [==============================] - 1s 165us/step - loss: 0.0054 - acc: 0.9985 - val_loss: 1.1423 - val_acc: 0.8335
- Epoch 50/50
- 6624/6680 [============================>.] - ETA: 0s - loss: 0.0046 - acc: 0.9985Epoch 00050: val_loss did not improve
- 6680/6680 [==============================] - 1s 164us/step - loss: 0.0045 - acc: 0.9985 - val_loss: 1.1445 - val_acc: 0.8347
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt output_prompt">Out[85]:</div>
- <div class="output_text output_subarea output_execute_result">
- <pre><keras.callbacks.History at 0x7f7cf14bd1d0></pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Load-the-Model-with-the-Best-Validation-Loss">(IMPLEMENTATION) Load the Model with the Best Validation Loss<a class="anchor-link" href="#(IMPLEMENTATION)-Load-the-Model-with-the-Best-Validation-Loss">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [86]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Load the model weights with the best validation loss.</span>
- <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="s1">'saved_models/weights.best.Resnet50_model.hdf5'</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Test-the-Model">(IMPLEMENTATION) Test the Model<a class="anchor-link" href="#(IMPLEMENTATION)-Test-the-Model">¶</a></h3><p>Try out your model on the test dataset of dog images. Ensure that your test accuracy is greater than 60%.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [87]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Calculate classification accuracy on the test dataset.</span>
- <span class="c1"># Get index of predicted dog breed for each image in test set</span>
- <span class="n">Resnet50_predictions</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">Resnet50_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">feature</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)))</span> <span class="k">for</span> <span class="n">feature</span> <span class="ow">in</span> <span class="n">test_Resnet50</span><span class="p">]</span>
- <span class="c1"># Report test accuracy</span>
- <span class="n">test_accuracy</span> <span class="o">=</span> <span class="mi">100</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">Resnet50_predictions</span><span class="p">)</span><span class="o">==</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">test_targets</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">Resnet50_predictions</span><span class="p">)</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Test accuracy: </span><span class="si">%.4f%%</span><span class="s1">'</span> <span class="o">%</span> <span class="n">test_accuracy</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Test accuracy: 83.2536%
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <h3 id="(IMPLEMENTATION)-Predict-Dog-Breed-with-the-Model">(IMPLEMENTATION) Predict Dog Breed with the Model<a class="anchor-link" href="#(IMPLEMENTATION)-Predict-Dog-Breed-with-the-Model">¶</a></h3><p>Write a function that takes an image path as input and returns the dog breed (<code>Affenpinscher</code>, <code>Afghan_hound</code>, etc) that is predicted by your model.</p>
- <p>Similar to the analogous function in Step 5, your function should have three steps:</p>
- <ol>
- <li>Extract the bottleneck features corresponding to the chosen CNN model.</li>
- <li>Supply the bottleneck features as input to the model to return the predicted vector. Note that the argmax of this prediction vector gives the index of the predicted dog breed.</li>
- <li>Use the <code>dog_names</code> array defined in Step 0 of this notebook to return the corresponding breed.</li>
- </ol>
- <p>The functions to extract the bottleneck features can be found in <code>extract_bottleneck_features.py</code>, and they have been imported in an earlier code cell. To obtain the bottleneck features corresponding to your chosen CNN architecture, you need to use the function</p>
- <pre><code>extract_{network}
- </code></pre>
- <p>where <code>{network}</code>, in the above filename, should be one of <code>VGG19</code>, <code>Resnet50</code>, <code>InceptionV3</code>, or <code>Xception</code>.</p>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [88]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Write a function that takes a path to an image as input</span>
- <span class="c1">### and returns the dog breed that is predicted by the model.</span>
- <span class="k">def</span> <span class="nf">Resnet50_predict_breed</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="c1"># extract bottleneck features</span>
- <span class="n">bottleneck_feature</span> <span class="o">=</span> <span class="n">extract_Resnet50</span><span class="p">(</span><span class="n">path_to_tensor</span><span class="p">(</span><span class="n">img_path</span><span class="p">))</span>
- <span class="c1"># obtain predicted vector</span>
- <span class="n">predicted_vector</span> <span class="o">=</span> <span class="n">Resnet50_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">bottleneck_feature</span><span class="p">)</span>
- <span class="c1"># return dog breed that is predicted by the model</span>
- <span class="k">return</span> <span class="n">dog_names</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">predicted_vector</span><span class="p">)]</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step6'></a></p>
- <h2 id="Step-6:-Write-your-Algorithm">Step 6: Write your Algorithm<a class="anchor-link" href="#Step-6:-Write-your-Algorithm">¶</a></h2><p>Write an algorithm that accepts a file path to an image and first determines whether the image contains a human, dog, or neither. Then,</p>
- <ul>
- <li>if a <strong>dog</strong> is detected in the image, return the predicted breed.</li>
- <li>if a <strong>human</strong> is detected in the image, return the resembling dog breed.</li>
- <li>if <strong>neither</strong> is detected in the image, provide output that indicates an error.</li>
- </ul>
- <p>You are welcome to write your own functions for detecting humans and dogs in images, but feel free to use the <code>face_detector</code> and <code>dog_detector</code> functions developed above. You are <strong>required</strong> to use your CNN from Step 5 to predict dog breed.</p>
- <p>Some sample output for our algorithm is provided below, but feel free to design your own user experience!</p>
- <p><img src="images/sample_human_output.png" alt="Sample Human Output"></p>
- <h3 id="(IMPLEMENTATION)-Write-your-Algorithm">(IMPLEMENTATION) Write your Algorithm<a class="anchor-link" href="#(IMPLEMENTATION)-Write-your-Algorithm">¶</a></h3>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [89]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### TODO: Write your algorithm.</span>
- <span class="c1">### Feel free to use as many code cells as needed.</span>
- <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
- <span class="kn">import</span> <span class="nn">matplotlib.image</span> <span class="k">as</span> <span class="nn">mpimg</span>
- <span class="k">def</span> <span class="nf">face_dog_breed</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="n">img</span><span class="o">=</span><span class="n">mpimg</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">img_path</span><span class="p">)</span>
- <span class="n">imgplot</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
- <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
- <span class="k">if</span> <span class="n">face_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Human Face Detected!'</span><span class="p">)</span>
- <span class="k">return</span> <span class="s2">"Looks like a </span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">Resnet50_predict_breed</span><span class="p">(</span><span class="n">img_path</span><span class="p">))</span>
- <span class="k">elif</span> <span class="n">dog_detector</span><span class="p">(</span><span class="n">img_path</span><span class="p">):</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Dog Face Detected'</span><span class="p">)</span>
- <span class="k">return</span> <span class="s2">"It is a </span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">Resnet50_predict_breed</span><span class="p">(</span><span class="n">img_path</span><span class="p">))</span>
- <span class="k">else</span><span class="p">:</span>
- <span class="nb">print</span><span class="p">(</span><span class="s1">'Recheck! There is no dog or human detected in the image!'</span><span class="p">)</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
- </div>
- <div class="inner_cell">
- <div class="text_cell_render border-box-sizing rendered_html">
- <hr>
- <p><a id='step7'></a></p>
- <h2 id="Step-7:-Test-Your-Algorithm">Step 7: Test Your Algorithm<a class="anchor-link" href="#Step-7:-Test-Your-Algorithm">¶</a></h2><p>In this section, you will take your new algorithm for a spin! What kind of dog does the algorithm think that <strong>you</strong> look like? If you have a dog, does it predict your dog's breed accurately? If you have a cat, does it mistakenly think that your cat is a dog?</p>
- <h3 id="(IMPLEMENTATION)-Test-Your-Algorithm-on-Sample-Images!">(IMPLEMENTATION) Test Your Algorithm on Sample Images!<a class="anchor-link" href="#(IMPLEMENTATION)-Test-Your-Algorithm-on-Sample-Images!">¶</a></h3><p>Test your algorithm at least six images on your computer. Feel free to use any images you like. Use at least two human and two dog images.</p>
- <p><strong>Question 6:</strong> Is the output better than you expected :) ? Or worse :( ? Provide at least three possible points of improvement for your algorithm.</p>
- <p><strong>Answer:</strong> The output is about the better than what I expected. The dog breeds were predicted accurately, and human faces were detected. Non-human and non-dog images got an error.</p>
- <h4 id="Improvements:">Improvements:<a class="anchor-link" href="#Improvements:">¶</a></h4><p>Increase the accuracy of the face detector as it sometimes misclassifies dog as humans. In question 1, the percent of detected human faces in dog_files_short is 11.0 %. We can use multiple OpenCV detectors and combine their results for better human face detection.</p>
- <ul>
- <li><p>Enhance the dog detector for Dog Mutts; currently, the algorithm is almost guaranteed to fail for every mixed breed dog.</p>
- </li>
- <li><p>Enhance the returned prediction result as if a returned prediction probability over 95% then it would be approximately proper classification, but when the returned prediction probability is below 50% or somewhat near, then it should not accept the classification.</p>
- </li>
- </ul>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [90]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## TODO: Execute your algorithm from Step 6 on</span>
- <span class="c1">## at least 6 images on your computer.</span>
- <span class="c1">## Feel free to use as many code cells as needed.</span>
- <span class="kn">import</span> <span class="nn">urllib.request</span>
- <span class="n">urls</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'https://www.gbpolice.org/images/K9/GBPD_DOG_IMG02.jpg'</span><span class="p">,</span>
- <span class="s1">'https://vetstreet-brightspot.s3.amazonaws.com/e5/b4/ca8e2af94c3883e042c1f610fec4/saint-bernard-ap-1fjqfu-645-x-380.jpg'</span><span class="p">,</span>
- <span class="s1">'https://upload.wikimedia.org/wikipedia/commons/thumb/6/6b/Taka_Shiba.jpg/1200px-Taka_Shiba.jpg'</span><span class="p">,</span>
- <span class="s1">'http://mmusicmag.com/m/wp-content/uploads/2015/01/Slash-Issue-No37.jpg'</span><span class="p">,</span>
- <span class="s1">'http://assets.blabbermouth.net/media/daviddraimansolo2015_638.jpg'</span><span class="p">,</span>
- <span class="s1">'https://dmi3w0goirzgw.cloudfront.net/gallery-images/840x560/406000/200/406260.jpg'</span><span class="p">,</span>
- <span class="s1">'https://www.pets4homes.co.uk/images/articles/771/large/cat-lifespan-the-life-expectancy-of-cats-568e40723c336.jpg'</span>
- <span class="p">]</span>
- <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">url</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">urls</span><span class="p">):</span>
- <span class="n">urllib</span><span class="o">.</span><span class="n">request</span><span class="o">.</span><span class="n">urlretrieve</span><span class="p">(</span><span class="n">url</span><span class="p">,</span><span class="s1">'img</span><span class="si">{}</span><span class="s1">.jpg'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- </div>
- <div class="cell border-box-sizing code_cell rendered">
- <div class="input">
- <div class="prompt input_prompt">In [91]:</div>
- <div class="inner_cell">
- <div class="input_area">
- <div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img1.jpg'</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img2.jpg'</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img3.jpg'</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img4.jpg'</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img5.jpg'</span><span class="p">))</span>
- <span class="nb">print</span><span class="p">(</span><span class="n">face_dog_breed</span><span class="p">(</span><span class="s1">'img6.jpg'</span><span class="p">))</span>
- </pre></div>
- </div>
- </div>
- </div>
- <div class="output_wrapper">
- <div class="output">
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Dog Face Detected
- It is a in/126.Saint_bernard
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Dog Face Detected
- It is a in/004.Akita
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Human Face Detected!
- Looks like a in/041.Bullmastiff
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Human Face Detected!
- Looks like a in/127.Silky_terrier
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Recheck! There is no dog or human detected in the image!
- None
- </pre>
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_png output_subarea ">
- <img src="data:image/png;base64,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
- "
- >
- </div>
- </div>
- <div class="output_area">
- <div class="prompt"></div>
- <div class="output_subarea output_stream output_stdout output_text">
- <pre>Recheck! There is no dog or human detected in the image!
- None
- </pre>
- </div>
- </div>
- </div>
- </div>
- </div>
- </div>
- </div>
- </body>
-
- </html>
|
