models.json 246 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798991001011021031041051061071081091101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491501511521531541551561571581591601611621631641651661671681691701711721731741751761771781791801811821831841851861871881891901911921931941951961971981992002012022032042052062072082092102112122132142152162172182192202212222232242252262272282292302312322332342352362372382392402412422432442452462472482492502512522532542552562572582592602612622632642652662672682692702712722732742752762772782792802812822832842852862872882892902912922932942952962972982993003013023033043053063073083093103113123133143153163173183193203213223233243253263273283293303313323333343353363373383393403413423433443453463473483493503513523533543553563573583593603613623633643653663673683693703713723733743753763773783793803813823833843853863873883893903913923933943953963973983994004014024034044054064074084094104114124134144154164174184194204214224234244254264274284294304314324334344354364374384394404414424434444454464474484494504514524534544554564574584594604614624634644654664674684694704714724734744754764774784794804814824834844854864874884894904914924934944954964974984995005015025035045055065075085095105115125135145155165175185195205215225235245255265275285295305315325335345355365375385395405415425435445455465475485495505515525535545555565575585595605615625635645655665675685695705715725735745755765775785795805815825835845855865875885895905915925935945955965975985996006016026036046056066076086096106116126136146156166176186196206216226236246256266276286296306316326336346356366376386396406416426436446456466476486496506516526536546556566576586596606616626636646656666676686696706716726736746756766776786796806816826836846856866876886896906916926936946956966976986997007017027037047057067077087097107117127137147157167177187197207217227237247257267277287297307317327337347357367377387397407417427437447457467477487497507517527537547557567577587597607617627637647657667677687697707717727737747757767777787797807817827837847857867877887897907917927937947957967977987998008018028038048058068078088098108118128138148158168178188198208218228238248258268278288298308318328338348358368378388398408418428438448458468478488498508518528538548558568578588598608618628638648658668678688698708718728738748758768778788798808818828838848858868878888898908918928938948958968978988999009019029039049059069079089099109119129139149159169179189199209219229239249259269279289299309319329339349359369379389399409419429439449459469479489499509519529539549559569579589599609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959969979989991000100110021003100410051006100710081009101010111012101310141015101610171018101910201021102210231024102510261027102810291030103110321033103410351036103710381039104010411042104310441045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810891090109110921093109410951096109710981099110011011102110311041105110611071108110911101111111211131114111511161117111811191120112111221123112411251126112711281129113011311132113311341135113611371138113911401141114211431144114511461147114811491150115111521153115411551156115711581159116011611162116311641165116611671168116911701171117211731174117511761177117811791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240124112421243124412451246124712481249125012511252125312541255125612571258125912601261126212631264126512661267126812691270127112721273127412751276127712781279128012811282128312841285128612871288128912901291129212931294129512961297129812991300130113021303130413051306130713081309131013111312131313141315131613171318131913201321132213231324132513261327132813291330133113321333133413351336133713381339134013411342134313441345134613471348134913501351135213531354135513561357135813591360136113621363136413651366136713681369137013711372137313741375137613771378137913801381138213831384138513861387138813891390139113921393139413951396139713981399140014011402140314041405140614071408140914101411141214131414141514161417141814191420142114221423142414251426142714281429143014311432143314341435143614371438143914401441144214431444144514461447144814491450145114521453145414551456145714581459146014611462146314641465146614671468146914701471147214731474147514761477147814791480148114821483148414851486148714881489149014911492149314941495149614971498149915001501150215031504150515061507150815091510151115121513151415151516151715181519152015211522152315241525152615271528152915301531153215331534153515361537153815391540154115421543154415451546154715481549155015511552155315541555155615571558155915601561156215631564156515661567156815691570157115721573157415751576157715781579158015811582158315841585158615871588158915901591159215931594159515961597159815991600160116021603160416051606160716081609161016111612161316141615161616171618161916201621162216231624162516261627162816291630163116321633163416351636163716381639164016411642164316441645164616471648164916501651165216531654165516561657165816591660166116621663166416651666166716681669167016711672167316741675167616771678167916801681168216831684168516861687168816891690169116921693169416951696169716981699170017011702170317041705170617071708170917101711171217131714171517161717171817191720172117221723172417251726172717281729173017311732173317341735173617371738173917401741174217431744174517461747174817491750175117521753175417551756175717581759176017611762176317641765176617671768176917701771177217731774177517761777177817791780178117821783178417851786178717881789179017911792179317941795179617971798179918001801180218031804180518061807180818091810181118121813181418151816181718181819182018211822182318241825182618271828182918301831183218331834183518361837183818391840184118421843184418451846184718481849185018511852185318541855185618571858185918601861186218631864186518661867186818691870187118721873187418751876187718781879188018811882188318841885188618871888188918901891189218931894189518961897189818991900190119021903190419051906190719081909191019111912191319141915191619171918191919201921192219231924192519261927192819291930193119321933193419351936193719381939194019411942194319441945194619471948194919501951195219531954195519561957195819591960196119621963196419651966196719681969197019711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044204520462047204820492050205120522053205420552056205720582059206020612062206320642065206620672068206920702071207220732074207520762077207820792080208120822083208420852086208720882089209020912092209320942095209620972098209921002101210221032104210521062107210821092110211121122113211421152116211721182119212021212122212321242125212621272128212921302131213221332134213521362137213821392140214121422143214421452146214721482149215021512152215321542155215621572158215921602161216221632164216521662167216821692170217121722173217421752176217721782179218021812182218321842185218621872188218921902191219221932194219521962197219821992200220122022203220422052206220722082209221022112212221322142215221622172218221922202221222222232224222522262227222822292230223122322233223422352236223722382239224022412242224322442245224622472248224922502251225222532254225522562257225822592260226122622263226422652266226722682269227022712272227322742275227622772278227922802281228222832284228522862287228822892290229122922293229422952296229722982299230023012302230323042305230623072308230923102311231223132314231523162317231823192320232123222323232423252326232723282329233023312332233323342335233623372338233923402341234223432344234523462347234823492350235123522353235423552356235723582359236023612362236323642365236623672368236923702371237223732374237523762377237823792380238123822383238423852386238723882389239023912392239323942395239623972398239924002401240224032404240524062407240824092410241124122413241424152416241724182419242024212422242324242425242624272428242924302431243224332434243524362437243824392440244124422443244424452446244724482449245024512452245324542455245624572458245924602461246224632464246524662467246824692470247124722473247424752476247724782479248024812482248324842485248624872488248924902491249224932494249524962497249824992500250125022503250425052506250725082509251025112512251325142515251625172518251925202521252225232524252525262527252825292530253125322533253425352536253725382539254025412542254325442545254625472548254925502551255225532554255525562557255825592560256125622563256425652566256725682569257025712572257325742575257625772578257925802581258225832584258525862587258825892590259125922593259425952596259725982599260026012602260326042605260626072608260926102611261226132614261526162617261826192620262126222623262426252626262726282629263026312632263326342635263626372638263926402641264226432644264526462647264826492650265126522653265426552656265726582659266026612662266326642665266626672668266926702671267226732674267526762677267826792680268126822683268426852686268726882689269026912692269326942695269626972698269927002701270227032704270527062707270827092710271127122713271427152716271727182719272027212722272327242725272627272728272927302731273227332734273527362737273827392740274127422743274427452746274727482749275027512752275327542755275627572758275927602761276227632764276527662767276827692770277127722773277427752776277727782779278027812782278327842785278627872788278927902791279227932794279527962797279827992800280128022803280428052806280728082809281028112812281328142815281628172818281928202821282228232824282528262827282828292830283128322833283428352836283728382839284028412842284328442845284628472848284928502851285228532854285528562857285828592860286128622863286428652866286728682869287028712872287328742875287628772878287928802881288228832884288528862887288828892890289128922893289428952896289728982899290029012902290329042905290629072908290929102911291229132914291529162917291829192920292129222923292429252926292729282929293029312932293329342935293629372938293929402941294229432944294529462947294829492950295129522953295429552956295729582959296029612962296329642965296629672968296929702971297229732974297529762977297829792980298129822983298429852986298729882989299029912992299329942995299629972998299930003001300230033004300530063007300830093010301130123013301430153016301730183019302030213022302330243025302630273028302930303031303230333034303530363037303830393040304130423043304430453046304730483049305030513052305330543055305630573058305930603061306230633064306530663067306830693070307130723073307430753076307730783079308030813082308330843085308630873088308930903091309230933094309530963097309830993100310131023103310431053106310731083109311031113112311331143115311631173118311931203121312231233124312531263127312831293130313131323133313431353136313731383139314031413142314331443145314631473148314931503151315231533154315531563157315831593160316131623163316431653166316731683169317031713172317331743175317631773178317931803181318231833184318531863187318831893190319131923193319431953196319731983199320032013202320332043205320632073208320932103211321232133214321532163217321832193220322132223223322432253226322732283229323032313232323332343235323632373238323932403241324232433244324532463247324832493250325132523253325432553256325732583259326032613262326332643265326632673268326932703271327232733274327532763277327832793280328132823283328432853286328732883289329032913292329332943295329632973298329933003301330233033304330533063307330833093310331133123313331433153316331733183319332033213322332333243325332633273328332933303331333233333334333533363337333833393340334133423343334433453346334733483349335033513352335333543355335633573358335933603361336233633364336533663367336833693370337133723373337433753376337733783379338033813382338333843385338633873388338933903391339233933394339533963397339833993400340134023403340434053406340734083409341034113412341334143415341634173418341934203421342234233424342534263427342834293430343134323433343434353436343734383439344034413442344334443445344634473448344934503451345234533454345534563457345834593460346134623463346434653466346734683469347034713472347334743475347634773478347934803481348234833484348534863487348834893490349134923493349434953496349734983499350035013502350335043505350635073508350935103511351235133514351535163517351835193520352135223523352435253526352735283529353035313532353335343535353635373538353935403541354235433544354535463547354835493550355135523553355435553556355735583559356035613562356335643565356635673568356935703571357235733574357535763577357835793580358135823583358435853586358735883589359035913592359335943595359635973598359936003601360236033604360536063607360836093610361136123613361436153616361736183619362036213622362336243625362636273628362936303631363236333634363536363637363836393640364136423643364436453646364736483649365036513652365336543655365636573658365936603661366236633664366536663667366836693670367136723673367436753676367736783679368036813682368336843685368636873688368936903691369236933694369536963697369836993700370137023703370437053706370737083709371037113712371337143715371637173718371937203721372237233724372537263727372837293730373137323733373437353736373737383739374037413742374337443745374637473748374937503751375237533754375537563757375837593760376137623763376437653766376737683769377037713772377337743775377637773778377937803781378237833784378537863787378837893790379137923793379437953796379737983799380038013802380338043805380638073808380938103811381238133814381538163817381838193820382138223823382438253826382738283829383038313832383338343835383638373838383938403841384238433844384538463847384838493850385138523853385438553856385738583859386038613862386338643865386638673868386938703871387238733874387538763877387838793880388138823883388438853886388738883889389038913892389338943895389638973898389939003901390239033904390539063907390839093910391139123913391439153916391739183919392039213922392339243925392639273928392939303931393239333934393539363937393839393940394139423943394439453946394739483949395039513952395339543955395639573958395939603961396239633964396539663967396839693970397139723973397439753976397739783979398039813982398339843985398639873988398939903991399239933994399539963997399839994000400140024003400440054006400740084009401040114012401340144015401640174018401940204021402240234024402540264027402840294030403140324033403440354036403740384039404040414042404340444045404640474048404940504051405240534054405540564057405840594060406140624063406440654066406740684069407040714072407340744075407640774078407940804081408240834084408540864087408840894090409140924093409440954096409740984099410041014102410341044105410641074108410941104111411241134114411541164117411841194120412141224123412441254126412741284129413041314132413341344135413641374138413941404141414241434144414541464147414841494150415141524153415441554156415741584159416041614162416341644165416641674168416941704171417241734174417541764177417841794180418141824183418441854186418741884189419041914192419341944195419641974198419942004201420242034204420542064207420842094210421142124213421442154216421742184219422042214222422342244225422642274228422942304231423242334234423542364237423842394240424142424243424442454246424742484249425042514252425342544255425642574258425942604261426242634264426542664267426842694270427142724273427442754276427742784279428042814282428342844285428642874288428942904291429242934294429542964297429842994300430143024303430443054306430743084309431043114312431343144315431643174318431943204321432243234324432543264327432843294330433143324333433443354336433743384339434043414342434343444345434643474348434943504351435243534354435543564357435843594360436143624363436443654366436743684369437043714372437343744375437643774378437943804381438243834384438543864387438843894390439143924393439443954396439743984399440044014402440344044405440644074408440944104411441244134414441544164417441844194420442144224423442444254426442744284429443044314432443344344435443644374438443944404441444244434444444544464447444844494450445144524453445444554456445744584459446044614462446344644465446644674468446944704471447244734474447544764477447844794480448144824483448444854486448744884489449044914492449344944495449644974498449945004501450245034504450545064507450845094510451145124513451445154516451745184519452045214522452345244525452645274528452945304531453245334534453545364537453845394540454145424543454445454546454745484549455045514552455345544555455645574558455945604561456245634564456545664567456845694570457145724573457445754576457745784579458045814582458345844585458645874588458945904591459245934594459545964597459845994600460146024603460446054606460746084609461046114612461346144615461646174618461946204621462246234624462546264627462846294630463146324633463446354636463746384639464046414642464346444645464646474648464946504651465246534654465546564657465846594660466146624663466446654666466746684669467046714672467346744675467646774678467946804681468246834684468546864687468846894690469146924693469446954696469746984699470047014702470347044705470647074708470947104711471247134714471547164717471847194720472147224723472447254726472747284729473047314732473347344735473647374738473947404741474247434744474547464747474847494750475147524753475447554756475747584759476047614762476347644765476647674768476947704771477247734774477547764777477847794780478147824783478447854786478747884789479047914792479347944795479647974798479948004801480248034804480548064807480848094810481148124813481448154816481748184819482048214822482348244825482648274828482948304831483248334834483548364837483848394840484148424843484448454846484748484849485048514852485348544855485648574858485948604861486248634864486548664867486848694870487148724873487448754876487748784879488048814882488348844885488648874888488948904891489248934894489548964897489848994900490149024903490449054906490749084909491049114912491349144915491649174918491949204921492249234924492549264927492849294930493149324933493449354936493749384939494049414942494349444945494649474948494949504951495249534954495549564957495849594960496149624963496449654966496749684969497049714972497349744975497649774978497949804981498249834984498549864987498849894990499149924993499449954996499749984999500050015002500350045005500650075008500950105011501250135014501550165017501850195020502150225023502450255026502750285029503050315032503350345035503650375038503950405041504250435044504550465047504850495050505150525053505450555056505750585059506050615062506350645065506650675068506950705071507250735074507550765077507850795080508150825083508450855086508750885089509050915092509350945095509650975098509951005101510251035104510551065107510851095110511151125113511451155116511751185119512051215122512351245125512651275128512951305131513251335134513551365137513851395140514151425143514451455146514751485149515051515152515351545155515651575158515951605161516251635164516551665167516851695170517151725173517451755176517751785179518051815182518351845185518651875188518951905191519251935194519551965197519851995200520152025203520452055206520752085209521052115212521352145215521652175218521952205221522252235224522552265227522852295230523152325233523452355236523752385239524052415242524352445245524652475248524952505251525252535254525552565257525852595260526152625263526452655266526752685269527052715272527352745275527652775278527952805281528252835284528552865287528852895290529152925293529452955296529752985299530053015302530353045305530653075308530953105311531253135314531553165317531853195320532153225323532453255326532753285329533053315332533353345335533653375338533953405341534253435344534553465347534853495350535153525353535453555356535753585359536053615362536353645365536653675368536953705371537253735374537553765377537853795380538153825383538453855386538753885389539053915392539353945395539653975398539954005401540254035404540554065407540854095410541154125413541454155416541754185419542054215422542354245425542654275428542954305431543254335434543554365437543854395440544154425443544454455446544754485449545054515452545354545455545654575458545954605461546254635464546554665467546854695470547154725473547454755476547754785479548054815482548354845485548654875488548954905491549254935494549554965497549854995500550155025503550455055506550755085509551055115512551355145515551655175518551955205521552255235524552555265527552855295530553155325533553455355536553755385539554055415542554355445545554655475548554955505551555255535554555555565557555855595560556155625563556455655566556755685569557055715572557355745575557655775578557955805581558255835584558555865587558855895590559155925593559455955596559755985599560056015602560356045605560656075608560956105611561256135614561556165617561856195620562156225623562456255626562756285629563056315632563356345635563656375638563956405641564256435644564556465647564856495650565156525653565456555656565756585659566056615662566356645665566656675668566956705671567256735674567556765677567856795680568156825683568456855686568756885689569056915692569356945695569656975698569957005701570257035704570557065707570857095710571157125713571457155716571757185719572057215722572357245725572657275728572957305731573257335734573557365737573857395740574157425743574457455746574757485749575057515752575357545755575657575758575957605761576257635764576557665767576857695770577157725773577457755776577757785779578057815782578357845785578657875788578957905791579257935794579557965797579857995800580158025803580458055806580758085809581058115812581358145815581658175818581958205821582258235824582558265827582858295830583158325833583458355836583758385839584058415842584358445845584658475848584958505851585258535854585558565857585858595860586158625863586458655866586758685869587058715872587358745875587658775878587958805881588258835884588558865887588858895890589158925893589458955896589758985899590059015902590359045905590659075908590959105911591259135914591559165917591859195920592159225923592459255926592759285929593059315932593359345935593659375938593959405941
  1. [
  2. {
  3. "type": "any",
  4. "target": "config.json",
  5. "source": "https://github.com/lutzroeder/netron/files/5398758/config.json.zip[config.json]",
  6. "error": "Invalid file content. File contains keras-yolo2 configuation.",
  7. "link": "https://github.com/lutzroeder/netron/issues/458"
  8. },
  9. {
  10. "type": "any",
  11. "target": "config.pbtxt",
  12. "source": "https://github.com/lutzroeder/netron/files/5398767/config.pbtxt.zip[config.pbtxt]",
  13. "error": "Invalid file content. File contains Triton Inference Server configuration.",
  14. "link": "https://github.com/NVIDIA/triton-inference-server"
  15. },
  16. {
  17. "type": "any",
  18. "target": "empty.zip",
  19. "source": "https://github.com/lutzroeder/netron/files/5581087/empty.zip",
  20. "error": "Invalid file content. File contains Zip archive in 'empty.zip'.",
  21. "link": "https://github.com/lutzroeder/netron/issues/458"
  22. },
  23. {
  24. "type": "any",
  25. "target": "imagenet_2012_challenge_label_map_proto.pbtxt",
  26. "source": "https://raw.githubusercontent.com/dmlc/web-data/master/tensorflow/models/InceptionV1/imagenet_2012_challenge_label_map_proto.pbtxt",
  27. "error": "Invalid file content. File contains ImageNet LabelMap data."
  28. },
  29. {
  30. "type": "any",
  31. "target": "labelmap.pbtxt",
  32. "source": "https://github.com/lutzroeder/netron/files/5398649/labelmap.zip[labelmap.pbtxt]",
  33. "error": "Invalid file content. File contains StringIntLabelMapProto data.",
  34. "link": "https://github.com/lutzroeder/netron/issues/458"
  35. },
  36. {
  37. "type": "any",
  38. "target": "gzip_invalid_archive.tar.gz",
  39. "source": "https://github.com/lutzroeder/netron/files/5468427/gzip_invalid_archive.tar.gz",
  40. "error": "Invalid gzip archive in 'gzip_invalid_archive.tar.gz'.",
  41. "link": "https://github.com/lutzroeder/netron/issues/249"
  42. },
  43. {
  44. "type": "any",
  45. "target": "gzip_invalid_compression.tar.gz",
  46. "source": "https://github.com/lutzroeder/netron/files/3027193/gzip_invalid_compression.tar.gz",
  47. "error": "Invalid compression method '1' in 'gzip_invalid_compression.tar.gz'.",
  48. "link": "https://github.com/lutzroeder/netron/issues/249"
  49. },
  50. {
  51. "type": "any",
  52. "target": "invalid_git_lfs.mlmodel",
  53. "source": "https://github.com/lutzroeder/netron/files/4432767/invalid_git_lfs.mlmodel.zip[invalid_git_lfs.mlmodel]",
  54. "error": "Invalid file content. File contains Git LFS header.",
  55. "link": "https://github.com/lutzroeder/netron/issues/458"
  56. },
  57. {
  58. "type": "any",
  59. "target": "invalid_html.mlmodel.zip",
  60. "source": "https://github.com/lutzroeder/netron/files/4432768/invalid_html.mlmodel.zip",
  61. "error": "Invalid file content. File contains HTML markup.",
  62. "link": "https://github.com/lutzroeder/netron/issues/458"
  63. },
  64. {
  65. "type": "any",
  66. "target": "invalid_html.tflite",
  67. "source": "https://github.com/lutzroeder/netron/files/4432789/invalid_html.tflite.zip[invalid_html.tflite]",
  68. "error": "Invalid file content. File contains HTML markup.",
  69. "link": "https://github.com/lutzroeder/netron/issues/458"
  70. },
  71. {
  72. "type": "any",
  73. "target": "vk_swiftshader_icd.json",
  74. "source": "https://github.com/lutzroeder/netron/files/5398770/vk_swiftshader_icd.json.zip[vk_swiftshader_icd.json]",
  75. "error": "Invalid file content. File contains Vulkan SwiftShader ICD manifest.",
  76. "link": "https://github.com/lutzroeder/netron/issues/458"
  77. },
  78. {
  79. "type": "any",
  80. "target": "yolo-1c.meta",
  81. "source": "https://github.com/lutzroeder/netron/files/5398632/yolo-1c.meta.zip[yolo-1c.meta]",
  82. "error": "Invalid file content. File contains Darkflow metadata.",
  83. "link": "https://github.com/lutzroeder/netron/issues/458"
  84. },
  85. {
  86. "type": "any",
  87. "target": "zip_invalid_archive.zip",
  88. "source": "https://github.com/lutzroeder/netron/files/5468425/zip_invalid_archive.zip",
  89. "error": "Invalid Zip archive in 'zip_invalid_archive.zip'.",
  90. "link": "https://github.com/lutzroeder/netron/issues/250"
  91. },
  92. {
  93. "type": "armnn",
  94. "target": "simple_network.armnn",
  95. "source": "https://github.com/lutzroeder/netron/files/4951689/simple_network.zip[simple_network.armnn]",
  96. "format": "Arm NN",
  97. "link": "https://github.com/lutzroeder/netron/issues/515"
  98. },
  99. {
  100. "type": "armnn",
  101. "target": "ssd_mobilenet_v3_small_coco_2019_08_14.armnn",
  102. "source": "https://raw.githubusercontent.com/ARM-software/armnn/master/samples/serialized/ssd_mobilenet_v3_small_coco_2019_08_14.armnn",
  103. "format": "Arm NN",
  104. "link": "https://github.com/ARM-software/armnn"
  105. },
  106. {
  107. "type": "armnn",
  108. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q8.armnn",
  109. "source": "https://github.com/lutzroeder/netron/files/3839429/samples.zip[ssd_mobilenet_v3_small_coco_2019_08_14_q8.armnn]",
  110. "format": "Arm NN",
  111. "link": "https://github.com/lutzroeder/netron/issues/515"
  112. },
  113. {
  114. "type": "armnn",
  115. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q8.json",
  116. "source": "https://github.com/lutzroeder/netron/files/4945145/ssd_mobilenet_v3_small_coco_2019_08_14_q8.zip[ssd_mobilenet_v3_small_coco_2019_08_14_q8.json]",
  117. "format": "Arm NN",
  118. "link": "https://github.com/lutzroeder/netron/issues/515"
  119. },
  120. {
  121. "type": "armnn",
  122. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q16.armnn",
  123. "source": "https://github.com/lutzroeder/netron/files/3839429/samples.zip[ssd_mobilenet_v3_small_coco_2019_08_14_q16.armnn]",
  124. "format": "Arm NN",
  125. "link": "https://github.com/lutzroeder/netron/issues/515"
  126. },
  127. {
  128. "type": "barracuda",
  129. "target": "3DBallHardLearning.nn",
  130. "source": "https://raw.githubusercontent.com/reinforcement-learning-kr/rl_bootcamp/master/UnitySDK/Assets/ML-Agents/Examples/3DBall/TFModels/3DBallHardLearning.nn",
  131. "format": "Barracuda v16",
  132. "link": "https://github.com/reinforcement-learning-kr/rl_bootcamp"
  133. },
  134. {
  135. "type": "barracuda",
  136. "target": "continuous2vis8vec2action.nn",
  137. "source": "https://raw.githubusercontent.com/Unity-Technologies/ml-agents/master/com.unity.ml-agents/Tests/Editor/TestModels/continuous2vis8vec2action.nn",
  138. "format": "Barracuda v16",
  139. "link": "https://github.com/Unity-Technologies/ml-agents"
  140. },
  141. {
  142. "type": "barracuda",
  143. "target": "mobilenet_v2.nn",
  144. "source": "https://raw.githubusercontent.com/Syn-McJ/TFClassify-Unity-Barracuda/master/Assets/Resources/mobilenet_v2.nn",
  145. "format": "Barracuda v16",
  146. "link": "https://github.com/Syn-McJ/TFClassify-Unity-Barracuda"
  147. },
  148. {
  149. "type": "barracuda",
  150. "target": "SoccerTwos.nn",
  151. "source": "https://raw.githubusercontent.com/Unity-Technologies/ml-agents/master/Project/Assets/ML-Agents/Examples/Soccer/TFModels/SoccerTwos.nn",
  152. "format": "Barracuda v16",
  153. "link": "https://github.com/Unity-Technologies/ml-agents"
  154. },
  155. {
  156. "type": "barracuda",
  157. "target": "HighQualityTrainedModel.nn",
  158. "source": "https://digital-standard.com/threedpose/models/HighQualityTrainedModel.nn",
  159. "format": "Barracuda v16",
  160. "link": "https://github.com/digista-tanaka/ThreeDPoseTracker"
  161. },
  162. {
  163. "type": "bigdl",
  164. "target": "analytics-zoo_alexnet-quantize_imagenet_0.1.0.model",
  165. "source": "https://sourceforge.net/projects/analytics-zoo/files/analytics-zoo-models/image-classification/analytics-zoo_alexnet-quantize_imagenet_0.1.0.model/download",
  166. "format": "BigDL v0.5.0",
  167. "link": "https://analytics-zoo.github.io/master/#ProgrammingGuide/image-classification"
  168. },
  169. {
  170. "type": "bigdl",
  171. "target": "analytics-zoo_inception-v1_imagenet_0.1.0.model",
  172. "source": "https://sourceforge.net/projects/analytics-zoo/files/analytics-zoo-models/image-classification/analytics-zoo_inception-v1_imagenet_0.1.0.model/download",
  173. "format": "BigDL v0.5.0",
  174. "link": "https://github.com/intel-analytics/analytics-zoo/tree/master/pyzoo/zoo/examples/nnframes/imageTransferLearning"
  175. },
  176. {
  177. "type": "bigdl",
  178. "target": "analytics-zoo_squeezenet-quantize_imagenet_0.1.0.model",
  179. "source": "https://sourceforge.net/projects/analytics-zoo/files/analytics-zoo-models/image-classification/analytics-zoo_squeezenet-quantize_imagenet_0.1.0.model/download",
  180. "format": "BigDL v0.5.0",
  181. "link": "https://analytics-zoo.github.io/master/#ProgrammingGuide/image-classification"
  182. },
  183. {
  184. "type": "caffe",
  185. "target": "1D_lstm.prototxt",
  186. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/1D_lstm.prototxt",
  187. "format": "Caffe v2",
  188. "link": "https://github.com/cwlacewe/netscope"
  189. },
  190. {
  191. "type": "caffe",
  192. "target": "age_net.caffemodel",
  193. "source": "https://raw.githubusercontent.com/eveningglow/age-and-gender-classification/master/model/age_net.caffemodel",
  194. "format": "Caffe v1",
  195. "link": "https://github.com/eveningglow/age-and-gender-classification"
  196. },
  197. {
  198. "type": "caffe",
  199. "target": "alexnet.prototxt",
  200. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/alexnet.prototxt",
  201. "format": "Caffe v2",
  202. "link": "https://github.com/cwlacewe/netscope"
  203. },
  204. {
  205. "type": "caffe",
  206. "target": "AlexNet_SalObjSub.caffemodel",
  207. "source": "http://www.cs.bu.edu/groups/ivc/data/SOS/AlexNet_SalObjSub.caffemodel",
  208. "format": "Caffe v1",
  209. "link": "https://github.com/natanielruiz/net-archive/tree/master/salient-object-alexnet"
  210. },
  211. {
  212. "type": "caffe",
  213. "target": "AlexNet_SalObjSub_deploy.prototxt",
  214. "source": "https://raw.githubusercontent.com/natanielruiz/net-archive/master/salient-object-alexnet/deploy.prototxt",
  215. "format": "Caffe v1",
  216. "link": "https://github.com/natanielruiz/net-archive/tree/master/salient-object-alexnet"
  217. },
  218. {
  219. "type": "caffe",
  220. "target": "autocolorize.prototxt",
  221. "source": "https://github.com/lutzroeder/netron/files/4923194/autocolorize.zip[autocolorize.prototxt]",
  222. "format": "Caffe v2",
  223. "link": "https://github.com/lutzroeder/netron/issues/276"
  224. },
  225. {
  226. "type": "caffe",
  227. "target": "bvlc_alexnet.caffemodel",
  228. "source": "http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel",
  229. "format": "Caffe v1",
  230. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_alexnet"
  231. },
  232. {
  233. "type": "caffe",
  234. "target": "bvlc_caffenet_full_conv.prototxt",
  235. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/net_surgery/bvlc_caffenet_full_conv.prototxt",
  236. "format": "Caffe v2",
  237. "link": "https://github.com/BVLC/caffe/tree/master/examples/net_surgery"
  238. },
  239. {
  240. "type": "caffe",
  241. "target": "bvlc_alexnet_deploy.prototxt",
  242. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/models/bvlc_alexnet/deploy.prototxt",
  243. "format": "Caffe v2",
  244. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_alexnet"
  245. },
  246. {
  247. "type": "caffe",
  248. "target": "bvlc_googlenet.caffemodel",
  249. "source": "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel",
  250. "format": "Caffe v1",
  251. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet"
  252. },
  253. {
  254. "type": "caffe",
  255. "target": "bvlc_reference_caffenet.caffemodel",
  256. "source": "http://dl.caffe.berkeleyvision.org/bvlc_reference_caffenet.caffemodel",
  257. "format": "Caffe v1",
  258. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_reference_caffenet"
  259. },
  260. {
  261. "type": "caffe",
  262. "target": "caffe_array.prototxt",
  263. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_array.prototxt]",
  264. "format": "Caffe v2",
  265. "link": "https://github.com/lutzroeder/netron/issues/276"
  266. },
  267. {
  268. "type": "caffe",
  269. "target": "caffe_invalid_file.caffemodel",
  270. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_invalid_file.caffemodel]",
  271. "error": "File format is not caffe.NetParameter (Invalid type 4 at offset 11) in 'caffe_invalid_file.caffemodel'.",
  272. "link": "https://github.com/lutzroeder/netron/issues/276"
  273. },
  274. {
  275. "type": "caffe",
  276. "target": "caffe_invalid_semicolon.prototxt",
  277. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_invalid_semicolon.prototxt]",
  278. "error": "File text format is not caffe.NetParameter (Unexpected token ';' at 7:18) in 'caffe_invalid_semicolon.prototxt'.",
  279. "link": "https://github.com/lutzroeder/netron/issues/276"
  280. },
  281. {
  282. "type": "caffe",
  283. "target": "caffe_semicolon.prototxt",
  284. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_semicolon.prototxt]",
  285. "format": "Caffe v2",
  286. "link": "https://github.com/lutzroeder/netron/issues/276"
  287. },
  288. {
  289. "type": "caffe",
  290. "target": "caffenet.prototxt",
  291. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/caffenet.prototxt",
  292. "format": "Caffe v2",
  293. "link": "https://github.com/cwlacewe/netscope"
  294. },
  295. {
  296. "type": "caffe",
  297. "target": "cifar10_full_sigmoid_solver_bn.prototxt,cifar10_full_sigmoid_train_test_bn.prototxt",
  298. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/cifar10/cifar10_full_sigmoid_solver_bn.prototxt,https://raw.githubusercontent.com/BVLC/caffe/master/examples/cifar10/cifar10_full_sigmoid_train_test_bn.prototxt",
  299. "format": "Caffe v2",
  300. "link": "https://github.com/BVLC/caffe/tree/master/examples/cifar10"
  301. },
  302. {
  303. "type": "caffe",
  304. "target": "cityscapes_713_pspnet.prototxt",
  305. "source": "https://gist.githubusercontent.com/meetshah1995/6bfb59e6a3cfcb4e2bb8d47f827c2928/raw/cd1ea0091d6f9b40530d3390dad41fed60bd02aa/cityscapes_713_pspnet.prototxt",
  306. "format": "Caffe v2",
  307. "link": "https://gist.github.com/meetshah1995/6bfb59e6a3cfcb4e2bb8d47f827c2928"
  308. },
  309. {
  310. "type": "caffe",
  311. "target": "conv.prototxt",
  312. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/net_surgery/conv.prototxt",
  313. "format": "Caffe v2",
  314. "link": "https://github.com/BVLC/caffe/tree/master/examples/net_surgery"
  315. },
  316. {
  317. "type": "caffe",
  318. "target": "deepyeast.caffemodel",
  319. "source": "https://kodu.ut.ee/~leopoldp/2016_DeepYeast/code/caffe_model/HOwt_png_vgg_A_bn_iter_130000.caffemodel",
  320. "format": "Caffe v2",
  321. "link": "https://github.com/BVLC/caffe/wiki/Model-Zoo#deepyeast"
  322. },
  323. {
  324. "type": "caffe",
  325. "target": "DenseNet_169.prototxt",
  326. "source": "https://raw.githubusercontent.com/shicai/DenseNet-Caffe/master/DenseNet_169.prototxt",
  327. "format": "Caffe v2",
  328. "link": "https://github.com/shicai/DenseNet-Caffe"
  329. },
  330. {
  331. "type": "caffe",
  332. "target": "deploy_iResNet_ROB.tpl.prototxt",
  333. "source": "https://raw.githubusercontent.com/leonzfa/iResNet/master/models/model/deploy_iResNet_ROB.tpl.prototxt",
  334. "error": "File text format is not caffe.NetParameter (Couldn't parse float '$SCALE_WIDTH' at 727:47) in 'deploy_iResNet_ROB.tpl.prototxt'.",
  335. "link": "https://github.com/leonzfa/iResNet"
  336. },
  337. {
  338. "type": "caffe",
  339. "target": "faster_rcnn_train_test_21cls.pt",
  340. "source": "https://raw.githubusercontent.com/sanghoon/pva-faster-rcnn/master/models/pvanet/pva9.1/faster_rcnn_train_test_21cls.pt",
  341. "format": "Caffe v2",
  342. "link": "https://github.com/sanghoon/pva-faster-rcnn"
  343. },
  344. {
  345. "type": "caffe",
  346. "target": "fasterRCNN_AlexNet.prototxt",
  347. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_AlexNet.prototxt",
  348. "format": "Caffe v2",
  349. "link": "https://github.com/cwlacewe/netscope"
  350. },
  351. {
  352. "type": "caffe",
  353. "target": "fasterRCNN_ResNet.prototxt",
  354. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_ResNet.prototxt",
  355. "format": "Caffe v2",
  356. "link": "https://github.com/cwlacewe/netscope"
  357. },
  358. {
  359. "type": "caffe",
  360. "target": "fasterRCNN_VGG.prototxt",
  361. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_VGG.prototxt",
  362. "format": "Caffe v2",
  363. "link": "https://github.com/cwlacewe/netscope"
  364. },
  365. {
  366. "type": "caffe",
  367. "target": "fasterRCNN_ZynqNet.prototxt",
  368. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_ZynqNet.prototxt",
  369. "format": "Caffe v2",
  370. "link": "https://github.com/cwlacewe/netscope"
  371. },
  372. {
  373. "type": "caffe",
  374. "target": "fcn-16s.prototxt",
  375. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fcn-16s.prototxt",
  376. "format": "Caffe v1",
  377. "link": "https://github.com/cwlacewe/netscope"
  378. },
  379. {
  380. "type": "caffe",
  381. "target": "fcn-8s-pascal-deploy.prototxt",
  382. "source": "https://raw.githubusercontent.com/HyeonwooNoh/DeconvNet/master/model/FCN/fcn-8s-pascal-deploy.prototxt",
  383. "format": "Caffe v1",
  384. "link": "https://github.com/HyeonwooNoh/DeconvNet"
  385. },
  386. {
  387. "type": "caffe",
  388. "target": "feat_ext_C3D_examples_imagenet_alexnet_train.prototxt",
  389. "source": "https://github.com/lutzroeder/netron/files/5534696/feat_ext_C3D_examples_imagenet_alexnet_train.prototxt.zip[feat_ext_C3D_examples_imagenet_alexnet_train.prototxt]",
  390. "format": "Caffe v1",
  391. "link": "https://github.com/lutzroeder/netron/issues/276"
  392. },
  393. {
  394. "type": "caffe",
  395. "target": "finetune_flickr_style.caffemodel",
  396. "source": "http://dl.caffe.berkeleyvision.org/finetune_flickr_style.caffemodel",
  397. "format": "Caffe v1",
  398. "link": "https://github.com/BVLC/caffe/tree/master/models/finetune_flickr_style"
  399. },
  400. {
  401. "type": "caffe",
  402. "target": "googlenet.prototxt",
  403. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/googlenet.prototxt",
  404. "format": "Caffe v2",
  405. "link": "https://github.com/cwlacewe/netscope"
  406. },
  407. {
  408. "type": "caffe",
  409. "target": "googlelet_places205_train_iter_2400000.caffemodel",
  410. "source": "http://places.csail.mit.edu/model/googlenet_places205.tar.gz[googlenet_places205/googlelet_places205_train_iter_2400000.caffemodel]",
  411. "format": "Caffe v2",
  412. "link": "http://places.csail.mit.edu/downloadCNN.html"
  413. },
  414. {
  415. "type": "caffe",
  416. "target": "inceptionv3.prototxt",
  417. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv3.prototxt",
  418. "format": "Caffe v2",
  419. "link": "https://github.com/cwlacewe/netscope"
  420. },
  421. {
  422. "type": "caffe",
  423. "target": "inceptionv3_orig.prototxt",
  424. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv3_orig.prototxt",
  425. "format": "Caffe v2",
  426. "link": "https://github.com/cwlacewe/netscope"
  427. },
  428. {
  429. "type": "caffe",
  430. "target": "inceptionv4.prototxt",
  431. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4.prototxt",
  432. "format": "Caffe v2",
  433. "link": "https://github.com/cwlacewe/netscope"
  434. },
  435. {
  436. "type": "caffe",
  437. "target": "inceptionv4_resnet.prototxt",
  438. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4_resnet.prototxt",
  439. "format": "Caffe v2",
  440. "link": "https://github.com/cwlacewe/netscope"
  441. },
  442. {
  443. "type": "caffe",
  444. "target": "inceptionv4_resnet.prototxt",
  445. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4_resnet.prototxt",
  446. "format": "Caffe v2",
  447. "link": "https://github.com/cwlacewe/netscope"
  448. },
  449. {
  450. "type": "caffe",
  451. "target": "lenet_consolidated_solver.prototxt",
  452. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/mnist/lenet_consolidated_solver.prototxt",
  453. "format": "Caffe v1",
  454. "link": "https://github.com/BVLC/caffe/tree/master/examples/mnist"
  455. },
  456. {
  457. "type": "caffe",
  458. "target": "lenet.prototxt",
  459. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/mnist/lenet.prototxt",
  460. "format": "Caffe v2",
  461. "link": "https://github.com/BVLC/caffe/tree/master/examples/mnist"
  462. },
  463. {
  464. "type": "caffe",
  465. "target": "linreg.prototxt",
  466. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/pycaffe/linreg.prototxt",
  467. "format": "Caffe v2",
  468. "link": "https://github.com/BVLC/caffe/tree/master/examples/pycaffe"
  469. },
  470. {
  471. "type": "caffe",
  472. "target": "lstm.prototxt",
  473. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/lstm.prototxt",
  474. "format": "Caffe v2",
  475. "link": "https://github.com/cwlacewe/netscope"
  476. },
  477. {
  478. "type": "caffe",
  479. "target": "mobilenet.caffemodel",
  480. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet.caffemodel",
  481. "format": "Caffe v2",
  482. "link": "https://github.com/shicai/MobileNet-Caffe"
  483. },
  484. {
  485. "type": "caffe",
  486. "target": "mobilenet_deploy.prototxt",
  487. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_deploy.prototxt",
  488. "format": "Caffe v2",
  489. "link": "https://github.com/shicai/MobileNet-Caffe"
  490. },
  491. {
  492. "type": "caffe",
  493. "target": "mobilenet_yolov3_lite_train.prototxt",
  494. "source": "https://raw.githubusercontent.com/eric612/Caffe-YOLOv3-Windows/master/models/yolov3/mobilenet_yolov3_lite_train.prototxt",
  495. "format": "Caffe v2",
  496. "link": "https://github.com/eric612/Caffe-YOLOv3-Windows"
  497. },
  498. {
  499. "type": "caffe",
  500. "target": "mobilenet_yolov3_solver.prototxt,mobilenet_yolov3_train.prototxt",
  501. "source": "https://raw.githubusercontent.com/eric612/Caffe-YOLOv3-Windows/master/models/yolov3/mobilenet_yolov3_solver.prototxt,https://raw.githubusercontent.com/eric612/Caffe-YOLOv3-Windows/master/models/yolov3/mobilenet_yolov3_train.prototxt",
  502. "format": "Caffe v2",
  503. "link": "https://github.com/eric612/Caffe-YOLOv3-Windows"
  504. },
  505. {
  506. "type": "caffe",
  507. "target": "mobilenet_v2.caffemodel",
  508. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_v2.caffemodel",
  509. "format": "Caffe v2",
  510. "link": "https://github.com/shicai/MobileNet-Caffe"
  511. },
  512. {
  513. "type": "caffe",
  514. "target": "mobilenet_v2_deploy.prototxt",
  515. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_v2_deploy.prototxt",
  516. "format": "Caffe v2",
  517. "link": "https://github.com/shicai/MobileNet-Caffe"
  518. },
  519. {
  520. "type": "caffe",
  521. "target": "MobileNetSSD_train.prototxt",
  522. "source": "https://github.com/lutzroeder/netron/files/3771164/MobileNetSSD_train.prototxt.txt",
  523. "format": "Caffe v2",
  524. "link": "https://github.com/lutzroeder/netron/issues/358"
  525. },
  526. {
  527. "type": "caffe",
  528. "target": "mnist_siamese_solver.prototxt,mnist_siamese_train_test.prototxt",
  529. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/siamese/mnist_siamese_solver.prototxt,https://raw.githubusercontent.com/BVLC/caffe/master/examples/siamese/mnist_siamese_train_test.prototxt",
  530. "format": "Caffe v2",
  531. "link": "https://github.com/BVLC/caffe/tree/master/examples/siamese"
  532. },
  533. {
  534. "type": "caffe",
  535. "target": "netron_issue_306.prototxt",
  536. "source": "https://github.com/lutzroeder/netron/files/3440457/netron_issue_306.zip[netron_issue_306.pbtxt]",
  537. "format": "Caffe v2",
  538. "link": "https://github.com/lutzroeder/netron/issues/306"
  539. },
  540. {
  541. "type": "caffe",
  542. "target": "nin.prototxt",
  543. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/nin.prototxt",
  544. "format": "Caffe v1",
  545. "link": "https://github.com/cwlacewe/netscope"
  546. },
  547. {
  548. "type": "caffe",
  549. "target": "ORION_extended_trainval.prototxt",
  550. "source": "https://raw.githubusercontent.com/lmb-freiburg/orion/master/net_archs/modelnet10/ORION_extended_trainval.prototxt",
  551. "format": "Caffe v2",
  552. "link": "https://github.com/lmb-freiburg/orion"
  553. },
  554. {
  555. "type": "caffe",
  556. "target": "panoramic_object_detection_deploy_crop.prototxt.prototxt",
  557. "source": "https://raw.githubusercontent.com/gdlg/panoramic-object-detection/master/examples/inference/deploy_crop.prototxt",
  558. "format": "Caffe v2",
  559. "link": "https://github.com/gdlg/panoramic-object-detection/tree/master/examples/inference"
  560. },
  561. {
  562. "type": "caffe",
  563. "target": "ResNet-18-deploy.prototxt",
  564. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-18-deploy.prototxt",
  565. "format": "Caffe v2",
  566. "link": "https://github.com/cwlacewe/netscope"
  567. },
  568. {
  569. "type": "caffe",
  570. "target": "ResNet-34.prototxt",
  571. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-34.prototxt",
  572. "format": "Caffe v2",
  573. "link": "https://github.com/cwlacewe/netscope"
  574. },
  575. {
  576. "type": "caffe",
  577. "target": "resnet-50.prototxt",
  578. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/resnet-50.prototxt",
  579. "format": "Caffe v2",
  580. "link": "https://github.com/cwlacewe/netscope"
  581. },
  582. {
  583. "type": "caffe",
  584. "target": "ResNet-50-model.caffemodel",
  585. "source": "https://deepdetect.com/models/resnet/ResNet-50-model.caffemodel",
  586. "format": "Caffe v2",
  587. "link": "https://deepdetect.com/models/resnet/"
  588. },
  589. {
  590. "type": "caffe",
  591. "target": "ResNet-50-deploy.prototxt",
  592. "source": "https://deepdetect.com/models/resnet/ResNet-50-deploy.prototxt",
  593. "format": "Caffe v2",
  594. "link": "https://deepdetect.com/models/resnet/"
  595. },
  596. {
  597. "type": "caffe",
  598. "target": "ResNet-50_merged.qconv.winograd.cwl.prototxt",
  599. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-50_merged.qconv.winograd.cwl.prototxt",
  600. "link": "https://github.com/cwlacewe/netscope"
  601. },
  602. {
  603. "type": "caffe",
  604. "target": "ResNet-152-model.caffemodel",
  605. "source": "https://deepdetect.com/models/resnet/ResNet-152-model.caffemodel",
  606. "format": "Caffe v2",
  607. "link": "https://deepdetect.com/models/resnet/"
  608. },
  609. {
  610. "type": "caffe",
  611. "target": "ResNet-152-deploy.prototxt",
  612. "source": "https://deepdetect.com/models/resnet/ResNet-152-deploy.prototxt",
  613. "format": "Caffe v2",
  614. "link": "https://deepdetect.com/models/resnet/"
  615. },
  616. {
  617. "type": "caffe",
  618. "target": "resnet-152.prototxt",
  619. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/resnet-152.prototxt",
  620. "format": "Caffe v2",
  621. "link": "https://github.com/cwlacewe/netscope"
  622. },
  623. {
  624. "type": "caffe",
  625. "target": "s2s_vgg_pstream_allvocab_fac2_iter_16000.caffemodel",
  626. "source": "https://www.dropbox.com/s/raw/wn6k2oqurxzt6e2/s2s_vgg_pstream_allvocab_fac2_iter_16000.caffemodel",
  627. "error": "File format is not caffe.NetParameter (Invalid type 6 at offset 124546861) in 's2s_vgg_pstream_allvocab_fac2_iter_16000.caffemodel'.",
  628. "format": "Caffe v1",
  629. "link": "https://github.com/truongthanhdat/Video2Text"
  630. },
  631. {
  632. "type": "caffe",
  633. "target": "seq2seq_train_ep7_tar.prototxt",
  634. "source": "https://raw.githubusercontent.com/jasjeetIM/Seq2Seq/master/models/s2s/train_ep7_tar.prototxt",
  635. "format": "Caffe v2",
  636. "link": "https://github.com/jasjeetIM/Seq2Seq"
  637. },
  638. {
  639. "type": "caffe",
  640. "target": "se_resnet_50_v1_deploy.prototxt",
  641. "source": "https://raw.githubusercontent.com/shicai/SENet-Caffe/master/se_resnet_50_v1_deploy.prototxt",
  642. "format": "Caffe v2",
  643. "link": "https://github.com/shicai/SENet-Caffe"
  644. },
  645. {
  646. "type": "caffe",
  647. "target": "segnet_basic_inference.prototxt",
  648. "source": "https://raw.githubusercontent.com/alexgkendall/SegNet-Tutorial/master/Models/segnet_basic_inference.prototxt",
  649. "format": "Caffe v2",
  650. "link": "https://github.com/alexgkendall/SegNet-Tutorial"
  651. },
  652. {
  653. "type": "caffe",
  654. "target": "shufflenet_1x_g3_train.prototxt",
  655. "source": "https://raw.githubusercontent.com/Ewenwan/ShuffleNet-2/master/shufflenet_1x_g3_train.prototxt",
  656. "format": "Caffe v2",
  657. "link": "https://github.com/Ewenwan/ShuffleNet-2"
  658. },
  659. {
  660. "type": "caffe",
  661. "target": "squeezenet_v1.1.caffemodel",
  662. "source": "https://raw.githubusercontent.com/DeepScale/SqueezeNet/master/SqueezeNet_v1.1/squeezenet_v1.1.caffemodel",
  663. "format": "Caffe v2",
  664. "link": "https://github.com/DeepScale/SqueezeNet"
  665. },
  666. {
  667. "type": "caffe",
  668. "target": "sq11b2a_e3.prototxt",
  669. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/sq11b2a_e3.prototxt",
  670. "format": "Caffe v2",
  671. "link": "https://github.com/cwlacewe/netscope"
  672. },
  673. {
  674. "type": "caffe",
  675. "target": "squeezenet.prototxt",
  676. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/squeezenet.prototxt",
  677. "format": "Caffe v2",
  678. "link": "https://github.com/cwlacewe/netscope"
  679. },
  680. {
  681. "type": "caffe",
  682. "target": "squeezenet_v11.prototxt",
  683. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/squeezenet_v11.prototxt",
  684. "format": "Caffe v2",
  685. "link": "https://github.com/cwlacewe/netscope"
  686. },
  687. {
  688. "type": "caffe",
  689. "target": "ssd_16nodes_512_batch_train.prototxt",
  690. "source": "https://raw.githubusercontent.com/intel/caffe/master/models/intel_optimized_models/multinode/ssd_16nodes_512_batch/train.prototxt",
  691. "format": "Caffe v2",
  692. "link": "https://github.com/intel/caffe"
  693. },
  694. {
  695. "type": "caffe",
  696. "target": "SSD300.prototxt",
  697. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/SSD300.prototxt",
  698. "format": "Caffe v2",
  699. "link": "https://github.com/cwlacewe/netscope"
  700. },
  701. {
  702. "type": "caffe",
  703. "target": "tsn_bn_inception_flow_deploy.prototxt",
  704. "source": "https://raw.githubusercontent.com/yjxiong/temporal-segment-networks/master/models/hmdb51/tsn_bn_inception_flow_deploy.prototxt",
  705. "format": "Caffe v2",
  706. "link": "https://github.com/yjxiong/temporal-segment-networks"
  707. },
  708. {
  709. "type": "caffe",
  710. "target": "vanillaCNN.caffemodel",
  711. "source": "https://raw.githubusercontent.com/ishay2b/VanillaCNN/master/ZOO/vanillaCNN.caffemodel",
  712. "format": "Caffe v2",
  713. "link": "https://gist.github.com/ishay2b/58248e5f3c3bf575ac40"
  714. },
  715. {
  716. "type": "caffe",
  717. "target": "vgg-16.prototxt",
  718. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/vgg-16.prototxt",
  719. "format": "Caffe v1",
  720. "link": "https://github.com/cwlacewe/netscope"
  721. },
  722. {
  723. "type": "caffe",
  724. "target": "VGG_CNN_M_2048_deploy.prototxt",
  725. "source": "https://raw.githubusercontent.com/natanielruiz/net-archive/master/vgg_cnn_m_2048/VGG_CNN_M_2048_deploy.prototxt",
  726. "format": "Caffe v1",
  727. "link": "https://github.com/natanielruiz/net-archive"
  728. },
  729. {
  730. "type": "caffe",
  731. "target": "VGG_VOC0712Plus_SSD_300x300_ft_deploy.prototxt",
  732. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/VGG_VOC0712Plus_SSD_300x300_ft_deploy.prototxt",
  733. "format": "Caffe v2",
  734. "link": "https://github.com/cwlacewe/netscope"
  735. },
  736. {
  737. "type": "caffe",
  738. "target": "YOLO.prototxt",
  739. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/YOLO.prototxt",
  740. "format": "Caffe v2",
  741. "link": "https://github.com/cwlacewe/netscope"
  742. },
  743. {
  744. "type": "caffe",
  745. "target": "yolov3_gen.prototext.txt",
  746. "source": "https://github.com/lutzroeder/netron/files/5615031/yolov3_gen.prototext.txt.zip[yolov3_gen.prototext.txt]",
  747. "format": "Caffe v2",
  748. "link": "https://github.com/lutzroeder/netron/issues/276"
  749. },
  750. {
  751. "type": "caffe",
  752. "target": "yolov3-tiny.prototxt",
  753. "source": "https://raw.githubusercontent.com/eric612/MobileNet-YOLO/master/models/darknet_yolov3/yolov3-tiny.prototxt",
  754. "format": "Caffe v2",
  755. "link": "https://github.com/eric612/MobileNet-YOLO/tree/master/models/darknet_yolov3"
  756. },
  757. {
  758. "type": "caffe",
  759. "target": "yolov3-spp.prototxt",
  760. "source": "https://raw.githubusercontent.com/eric612/MobileNet-YOLO/master/models/darknet_yolov3/yolov3-spp.prototxt",
  761. "format": "Caffe v2",
  762. "link": "https://github.com/eric612/MobileNet-YOLO/tree/master/models/darknet_yolov3"
  763. },
  764. {
  765. "type": "caffe",
  766. "target": "zynqnet.prototxt",
  767. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/zynqnet.prototxt",
  768. "format": "Caffe v2",
  769. "link": "https://github.com/cwlacewe/netscope"
  770. },
  771. {
  772. "type": "caffe2",
  773. "target": "bvlc_alexnet/predict_net.pb,bvlc_alexnet/init_net.pb",
  774. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_alexnet/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_alexnet/init_net.pb",
  775. "format": "Caffe2",
  776. "link": "https://github.com/caffe2/models"
  777. },
  778. {
  779. "type": "caffe2",
  780. "target": "bvlc_alexnet/init_net.pb",
  781. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_alexnet/init_net.pb",
  782. "format": "Caffe2",
  783. "link": "https://github.com/caffe2/models"
  784. },
  785. {
  786. "type": "caffe2",
  787. "target": "bvlc_alexnet/predict_net.pbtxt,bvlc_alexnet/init_net.pb",
  788. "source": "https://raw.githubusercontent.com/caffe2/models/master/bvlc_alexnet/predict_net.pbtxt,https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_alexnet/init_net.pb",
  789. "format": "Caffe2",
  790. "link": "https://github.com/caffe2/models"
  791. },
  792. {
  793. "type": "caffe2",
  794. "target": "bvlc_googlenet/predict_net.pb,bvlc_googlenet/init_net.pb",
  795. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_googlenet/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_googlenet/init_net.pb",
  796. "format": "Caffe2",
  797. "link": "https://github.com/caffe2/models"
  798. },
  799. {
  800. "type": "caffe2",
  801. "target": "densenet121/predict_net.pb,densenet121/init_net.pb",
  802. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/densenet121/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/densenet121/init_net.pb",
  803. "format": "Caffe2",
  804. "link": "https://github.com/caffe2/models"
  805. },
  806. {
  807. "type": "caffe2",
  808. "target": "e2e_faster_rcnn_R-50-C4_1x/predict_net.pb,e2e_faster_rcnn_R-50-C4_1x/init_net.pb",
  809. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/detectron/e2e_faster_rcnn_R-50-C4_1x/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/detectron/e2e_faster_rcnn_R-50-C4_1x/init_net.pb",
  810. "format": "Caffe2",
  811. "link": "https://github.com/caffe2/models"
  812. },
  813. {
  814. "type": "caffe2",
  815. "target": "FBNet-A-int8/model.pbtxt,FBNet-A-int8/model_init.pb",
  816. "source": "https://dl.fbaipublicfiles.com/fbnet/models/FBNet_caffe2.zip[FBNet/FBNet-A/int8/model.pbtxt,FBNet/FBNet-A/int8/model_init.pb]",
  817. "format": "Caffe2",
  818. "link": "https://github.com/facebookresearch/mobile-vision"
  819. },
  820. {
  821. "type": "caffe2",
  822. "target": "generalized_rcnn/net.pbtxt",
  823. "source": "https://github.com/lutzroeder/netron/files/2801714/net.pbtxt.txt",
  824. "format": "Caffe2",
  825. "action": "skip-render",
  826. "link": "https://github.com/lutzroeder/netron/issues/223"
  827. },
  828. {
  829. "type": "caffe2",
  830. "target": "generalized_rcnn/predict_net.pbtxt",
  831. "source": "https://github.com/lutzroeder/netron/files/2802044/predict_net.pbtxt.txt",
  832. "format": "Caffe2",
  833. "link": "https://github.com/lutzroeder/netron/issues/223"
  834. },
  835. {
  836. "type": "caffe2",
  837. "target": "inception_v2/predict_net.pb,inception_v2/init_net.pb",
  838. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/inception_v2/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/inception_v2/init_net.pb",
  839. "format": "Caffe2",
  840. "link": "https://github.com/caffe2/models"
  841. },
  842. {
  843. "type": "caffe2",
  844. "target": "lenet/predict_net.pbtxt,lenet/init_net.pbtxt",
  845. "source": "https://raw.githubusercontent.com/jolibrain/deepdetect/master/templates/caffe2/lenet/predict_net.pbtxt,https://raw.githubusercontent.com/jolibrain/deepdetect/master/templates/caffe2/lenet/init_net.pbtxt",
  846. "format": "Caffe2",
  847. "link": "https://github.com/jolibrain/deepdetect/tree/master/templates/caffe2"
  848. },
  849. {
  850. "type": "caffe2",
  851. "target": "mask_rcnn_2go/model.pbtxt",
  852. "source": "https://raw.githubusercontent.com/caffe2/models/master/mask_rcnn_2go/model/fp32/model.pbtxt",
  853. "format": "Caffe2",
  854. "link": "https://github.com/lutzroeder/netron/issues/168"
  855. },
  856. {
  857. "type": "caffe2",
  858. "target": "mobilenet_v2/predict_net.pb,mobilenet_v2/init_net.pb",
  859. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2/init_net.pb",
  860. "format": "Caffe2",
  861. "link": "https://github.com/caffe2/models"
  862. },
  863. {
  864. "type": "caffe2",
  865. "target": "mobilenet_v2/predict_net.pb",
  866. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2/predict_net.pb",
  867. "format": "Caffe2",
  868. "link": "https://github.com/caffe2/models"
  869. },
  870. {
  871. "type": "caffe2",
  872. "target": "mobilenet_v2_quantized/predict_net.pb,mobilenet_v2_quantized/init_net.pb",
  873. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2_1.0_224_quant/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2_1.0_224_quant/init_net.pb",
  874. "format": "Caffe2",
  875. "link": "https://github.com/caffe2/models"
  876. },
  877. {
  878. "type": "caffe2",
  879. "target": "resnet50_quantized/resnet50_quantized_predict_net.pb,resnet50_quantized/resnet50_quantized_init_net.pb",
  880. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/resnet50_quantized/resnet50_quantized_predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/resnet50_quantized/resnet50_quantized_init_net.pb",
  881. "format": "Caffe2",
  882. "link": "https://github.com/caffe2/models/tree/master/resnet50_quantized"
  883. },
  884. {
  885. "type": "caffe2",
  886. "target": "onnx_while/predict_net.pb,onnx_while/inits_net.pb",
  887. "source": "https://github.com/lutzroeder/netron/files/2522635/onnxwhile.zip[predict_net.pb,init_net.pb]",
  888. "format": "Caffe2",
  889. "link": "https://github.com/lutzroeder/netron/issues/168"
  890. },
  891. {
  892. "type": "caffe2",
  893. "target": "ops/ops.pbtxt",
  894. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/core/ops/ops.pbtxt",
  895. "error": "Invalid file content. File contains TensorFlow OpList data.",
  896. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/ops.pbtxt"
  897. },
  898. {
  899. "type": "caffe2",
  900. "target": "resnet50/predict_net.pb,resnet50/init_net.pb",
  901. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/resnet50/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/resnet50/init_net.pb",
  902. "format": "Caffe2",
  903. "link": "https://github.com/caffe2/models"
  904. },
  905. {
  906. "type": "caffe2",
  907. "target": "squeezenet/squeezenet.pb,squeezenet/init_net.pb",
  908. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/squeezenet/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/squeezenet/init_net.pb",
  909. "format": "Caffe2",
  910. "link": "https://github.com/caffe2/models"
  911. },
  912. {
  913. "type": "caffe2",
  914. "target": "vgg19/predict_net.pb,vgg19/init_net.pb",
  915. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/vgg19/predict_net.pb,https://s3.amazonaws.com/download.caffe2.ai/models/vgg19/init_net.pb",
  916. "format": "Caffe2",
  917. "link": "https://github.com/caffe2/models"
  918. },
  919. {
  920. "type": "cntk",
  921. "target": "01_OneHidden.dnn",
  922. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tests/UnitTests/NetworkTests/Models/01_OneHidden.dnn",
  923. "format": "CNTK v1.18",
  924. "link": "https://github.com/Microsoft/CNTK"
  925. },
  926. {
  927. "type": "cntk",
  928. "target": "AlexNet.model",
  929. "source": "https://www.cntk.ai/Models/AlexNet/AlexNet.model",
  930. "format": "CNTK v1.14"
  931. },
  932. {
  933. "type": "cntk",
  934. "target": "cifar10.pretrained.cmf",
  935. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/ImageHandsOn/cifar10.pretrained.cmf",
  936. "format": "CNTK v1.14",
  937. "link": "https://github.com/Microsoft/CNTK"
  938. },
  939. {
  940. "type": "cntk",
  941. "target": "cifar10.ResNet.cmf",
  942. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/ImageHandsOn/cifar10.ResNet.cmf",
  943. "format": "CNTK v1.10",
  944. "link": "https://github.com/Microsoft/CNTK"
  945. },
  946. {
  947. "type": "cntk",
  948. "target": "cntkSpeechFF.dnn",
  949. "source": "https://github.com/lutzroeder/netron/files/3243442/cntkSpeechFF.dnn.zip[cntkSpeechFF.dnn]",
  950. "format": "CNTK v1.31",
  951. "link": "https://github.com/lutzroeder/netron/issues/153"
  952. },
  953. {
  954. "type": "cntk",
  955. "target": "ResNet_18.model",
  956. "source": "https://www.cntk.ai/Models/ResNet/ResNet_18.model",
  957. "format": "CNTK v1.17"
  958. },
  959. {
  960. "type": "cntk",
  961. "target": "ResNet20_CIFAR10_DataAug.dnn",
  962. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tests/UnitTests/NetworkTests/Models/ResNet20_CIFAR10_DataAug.dnn",
  963. "format": "CNTK v1.18",
  964. "link": "https://github.com/Microsoft/CNTK"
  965. },
  966. {
  967. "type": "cntk",
  968. "target": "slu.forward.backward.cmf",
  969. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.backward.cmf",
  970. "format": "CNTK v1.14",
  971. "link": "https://github.com/Microsoft/CNTK"
  972. },
  973. {
  974. "type": "cntk",
  975. "target": "slu.forward.cmf",
  976. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.cmf",
  977. "format": "CNTK v1.14",
  978. "link": "https://github.com/Microsoft/CNTK"
  979. },
  980. {
  981. "type": "cntk",
  982. "target": "slu.forward.nobn.cmf",
  983. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.nobn.cmf",
  984. "format": "CNTK v1.14",
  985. "link": "https://github.com/Microsoft/CNTK"
  986. },
  987. {
  988. "type": "cntk",
  989. "target": "slu.forward.lookahead.cmf",
  990. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.lookahead.cmf",
  991. "format": "CNTK v1.14",
  992. "link": "https://github.com/Microsoft/CNTK"
  993. },
  994. {
  995. "type": "cntk",
  996. "target": "Bean.cntk",
  997. "source": "https://media.githubusercontent.com/media/Microsoft/ELL-models/master/models/ILSVRC2012/Bean/Bean.cntk.zip[Bean.cntk]",
  998. "format": "CNTK v2",
  999. "link": "https://github.com/Microsoft/ELL-models"
  1000. },
  1001. {
  1002. "type": "cntk",
  1003. "target": "BNInception_ImageNet_Caffe.model",
  1004. "source": "https://www.cntk.ai/Models/Caffe_Converted/BNInception_ImageNet_Caffe.model",
  1005. "format": "CNTK v2",
  1006. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/download_model.py"
  1007. },
  1008. {
  1009. "type": "cntk",
  1010. "target": "Chalta.model",
  1011. "source": "https://media.githubusercontent.com/media/Microsoft/ELL-models/master/models/ILSVRC2012/Chalta/Chalta.cntk.zip[Chalta.cntk]",
  1012. "format": "CNTK v2",
  1013. "link": "https://github.com/Microsoft/ELL-models"
  1014. },
  1015. {
  1016. "type": "cntk",
  1017. "target": "d_I160x160x3CMCMCMCMCMCMC1AS.model",
  1018. "source": "https://media.githubusercontent.com/media/Microsoft/ELL-models/master/models/ILSVRC2012/d_I160x160x3CMCMCMCMCMCMC1AS/d_I160x160x3CMCMCMCMCMCMC1AS.cntk.zip[d_I160x160x3CMCMCMCMCMCMC1AS.cntk]",
  1019. "format": "CNTK v2",
  1020. "link": "https://github.com/Microsoft/ELL-models/tree/master/models/ILSVRC2012/d_I160x160x3CMCMCMCMCMCMC1AS"
  1021. },
  1022. {
  1023. "type": "cntk",
  1024. "target": "DRNN.model",
  1025. "source": "https://www.cntk.ai/Models/SuperResolution/DRNN.model",
  1026. "format": "CNTK v2",
  1027. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1028. },
  1029. {
  1030. "type": "cntk",
  1031. "target": "initial_policy_network.dnn",
  1032. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/bindings/python/cntk/contrib/deeprl/tests/data/initial_policy_network.dnn",
  1033. "format": "CNTK v2",
  1034. "link": "https://github.com/Microsoft/CNTK"
  1035. },
  1036. {
  1037. "type": "cntk",
  1038. "target": "InceptionV3_ImageNet_CNTK.model",
  1039. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/InceptionV3_ImageNet_CNTK.model",
  1040. "format": "CNTK v2",
  1041. "link": "https://github.com/Microsoft/MMdnn/blob/master/mmdnn/conversion/examples/cntk/extract_model.py"
  1042. },
  1043. {
  1044. "type": "cntk",
  1045. "target": "ResNet18_ImageNet_CNTK.model",
  1046. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet18_ImageNet_CNTK.model",
  1047. "format": "CNTK v2",
  1048. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1049. },
  1050. {
  1051. "type": "cntk",
  1052. "target": "ResNet20_CIFAR10_CNTK.model",
  1053. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet20_CIFAR10_CNTK.model",
  1054. "format": "CNTK v2",
  1055. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1056. },
  1057. {
  1058. "type": "cntk",
  1059. "target": "ResNet34_ImageNet_CNTK.model",
  1060. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet34_ImageNet_CNTK.model"
  1061. },
  1062. {
  1063. "type": "cntk",
  1064. "target": "ResNet110_CIFAR10_CNTK.model",
  1065. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet110_CIFAR10_CNTK.model",
  1066. "format": "CNTK v2",
  1067. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1068. },
  1069. {
  1070. "type": "cntk",
  1071. "target": "SRGAN.model",
  1072. "source": "https://www.cntk.ai/Models/SuperResolution/SRGAN.model",
  1073. "format": "CNTK v2",
  1074. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1075. },
  1076. {
  1077. "type": "cntk",
  1078. "target": "SRResNet.model",
  1079. "source": "https://www.cntk.ai/Models/SuperResolution/SRResNet.model",
  1080. "format": "CNTK v2",
  1081. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1082. },
  1083. {
  1084. "type": "cntk",
  1085. "target": "tutorial_103b_mnist.model",
  1086. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103b_mnist.model]",
  1087. "format": "CNTK v2",
  1088. "link": "https://github.com/lutzroeder/netron/issues/153"
  1089. },
  1090. {
  1091. "type": "cntk",
  1092. "target": "tutorial_103c_mnist.model",
  1093. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103c_mnist.model]",
  1094. "format": "CNTK v2",
  1095. "link": "https://github.com/lutzroeder/netron/issues/153"
  1096. },
  1097. {
  1098. "type": "cntk",
  1099. "target": "tutorial_103d_mnist.model",
  1100. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103d_mnist.model]",
  1101. "format": "CNTK v2",
  1102. "link": "https://github.com/lutzroeder/netron/issues/153"
  1103. },
  1104. {
  1105. "type": "cntk",
  1106. "target": "tutorial_106a_lstm.model",
  1107. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_106a_lstm.model]",
  1108. "format": "CNTK v2",
  1109. "link": "https://github.com/lutzroeder/netron/issues/153"
  1110. },
  1111. {
  1112. "type": "cntk",
  1113. "target": "VGG16_ImageNet_Caffe.model",
  1114. "source": "https://www.cntk.ai/Models/Caffe_Converted/VGG16_ImageNet_Caffe.model"
  1115. },
  1116. {
  1117. "type": "cntk",
  1118. "target": "VDSR.model",
  1119. "source": "https://www.cntk.ai/Models/SuperResolution/VDSR.model",
  1120. "format": "CNTK v2",
  1121. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1122. },
  1123. {
  1124. "type": "coreml",
  1125. "target": "BERTSQUADFP16.mlmodel",
  1126. "source": "https://docs-assets.developer.apple.com/coreml/models/Text/QuestionAnswering/BERT_SQUAD/BERTSQUADFP16.mlmodel",
  1127. "format": "Core ML v4",
  1128. "link": "https://developer.apple.com/machine-learning/models"
  1129. },
  1130. {
  1131. "type": "coreml",
  1132. "target": "CarClassifier.mlmodel",
  1133. "source": "https://raw.githubusercontent.com/PZ1Sharer05/CreateMLmodels/master/CarClassifier.mlmodel",
  1134. "format": "Core ML v1",
  1135. "link": "https://github.com/PZ1Sharer05/CreateMLmodels"
  1136. },
  1137. {
  1138. "type": "coreml",
  1139. "target": "DocumentClassification.mlmodel",
  1140. "source": "https://raw.githubusercontent.com/toddkramer/DocumentClassifier/master/Sources/DocumentClassification.mlmodel",
  1141. "format": "Core ML v1",
  1142. "link": "https://github.com/toddkramer/DocumentClassifier"
  1143. },
  1144. {
  1145. "type": "coreml",
  1146. "target": "DeepLabV3.mlmodel",
  1147. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageSegmentation/DeepLabV3/DeepLabV3.mlmodel",
  1148. "format": "Core ML v3",
  1149. "link": "https://developer.apple.com/machine-learning/models"
  1150. },
  1151. {
  1152. "type": "coreml",
  1153. "target": "EnvSceneClassification.mlmodel",
  1154. "source": "https://raw.githubusercontent.com/anujdutt9/iOS-Audio-Classification/cdf5b72dc351a83168369d0afbd0eeba9ecae448/RealTimeSoundClassifier/RealTimeSoundClassifier/EnvSceneClassification.mlmodel",
  1155. "format": "Core ML v3",
  1156. "link": "https://github.com/anujdutt9/iOS-Audio-Classification"
  1157. },
  1158. {
  1159. "type": "coreml",
  1160. "target": "coreml_invalid_file.mlmodel",
  1161. "source": "https://github.com/lutzroeder/netron/files/3219681/coreml_invalid_file.mlmodel.zip",
  1162. "error": "Invalid file content. File contains Zip archive in 'coreml_invalid_file.mlmodel'.",
  1163. "format": "Core ML v1",
  1164. "link": "https://github.com/lutzroeder/netron/issues/193"
  1165. },
  1166. {
  1167. "type": "coreml",
  1168. "target": "Exermote.mlmodel",
  1169. "source": "https://raw.githubusercontent.com/Lausbert/Exermote/master/ExermoteInference/ExermoteCoreML/ExermoteCoreML/Model/Exermote.mlmodel",
  1170. "format": "Core ML v1"
  1171. },
  1172. {
  1173. "type": "coreml",
  1174. "target": "faces_model.mlmodel",
  1175. "source": "https://github.com/NovaTecConsulting/FaceRecognition-in-ARKit/files/1526806/faces_model.mlmodel.zip[faces_model.mlmodel]",
  1176. "format": "Core ML v1",
  1177. "link": "https://github.com/NovaTecConsulting/FaceRecognition-in-ARKit/issues/3"
  1178. },
  1179. {
  1180. "type": "coreml",
  1181. "target": "FCRNFP16.mlmodel",
  1182. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/DepthEstimation/FCRN/FCRNFP16.mlmodel",
  1183. "format": "Core ML v2",
  1184. "link": "https://developer.apple.com/machine-learning/models"
  1185. },
  1186. {
  1187. "type": "coreml",
  1188. "target": "float16.mlmodel",
  1189. "source": "https://github.com/lutzroeder/netron/files/2382815/model.zip[model.mlmodel]",
  1190. "format": "Core ML v2",
  1191. "link": "https://github.com/lutzroeder/netron/issues/149"
  1192. },
  1193. {
  1194. "type": "coreml",
  1195. "target": "FNS-Candy.mlmodel",
  1196. "source": "https://raw.githubusercontent.com/ileafsolutions/StyleArt/master/StyleArt/CoreMLModels/FNS-Candy.mlmodel",
  1197. "link": "https://github.com/ileafsolutions/StyleArt"
  1198. },
  1199. {
  1200. "type": "coreml",
  1201. "target": "food.mlmodel",
  1202. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food.mlmodel",
  1203. "format": "Core ML v1",
  1204. "link": "https://github.com/kingreza/quantization"
  1205. },
  1206. {
  1207. "type": "coreml",
  1208. "target": "food_kmeans_1.mlmodel",
  1209. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_1.mlmodel",
  1210. "format": "Core ML v3",
  1211. "link": "https://github.com/kingreza/quantization"
  1212. },
  1213. {
  1214. "type": "coreml",
  1215. "target": "food_kmeans_2.mlmodel",
  1216. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_2.mlmodel",
  1217. "format": "Core ML v3",
  1218. "link": "https://github.com/kingreza/quantization"
  1219. },
  1220. {
  1221. "type": "coreml",
  1222. "target": "food_kmeans_3.mlmodel",
  1223. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_3.mlmodel",
  1224. "format": "Core ML v3",
  1225. "link": "https://github.com/kingreza/quantization"
  1226. },
  1227. {
  1228. "type": "coreml",
  1229. "target": "food_kmeans_4.mlmodel",
  1230. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_4.mlmodel",
  1231. "format": "Core ML v3",
  1232. "link": "https://github.com/kingreza/quantization"
  1233. },
  1234. {
  1235. "type": "coreml",
  1236. "target": "food_kmeans_5.mlmodel",
  1237. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_5.mlmodel",
  1238. "format": "Core ML v3",
  1239. "link": "https://github.com/kingreza/quantization"
  1240. },
  1241. {
  1242. "type": "coreml",
  1243. "target": "food_kmeans_6.mlmodel",
  1244. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_6.mlmodel",
  1245. "format": "Core ML v3",
  1246. "link": "https://github.com/kingreza/quantization"
  1247. },
  1248. {
  1249. "type": "coreml",
  1250. "target": "food_kmeans_7.mlmodel",
  1251. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_7.mlmodel",
  1252. "format": "Core ML v3",
  1253. "link": "https://github.com/kingreza/quantization"
  1254. },
  1255. {
  1256. "type": "coreml",
  1257. "target": "food_kmeans_8.mlmodel",
  1258. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_8.mlmodel",
  1259. "format": "Core ML v3",
  1260. "link": "https://github.com/kingreza/quantization"
  1261. },
  1262. {
  1263. "type": "coreml",
  1264. "target": "food_kmeans_16.mlmodel",
  1265. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_16.mlmodel",
  1266. "format": "Core ML v2",
  1267. "link": "https://github.com/kingreza/quantization"
  1268. },
  1269. {
  1270. "type": "coreml",
  1271. "target": "food_linear_1.mlmodel",
  1272. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_1.mlmodel",
  1273. "format": "Core ML v3",
  1274. "link": "https://github.com/kingreza/quantization"
  1275. },
  1276. {
  1277. "type": "coreml",
  1278. "target": "food_linear_2.mlmodel",
  1279. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_2.mlmodel",
  1280. "format": "Core ML v3",
  1281. "link": "https://github.com/kingreza/quantization"
  1282. },
  1283. {
  1284. "type": "coreml",
  1285. "target": "food_linear_3.mlmodel",
  1286. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_3.mlmodel",
  1287. "format": "Core ML v3",
  1288. "link": "https://github.com/kingreza/quantization"
  1289. },
  1290. {
  1291. "type": "coreml",
  1292. "target": "food_linear_4.mlmodel",
  1293. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_4.mlmodel",
  1294. "format": "Core ML v3",
  1295. "link": "https://github.com/kingreza/quantization"
  1296. },
  1297. {
  1298. "type": "coreml",
  1299. "target": "food_linear_5.mlmodel",
  1300. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_5.mlmodel",
  1301. "format": "Core ML v3",
  1302. "link": "https://github.com/kingreza/quantization"
  1303. },
  1304. {
  1305. "type": "coreml",
  1306. "target": "food_linear_6.mlmodel",
  1307. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_6.mlmodel",
  1308. "format": "Core ML v3",
  1309. "link": "https://github.com/kingreza/quantization"
  1310. },
  1311. {
  1312. "type": "coreml",
  1313. "target": "food_linear_7.mlmodel",
  1314. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_7.mlmodel",
  1315. "format": "Core ML v3",
  1316. "link": "https://github.com/kingreza/quantization"
  1317. },
  1318. {
  1319. "type": "coreml",
  1320. "target": "food_linear_8.mlmodel",
  1321. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_8.mlmodel",
  1322. "format": "Core ML v3",
  1323. "link": "https://github.com/kingreza/quantization"
  1324. },
  1325. {
  1326. "type": "coreml",
  1327. "target": "food_linear_16.mlmodel",
  1328. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_16.mlmodel",
  1329. "format": "Core ML v2",
  1330. "link": "https://github.com/kingreza/quantization"
  1331. },
  1332. {
  1333. "type": "coreml",
  1334. "target": "food_linear_lut_1.mlmodel",
  1335. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_1.mlmodel",
  1336. "format": "Core ML v3",
  1337. "link": "https://github.com/kingreza/quantization"
  1338. },
  1339. {
  1340. "type": "coreml",
  1341. "target": "food_linear_lut_2.mlmodel",
  1342. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_2.mlmodel",
  1343. "format": "Core ML v3",
  1344. "link": "https://github.com/kingreza/quantization"
  1345. },
  1346. {
  1347. "type": "coreml",
  1348. "target": "food_linear_lut_3.mlmodel",
  1349. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_3.mlmodel",
  1350. "format": "Core ML v3",
  1351. "link": "https://github.com/kingreza/quantization"
  1352. },
  1353. {
  1354. "type": "coreml",
  1355. "target": "food_linear_lut_4.mlmodel",
  1356. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_4.mlmodel",
  1357. "format": "Core ML v3",
  1358. "link": "https://github.com/kingreza/quantization"
  1359. },
  1360. {
  1361. "type": "coreml",
  1362. "target": "food_linear_lut_5.mlmodel",
  1363. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_5.mlmodel",
  1364. "format": "Core ML v3",
  1365. "link": "https://github.com/kingreza/quantization"
  1366. },
  1367. {
  1368. "type": "coreml",
  1369. "target": "food_linear_lut_6.mlmodel",
  1370. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_6.mlmodel",
  1371. "format": "Core ML v3",
  1372. "link": "https://github.com/kingreza/quantization"
  1373. },
  1374. {
  1375. "type": "coreml",
  1376. "target": "food_linear_lut_7.mlmodel",
  1377. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_7.mlmodel",
  1378. "format": "Core ML v3",
  1379. "link": "https://github.com/kingreza/quantization"
  1380. },
  1381. {
  1382. "type": "coreml",
  1383. "target": "food_linear_lut_8.mlmodel",
  1384. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_8.mlmodel",
  1385. "format": "Core ML v3",
  1386. "link": "https://github.com/kingreza/quantization"
  1387. },
  1388. {
  1389. "type": "coreml",
  1390. "target": "food_linear_lut_16.mlmodel",
  1391. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_16.mlmodel",
  1392. "format": "Core ML v2",
  1393. "link": "https://github.com/kingreza/quantization"
  1394. },
  1395. {
  1396. "type": "coreml",
  1397. "target": "GoogLeNetPlaces.mlmodel",
  1398. "source": "https://docs-assets.developer.apple.com/coreml/models/GoogLeNetPlaces.mlmodel"
  1399. },
  1400. {
  1401. "type": "coreml",
  1402. "target": "HED_so.mlmodel",
  1403. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_so.mlmodel",
  1404. "link": "https://github.com/s1ddok/HED-CoreML"
  1405. },
  1406. {
  1407. "type": "coreml",
  1408. "target": "HED_so3.mlmodel",
  1409. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_so3.mlmodel",
  1410. "link": "https://github.com/s1ddok/HED-CoreML"
  1411. },
  1412. {
  1413. "type": "coreml",
  1414. "target": "HED_fuse.mlmodel",
  1415. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_fuse.mlmodel",
  1416. "link": "https://github.com/s1ddok/HED-CoreML"
  1417. },
  1418. {
  1419. "type": "coreml",
  1420. "target": "imdb_lstm.mlmodel",
  1421. "source": "https://github.com/lutzroeder/netron/files/2591614/imdb_lstm.mlmodel.zip[imdb_lstm.mlmodel]",
  1422. "format": "Core ML v1",
  1423. "link": "https://github.com/lutzroeder/netron/issues/149"
  1424. },
  1425. {
  1426. "type": "coreml",
  1427. "target": "imdb_bidirectional_lstm.mlmodel",
  1428. "source": "https://github.com/lutzroeder/netron/files/2591615/imdb_bidirectional_lstm.mlmodel.zip[imdb_bidirectional_lstm.mlmodel]",
  1429. "format": "Core ML v1",
  1430. "link": "https://github.com/lutzroeder/netron/issues/149"
  1431. },
  1432. {
  1433. "type": "coreml",
  1434. "target": "Inceptionv3.mlmodel",
  1435. "source": "https://docs-assets.developer.apple.com/coreml/models/Inceptionv3.mlmodel"
  1436. },
  1437. {
  1438. "type": "coreml",
  1439. "target": "iris.mlmodel",
  1440. "source": "https://raw.githubusercontent.com/gavi/Iris/master/Iris/iris.mlmodel",
  1441. "format": "Core ML v1",
  1442. "link": "https://github.com/gavi/Iris"
  1443. },
  1444. {
  1445. "type": "coreml",
  1446. "target": "LinkedUpdatableTinyDrawingClassifier.mlmodel",
  1447. "source": "https://github.com/lutzroeder/netron/files/4500539/LinkedUpdatableTinyDrawingClassifier.zip[LinkedUpdatableTinyDrawingClassifier.mlmodel]",
  1448. "format": "Core ML v4",
  1449. "link": "https://github.com/lutzroeder/netron/issues/193"
  1450. },
  1451. {
  1452. "type": "coreml",
  1453. "target": "MessageClassifier.mlmodel",
  1454. "source": "https://raw.githubusercontent.com/llSourcell/A_guide_to_coreML/master/MessageClassifier.mlmodel",
  1455. "link": "https://github.com/llSourcell/A_guide_to_coreML"
  1456. },
  1457. {
  1458. "type": "coreml",
  1459. "target": "MNIST.mlmodel",
  1460. "source": "https://github.com/ph1ps/MNIST-CoreML/raw/master/MNISTPrediction/MNIST.mlmodel",
  1461. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1462. },
  1463. {
  1464. "type": "coreml",
  1465. "target": "MNISTClassifier.mlmodel",
  1466. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/DrawingClassification/MNISTClassifier/MNISTClassifier.mlmodel",
  1467. "format": "Core ML v1",
  1468. "link": "https://developer.apple.com/machine-learning/models"
  1469. },
  1470. {
  1471. "type": "coreml",
  1472. "target": "MobileNet.mlmodel",
  1473. "source": "https://docs-assets.developer.apple.com/coreml/models/MobileNet.mlmodel"
  1474. },
  1475. {
  1476. "type": "coreml",
  1477. "target": "mobilenet_v2_1.4_224.mlmodel",
  1478. "source": "https://github.com/tf-coreml/tf-coreml/files/2575260/mobilenet_v2_1.4_224.mlmodel.zip[mobilenet_v2_1.4_224.mlmodel]",
  1479. "format": "Core ML v1",
  1480. "link": "https://github.com/tf-coreml/tf-coreml/issues/252"
  1481. },
  1482. {
  1483. "type": "coreml",
  1484. "target": "MovieRecommender.mlmodel",
  1485. "source": "https://raw.githubusercontent.com/anupamchugh/iowncode/master/CoreMLRecommender/CoreMLRecommender/MovieRecommender.mlmodel",
  1486. "format": "Core ML v4",
  1487. "link": "https://github.com/anupamchugh/iowncode/tree/master/CoreMLRecommender"
  1488. },
  1489. {
  1490. "type": "coreml",
  1491. "target": "NamesDT.mlmodel",
  1492. "source": "https://github.com/cocoa-ai/NamesCoreMLDemo/raw/master/Names/Resources/NamesDT.mlmodel",
  1493. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1494. },
  1495. {
  1496. "type": "coreml",
  1497. "target": "onehot_simple.mlmodel",
  1498. "source": "https://raw.githubusercontent.com/onnx/onnxmltools/master/tests/data/onehot_simple.mlmodel",
  1499. "link": "https://github.com/onnx/onnxmltools/tree/master/tests/data"
  1500. },
  1501. {
  1502. "type": "coreml",
  1503. "target": "PoseEstimationForMobile.mlmodel",
  1504. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.mlmodel",
  1505. "format": "Core ML v1",
  1506. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  1507. },
  1508. {
  1509. "type": "coreml",
  1510. "target": "ProductTagger.mlmodel",
  1511. "source": "https://raw.githubusercontent.com/aidev1065/CustomEntityRecognition/master/ProductTagger.mlmodel",
  1512. "format": "Core ML v3",
  1513. "link": "https://github.com/aidev1065/CustomEntityRecognition"
  1514. },
  1515. {
  1516. "type": "coreml",
  1517. "target": "ProgrammingLanguageClassifier.mlmodel",
  1518. "source": "https://raw.githubusercontent.com/Flight-School/Programming-Language-Classifier/master/ProgrammingLanguageClassifier.mlmodel",
  1519. "format": "Core ML v3",
  1520. "link": "https://github.com/Flight-School/Programming-Language-Classifier"
  1521. },
  1522. {
  1523. "type": "coreml",
  1524. "target": "ReadTheRoom.mlmodel",
  1525. "source": "https://raw.githubusercontent.com/CapTechMobile/blogfest-coreml/d8e8c15d33e9591c9e81cb18e5ea4b2fb6972503/ReadTheRoom/ReadTheRoom.mlmodel",
  1526. "format": "Core ML v4",
  1527. "link": "https://github.com/CapTechMobile/blogfest-coreml"
  1528. },
  1529. {
  1530. "type": "coreml",
  1531. "target": "Resnet50.mlmodel",
  1532. "source": "https://docs-assets.developer.apple.com/coreml/models/Resnet50.mlmodel"
  1533. },
  1534. {
  1535. "type": "coreml",
  1536. "target": "SentimentPolarity.mlmodel",
  1537. "source": "https://github.com/cocoa-ai/SentimentCoreMLDemo/raw/master/SentimentPolarity/Resources/SentimentPolarity.mlmodel",
  1538. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1539. },
  1540. {
  1541. "type": "coreml",
  1542. "target": "sentiment_model.mlmodel",
  1543. "source": "https://github.com/lutzroeder/netron/files/2591618/sentiment_model.mlmodel.zip[sentiment_model.mlmodel]",
  1544. "format": "Core ML v1",
  1545. "link": "https://github.com/lutzroeder/netron/issues/149"
  1546. },
  1547. {
  1548. "type": "coreml",
  1549. "target": "SqueezeNet.mlmodel",
  1550. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNet.mlmodel",
  1551. "format": "Core ML v1",
  1552. "link": "https://developer.apple.com/machine-learning/models"
  1553. },
  1554. {
  1555. "type": "coreml",
  1556. "target": "SqueezeNetFP16.mlmodel",
  1557. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNetFP16.mlmodel",
  1558. "format": "Core ML v2",
  1559. "link": "https://developer.apple.com/machine-learning/models"
  1560. },
  1561. {
  1562. "type": "coreml",
  1563. "target": "SqueezeNetInt8LUT.mlmodel",
  1564. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNetInt8LUT.mlmodel",
  1565. "format": "Core ML v3",
  1566. "link": "https://developer.apple.com/machine-learning/models"
  1567. },
  1568. {
  1569. "type": "coreml",
  1570. "target": "test_categorical_imputer.mlmodel",
  1571. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_categorical_imputer.mlmodel]",
  1572. "format": "Core ML v1",
  1573. "link": "https://github.com/lutzroeder/netron/issues/193"
  1574. },
  1575. {
  1576. "type": "coreml",
  1577. "target": "test_keras_embedding_model.mlmodel",
  1578. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_keras_embedding_model.mlmodel]",
  1579. "format": "Core ML v1",
  1580. "link": "https://github.com/lutzroeder/netron/issues/193"
  1581. },
  1582. {
  1583. "type": "coreml",
  1584. "target": "test_linear_regressor.mlmodel",
  1585. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_linear_regressor.mlmodel]",
  1586. "format": "Core ML v1",
  1587. "link": "https://github.com/lutzroeder/netron/issues/193"
  1588. },
  1589. {
  1590. "type": "coreml",
  1591. "target": "test_normalizer_boston.mlmodel",
  1592. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_normalizer_boston.mlmodel]",
  1593. "format": "Core ML v1",
  1594. "link": "https://github.com/lutzroeder/netron/issues/193"
  1595. },
  1596. {
  1597. "type": "coreml",
  1598. "target": "test_normalizer_random.mlmodel",
  1599. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_normalizer_random.mlmodel]",
  1600. "format": "Core ML v1",
  1601. "link": "https://github.com/lutzroeder/netron/issues/193"
  1602. },
  1603. {
  1604. "type": "coreml",
  1605. "target": "test_one_hot_encoder_many_columns.mlmodel",
  1606. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_many_columns.mlmodel]",
  1607. "format": "Core ML v1",
  1608. "link": "https://github.com/lutzroeder/netron/issues/193"
  1609. },
  1610. {
  1611. "type": "coreml",
  1612. "target": "test_one_hot_encoder_one_column_of_several.mlmodel",
  1613. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_one_column_of_several.mlmodel]",
  1614. "format": "Core ML v1",
  1615. "link": "https://github.com/lutzroeder/netron/issues/193"
  1616. },
  1617. {
  1618. "type": "coreml",
  1619. "target": "test_one_hot_encoder_pipeline.mlmodel",
  1620. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_pipeline.mlmodel]",
  1621. "format": "Core ML v1",
  1622. "link": "https://github.com/lutzroeder/netron/issues/193"
  1623. },
  1624. {
  1625. "type": "coreml",
  1626. "target": "test_random_forest_classifier.mlmodel",
  1627. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_random_forest_classifier.mlmodel]",
  1628. "format": "Core ML v1",
  1629. "link": "https://github.com/lutzroeder/netron/issues/193"
  1630. },
  1631. {
  1632. "type": "coreml",
  1633. "target": "test_random_forest_regressor.mlmodel",
  1634. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_random_forest_regressor.mlmodel]",
  1635. "format": "Core ML v1",
  1636. "link": "https://github.com/lutzroeder/netron/issues/193"
  1637. },
  1638. {
  1639. "type": "coreml",
  1640. "target": "test_support_vector_classifier.mlmodel",
  1641. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_support_vector_classifier.mlmodel]",
  1642. "format": "Core ML v1",
  1643. "link": "https://github.com/lutzroeder/netron/issues/193"
  1644. },
  1645. {
  1646. "type": "coreml",
  1647. "target": "test_support_vector_regressor.mlmodel",
  1648. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_support_vector_regressor.mlmodel]",
  1649. "format": "Core ML v1",
  1650. "link": "https://github.com/lutzroeder/netron/issues/193"
  1651. },
  1652. {
  1653. "type": "coreml",
  1654. "target": "test_tree_regressor.mlmodel",
  1655. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_tree_regressor.mlmodel]",
  1656. "format": "Core ML v1",
  1657. "link": "https://github.com/lutzroeder/netron/issues/193"
  1658. },
  1659. {
  1660. "type": "coreml",
  1661. "target": "TinyYOLO.mlmodel",
  1662. "source": "https://raw.githubusercontent.com/hollance/YOLO-CoreML-MPSNNGraph/master/TinyYOLO-CoreML/TinyYOLO-CoreML/TinyYOLO.mlmodel"
  1663. },
  1664. {
  1665. "type": "coreml",
  1666. "target": "UpdatableKNN.mlmodel",
  1667. "source": "https://github.com/lutzroeder/netron/files/3424578/UpdatableKNN.zip[UpdatableKNN.mlmodel]",
  1668. "format": "Core ML v4",
  1669. "link": "https://github.com/lutzroeder/netron/issues/193"
  1670. },
  1671. {
  1672. "type": "coreml",
  1673. "target": "UpdatableMNISTDigitClassifier.mlmodel",
  1674. "source": "https://github.com/lutzroeder/netron/files/3424579/UpdatableMNISTDigitClassifier.zip[UpdatableMNISTDigitClassifier.mlmodel]",
  1675. "format": "Core ML v1",
  1676. "link": "https://github.com/lutzroeder/netron/issues/193"
  1677. },
  1678. {
  1679. "type": "coreml",
  1680. "target": "VGG16.mlmodel",
  1681. "source": "https://docs-assets.developer.apple.com/coreml/models/VGG16.mlmodel"
  1682. },
  1683. {
  1684. "type": "coreml",
  1685. "target": "wave.mlmodel",
  1686. "source": "https://raw.githubusercontent.com/UnusualWolf/coreML/master/StyleArt-master/StyleArt/CoreMLModels/wave.mlmodel",
  1687. "format": "Core ML v1",
  1688. "link": "https://github.com/UnusualWolf/coreML"
  1689. },
  1690. {
  1691. "type": "coreml",
  1692. "target": "YOLOv3.mlmodel",
  1693. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ObjectDetection/YOLOv3/YOLOv3.mlmodel",
  1694. "format": "Core ML v3",
  1695. "link": "https://developer.apple.com/machine-learning/models"
  1696. },
  1697. {
  1698. "type": "coreml",
  1699. "target": "YOLOv3Tiny.mlmodel",
  1700. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ObjectDetection/YOLOv3Tiny/YOLOv3Tiny.mlmodel",
  1701. "format": "Core ML v3",
  1702. "link": "https://developer.apple.com/machine-learning/models"
  1703. },
  1704. {
  1705. "type": "darknet",
  1706. "target": "alexnet.cfg,alexnet.weights",
  1707. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/alexnet.cfg,https://pjreddie.com/media/files/alexnet.weights",
  1708. "format": "Darknet",
  1709. "link": "https://pjreddie.com/darknet/imagenet"
  1710. },
  1711. {
  1712. "type": "darknet",
  1713. "target": "csresnext50-panet-spp.cfg",
  1714. "source": "https://raw.githubusercontent.com/WongKinYiu/CrossStagePartialNetworks/master/cfg/csresnext50-panet-spp.cfg",
  1715. "format": "Darknet",
  1716. "link": "https://github.com/lutzroeder/netron/issues/381"
  1717. },
  1718. {
  1719. "type": "darknet",
  1720. "target": "darknet_invalid_file.cfg",
  1721. "source": "https://github.com/lutzroeder/netron/files/3219696/darknet_invalid_file.cfg.zip[darknet_invalid_file.cfg]",
  1722. "error": "Invalid cfg 'xxxx' at line 4 in 'darknet_invalid_file.cfg'.",
  1723. "link": "https://github.com/lutzroeder/netron/issues/277"
  1724. },
  1725. {
  1726. "type": "darknet",
  1727. "target": "darknet53_448.weights,darknet53_448.cfg",
  1728. "source": "https://pjreddie.com/media/files/darknet53_448.weights,https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/darknet53_448.cfg",
  1729. "format": "Darknet",
  1730. "link": "https://pjreddie.com/darknet/imagenet"
  1731. },
  1732. {
  1733. "type": "darknet",
  1734. "target": "enet-coco.model",
  1735. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/enet-coco.cfg",
  1736. "format": "Darknet",
  1737. "link": "https://github.com/lutzroeder/netron/issues/381"
  1738. },
  1739. {
  1740. "type": "darknet",
  1741. "target": "face_small_3.cfg",
  1742. "source": "https://raw.githubusercontent.com/zlmo/Face-Detection/master/cfg/face_small_3.cfg",
  1743. "format": "Darknet",
  1744. "link": "https://github.com/zlmo/Face-Detection"
  1745. },
  1746. {
  1747. "type": "darknet",
  1748. "target": "Gaussian_yolov3_BDD.cfg",
  1749. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/Gaussian_yolov3_BDD.cfg",
  1750. "format": "Darknet",
  1751. "link": "https://github.com/AlexeyAB/darknet"
  1752. },
  1753. {
  1754. "type": "darknet",
  1755. "target": "go.cfg,go.weights",
  1756. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/go.cfg,https://pjreddie.com/media/files/go.weights",
  1757. "format": "Darknet",
  1758. "link": "https://pjreddie.com/darknet/darkgo-go-in-darknet"
  1759. },
  1760. {
  1761. "type": "darknet",
  1762. "target": "grrm.cfg,grrm.weights",
  1763. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/rnn.cfg,https://pjreddie.com/media/files/grrm.weights",
  1764. "format": "Darknet",
  1765. "link": "https://pjreddie.com/darknet/rnns-in-darknet"
  1766. },
  1767. {
  1768. "type": "darknet",
  1769. "target": "gru.cfg",
  1770. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/gru.cfg",
  1771. "format": "Darknet",
  1772. "link": "https://pjreddie.com/darknet"
  1773. },
  1774. {
  1775. "type": "darknet",
  1776. "target": "jnet-conv.cfg,jnet-conv.weights",
  1777. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/jnet-conv.cfg,https://pjreddie.com/media/files/jnet-conv.weights",
  1778. "format": "Darknet",
  1779. "link": "https://pjreddie.com/darknet/nightmare"
  1780. },
  1781. {
  1782. "type": "darknet",
  1783. "target": "lstm.train.cfg",
  1784. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/lstm.train.cfg",
  1785. "format": "Darknet",
  1786. "link": "https://github.com/AlexeyAB/darknet"
  1787. },
  1788. {
  1789. "type": "darknet",
  1790. "target": "mixnet_m_gpu.cfg",
  1791. "source": "https://github.com/lutzroeder/netron/files/3935529/mixnet_m_gpu.cfg.txt",
  1792. "format": "Darknet",
  1793. "link": "https://github.com/lutzroeder/netron/issues/381"
  1794. },
  1795. {
  1796. "type": "darknet",
  1797. "target": "netron_issue_539_1.cfg",
  1798. "source": "https://github.com/lutzroeder/netron/files/5048435/netron_issue_539_1.zip[netron_issue_539_1.cfg]",
  1799. "format": "Darknet",
  1800. "link": "https://github.com/lutzroeder/netron/issues/539"
  1801. },
  1802. {
  1803. "type": "darknet",
  1804. "target": "netron_issue_539_2.cfg",
  1805. "source": "https://github.com/lutzroeder/netron/files/5048436/netron_issue_539_2.zip[netron_issue_539_2.cfg]",
  1806. "format": "Darknet",
  1807. "link": "https://github.com/lutzroeder/netron/issues/539"
  1808. },
  1809. {
  1810. "type": "darknet",
  1811. "target": "netron_issue_539_3.cfg",
  1812. "source": "https://github.com/lutzroeder/netron/files/5612917/netron_issue_539_3.zip[netron_issue_539_3.cfg]",
  1813. "format": "Darknet",
  1814. "link": "https://github.com/lutzroeder/netron/issues/539"
  1815. },
  1816. {
  1817. "type": "darknet",
  1818. "target": "netron_issue_541.cfg",
  1819. "source": "https://github.com/lutzroeder/netron/files/4968181/netron_issue_541.zip[netron_issue_541.cfg]",
  1820. "format": "Darknet",
  1821. "link": "https://github.com/lutzroeder/netron/issues/541"
  1822. },
  1823. {
  1824. "type": "darknet",
  1825. "target": "netron_issue_569.cfg",
  1826. "source": "https://github.com/lutzroeder/netron/files/5025566/netron_issue_569.zip[netron_issue_569.cfg]",
  1827. "format": "Darknet",
  1828. "link": "https://github.com/lutzroeder/netron/issues/569"
  1829. },
  1830. {
  1831. "type": "darknet",
  1832. "target": "resnet18.cfg,resnet18.weights",
  1833. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/resnet18.cfg,https://pjreddie.com/media/files/resnet18.weights",
  1834. "format": "Darknet",
  1835. "link": "https://pjreddie.com/darknet/imagenet"
  1836. },
  1837. {
  1838. "type": "darknet",
  1839. "target": "resnet152.cfg,resnet152.weights",
  1840. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/resnet152.cfg,https://pjreddie.com/media/files/resnet152.weights",
  1841. "format": "Darknet",
  1842. "link": "https://pjreddie.com/darknet/imagenet"
  1843. },
  1844. {
  1845. "type": "darknet",
  1846. "target": "tiny.cfg,tiny.weights",
  1847. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/tiny.cfg,https://pjreddie.com/media/files/tiny.weights",
  1848. "format": "Darknet",
  1849. "link": "https://pjreddie.com/darknet/tiny-darknet"
  1850. },
  1851. {
  1852. "type": "darknet",
  1853. "target": "vgg_bn_ssd300.cfg",
  1854. "source": "https://github.com/lutzroeder/netron/files/5287397/vgg_bn_ssd300.cfg.zip[vgg_bn_ssd300.cfg]",
  1855. "error": "First section must be [net] or [network] in 'vgg_bn_ssd300.cfg'.",
  1856. "link": "https://github.com/lutzroeder/netron/issues/277"
  1857. },
  1858. {
  1859. "type": "darknet",
  1860. "target": "yolo-coco.cfg",
  1861. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov1/yolo-coco.cfg",
  1862. "format": "Darknet",
  1863. "link": "https://github.com/AlexeyAB/darknet"
  1864. },
  1865. {
  1866. "type": "darknet",
  1867. "target": "yolo-voc.cfg",
  1868. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo-voc.cfg",
  1869. "format": "Darknet",
  1870. "link": "https://github.com/AlexeyAB/darknet"
  1871. },
  1872. {
  1873. "type": "darknet",
  1874. "target": "yolo.cfg",
  1875. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo.cfg",
  1876. "format": "Darknet",
  1877. "link": "https://github.com/AlexeyAB/darknet"
  1878. },
  1879. {
  1880. "type": "darknet",
  1881. "target": "yolo_v3_tiny_pan3_aa_ae_mixup_scale_giou.cfg",
  1882. "source": "https://github.com/lutzroeder/netron/files/4006371/yolo_v3_tiny_pan3_aa_ae_mixup_scale_giou.cfg.zip[yolo_v3_tiny_pan3_aa_ae_mixup_scale_giou.cfg]",
  1883. "format": "Darknet",
  1884. "link": "https://github.com/lutzroeder/netron/issues/277"
  1885. },
  1886. {
  1887. "type": "darknet",
  1888. "target": "yolo_v3_tiny_lstm.cfg",
  1889. "source": "https://github.com/lutzroeder/netron/files/4999065/yolo_v3_tiny_lstm.zip[yolo_v3_tiny_lstm.cfg]",
  1890. "format": "Darknet",
  1891. "link": "https://github.com/lutzroeder/netron/issues/562"
  1892. },
  1893. {
  1894. "type": "darknet",
  1895. "target": "yolov3-spp.cfg,yolov3-spp.weights",
  1896. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3-spp.cfg,https://pjreddie.com/media/files/yolov3-spp.weights",
  1897. "format": "Darknet",
  1898. "link": "https://pjreddie.com/darknet/yolo"
  1899. },
  1900. {
  1901. "type": "darknet",
  1902. "target": "yolov3-tiny.cfg,yolov3-tiny.weights",
  1903. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3-tiny.cfg,https://pjreddie.com/media/files/yolov3-tiny.weights",
  1904. "format": "Darknet",
  1905. "link": "https://github.com/AlexeyAB/darknet"
  1906. },
  1907. {
  1908. "type": "darknet",
  1909. "target": "yolov3-tiny_default.cfg.txt",
  1910. "source": "https://github.com/lutzroeder/netron/files/5615015/yolov3-tiny_default.cfg.txt.zip[yolov3-tiny_default.cfg.txt]",
  1911. "format": "Darknet",
  1912. "link": "https://github.com/lutzroeder/netron/issues/277"
  1913. },
  1914. {
  1915. "type": "darknet",
  1916. "target": "yolov3-tiny_3l_shortcut_multilayer_per_feature_softmax.cfg",
  1917. "source": "https://github.com/lutzroeder/netron/files/4074756/yolov3-tiny_3l_shortcut_multilayer_per_feature_softmax.cfg.zip[yolov3-tiny_3l_shortcut_multilayer_per_feature_softmax.cfg]",
  1918. "format": "Darknet",
  1919. "link": "https://github.com/lutzroeder/netron/issues/410"
  1920. },
  1921. {
  1922. "type": "darknet",
  1923. "target": "yolov3_1088x608.cfg",
  1924. "source": "https://github.com/lutzroeder/netron/files/4391007/yolov3_1088x608.cfg.zip[yolov3_1088x608.cfg]",
  1925. "format": "Darknet",
  1926. "link": "https://github.com/lutzroeder/netron/issues/277"
  1927. },
  1928. {
  1929. "type": "darknet",
  1930. "target": "yolov4-tiny.cfg,yolov4-tiny.weights",
  1931. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4-tiny.cfg,https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-tiny.weights",
  1932. "format": "Darknet",
  1933. "link": "https://github.com/lutzroeder/netron/issues/531"
  1934. },
  1935. {
  1936. "type": "darknet",
  1937. "target": "yolo9000.cfg",
  1938. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo9000.cfg",
  1939. "format": "Darknet",
  1940. "link": "https://github.com/AlexeyAB/darknet"
  1941. },
  1942. {
  1943. "type": "dl4j",
  1944. "target": "lenet_dl4j_mnist_inference.zip",
  1945. "source": "https://dl4jdata.blob.core.windows.net/models/lenet_dl4j_mnist_inference.zip",
  1946. "format": "Deeplearning4j",
  1947. "link": "https://github.com/eclipse/deeplearning4j"
  1948. },
  1949. {
  1950. "type": "dl4j",
  1951. "target": "nasnetmobile_dl4j_inference.v1.zip",
  1952. "source": "https://dl4jdata.blob.core.windows.net/models/nasnetmobile_dl4j_inference.v1.zip",
  1953. "format": "Deeplearning4j",
  1954. "link": "https://github.com/eclipse/deeplearning4j"
  1955. },
  1956. {
  1957. "type": "dl4j",
  1958. "target": "resnet50_dl4j_inference.v3.zip",
  1959. "source": "https://dl4jdata.blob.core.windows.net/models/resnet50_dl4j_inference.v3.zip",
  1960. "format": "Deeplearning4j",
  1961. "link": "https://github.com/eclipse/deeplearning4j"
  1962. },
  1963. {
  1964. "type": "dl4j",
  1965. "target": "squeezenet_dl4j_inference.v2.zip",
  1966. "source": "https://dl4jdata.blob.core.windows.net/models/squeezenet_dl4j_inference.v2.zip",
  1967. "format": "Deeplearning4j",
  1968. "link": "https://github.com/eclipse/deeplearning4j"
  1969. },
  1970. {
  1971. "type": "dl4j",
  1972. "target": "tiny-yolo-voc_dl4j_inference.v2.zip",
  1973. "source": "https://dl4jdata.blob.core.windows.net/models/tiny-yolo-voc_dl4j_inference.v2.zip",
  1974. "format": "Deeplearning4j",
  1975. "link": "https://github.com/eclipse/deeplearning4j"
  1976. },
  1977. {
  1978. "type": "dl4j",
  1979. "target": "unet_dl4j_segment_inference.v1.zip",
  1980. "source": "https://dl4jdata.blob.core.windows.net/models/unet_dl4j_segment_inference.v1.zip",
  1981. "format": "Deeplearning4j",
  1982. "link": "https://github.com/eclipse/deeplearning4j"
  1983. },
  1984. {
  1985. "type": "dl4j",
  1986. "target": "xception_dl4j_inference.v2.zip",
  1987. "source": "https://dl4jdata.blob.core.windows.net/models/xception_dl4j_inference.v2.zip",
  1988. "format": "Deeplearning4j",
  1989. "link": "https://github.com/eclipse/deeplearning4j"
  1990. },
  1991. {
  1992. "type": "dl4j",
  1993. "target": "yolo2_dl4j_inference.v3.zip",
  1994. "source": "https://dl4jdata.blob.core.windows.net/models/yolo2_dl4j_inference.v3.zip",
  1995. "format": "Deeplearning4j",
  1996. "link": "https://github.com/eclipse/deeplearning4j"
  1997. },
  1998. {
  1999. "type": "dlc",
  2000. "target": "inception_v3_quantized.dlc",
  2001. "source": "https://github.com/lutzroeder/netron/files/5615377/inception_v3_quantized.dlc.zip[inception_v3_quantized.dlc]",
  2002. "error": "File contains undocumented DLC data in 'inception_v3_quantized.dlc'.",
  2003. "link": "https://github.com/lutzroeder/netron/issues/640"
  2004. },
  2005. {
  2006. "type": "dnn",
  2007. "target": "brows_model.dnn",
  2008. "source": "https://github.com/lutzroeder/netron/files/5118426/brows_model.zip[brows_model.dnn]",
  2009. "format": "SnapML v1",
  2010. "link": "https://github.com/lutzroeder/netron/issues/581"
  2011. },
  2012. {
  2013. "type": "flux",
  2014. "target": "helloworld.bson",
  2015. "source": "https://github.com/lutzroeder/netron/files/3638212/helloworld.zip[helloworld.bson]",
  2016. "format": "Flux",
  2017. "link": "https://github.com/lutzroeder/netron/issues/334"
  2018. },
  2019. {
  2020. "type": "keras",
  2021. "target": "babi_rnn.h5",
  2022. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[babi_rnn.h5]",
  2023. "format": "Keras v2.1.2",
  2024. "link": "https://github.com/lutzroeder/netron/issues/57"
  2025. },
  2026. {
  2027. "type": "keras",
  2028. "target": "bidirectional_lstm.h5",
  2029. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[bidirectional_lstm.h5]",
  2030. "format": "Keras v2.1.2",
  2031. "link": "https://github.com/lutzroeder/netron/issues/57"
  2032. },
  2033. {
  2034. "type": "keras",
  2035. "target": "cats_and_dogs_small_1.h5",
  2036. "source": "https://raw.githubusercontent.com/wwells/CUNY_DATA_698/master/DL_Coursework/DLR/cats_and_dogs_small_1.h5",
  2037. "format": "Keras v2.1.5",
  2038. "link": "https://github.com/wwells/CUNY_DATA_698/tree/master/DL_Coursework/DLR"
  2039. },
  2040. {
  2041. "type": "keras",
  2042. "target": "cats_and_dogs_small_2.h5",
  2043. "source": "https://raw.githubusercontent.com/kylehamilton/deep-learning-with-r-notebooks/master/cats_and_dogs_small_2.h5",
  2044. "format": "Keras v2.0.9",
  2045. "link": "https://github.com/kylehamilton/deep-learning-with-r-notebooks"
  2046. },
  2047. {
  2048. "type": "keras",
  2049. "target": "cats_and_dogs_2_activation.h5",
  2050. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[cats_and_dogs_2_activation.h5]",
  2051. "format": "Keras v2.1.3",
  2052. "link": "https://github.com/lutzroeder/netron/issues/57"
  2053. },
  2054. {
  2055. "type": "keras",
  2056. "target": "cifar10_m4_iter_70000.caffemodel.h5",
  2057. "source": "https://raw.githubusercontent.com/ARM-software/ML-examples/master/cmsisnn-cifar10/models/cifar10_m4_iter_70000.caffemodel.h5",
  2058. "format": "HDF5 Weights",
  2059. "link": "https://github.com/ARM-software/ML-examples"
  2060. },
  2061. {
  2062. "type": "keras",
  2063. "target": "CNN_SN_flaw1_v1.h5",
  2064. "source": "https://github.com/lutzroeder/netron/files/2452413/CNN_SN_flaw1_v1.h5.zip[CNN_SN_flaw1_v1.h5]",
  2065. "format": "Keras v2.2.3",
  2066. "link": "https://github.com/lutzroeder/netron/issues/157"
  2067. },
  2068. {
  2069. "type": "keras",
  2070. "target": "DenseNet121.h5",
  2071. "script": "./tools/tf sync install zoo",
  2072. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2073. },
  2074. {
  2075. "type": "keras",
  2076. "target": "generating_images_with_vaes.h5",
  2077. "source": "https://github.com/lutzroeder/netron/files/2592326/generating_images_with_vaes.h5.zip[generating_images_with_vaes.h5]",
  2078. "format": "Keras v2.1.3",
  2079. "link": "https://github.com/fchollet/deep-learning-with-python-notebooks/blob/master/8.4-generating-images-with-vaes.ipynb"
  2080. },
  2081. {
  2082. "type": "keras",
  2083. "target": "generator_model.h5",
  2084. "source": "https://raw.githubusercontent.com/mattya/chainer-DCGAN/master/generator_model.h5",
  2085. "format": "HDF5 Weights",
  2086. "link": "https://github.com/mattya/chainer-DCGAN"
  2087. },
  2088. {
  2089. "type": "keras",
  2090. "target": "imdb_embedding.h5",
  2091. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[imdb_embedding.h5]",
  2092. "format": "Keras v2.1.3",
  2093. "link": "https://github.com/lutzroeder/netron/issues/57"
  2094. },
  2095. {
  2096. "type": "keras",
  2097. "target": "imdb_simplernn.h5",
  2098. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[imdb_simplernn.h5]",
  2099. "format": "Keras v2.1.3",
  2100. "link": "https://github.com/lutzroeder/netron/issues/57"
  2101. },
  2102. {
  2103. "type": "keras",
  2104. "target": "InceptionResNetV2.h5",
  2105. "script": "./tools/tf sync install zoo",
  2106. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2107. },
  2108. {
  2109. "type": "keras",
  2110. "target": "InceptionV3.h5",
  2111. "script": "./tools/tf sync install zoo",
  2112. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2113. },
  2114. {
  2115. "type": "keras",
  2116. "target": "keras_invalid_file.h5",
  2117. "source": "https://github.com/lutzroeder/netron/files/3364286/keras_invalid_file.zip[keras_invalid_file.h5]",
  2118. "error": "File has no content.",
  2119. "link": "https://github.com/lutzroeder/netron/issues/57"
  2120. },
  2121. {
  2122. "type": "keras",
  2123. "target": "lstm_seq2seq.h5",
  2124. "source": "https://github.com/lutzroeder/netron/files/2592328/lstm_seq2seq.zip[lstm_seq2seq.h5]",
  2125. "format": "Keras v2.1.2",
  2126. "link": "https://github.com/lutzroeder/netron/issues/57"
  2127. },
  2128. {
  2129. "type": "keras",
  2130. "target": "lstm_seq2seq.json",
  2131. "source": "https://github.com/lutzroeder/netron/files/2592328/lstm_seq2seq.zip[lstm_seq2seq.json] ",
  2132. "format": "Keras",
  2133. "link": "https://github.com/lutzroeder/netron/issues/57"
  2134. },
  2135. {
  2136. "type": "keras",
  2137. "target": "mlp.h5",
  2138. "source": "https://github.com/lutzroeder/netron/files/3666244/mlp.zip[mlp.h5]",
  2139. "format": "HDF5 Weights",
  2140. "link": "https://github.com/lutzroeder/netron/issues/337"
  2141. },
  2142. {
  2143. "type": "keras",
  2144. "target": "mimo.h5",
  2145. "source": "https://github.com/lutzroeder/netron/files/2565761/mimo.h5.zip[mimo.h5]",
  2146. "format": "Keras v2.2.0",
  2147. "link": "https://github.com/lutzroeder/netron/issues/138"
  2148. },
  2149. {
  2150. "type": "keras",
  2151. "target": "mnist_float16.h5",
  2152. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float16.h5]",
  2153. "format": "Keras v2.1.2",
  2154. "link": "https://github.com/lutzroeder/netron/issues/57"
  2155. },
  2156. {
  2157. "type": "keras",
  2158. "target": "mnist_float32.h5",
  2159. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float32.h5]",
  2160. "format": "Keras v2.1.2",
  2161. "link": "https://github.com/lutzroeder/netron/issues/57"
  2162. },
  2163. {
  2164. "type": "keras",
  2165. "target": "mnist_float64.h5",
  2166. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float64.h5]",
  2167. "format": "Keras v2.1.2",
  2168. "link": "https://github.com/lutzroeder/netron/issues/57"
  2169. },
  2170. {
  2171. "type": "keras",
  2172. "target": "mobilenet.h5",
  2173. "source": "https://raw.githubusercontent.com/aio-libs/aiohttp-demos/master/demos/imagetagger/tests/data/mobilenet.h5",
  2174. "format": "Keras v2.2.2",
  2175. "link": "https://github.com/aio-libs/aiohttp-demos/tree/master/demos/imagetagger/tests/data"
  2176. },
  2177. {
  2178. "type": "keras",
  2179. "target": "mobilenet_v1_1.0_224_quant.hdf5",
  2180. "source": "https://github.com/lutzroeder/netron/files/4484451/mobilenet_v1_1.0_224_quant.zip[mobilenet_v1_1.0_224_quant.hdf5]",
  2181. "format": "HDF5 Weights",
  2182. "link": "https://github.com/lutzroeder/netron/issues/467"
  2183. },
  2184. {
  2185. "type": "keras",
  2186. "target": "MobileNetV2.h5",
  2187. "script": "./tools/tf sync install zoo",
  2188. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2189. },
  2190. {
  2191. "type": "keras",
  2192. "target": "NASNetMobile.h5",
  2193. "script": "./tools/tf sync install zoo",
  2194. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2195. },
  2196. {
  2197. "type": "keras",
  2198. "target": "nested_bidrectional.h5",
  2199. "source": "https://github.com/lutzroeder/netron/files/4304644/nested_bidrectional.zip[nested_bidrectional.h5]",
  2200. "format": "Keras v2.3.1",
  2201. "link": "https://github.com/lutzroeder/netron/issues/428"
  2202. },
  2203. {
  2204. "type": "keras",
  2205. "target": "nested_bidrectional_weights.h5",
  2206. "source": "https://github.com/lutzroeder/netron/files/4304644/nested_bidrectional.zip[nested_bidrectional_weights.h5]",
  2207. "format": "Keras v2.3.1",
  2208. "link": "https://github.com/lutzroeder/netron/issues/428"
  2209. },
  2210. {
  2211. "type": "keras",
  2212. "target": "netron_issue_326.json",
  2213. "source": "https://github.com/lutzroeder/netron/files/3563087/netron_issue_326.zip[netron_issue_326.json]",
  2214. "format": "Keras v2.2.4-tf",
  2215. "link": "https://github.com/lutzroeder/netron/issues/326"
  2216. },
  2217. {
  2218. "type": "keras",
  2219. "target": "netron_issue_428.h5",
  2220. "source": "https://github.com/lutzroeder/netron/files/4221535/netron_issue_428.zip[netron_issue_428.h5]",
  2221. "format": "Keras v2.2.4-tf",
  2222. "link": "https://github.com/lutzroeder/netron/issues/428"
  2223. },
  2224. {
  2225. "type": "keras",
  2226. "target": "netron_issue_435.h5",
  2227. "source": "https://github.com/lutzroeder/netron/files/4269953/netron_issue_435.zip[netron_issue_435.h5]",
  2228. "format": "Keras v2.2.4",
  2229. "link": "https://github.com/lutzroeder/netron/issues/435"
  2230. },
  2231. {
  2232. "type": "keras",
  2233. "target": "netron_issue_553.h5",
  2234. "source": "https://github.com/lutzroeder/netron/files/4979486/netron_issue_553.zip[netron_issue_553.h5]",
  2235. "format": "Keras v2.2.4-tf",
  2236. "link": "https://github.com/lutzroeder/netron/issues/553"
  2237. },
  2238. {
  2239. "type": "keras",
  2240. "target": "nietzsche.h5",
  2241. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[nietzsche.h5]",
  2242. "format": "Keras v2.1.3",
  2243. "link": "https://github.com/lutzroeder/netron/issues/57"
  2244. },
  2245. {
  2246. "type": "keras",
  2247. "target": "residual_cnn.h5",
  2248. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[residual_cnn.h5]",
  2249. "format": "Keras v2.1.2",
  2250. "link": "https://github.com/lutzroeder/netron/issues/57"
  2251. },
  2252. {
  2253. "type": "keras",
  2254. "target": "resnet50_weights_tf_dim_ordering_tf_kernels.h5",
  2255. "source": "https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels.h5",
  2256. "format": "Keras"
  2257. },
  2258. {
  2259. "type": "keras",
  2260. "target": "sentiment_model.h5",
  2261. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[sentiment_model.h5]",
  2262. "format": "Keras v2.1.3",
  2263. "link": "https://github.com/lutzroeder/netron/issues/57"
  2264. },
  2265. {
  2266. "type": "keras",
  2267. "target": "siamese_net.json",
  2268. "source": "https://github.com/lutzroeder/netron/files/2592353/siamese_net.json.zip[siamese_net.json]",
  2269. "format": "Keras",
  2270. "link": "https://github.com/lutzroeder/netron/issues/130"
  2271. },
  2272. {
  2273. "type": "keras",
  2274. "target": "snapshot_parent_0097.h5",
  2275. "source": "https://raw.githubusercontent.com/uber-research/deep-neuroevolution/master/visual_inspector/sample_data/mujoco/final_xy_bc/snapshots/snapshot_gen_0097/snapshot_parent_0097.h5",
  2276. "error": "File format is not HDF5 Weights in 'snapshot_parent_0097.h5'.",
  2277. "link": "https://github.com/uber-research/deep-neuroevolution"
  2278. },
  2279. {
  2280. "type": "keras",
  2281. "target": "time_distributed.h5",
  2282. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[time_distributed.h5]",
  2283. "format": "Keras v2.1.2",
  2284. "link": "https://github.com/lutzroeder/netron/issues/57"
  2285. },
  2286. {
  2287. "type": "keras",
  2288. "target": "tiny-yolo-voc.h5",
  2289. "source": "https://raw.githubusercontent.com/hollance/YOLO-CoreML-MPSNNGraph/master/Convert/yad2k/model_data/tiny-yolo-voc.h5",
  2290. "format": "Keras v1.2.2",
  2291. "link": "https://github.com/hollance/YOLO-CoreML-MPSNNGraph/tree/master/Convert/yad2k/model_data"
  2292. },
  2293. {
  2294. "type": "keras",
  2295. "target": "tiramisu_fc_dense103_model.json",
  2296. "source": "https://raw.githubusercontent.com/0bserver07/One-Hundred-Layers-Tiramisu/master/tiramisu_fc_dense103_model.json",
  2297. "format": "Keras v2.0.2", "runtime": "tensorflow",
  2298. "link": "https://github.com/0bserver07/One-Hundred-Layers-Tiramisu"
  2299. },
  2300. {
  2301. "type": "keras",
  2302. "target": "yolov3-tiny.h5",
  2303. "source": "https://github.com/lutzroeder/netron/files/5192003/yolov3-tiny.zip[yolov3-tiny.h5]",
  2304. "format": "Keras v2.4.0", "runtime": "tensorflow",
  2305. "link": "https://github.com/lutzroeder/netron/issues/540"
  2306. },
  2307. {
  2308. "type": "keras",
  2309. "target": "VGG19.h5",
  2310. "script": "./tools/tf sync install zoo",
  2311. "link": "https://www.tensorflow.org/api_docs/python/tf/keras/applications"
  2312. },
  2313. {
  2314. "type": "mediapipe",
  2315. "target": "clipped_images_from_file_at_24fps.pbtxt",
  2316. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/media_sequence/clipped_images_from_file_at_24fps.pbtxt",
  2317. "format": "MediaPipe",
  2318. "link": "https://github.com/google/mediapipe"
  2319. },
  2320. {
  2321. "type": "mediapipe",
  2322. "target": "face_detection_mobile_cpu.pbtxt",
  2323. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/face_detection/face_detection_mobile_cpu.pbtxt",
  2324. "format": "MediaPipe",
  2325. "link": "https://github.com/google/mediapipe"
  2326. },
  2327. {
  2328. "type": "mediapipe",
  2329. "target": "hand_detection_mobile.pbtxt",
  2330. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/hand_tracking/hand_detection_mobile.pbtxt",
  2331. "format": "MediaPipe",
  2332. "link": "https://github.com/google/mediapipe"
  2333. },
  2334. {
  2335. "type": "mediapipe",
  2336. "target": "hand_tracking_mobile.pbtxt",
  2337. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/hand_tracking/hand_tracking_mobile.pbtxt",
  2338. "format": "MediaPipe",
  2339. "link": "https://github.com/google/mediapipe"
  2340. },
  2341. {
  2342. "type": "mediapipe",
  2343. "target": "object_detection_desktop_live.pbtxt",
  2344. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/examples/coral/graphs/object_detection_desktop_live.pbtxt",
  2345. "format": "MediaPipe",
  2346. "link": "https://github.com/google/mediapipe"
  2347. },
  2348. {
  2349. "type": "mediapipe",
  2350. "target": "object_occlusion_tracking.pbtxt",
  2351. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/object_detection_3d/object_occlusion_tracking.pbtxt",
  2352. "format": "MediaPipe",
  2353. "link": "https://github.com/lutzroeder/netron/issues/444"
  2354. },
  2355. {
  2356. "type": "mediapipe",
  2357. "target": "tvl1_flow_and_rgb_from_file.pbtxt",
  2358. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/media_sequence/tvl1_flow_and_rgb_from_file.pbtxt",
  2359. "format": "MediaPipe",
  2360. "link": "https://github.com/google/mediapipe"
  2361. },
  2362. {
  2363. "type": "mediapipe",
  2364. "target": "yt8m_dataset_model_inference.pbtxt",
  2365. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/youtube8m/yt8m_dataset_model_inference.pbtxt",
  2366. "format": "MediaPipe",
  2367. "link": "https://github.com/google/mediapipe"
  2368. },
  2369. {
  2370. "type": "mlnet",
  2371. "target": "BinaryClassification_AutoML_SentimentModel.zip",
  2372. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/BinaryClassification_AutoML/SentimentAnalysis/MLModels/SentimentModel.zip",
  2373. "format": "ML.NET v1.0.27701.1",
  2374. "link": "https://github.com/dotnet/machinelearning-samples"
  2375. },
  2376. {
  2377. "type": "mlnet",
  2378. "target": "BikeDemandForecasting.zip",
  2379. "source": "https://github.com/lutzroeder/netron/files/4042150/MLModel.zip",
  2380. "format": "ML.NET v1.4.28305.1",
  2381. "link": "https://github.com/dotnet/machinelearning-samples"
  2382. },
  2383. {
  2384. "type": "mlnet",
  2385. "target": "ep_model1.zip",
  2386. "source": "https://github.com/lutzroeder/netron/files/4216033/ep_model1.zip",
  2387. "format": "ML.NET v1.0.0.0",
  2388. "link": "https://github.com/lutzroeder/netron/issues/170"
  2389. },
  2390. {
  2391. "type": "mlnet",
  2392. "target": "ep_model3.zip",
  2393. "source": "https://github.com/lutzroeder/netron/files/4216304/ep_model3.zip",
  2394. "format": "ML.NET v1.0.0.0",
  2395. "link": "https://github.com/lutzroeder/netron/issues/170"
  2396. },
  2397. {
  2398. "type": "mlnet",
  2399. "target": "FastTreeModel.zip",
  2400. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/FastTreeModel.zip",
  2401. "format": "ML.NET v1.0.0.0",
  2402. "link": "https://github.com/dotnet/machinelearning-samples"
  2403. },
  2404. {
  2405. "type": "mlnet",
  2406. "target": "FastTreeTweedieModel.zip",
  2407. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/FastTreeTweedieModel.zip",
  2408. "format": "ML.NET v1.0.0.0",
  2409. "link": "https://github.com/dotnet/machinelearning-samples"
  2410. },
  2411. {
  2412. "type": "mlnet",
  2413. "target": "GitHubLabelerModel.zip",
  2414. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/MulticlassClassification-GitHubLabeler/GitHubLabeler/MLModels/GitHubLabelerModel.zip",
  2415. "format": "ML.NET v1.0.27701.1",
  2416. "link": "https://github.com/dotnet/machinelearning-samples"
  2417. },
  2418. {
  2419. "type": "mlnet",
  2420. "target": "ImageClassification.Predict.imageClassifier.zip",
  2421. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/MLNETModel/imageClassifier.zip",
  2422. "format": "ML.NET v1.4.28230.4",
  2423. "link": "https://github.com/dotnet/machinelearning-samples"
  2424. },
  2425. {
  2426. "type": "mlnet",
  2427. "target": "IrisClassificationModel.zip",
  2428. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/MulticlassClassification_Iris/IrisClassification/MLModels/IrisClassificationModel.zip",
  2429. "format": "ML.NET v1.0.0.0",
  2430. "link": "https://github.com/dotnet/machinelearning-samples"
  2431. },
  2432. {
  2433. "type": "mlnet",
  2434. "target": "MovieRecommender_Model.zip",
  2435. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/Recommendation-MovieRecommender/MovieRecommender_Model/Model/model.zip",
  2436. "format": "ML.NET v1.4.28230.4",
  2437. "link": "https://github.com/dotnet/machinelearning-samples"
  2438. },
  2439. {
  2440. "type": "mlnet",
  2441. "target": "ngram.zip",
  2442. "source": "https://github.com/lutzroeder/netron/files/4216079/ngram.zip?raw=true",
  2443. "format": "ML.NET v3.10.29.504",
  2444. "link": "https://github.com/lutzroeder/netron/issues/170"
  2445. },
  2446. {
  2447. "type": "mlnet",
  2448. "target": "PoissonModel.zip",
  2449. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/PoissonModel.zip",
  2450. "format": "ML.NET v1.0.0.0",
  2451. "link": "https://github.com/dotnet/machinelearning-samples"
  2452. },
  2453. {
  2454. "type": "mlnet",
  2455. "target": "product_month_fastTreeTweedie.zip",
  2456. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/Forecasting-Sales/src/eShopDashboard/Forecast/ModelFiles/product_month_fastTreeTweedie.zip",
  2457. "format": "ML.NET v1.3.28006.10",
  2458. "link": "https://github.com/dotnet/machinelearning-samples"
  2459. },
  2460. {
  2461. "type": "mlnet",
  2462. "target": "ProductSalesChangePointModel.zip",
  2463. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/AnomalyDetection-Sales/SpikeDetectionE2EApp/MLModels/ProductSalesChangePointModel.zip",
  2464. "format": "ML.NET v1.4.28305.1",
  2465. "link": "https://github.com/dotnet/machinelearning-samples"
  2466. },
  2467. {
  2468. "type": "mlnet",
  2469. "target": "ProductSalesSpikeModel.zip",
  2470. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/AnomalyDetection-Sales/SpikeDetectionE2EApp/MLModels/ProductSalesSpikeModel.zip",
  2471. "format": "ML.NET v1.4.28305.1",
  2472. "link": "https://github.com/dotnet/machinelearning-samples"
  2473. },
  2474. {
  2475. "type": "mlnet",
  2476. "target": "randomizedPca.zip",
  2477. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/AnomalyDetection_CreditCardFraudDetection/CreditCardFraudDetection.Predictor/assets/input/randomizedPca.zip",
  2478. "format": "ML.NET v1.2.27902.10",
  2479. "link": "https://github.com/dotnet/machinelearning-samples"
  2480. },
  2481. {
  2482. "type": "mlnet",
  2483. "target": "retailClustering.zip",
  2484. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Clustering_CustomerSegmentation/CustomerSegmentation.Train/assets/outputs/retailClustering.zip",
  2485. "format": "ML.NET v1.0.27701.1",
  2486. "link": "https://github.com/dotnet/machinelearning-samples"
  2487. },
  2488. {
  2489. "type": "mlnet",
  2490. "target": "SDCAModel.zip",
  2491. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/SDCAModel.zip",
  2492. "format": "ML.NET v1.0.0.0",
  2493. "link": "https://github.com/dotnet/machinelearning-samples"
  2494. },
  2495. {
  2496. "type": "mlnet",
  2497. "target": "TaxiFareModel.zip",
  2498. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_AutoML/TaxiFarePrediction/MLModels/TaxiFareModel.zip",
  2499. "format": "ML.NET v1.5.28926.5",
  2500. "link": "https://github.com/dotnet/machinelearning-samples"
  2501. },
  2502. {
  2503. "type": "mlnet",
  2504. "target": "termlookup_with_key.zip",
  2505. "source": "https://github.com/lutzroeder/netron/files/4216237/termlookup_with_key.zip?raw=true",
  2506. "format": "ML.NET v1.0.0.0",
  2507. "link": "https://github.com/lutzroeder/netron/issues/170"
  2508. },
  2509. {
  2510. "type": "mlnet",
  2511. "target": "TinyYoloModel.zip",
  2512. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/61b428c746f39069a9d1d92f9e0f819e6beb30f3/samples/csharp/end-to-end-apps/DeepLearning_ObjectDetection_Onnx/OnnxObjectDetectionE2EAPP/ML/MLNETModel/TinyYoloModel.zip",
  2513. "format": "ML.NET v1.0.27701.1"
  2514. },
  2515. {
  2516. "type": "mnn",
  2517. "target": "blazeface.mnn",
  2518. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/blazeface/tensorflow/jni/blazeface.mnn",
  2519. "format": "MNN v2",
  2520. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2521. },
  2522. {
  2523. "type": "mnn",
  2524. "target": "blazeface_quant.mnn",
  2525. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/blazeface/tensorflow/jni/blazeface_quant.mnn",
  2526. "format": "MNN v2",
  2527. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2528. },
  2529. {
  2530. "type": "mnn",
  2531. "target": "face_det.mnn",
  2532. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/mssd/tflite/jni/face_det.mnn",
  2533. "format": "MNN v2",
  2534. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2535. },
  2536. {
  2537. "type": "mnn",
  2538. "target": "Kmeans.mnn",
  2539. "source": "https://github.com/lutzroeder/netron/files/5405963/Kmeans.mnn.zip[Kmeans.mnn]",
  2540. "format": "MNN v2",
  2541. "link": "https://github.com/lutzroeder/netron/issues/341"
  2542. },
  2543. {
  2544. "type": "mnn",
  2545. "target": "inception-v3.mnn",
  2546. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/inception-v3.mnn",
  2547. "format": "MNN v2",
  2548. "link": "https://github.com/alibaba/MNN"
  2549. },
  2550. {
  2551. "type": "mnn",
  2552. "target": "inception-v3.mnn",
  2553. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/inception-v3.mnn",
  2554. "format": "MNN v2",
  2555. "link": "https://github.com/alibaba/MNN"
  2556. },
  2557. {
  2558. "type": "mnn",
  2559. "target": "mobilenet-v1-1.0.mnn",
  2560. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/mobilenet-v1-1.0.mnn",
  2561. "format": "MNN v2",
  2562. "link": "https://github.com/alibaba/MNN"
  2563. },
  2564. {
  2565. "type": "mnn",
  2566. "target": "MobileNetV2_224.mnn",
  2567. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/MobileNetV2_224.mnn",
  2568. "format": "MNN v2",
  2569. "link": "https://github.com/alibaba/MNN"
  2570. },
  2571. {
  2572. "type": "mnn",
  2573. "target": "resnet-v2-50.mnn",
  2574. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/resnet-v2-50.mnn",
  2575. "format": "MNN v2",
  2576. "link": "https://github.com/alibaba/MNN"
  2577. },
  2578. {
  2579. "type": "mnn",
  2580. "target": "simple.mnn",
  2581. "source": "https://github.com/lutzroeder/netron/files/3698466/simple.mnn.zip[simple.mnn]",
  2582. "format": "MNN v2",
  2583. "link": "https://github.com/lutzroeder/netron/issues/341"
  2584. },
  2585. {
  2586. "type": "mnn",
  2587. "target": "SqueezeNetV1.0.mnn",
  2588. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/SqueezeNetV1.0.mnn",
  2589. "format": "MNN v2",
  2590. "link": "https://github.com/alibaba/MNN"
  2591. },
  2592. {
  2593. "type": "mnn",
  2594. "target": "tf_body_det.mnn",
  2595. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/mssd/tensorflow/jni/tf_body_det.mnn",
  2596. "format": "MNN v2",
  2597. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2598. },
  2599. {
  2600. "type": "mslite",
  2601. "target": "conv_autopad_onnx.ms",
  2602. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/conv_autopad_onnx.ms",
  2603. "format": "MindSpore Lite v1.0.0",
  2604. "link": "https://github.com/mindspore-ai/mindspore"
  2605. },
  2606. {
  2607. "type": "mslite",
  2608. "target": "deeplab_mobilenetv2_513_tflite.ms",
  2609. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/deeplab_mobilenetv2_513_tflite.ms",
  2610. "format": "MindSpore Lite v1.0.0",
  2611. "link": "https://github.com/mindspore-ai/mindspore"
  2612. },
  2613. {
  2614. "type": "mslite",
  2615. "target": "densenet_tflite.ms",
  2616. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/densenet_tflite.ms",
  2617. "format": "MindSpore Lite v1.0.0",
  2618. "link": "https://github.com/mindspore-ai/mindspore"
  2619. },
  2620. {
  2621. "type": "mslite",
  2622. "target": "inception_resnet_v2_tflite.ms",
  2623. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/inception_resnet_v2_tflite.ms",
  2624. "format": "MindSpore Lite v1.0.0",
  2625. "link": "https://github.com/mindspore-ai/mindspore"
  2626. },
  2627. {
  2628. "type": "mslite",
  2629. "target": "mobilenet_v1_1.0_224_tflite.ms",
  2630. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/mobilenet_v1_1.0_224_tflite.ms",
  2631. "format": "MindSpore Lite v1.0.0",
  2632. "link": "https://github.com/mindspore-ai/mindspore"
  2633. },
  2634. {
  2635. "type": "mslite",
  2636. "target": "squeezenet1.1_onnx.ms",
  2637. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/squeezenet1.1_onnx.ms",
  2638. "format": "MindSpore Lite v1.0.0",
  2639. "link": "https://github.com/mindspore-ai/mindspore"
  2640. },
  2641. {
  2642. "type": "mslite",
  2643. "target": "ssd_onnx.ms",
  2644. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/ssd_onnx.ms",
  2645. "format": "MindSpore Lite v1.0.0",
  2646. "link": "https://github.com/mindspore-ai/mindspore"
  2647. },
  2648. {
  2649. "type": "mslite",
  2650. "target": "super-resolution-10_onnx.ms",
  2651. "source": "https://github.com/YvetteLaw/test/releases/download/v1.0/super-resolution-10_onnx.ms",
  2652. "format": "MindSpore Lite v1.0.0",
  2653. "link": "https://github.com/mindspore-ai/mindspore"
  2654. },
  2655. {
  2656. "type": "mxnet",
  2657. "target": "bvlc_alexnet-symbol.json,bvlc_alexnet-0000.params",
  2658. "source": "http://s3.amazonaws.com/store.carml.org/models/mxnet/bvlc_alexnet/bvlc_alexnet-symbol.json,http://s3.amazonaws.com/store.carml.org/models/mxnet/bvlc_alexnet/bvlc_alexnet-0000.params",
  2659. "format": "MXNet v0.10.0",
  2660. "link": "https://github.com/rai-project/mxnet/blob/master/builtin_models/BVLC-AlexNet.yml"
  2661. },
  2662. {
  2663. "type": "mxnet",
  2664. "target": "crepe.mar",
  2665. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/crepe.mar",
  2666. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2667. },
  2668. {
  2669. "type": "mxnet",
  2670. "target": "conv_weights_sharing.json",
  2671. "source": "https://github.com/lutzroeder/netron/files/3016064/conv_weights_sharing.json.zip[conv_weights_sharing.json]",
  2672. "format": "MXNet v1.3.0",
  2673. "link": "https://github.com/lutzroeder/netron/issues/245"
  2674. },
  2675. {
  2676. "type": "mxnet",
  2677. "target": "deep3d-symbol.json",
  2678. "source": "https://raw.githubusercontent.com/dmlc/mxnet-gtc-tutorial/master/deep3d/deep3d-symbol.json",
  2679. "format": "MXNet",
  2680. "link": "https://github.com/dmlc/mxnet-gtc-tutorial/tree/master/deep3d"
  2681. },
  2682. {
  2683. "type": "mxnet",
  2684. "target": "dpn68-symbol.json",
  2685. "source": "http://s3.amazonaws.com/store.carml.org/models/mxnet/dpn68/dpn68-symbol.json",
  2686. "format": "MXNet",
  2687. "link": "https://github.com/rai-project/mxnet/blob/master/builtin_models/DPN68.yml"
  2688. },
  2689. {
  2690. "type": "mxnet",
  2691. "target": "ferplus.model",
  2692. "source": "https://s3.amazonaws.com/model-server/models/FERPlus/ferplus.model",
  2693. "format": "MXNet Model Server v0.2",
  2694. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2695. },
  2696. {
  2697. "type": "mxnet",
  2698. "target": "inception_resnet_v2-symbol.json",
  2699. "source": "https://raw.githubusercontent.com/soeaver/mxnet-model/master/cls/inception/inception_resnet_v2-symbol.json",
  2700. "format": "MXNet v1.0.1",
  2701. "link": "https://github.com/soeaver/mxnet-model/tree/master/cls"
  2702. },
  2703. {
  2704. "type": "mxnet",
  2705. "target": "inception_v1.model",
  2706. "source": "https://s3.amazonaws.com/model-server/models/onnx-inception_v1/inception_v1.model",
  2707. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2708. },
  2709. {
  2710. "type": "mxnet",
  2711. "target": "inception_v3-symbol.json",
  2712. "source": "https://raw.githubusercontent.com/soeaver/mxnet-model/master/cls/inception/inception_v3-symbol.json",
  2713. "format": "MXNet v0.11.0",
  2714. "link": "https://github.com/soeaver/mxnet-model/tree/master/cls"
  2715. },
  2716. {
  2717. "type": "mxnet",
  2718. "target": "Inception-7-symbol.json",
  2719. "source": "https://raw.githubusercontent.com/bzshang/yelp-photo-classification/master/mxnet_model/inception_v3/Inception-7-symbol.json",
  2720. "format": "MXNet",
  2721. "link": "https://github.com/bzshang/yelp-photo-classification/tree/master/mxnet_model/inception_v3"
  2722. },
  2723. {
  2724. "type": "mxnet",
  2725. "target": "Inception-BN.model",
  2726. "source": "https://s3.amazonaws.com/model-server/models/inception-bn/Inception-BN.model"
  2727. },
  2728. {
  2729. "type": "mxnet",
  2730. "target": "Inception-BN-0126.params,Inception-BN-symbol.json",
  2731. "source": "http://data.mxnet.io/models/imagenet/inception-bn/Inception-BN-0126.params,http://data.mxnet.io/models/imagenet/inception-bn/Inception-BN-symbol.json",
  2732. "format": "MXNet",
  2733. "link": "https://mxnet.apache.org/model_zoo/index.html"
  2734. },
  2735. {
  2736. "type": "mxnet",
  2737. "target": "lstm_ptb.model",
  2738. "source": "https://s3.amazonaws.com/model-server/models/lstm_ptb/lstm_ptb.model",
  2739. "format": "MXNet Model Server v0.1",
  2740. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2741. },
  2742. {
  2743. "type": "mxnet",
  2744. "target": "lstm_ptb-symbol.json",
  2745. "source": "https://s3.amazonaws.com/model-server/models/lstm_ptb/lstm_ptb-symbol.json",
  2746. "format": "MXNet v0.11.0",
  2747. "link": "https://github.com/awslabs/mxnet-model-server/tree/master/examples/lstm_ptb"
  2748. },
  2749. {
  2750. "type": "mxnet",
  2751. "target": "mobilenet-v1-tvm.json",
  2752. "source": "https://github.com/lutzroeder/netron/files/2636924/mobilenet-v1-tvm.json.zip[mobilenet-v1-tvm.json]",
  2753. "format": "TVM",
  2754. "link": "https://github.com/lutzroeder/netron/issues/199"
  2755. },
  2756. {
  2757. "type": "mxnet",
  2758. "target": "nin.model",
  2759. "source": "https://s3.amazonaws.com/model-server/models/nin/nin.model",
  2760. "format": "MXNet Model Server v0.1",
  2761. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2762. },
  2763. {
  2764. "type": "mxnet",
  2765. "target": "resnet-18.model",
  2766. "source": "https://s3.amazonaws.com/model-server/models/resnet-18/resnet-18.model",
  2767. "format": "MXNet Model Server v0.1",
  2768. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2769. },
  2770. {
  2771. "type": "mxnet",
  2772. "target": "resnet-50-0000.params",
  2773. "source": "http://data.mxnet.io/models/imagenet/resnet/50-layers/resnet-50-0000.params",
  2774. "format": "MXNet",
  2775. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2776. },
  2777. {
  2778. "type": "mxnet",
  2779. "target": "resnet-101-symbol.json",
  2780. "source": "http://data.mxnet.io/models/imagenet/resnet/101-layers/resnet-101-symbol.json",
  2781. "format": "MXNet",
  2782. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2783. },
  2784. {
  2785. "type": "mxnet",
  2786. "target": "resnet-152-symbol.json",
  2787. "source": "http://data.mxnet.io/models/imagenet/resnet/152-layers/resnet-152-symbol.json",
  2788. "format": "MXNet",
  2789. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2790. },
  2791. {
  2792. "type": "mxnet",
  2793. "target": "resnet50_ssd_model.model",
  2794. "source": "https://s3.amazonaws.com/model-server/models/resnet50_ssd/resnet50_ssd_model.model",
  2795. "format": "MXNet Model Server v0.1",
  2796. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2797. },
  2798. {
  2799. "type": "mxnet",
  2800. "target": "resnext-101-64x4d.model",
  2801. "source": "https://s3.amazonaws.com/model-server/models/resnext-101-64x4d/resnext-101-64x4d.model",
  2802. "format": "MXNet Model Server v0.1", "runtime": "MXNet v0.12",
  2803. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2804. },
  2805. {
  2806. "type": "mxnet",
  2807. "target": "squeezenet_v1.1.model",
  2808. "source": "https://s3.amazonaws.com/model-server/models/squeezenet_v1.1/squeezenet_v1.1.model"
  2809. },
  2810. {
  2811. "type": "mxnet",
  2812. "target": "squeezenet_v1.1.mar",
  2813. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/squeezenet_v1.1.mar",
  2814. "format": "MXNet Model Archive v1.0",
  2815. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2816. },
  2817. {
  2818. "type": "mxnet",
  2819. "target": "squeezenet_v1.1.zip",
  2820. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/squeezenet_v1.1.mar",
  2821. "format": "MXNet",
  2822. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2823. },
  2824. {
  2825. "type": "mxnet",
  2826. "target": "vgg16.mar",
  2827. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/vgg16.mar"
  2828. },
  2829. {
  2830. "type": "ncnn",
  2831. "target": "centerface.param,centerface.bin",
  2832. "source": "https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/centerface.param,https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/centerface.bin",
  2833. "format": "ncnn",
  2834. "link": "https://github.com/MirrorYuChen/ncnn_example"
  2835. },
  2836. {
  2837. "type": "ncnn",
  2838. "target": "darknet_yolov2.cfg.ncnn,darknet_yolov2.weights.ncnn",
  2839. "source": "https://github.com/00liujj/gen-ncnn-models/raw/master/tests/darknet_yolov2.cfg.ncnn,https://github.com/00liujj/gen-ncnn-models/raw/master/tests/darknet_yolov2.weights.ncnn",
  2840. "format": "ncnn",
  2841. "link": "https://github.com/00liujj/gen-ncnn-models"
  2842. },
  2843. {
  2844. "type": "ncnn",
  2845. "target": "faces_wider_squeezenet.param,faces_wider_squeezenet.bin",
  2846. "source": "https://deepdetect.com/models/init/embedded/images/detection/squeezenet_ssd_faces_ncnn.tar.gz[faces_wider_squeezenet.param,faces_wider_squeezenet.bin]",
  2847. "format": "ncnn",
  2848. "link": "https://www.deepdetect.com/models/faces_embedded_ncnn"
  2849. },
  2850. {
  2851. "type": "ncnn",
  2852. "target": "frozen.pb.cfg.ncnn,frozen.pb.weights.ncnn",
  2853. "source": "https://github.com/00liujj/gen-ncnn-models/raw/master/tests/frozen.pb.cfg.ncnn,https://github.com/00liujj/gen-ncnn-models/raw/master/tests/frozen.pb.weights.ncnn",
  2854. "format": "ncnn",
  2855. "link": "https://github.com/00liujj/gen-ncnn-models"
  2856. },
  2857. {
  2858. "type": "ncnn",
  2859. "target": "googlenet.param",
  2860. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/googlenet.param",
  2861. "format": "ncnn",
  2862. "link": "https://github.com/Tencent/ncnn"
  2863. },
  2864. {
  2865. "type": "ncnn",
  2866. "target": "mnet-opt.param,mnet-opt.bin",
  2867. "source": "https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/mnet-opt.param,https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/mnet-opt.bin",
  2868. "format": "ncnn",
  2869. "link": "https://github.com/MirrorYuChen/ncnn_example"
  2870. },
  2871. {
  2872. "type": "ncnn",
  2873. "target": "mobilefacenet.bin,mobilefacenet.param",
  2874. "source": "https://raw.githubusercontent.com/GRAYKEY/mobilefacenet_ncnn/master/models/mobilefacenet.bin,https://raw.githubusercontent.com/GRAYKEY/mobilefacenet_ncnn/master/models/mobilefacenet.param",
  2875. "format": "ncnn",
  2876. "link": "https://github.com/GRAYKEY/mobilefacenet_ncnn"
  2877. },
  2878. {
  2879. "type": "ncnn",
  2880. "target": "mobilenetv2_yolov3.param",
  2881. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/mobilenetv2_yolov3.param",
  2882. "format": "ncnn",
  2883. "link": "https://github.com/Tencent/ncnn"
  2884. },
  2885. {
  2886. "type": "ncnn",
  2887. "target": "MobileNetSSD_deploy.param.bin,MobileNetSSD_deploy.bin",
  2888. "source": "https://raw.githubusercontent.com/chehongshu/ncnnforandroid_objectiondetection_Mobilenetssd/master/MobileNetSSD_demo/app/src/main/assets/MobileNetSSD_deploy.param.bin,https://raw.githubusercontent.com/chehongshu/ncnnforandroid_objectiondetection_Mobilenetssd/master/MobileNetSSD_demo/app/src/main/assets/MobileNetSSD_deploy.bin",
  2889. "format": "ncnn",
  2890. "link": "https://github.com/chehongshu/ncnnforandroid_objectiondetection_Mobilenetssd"
  2891. },
  2892. {
  2893. "type": "ncnn",
  2894. "target": "ncnn_yolo2_det3.bin,ncnn_yolo2_det3.param",
  2895. "source": "https://raw.githubusercontent.com/kyo055/ncnn_yolo2/master/models/det3.bin,https://raw.githubusercontent.com/kyo055/ncnn_yolo2/master/models/det3.param",
  2896. "format": "ncnn",
  2897. "link": "https://github.com/kyo055/ncnn_yolo2"
  2898. },
  2899. {
  2900. "type": "ncnn",
  2901. "target": "netron_issue_397.param",
  2902. "source": "https://github.com/lutzroeder/netron/files/3981934/det.txt",
  2903. "format": "ncnn",
  2904. "link": "https://github.com/lutzroeder/netron/issues/397"
  2905. },
  2906. {
  2907. "type": "ncnn",
  2908. "target": "proxylessnasnet.param",
  2909. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/proxylessnasnet.param",
  2910. "format": "ncnn",
  2911. "link": "https://github.com/Tencent/ncnn"
  2912. },
  2913. {
  2914. "type": "ncnn",
  2915. "target": "resnet18_int8.param",
  2916. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/resnet18_int8.param",
  2917. "format": "ncnn",
  2918. "link": "https://github.com/Tencent/ncnn"
  2919. },
  2920. {
  2921. "type": "ncnn",
  2922. "target": "shufflenet.param",
  2923. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/shufflenet.param",
  2924. "format": "ncnn",
  2925. "link": "https://github.com/Tencent/ncnn"
  2926. },
  2927. {
  2928. "type": "ncnn",
  2929. "target": "squeezenet.param",
  2930. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/squeezenet.param",
  2931. "format": "ncnn",
  2932. "link": "https://github.com/Tencent/ncnn"
  2933. },
  2934. {
  2935. "type": "ncnn",
  2936. "target": "squeezenet_v1.1.param.bin,squeezenet_v1.1.bin",
  2937. "source": "https://raw.githubusercontent.com/nihui/ncnn-android-squeezenet/master/app/src/main/assets/squeezenet_v1.1.param.bin,https://raw.githubusercontent.com/nihui/ncnn-android-squeezenet/master/app/src/main/assets/squeezenet_v1.1.bin",
  2938. "format": "ncnn",
  2939. "link": "https://github.com/Tencent/ncnn"
  2940. },
  2941. {
  2942. "type": "ncnn",
  2943. "target": "squeezenet_v1.1.bin",
  2944. "source": "https://raw.githubusercontent.com/nihui/ncnn-android-squeezenet/master/app/src/main/assets/squeezenet_v1.1.bin",
  2945. "error": "The file 'squeezenet_v1.1.param' does not exist in 'squeezenet_v1.1.bin'.",
  2946. "link": "https://github.com/Tencent/ncnn"
  2947. },
  2948. {
  2949. "type": "ncnn",
  2950. "target": "ssdmobilenet.param",
  2951. "source": "https://github.com/lutzroeder/netron/files/5165601/ssdmobilenet.zip[ssdmobilenet.param]",
  2952. "format": "ncnn",
  2953. "link": "https://github.com/lutzroeder/netron/issues/296"
  2954. },
  2955. {
  2956. "type": "ncnn",
  2957. "target": "vgg16.param",
  2958. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/vgg16.param",
  2959. "format": "ncnn",
  2960. "link": "https://github.com/Tencent/ncnn"
  2961. },
  2962. {
  2963. "type": "npz",
  2964. "target": "cifar10-1w-1a.npz",
  2965. "source": "https://raw.githubusercontent.com/Xilinx/BNN-PYNQ/master/bnn/src/training/cifar10-1w-1a.npz",
  2966. "format": "NumPy Zip",
  2967. "link": "https://github.com/Xilinx/BNN-PYNQ"
  2968. },
  2969. {
  2970. "type": "npz",
  2971. "target": "mlp.npz",
  2972. "source": "https://github.com/lutzroeder/netron/files/3666244/mlp.zip[mlp.npz]",
  2973. "format": "NumPy Zip",
  2974. "link": "https://github.com/lutzroeder/netron/issues/337"
  2975. },
  2976. {
  2977. "type": "onnx",
  2978. "target": "arcface-resnet100.onnx",
  2979. "source": "https://s3.amazonaws.com/onnx-model-zoo/arcface/resnet100/resnet100.onnx",
  2980. "format": "ONNX v3",
  2981. "link": "https://github.com/onnx/models/tree/master/models/face_recognition/ArcFace"
  2982. },
  2983. {
  2984. "type": "onnx",
  2985. "target": "bidaf.onnx",
  2986. "source": "https://onnxzoo.blob.core.windows.net/models/opset_9/bidaf/bidaf.onnx",
  2987. "format": "ONNX v4", "producer": "CNTK 2.7",
  2988. "link": "https://github.com/onnx/models/tree/master/bidaf"
  2989. },
  2990. {
  2991. "type": "onnx",
  2992. "target": "bertsquad-10.zip",
  2993. "source": "https://github.com/lutzroeder/netron/files/5251086/bertsquad-10.zip",
  2994. "format": "ONNX v5", "producer": "tf2onnx 1.5.2",
  2995. "action": "skip-render",
  2996. "link": "https://github.com/onnx/models/blob/master/text/machine_comprehension/bert-squad/README.md"
  2997. },
  2998. {
  2999. "type": "onnx",
  3000. "target": "bvlc_alexnet_opset_3.onnx.zip",
  3001. "source": "https://github.com/lutzroeder/netron/files/5296267/bvlc_alexnet_opset_3.onnx.zip",
  3002. "format": "ONNX v3",
  3003. "link": "https://github.com/lutzroeder/netron/issues/188"
  3004. },
  3005. {
  3006. "type": "onnx",
  3007. "target": "bvlc_googlenet_opset_9.onnx",
  3008. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/bvlc_googlenet.tar.gz[bvlc_googlenet/model.onnx]",
  3009. "link": "https://github.com/onnx/models/tree/master/bvlc_googlenet"
  3010. },
  3011. {
  3012. "type": "onnx",
  3013. "target": "candy.onnx",
  3014. "source": "https://raw.githubusercontent.com/Microsoft/Windows-Machine-Learning/master/Samples/FNSCandyStyleTransfer/UWP/cs/Assets/candy.onnx",
  3015. "format": "ONNX v3",
  3016. "link": "https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/FNSCandyStyleTransfer/UWP/cs/Assets"
  3017. },
  3018. {
  3019. "type": "onnx",
  3020. "target": "conv_autopad.onnx",
  3021. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/conv_autopad.onnx",
  3022. "format": "ONNX v3",
  3023. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3024. },
  3025. {
  3026. "type": "onnx",
  3027. "target": "denotation_Add_ImageNet1920WithImageMetadataBgr8_SRGB_0_255.onnx",
  3028. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataBgr8_SRGB_0_255.onnx]",
  3029. "format": "ONNX v3",
  3030. "link": "https://github.com/lutzroeder/netron/issues/183"
  3031. },
  3032. {
  3033. "type": "onnx",
  3034. "target": "denotation_Add_ImageNet1920WithImageMetadataBgra8_SRGB_0_255.onnx",
  3035. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataBgra8_SRGB_0_255.onnx]",
  3036. "format": "ONNX v3",
  3037. "link": "https://github.com/lutzroeder/netron/issues/183"
  3038. },
  3039. {
  3040. "type": "onnx",
  3041. "target": "denotation_Add_ImageNet1920WithImageMetadataRgb8_SRGB_0_255.onnx",
  3042. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataRgb8_SRGB_0_255.onnx]",
  3043. "format": "ONNX v3",
  3044. "link": "https://github.com/lutzroeder/netron/issues/183"
  3045. },
  3046. {
  3047. "type": "onnx",
  3048. "target": "denotation_Add_ImageNet1920WithImageMetadataRgba8_SRGB_0_255.onnx",
  3049. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataRgba8_SRGB_0_255.onnx]",
  3050. "format": "ONNX v3",
  3051. "link": "https://github.com/lutzroeder/netron/issues/183"
  3052. },
  3053. {
  3054. "type": "onnx",
  3055. "target": "densenet121_opset_9.onnx",
  3056. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/densenet121.tar.gz[densenet121/model.onnx]"
  3057. },
  3058. {
  3059. "type": "onnx",
  3060. "target": "DocumentClassification.onnx",
  3061. "source": "https://github.com/lutzroeder/netron/files/2592479/DocumentClassification.onnx.zip[DocumentClassification.onnx]",
  3062. "format": "ONNX v3",
  3063. "link": "https://github.com/lutzroeder/netron/issues/188"
  3064. },
  3065. {
  3066. "type": "onnx",
  3067. "target": "EfficientDet-d0.onnx.zip",
  3068. "source": "https://github.com/lutzroeder/netron/files/5296050/EfficientDet-d0.onnx.zip",
  3069. "format": "ONNX v6",
  3070. "error": "Maximum call stack size exceeded",
  3071. "link": "https://github.com/lutzroeder/netron/issues/589"
  3072. },
  3073. {
  3074. "type": "onnx",
  3075. "target": "eisber_model3.pbtxt",
  3076. "source": "https://github.com/lutzroeder/netron/files/4209090/eisber_model3.pbtxt.zip[eisber_model3.pbtxt]",
  3077. "format": "ONNX v3",
  3078. "link": "https://github.com/lutzroeder/netron/issues/139"
  3079. },
  3080. {
  3081. "type": "onnx",
  3082. "target": "eisber_model3_invalid.pbtxt",
  3083. "source": "https://github.com/lutzroeder/netron/files/5011185/eisber_model3_invalid.pbtxt.zip[eisber_model3_invalid.pbtxt]",
  3084. "error": "File text format is not onnx.ModelProto (Unexpected '}' instead of ':' at 6:3) in 'eisber_model3_invalid.pbtxt'.",
  3085. "link": "https://github.com/lutzroeder/netron/issues/139"
  3086. },
  3087. {
  3088. "type": "onnx",
  3089. "target": "end2end_tfc_w1a1_oqnt_streamlined.onnx",
  3090. "source": "https://github.com/lutzroeder/netron/files/4885362/end2end_tfc_w1a1_oqnt_streamlined.zip[end2end_tfc_w1a1_oqnt_streamlined.onnx]",
  3091. "format": "ONNX v4",
  3092. "link": "https://github.com/lutzroeder/netron/issues/532"
  3093. },
  3094. {
  3095. "type": "onnx",
  3096. "target": "Exermote.onnx",
  3097. "source": "https://github.com/lutzroeder/netron/files/2592478/Exermote.onnx.zip[Exermote.onnx]",
  3098. "format": "ONNX v3",
  3099. "link": "https://github.com/lutzroeder/netron/issues/188"
  3100. },
  3101. {
  3102. "type": "onnx",
  3103. "target": "emoji8.onnx",
  3104. "source": "https://raw.githubusercontent.com/Microsoft/Windows-Machine-Learning/master/Samples/Emoji8/UWP/cs/Emoji8/Models/model.onnx",
  3105. "format": "ONNX v3",
  3106. "link": "https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/Emoji8/UWP/cs/Emoji8"
  3107. },
  3108. {
  3109. "type": "onnx",
  3110. "target": "emotion_ferplus_opset_8.onnx",
  3111. "source": "https://onnxzoo.blob.core.windows.net/models/opset_8/emotion_ferplus/emotion_ferplus.tar.gz[emotion_ferplus/model.onnx]"
  3112. },
  3113. {
  3114. "type": "onnx",
  3115. "target": "FastStyleNet.onnx",
  3116. "source": "https://raw.githubusercontent.com/tkat0/chainer-nnvm-example/master/models/chainer-fast-neuralstyle/FastStyleNet.onnx",
  3117. "format": "ONNX v1", "producer": "Chainer 3.2.0"
  3118. },
  3119. {
  3120. "type": "onnx",
  3121. "target": "FCLayer_graph.onnx",
  3122. "source": "https://raw.githubusercontent.com/Xilinx/finn/master/notebooks/FCLayer_graph.onnx",
  3123. "format": "ONNX v6",
  3124. "link": "https://github.com/Xilinx/finn/tree/master/notebooks"
  3125. },
  3126. {
  3127. "type": "onnx",
  3128. "target": "input_0.pb",
  3129. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/shufflenet.tar.gz[shufflenet/test_data_set_0/input_0.pb]",
  3130. "format": "ONNX Tensor",
  3131. "link": "https://github.com/lutzroeder/netron/issues/550"
  3132. },
  3133. {
  3134. "type": "onnx",
  3135. "target": "inception_v1_opset_9.onnx",
  3136. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/inception_v1.tar.gz[inception_v1/model.onnx]"
  3137. },
  3138. {
  3139. "type": "onnx",
  3140. "target": "inception_v2_opset_6.onnx",
  3141. "source": "https://s3.amazonaws.com/download.onnx/models/opset_6/inception_v2.tar.gz[inception_v2/model.onnx]"
  3142. },
  3143. {
  3144. "type": "onnx",
  3145. "target": "inception_v2_opset_8.onnx",
  3146. "source": "https://s3.amazonaws.com/download.onnx/models/opset_8/inception_v2.tar.gz[inception_v2/model.onnx]"
  3147. },
  3148. {
  3149. "type": "onnx",
  3150. "target": "inception_v2_opset_9.onnx",
  3151. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/inception_v2.tar.gz[inception_v2/model.onnx]"
  3152. },
  3153. {
  3154. "type": "onnx",
  3155. "target": "Kmeans.onnx",
  3156. "source": "https://github.com/lutzroeder/netron/files/2592495/Kmeans.onnx.zip[Kmeans.onnx]",
  3157. "format": "ONNX v3", "producer": "ML.NET 0.7.27009.0",
  3158. "link": "https://github.com/lutzroeder/netron/issues/188"
  3159. },
  3160. {
  3161. "type": "onnx",
  3162. "target": "Kmeans.pbtxt",
  3163. "source": "https://github.com/lutzroeder/netron/files/4209089/Kmeans.pbtxt.zip[Kmeans.pbtxt]",
  3164. "format": "ONNX v3", "producer": "ML.NET 0.7.27009.0",
  3165. "link": "https://github.com/lutzroeder/netron/issues/139"
  3166. },
  3167. {
  3168. "type": "onnx",
  3169. "target": "LabelEncoder.onnx",
  3170. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/LabelEncoder.onnx",
  3171. "format": "ONNX v3",
  3172. "link": "https://github.com/Microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3173. },
  3174. {
  3175. "type": "onnx",
  3176. "target": "maskrcnn.onnx.zip",
  3177. "source": "https://github.com/lutzroeder/netron/files/5322320/maskrcnn.onnx.zip",
  3178. "format": "ONNX v6",
  3179. "action": "skip-render",
  3180. "link": "https://github.com/lutzroeder/netron/issues/188"
  3181. },
  3182. {
  3183. "type": "onnx",
  3184. "target": "mnist.onnx",
  3185. "source": "https://raw.githubusercontent.com/Microsoft/Windows-Machine-Learning/master/Samples/MNIST/Tutorial/cs/Assets/mnist.onnx",
  3186. "format": "ONNX v3",
  3187. "link": "https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/MNIST/Tutorial/cs/Assets"
  3188. },
  3189. {
  3190. "type": "onnx",
  3191. "target": "mnist_opset_9.onnx",
  3192. "source": "https://onnxzoo.blob.core.windows.net/models/opset_8/mnist/mnist.tar.gz[mnist/model.onnx]"
  3193. },
  3194. {
  3195. "type": "onnx",
  3196. "target": "mlnet_encoder.onnx",
  3197. "source": "https://raw.githubusercontent.com/Microsoft/onnxruntime/master/onnxruntime/test/testdata/mlnet_encoder.onnx",
  3198. "format": "ONNX v3",
  3199. "link": "https://github.com/Microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3200. },
  3201. {
  3202. "type": "onnx",
  3203. "target": "netron_issue_119.onnx",
  3204. "source": "https://github.com/lutzroeder/netron/files/4260629/netron_issue_119.zip[netron_issue_119.onnx]",
  3205. "format": "ONNX v4",
  3206. "link": "https://github.com/lutzroeder/netron/issues/119"
  3207. },
  3208. {
  3209. "type": "onnx",
  3210. "target": "netron_issue168_onnx_if.pbtxt",
  3211. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_if.pbtxt]",
  3212. "format": "ONNX v3",
  3213. "link": "https://github.com/lutzroeder/netron/issues/168"
  3214. },
  3215. {
  3216. "type": "onnx",
  3217. "target": "netron_issue168_onnx_loop.pbtxt",
  3218. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_loop.pbtxt]",
  3219. "format": "ONNX v3",
  3220. "link": "https://github.com/lutzroeder/netron/issues/168"
  3221. },
  3222. {
  3223. "type": "onnx",
  3224. "target": "netron_issue168_onnx_scan.pbtxt",
  3225. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_scan.pbtxt]",
  3226. "format": "ONNX v3",
  3227. "link": "https://github.com/lutzroeder/netron/issues/168"
  3228. },
  3229. {
  3230. "type": "onnx",
  3231. "target": "optional_1.onnx",
  3232. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/optional_1.onnx",
  3233. "format": "ONNX v3",
  3234. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3235. },
  3236. {
  3237. "type": "onnx",
  3238. "target": "resnet50_opset_9.onnx.zip",
  3239. "source": "https://github.com/lutzroeder/netron/files/5296268/resnet50_opset_9.onnx.zip",
  3240. "format": "ONNX v3",
  3241. "link": "https://github.com/lutzroeder/netron/issues/188"
  3242. },
  3243. {
  3244. "type": "onnx",
  3245. "target": "resnet50v2.onnx",
  3246. "source": "https://s3.amazonaws.com/onnx-model-zoo/resnet/resnet50v2/resnet50v2.onnx"
  3247. },
  3248. {
  3249. "type": "onnx",
  3250. "target": "reshape_opset_4.pb",
  3251. "source": "https://github.com/lutzroeder/netron/files/2592375/reshape_opset.zip[reshape_opset_4.pb]",
  3252. "format": "ONNX v3",
  3253. "link": "https://github.com/lutzroeder/netron/pull/97"
  3254. },
  3255. {
  3256. "type": "onnx",
  3257. "target": "reshape_opset_6.pb",
  3258. "source": "https://github.com/lutzroeder/netron/files/2592375/reshape_opset.zip[reshape_opset_6.pb]",
  3259. "format": "ONNX v3",
  3260. "link": "https://github.com/lutzroeder/netron/pull/97"
  3261. },
  3262. {
  3263. "type": "onnx",
  3264. "target": "shufflenet_float16.onnx",
  3265. "source": "https://github.com/lutzroeder/netron/files/2592368/shufflenet_float16.onnx.zip[shufflenet_float16.onnx]",
  3266. "format": "ONNX v3",
  3267. "link": "https://github.com/lutzroeder/netron/issues/186"
  3268. },
  3269. {
  3270. "type": "onnx",
  3271. "target": "shufflenet_opset_9.onnx",
  3272. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/shufflenet.tar.gz[shufflenet/model.onnx]",
  3273. "link": "https://github.com/onnx/models/tree/master/shufflenet"
  3274. },
  3275. {
  3276. "type": "onnx",
  3277. "target": "sparse_const.onnx",
  3278. "source": "https://github.com/lutzroeder/netron/files/5198627/sparse_const.zip[sparse_const.onnx]",
  3279. "format": "ONNX v7",
  3280. "link": "https://github.com/lutzroeder/netron/issues/188"
  3281. },
  3282. {
  3283. "type": "onnx",
  3284. "target": "squeezenet.onnx",
  3285. "source": "https://raw.githubusercontent.com/onnx/tutorials/master/tutorials/assets/squeezenet.onnx",
  3286. "format": "ONNX v1", "producer": "pytorch 0.2"
  3287. },
  3288. {
  3289. "type": "onnx",
  3290. "target": "squeezenet1.1.onnx",
  3291. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.onnx",
  3292. "format": "ONNX v3",
  3293. "link": "https://github.com/onnx/models/tree/master/vision/classification/squeezenet"
  3294. },
  3295. {
  3296. "type": "onnx",
  3297. "target": "squeezenet1.1_shape.onnx",
  3298. "source": "https://github.com/lutzroeder/netron/files/3935903/squeezenet1.1_shape.onnx.zip[squeezenet1.1_shape.onnx]",
  3299. "format": "ONNX v3",
  3300. "link": "https://github.com/lutzroeder/netron/issues/188"
  3301. },
  3302. {
  3303. "type": "onnx",
  3304. "target": "squeezenet1.1.pb",
  3305. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.onnx",
  3306. "format": "ONNX v3",
  3307. "link": "https://github.com/onnx/models/tree/master/models/image_classification/squeezenet"
  3308. },
  3309. {
  3310. "type": "onnx",
  3311. "target": "squeezenet1.1.tgz",
  3312. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.tar.gz",
  3313. "format": "ONNX v3",
  3314. "link": "https://github.com/onnx/models/tree/master/models/image_classification/squeezenet"
  3315. },
  3316. {
  3317. "type": "onnx",
  3318. "target": "ssd.onnx.zip",
  3319. "source": "https://github.com/lutzroeder/netron/files/5296269/ssd.onnx.zip",
  3320. "format": "ONNX v4",
  3321. "link": "https://github.com/lutzroeder/netron/issues/188"
  3322. },
  3323. {
  3324. "type": "onnx",
  3325. "target": "super-resolution-10.onnx",
  3326. "source": "https://media.githubusercontent.com/media/onnx/models/master/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx",
  3327. "format": "ONNX v4", "producer": "pytorch 1.1",
  3328. "link": "https://github.com/onnx/models/tree/master/vision/super_resolution/sub_pixel_cnn_2016"
  3329. },
  3330. {
  3331. "type": "onnx",
  3332. "target": "super_resolution_0.2.onnx",
  3333. "source": "https://gist.github.com/zhreshold/bcda4716699ac97ea44f791c24310193/raw/93672b029103648953c4e5ad3ac3aadf346a4cdc/super_resolution_0.2.onnx",
  3334. "format": "ONNX v1", "producer": "pytorch 0.2"
  3335. },
  3336. {
  3337. "type": "onnx",
  3338. "target": "test_LSTM_tanh_bidirectional.onnx",
  3339. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/CNTK/test_LSTM.tanh.bidirectional//model.onnx",
  3340. "format": "ONNX v3",
  3341. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3342. },
  3343. {
  3344. "type": "onnx",
  3345. "target": "test_RNN_bidirectional_one_layer_relu.onnx",
  3346. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/CNTK/test_RNN.bidirectional.one_layer.relu//model.onnx",
  3347. "format": "ONNX v3",
  3348. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3349. },
  3350. {
  3351. "type": "onnx",
  3352. "target": "test_lstm_with_peepholes.onnx",
  3353. "source": "https://raw.githubusercontent.com/onnx/onnx/master/onnx/backend/test/data/node/test_lstm_with_peepholes/model.onnx",
  3354. "format": "ONNX v3",
  3355. "link": "https://github.com/onnx/onnx/tree/master/onnx/backend/test/data"
  3356. },
  3357. {
  3358. "type": "onnx",
  3359. "target": "tiny_yolov2_opset_8.onnx",
  3360. "source": "https://onnxzoo.blob.core.windows.net/models/opset_8/tiny_yolov2/tiny_yolov2.tar.gz[tiny_yolov2/./Model.onnx]",
  3361. "link": "https://github.com/onnx/models/tree/master/vision/object_detection_segmentation/tiny_yolov2"
  3362. },
  3363. {
  3364. "type": "onnx",
  3365. "target": "YOLOv2_tiny.onnx",
  3366. "source": "https://raw.githubusercontent.com/tkat0/chainer-nnvm-example/master/models/YOLOv2_tiny/YOLOv2_tiny.onnx",
  3367. "format": "ONNX v1", "producer": "Chainer 3.2.0",
  3368. "link": "https://github.com/tkat0/chainer-nnvm-example"
  3369. },
  3370. {
  3371. "type": "onnx",
  3372. "target": "yolov3.onnx",
  3373. "source": "https://github.com/lutzroeder/netron/files/5581031/yolov3.onnx.zip[yolov3.onnx]",
  3374. "format": "ONNX v5", "producer": "keras2onnx 1.5.1",
  3375. "link": "https://github.com/lutzroeder/netron/issues/188"
  3376. },
  3377. {
  3378. "type": "onnx",
  3379. "target": "vgg19.onnx",
  3380. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/vgg19.tar.gz[vgg19/model.onnx]",
  3381. "format": "ONNX v3",
  3382. "link": "https://github.com/onnx/models/tree/master/vision/classification/vgg"
  3383. },
  3384. {
  3385. "type": "onnx",
  3386. "target": "zipmap_int64float.onnx",
  3387. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/zipmap_int64float.onnx",
  3388. "format": "ONNX v3",
  3389. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3390. },
  3391. {
  3392. "type": "openvino",
  3393. "target": "2018_R3_age-gender-recognition-retail-0013.xml,2018_R3_age-gender-recognition-retail-0013.bin",
  3394. "source": "https://download.01.org/openvinotoolkit/2018_R3/open_model_zoo/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml,https://download.01.org/openvinotoolkit/2018_R3/open_model_zoo/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.bin",
  3395. "format": "OpenVINO IR",
  3396. "link": "https://download.01.org/openvinotoolkit"
  3397. },
  3398. {
  3399. "type": "openvino",
  3400. "target": "2018_R3_rm_cnn4a.xml",
  3401. "source": "https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/rm_cnn4a_smbr/rm_cnn4a.xml",
  3402. "format": "OpenVINO IR",
  3403. "link": "https://download.01.org/openvinotoolkit"
  3404. },
  3405. {
  3406. "type": "openvino",
  3407. "target": "2018_R3_rm_lstm4f.xml,2018_R3_rm_lstm4f.bin",
  3408. "source": "https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/rm_lstm4f/rm_lstm4f.xml,https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/rm_lstm4f/rm_lstm4f.bin",
  3409. "format": "OpenVINO IR",
  3410. "link": "https://download.01.org/openvinotoolkit"
  3411. },
  3412. {
  3413. "type": "openvino",
  3414. "target": "2018_R3_wsj_dnn5b.xml",
  3415. "source": "https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/wsj_dnn5b_smbr/wsj_dnn5b.xml",
  3416. "format": "OpenVINO IR",
  3417. "link": "https://download.01.org/openvinotoolkit"
  3418. },
  3419. {
  3420. "type": "openvino",
  3421. "target": "2018_R4_emotions-recognition-retail-0003.bin,2018_R4_emotions-recognition-retail-0003.xml",
  3422. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.bin,https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.xml",
  3423. "format": "OpenVINO IR",
  3424. "link": "https://download.01.org/openvinotoolkit"
  3425. },
  3426. {
  3427. "type": "openvino",
  3428. "target": "2018_R4_face-detection-adas-0001.xml",
  3429. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-detection-adas-0001/FP32/face-detection-adas-0001.xml",
  3430. "format": "OpenVINO IR",
  3431. "link": "https://download.01.org/openvinotoolkit"
  3432. },
  3433. {
  3434. "type": "openvino",
  3435. "target": "2018_R4_face-detection-retail-0004.xml",
  3436. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-detection-retail-0004/FP32/face-detection-retail-0004.xml",
  3437. "format": "OpenVINO IR",
  3438. "link": "https://download.01.org/openvinotoolkit"
  3439. },
  3440. {
  3441. "type": "openvino",
  3442. "target": "2018_R4_face-person-detection-retail-0002.xml",
  3443. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-person-detection-retail-0002/FP32/face-person-detection-retail-0002.xml",
  3444. "format": "OpenVINO IR",
  3445. "link": "https://download.01.org/openvinotoolkit"
  3446. },
  3447. {
  3448. "type": "openvino",
  3449. "target": "2018_R4_face-reidentification-retail-0071.xml",
  3450. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-reidentification-retail-0071/FP32/face-reidentification-retail-0071.xml",
  3451. "format": "OpenVINO IR",
  3452. "link": "https://download.01.org/openvinotoolkit"
  3453. },
  3454. {
  3455. "type": "openvino",
  3456. "target": "2018_R4_facial-landmarks-35-adas-0001.xml",
  3457. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/facial-landmarks-35-adas-0001/FP32/facial-landmarks-35-adas-0001.xml",
  3458. "format": "OpenVINO IR",
  3459. "link": "https://download.01.org/openvinotoolkit"
  3460. },
  3461. {
  3462. "type": "openvino",
  3463. "target": "2018_R4_head-pose-estimation-adas-0001.xml",
  3464. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml",
  3465. "format": "OpenVINO IR",
  3466. "link": "https://download.01.org/openvinotoolkit"
  3467. },
  3468. {
  3469. "type": "openvino",
  3470. "target": "2018_R4_human-pose-estimation-0001.xml",
  3471. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml",
  3472. "format": "OpenVINO IR",
  3473. "link": "https://download.01.org/openvinotoolkit"
  3474. },
  3475. {
  3476. "type": "openvino",
  3477. "target": "2018_R4_landmarks-regression-retail-0009.xml",
  3478. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml",
  3479. "format": "OpenVINO IR",
  3480. "link": "https://download.01.org/openvinotoolkit"
  3481. },
  3482. {
  3483. "type": "openvino",
  3484. "target": "2018_R4_person-attributes-recognition-crossroad-0031.xml",
  3485. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-attributes-recognition-crossroad-0031/FP32/person-attributes-recognition-crossroad-0031.xml",
  3486. "format": "OpenVINO IR",
  3487. "link": "https://download.01.org/openvinotoolkit"
  3488. },
  3489. {
  3490. "type": "openvino",
  3491. "target": "2018_R4_pedestrian-detection-adas-0002.xml",
  3492. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/pedestrian-detection-adas-0002/FP32/pedestrian-detection-adas-0002.xml",
  3493. "format": "OpenVINO IR",
  3494. "link": "https://download.01.org/openvinotoolkit"
  3495. },
  3496. {
  3497. "type": "openvino",
  3498. "target": "2018_R4_person-detection-retail-0001.xml",
  3499. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-retail-0001/FP32/person-detection-retail-0001.xml",
  3500. "format": "OpenVINO IR",
  3501. "link": "https://download.01.org/openvinotoolkit"
  3502. },
  3503. {
  3504. "type": "openvino",
  3505. "target": "2018_R4_person-detection-retail-0013.xml",
  3506. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-retail-0013/FP32/person-detection-retail-0013.xml",
  3507. "format": "OpenVINO IR",
  3508. "link": "https://download.01.org/openvinotoolkit"
  3509. },
  3510. {
  3511. "type": "openvino",
  3512. "target": "2018_R4_person-reidentification-retail-0031.xml",
  3513. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0031/FP32/person-reidentification-retail-0031.xml",
  3514. "format": "OpenVINO IR",
  3515. "link": "https://download.01.org/openvinotoolkit"
  3516. },
  3517. {
  3518. "type": "openvino",
  3519. "target": "2018_R4_person-reidentification-retail-0076.xml",
  3520. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0076/FP32/person-reidentification-retail-0076.xml",
  3521. "format": "OpenVINO IR",
  3522. "link": "https://download.01.org/openvinotoolkit"
  3523. },
  3524. {
  3525. "type": "openvino",
  3526. "target": "2018_R4_person-detection-action-recognition-0003.xml",
  3527. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-action-recognition-0003/FP32/person-detection-action-recognition-0003.xml",
  3528. "format": "OpenVINO IR",
  3529. "link": "https://download.01.org/openvinotoolkit"
  3530. },
  3531. {
  3532. "type": "openvino",
  3533. "target": "2018_R4_person-reidentification-retail-0079.xml",
  3534. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0079/FP32/person-reidentification-retail-0079.xml",
  3535. "format": "OpenVINO IR",
  3536. "link": "https://download.01.org/openvinotoolkit"
  3537. },
  3538. {
  3539. "type": "openvino",
  3540. "target": "2018_R4_person-vehicle-bike-detection-crossroad-0078.xml",
  3541. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-vehicle-bike-detection-crossroad-0078/FP32/person-vehicle-bike-detection-crossroad-0078.xml",
  3542. "format": "OpenVINO IR",
  3543. "link": "https://download.01.org/openvinotoolkit"
  3544. },
  3545. {
  3546. "type": "openvino",
  3547. "target": "2018_R4_road-segmentation-adas-0001.xml",
  3548. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/road-segmentation-adas-0001/FP32/road-segmentation-adas-0001.xml",
  3549. "format": "OpenVINO IR",
  3550. "link": "https://download.01.org/openvinotoolkit"
  3551. },
  3552. {
  3553. "type": "openvino",
  3554. "target": "2018_R5_age-gender-recognition-retail-0013.xml",
  3555. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml",
  3556. "format": "OpenVINO IR",
  3557. "link": "https://download.01.org/openvinotoolkit"
  3558. },
  3559. {
  3560. "type": "openvino",
  3561. "target": "2018_R5_emotions-recognition-retail-0003.xml,2018_R5_emotions-recognition-retail-0003.bin",
  3562. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.xml,https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.bin",
  3563. "format": "OpenVINO IR",
  3564. "link": "https://download.01.org/openvinotoolkit"
  3565. },
  3566. {
  3567. "type": "openvino",
  3568. "target": "2018_R5_face-detection-adas-0001.xml",
  3569. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-detection-adas-0001/FP32/face-detection-adas-0001.xml",
  3570. "format": "OpenVINO IR",
  3571. "link": "https://download.01.org/openvinotoolkit"
  3572. },
  3573. {
  3574. "type": "openvino",
  3575. "target": "2018_R5_face-detection-retail-0004.xml",
  3576. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-detection-retail-0004/FP32/face-detection-retail-0004.xml",
  3577. "format": "OpenVINO IR",
  3578. "link": "https://download.01.org/openvinotoolkit"
  3579. },
  3580. {
  3581. "type": "openvino",
  3582. "target": "2018_R5_face-person-detection-retail-0002.xml",
  3583. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-person-detection-retail-0002/FP32/face-person-detection-retail-0002.xml",
  3584. "format": "OpenVINO IR",
  3585. "link": "https://download.01.org/openvinotoolkit"
  3586. },
  3587. {
  3588. "type": "openvino",
  3589. "target": "2018_R5_face-reidentification-retail-0095.xml",
  3590. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-reidentification-retail-0095/FP32/face-reidentification-retail-0095.xml",
  3591. "format": "OpenVINO IR",
  3592. "link": "https://download.01.org/openvinotoolkit"
  3593. },
  3594. {
  3595. "type": "openvino",
  3596. "target": "2018_R5_facial-landmarks-35-adas-0001.xml",
  3597. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/facial-landmarks-35-adas-0001/FP32/facial-landmarks-35-adas-0001.xml",
  3598. "format": "OpenVINO IR",
  3599. "link": "https://download.01.org/openvinotoolkit"
  3600. },
  3601. {
  3602. "type": "openvino",
  3603. "target": "2018_R5_head-pose-estimation-adas-0001.xml",
  3604. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml",
  3605. "format": "OpenVINO IR",
  3606. "link": "https://download.01.org/openvinotoolkit"
  3607. },
  3608. {
  3609. "type": "openvino",
  3610. "target": "2018_R5_human-pose-estimation-0001.xml",
  3611. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml",
  3612. "format": "OpenVINO IR",
  3613. "link": "https://download.01.org/openvinotoolkit"
  3614. },
  3615. {
  3616. "type": "openvino",
  3617. "target": "2018_R5_landmarks-regression-retail-0009.xml",
  3618. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml",
  3619. "format": "OpenVINO IR",
  3620. "link": "https://download.01.org/openvinotoolkit"
  3621. },
  3622. {
  3623. "type": "openvino",
  3624. "target": "2018_R4_landmarks-regression-retail-0009-fp16.xml,2018_R4_landmarks-regression-retail-0009-fp16.bin",
  3625. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/landmarks-regression-retail-0009/FP16/landmarks-regression-retail-0009.xml,https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/landmarks-regression-retail-0009/FP16/landmarks-regression-retail-0009.bin",
  3626. "format": "OpenVINO IR",
  3627. "link": "https://download.01.org/openvinotoolkit"
  3628. },
  3629. {
  3630. "type": "openvino",
  3631. "target": "2018_R4_license-plate-recognition-barrier-0001.xml",
  3632. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/license-plate-recognition-barrier-0001/FP32/license-plate-recognition-barrier-0001.xml",
  3633. "format": "OpenVINO IR",
  3634. "link": "https://download.01.org/openvinotoolkit"
  3635. },
  3636. {
  3637. "type": "openvino",
  3638. "target": "2018_R4_pedestrian-and-vehicle-detector-adas-0001.xml",
  3639. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/pedestrian-and-vehicle-detector-adas-0001/FP32/pedestrian-and-vehicle-detector-adas-0001.xml",
  3640. "format": "OpenVINO IR",
  3641. "link": "https://download.01.org/openvinotoolkit"
  3642. },
  3643. {
  3644. "type": "openvino",
  3645. "target": "2018_R4_semantic-segmentation-adas-0001.xml",
  3646. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/semantic-segmentation-adas-0001/FP32/semantic-segmentation-adas-0001.xml",
  3647. "format": "OpenVINO IR",
  3648. "link": "https://download.01.org/openvinotoolkit"
  3649. },
  3650. {
  3651. "type": "openvino",
  3652. "target": "2018_R4_single-image-super-resolution-0034.xml",
  3653. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/single-image-super-resolution-0034/FP32/single-image-super-resolution-0034.xml",
  3654. "format": "OpenVINO IR",
  3655. "link": "https://download.01.org/openvinotoolkit"
  3656. },
  3657. {
  3658. "type": "openvino",
  3659. "target": "2018_R4_vehicle-attributes-recognition-barrier-0039.xml",
  3660. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/vehicle-attributes-recognition-barrier-0039/FP32/vehicle-attributes-recognition-barrier-0039.xml",
  3661. "format": "OpenVINO IR",
  3662. "link": "https://download.01.org/openvinotoolkit"
  3663. },
  3664. {
  3665. "type": "openvino",
  3666. "target": "2018_R4_vehicle-detection-adas-0002.xml",
  3667. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/vehicle-detection-adas-0002/FP32/vehicle-detection-adas-0002.xml",
  3668. "format": "OpenVINO IR",
  3669. "link": "https://download.01.org/openvinotoolkit"
  3670. },
  3671. {
  3672. "type": "openvino",
  3673. "target": "2018_R4_vehicle-license-plate-detection-barrier-0106.xml",
  3674. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/vehicle-license-plate-detection-barrier-0106/FP32/vehicle-license-plate-detection-barrier-0106.xml",
  3675. "format": "OpenVINO IR",
  3676. "link": "https://download.01.org/openvinotoolkit"
  3677. },
  3678. {
  3679. "type": "openvino",
  3680. "target": "2018_R5_license-plate-recognition-barrier-0001.xml",
  3681. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/license-plate-recognition-barrier-0001/FP32/license-plate-recognition-barrier-0001.xml",
  3682. "format": "OpenVINO IR",
  3683. "link": "https://download.01.org/openvinotoolkit"
  3684. },
  3685. {
  3686. "type": "openvino",
  3687. "target": "2018_R5_pedestrian-and-vehicle-detector-adas-0001.xml",
  3688. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/pedestrian-and-vehicle-detector-adas-0001/FP32/pedestrian-and-vehicle-detector-adas-0001.xml",
  3689. "format": "OpenVINO IR",
  3690. "link": "https://download.01.org/openvinotoolkit"
  3691. },
  3692. {
  3693. "type": "openvino",
  3694. "target": "2018_R5_pedestrian-detection-adas-0002.xml",
  3695. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/pedestrian-detection-adas-0002/FP32/pedestrian-detection-adas-0002.xml",
  3696. "format": "OpenVINO IR",
  3697. "link": "https://download.01.org/openvinotoolkit"
  3698. },
  3699. {
  3700. "type": "openvino",
  3701. "target": "2018_R5_person-attributes-recognition-crossroad-0200.xml",
  3702. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-attributes-recognition-crossroad-0200/FP32/person-attributes-recognition-crossroad-0200.xml",
  3703. "format": "OpenVINO IR",
  3704. "link": "https://download.01.org/openvinotoolkit"
  3705. },
  3706. {
  3707. "type": "openvino",
  3708. "target": "2018_R5_person-detection-action-recognition-0004.xml",
  3709. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-action-recognition-0004/FP32/person-detection-action-recognition-0004.xml",
  3710. "format": "OpenVINO IR",
  3711. "link": "https://download.01.org/openvinotoolkit"
  3712. },
  3713. {
  3714. "type": "openvino",
  3715. "target": "2018_R5_person-detection-retail-0002.xml",
  3716. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-retail-0002/FP32/person-detection-retail-0002.xml",
  3717. "format": "OpenVINO IR",
  3718. "link": "https://download.01.org/openvinotoolkit"
  3719. },
  3720. {
  3721. "type": "openvino",
  3722. "target": "2018_R5_person-detection-retail-0013.xml",
  3723. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-retail-0013/FP32/person-detection-retail-0013.xml",
  3724. "format": "OpenVINO IR",
  3725. "link": "https://download.01.org/openvinotoolkit"
  3726. },
  3727. {
  3728. "type": "openvino",
  3729. "target": "2018_R5_person-reidentification-retail-0031.xml",
  3730. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0031/FP32/person-reidentification-retail-0031.xml",
  3731. "format": "OpenVINO IR",
  3732. "link": "https://download.01.org/openvinotoolkit"
  3733. },
  3734. {
  3735. "type": "openvino",
  3736. "target": "2018_R5_person-reidentification-retail-0076.xml",
  3737. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0076/FP32/person-reidentification-retail-0076.xml",
  3738. "format": "OpenVINO IR",
  3739. "link": "https://download.01.org/openvinotoolkit"
  3740. },
  3741. {
  3742. "type": "openvino",
  3743. "target": "2018_R5_person-reidentification-retail-0079.xml",
  3744. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0079/FP32/person-reidentification-retail-0079.xml",
  3745. "format": "OpenVINO IR",
  3746. "link": "https://download.01.org/openvinotoolkit"
  3747. },
  3748. {
  3749. "type": "openvino",
  3750. "target": "2018_R5_person-vehicle-bike-detection-crossroad-0078.xml",
  3751. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-vehicle-bike-detection-crossroad-0078/FP32/person-vehicle-bike-detection-crossroad-0078.xml",
  3752. "format": "OpenVINO IR",
  3753. "link": "https://download.01.org/openvinotoolkit"
  3754. },
  3755. {
  3756. "type": "openvino",
  3757. "target": "2018_R5_road-segmentation-adas-0001.xml",
  3758. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/road-segmentation-adas-0001/FP32/road-segmentation-adas-0001.xml",
  3759. "format": "OpenVINO IR",
  3760. "link": "https://download.01.org/openvinotoolkit"
  3761. },
  3762. {
  3763. "type": "openvino",
  3764. "target": "2018_R5_semantic-segmentation-adas-0001.xml",
  3765. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/semantic-segmentation-adas-0001/FP32/semantic-segmentation-adas-0001.xml",
  3766. "format": "OpenVINO IR",
  3767. "link": "https://download.01.org/openvinotoolkit"
  3768. },
  3769. {
  3770. "type": "openvino",
  3771. "target": "2018_R5_single-image-super-resolution-0063.xml",
  3772. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-0063/FP32/single-image-super-resolution-0063.xml",
  3773. "format": "OpenVINO IR",
  3774. "link": "https://download.01.org/openvinotoolkit"
  3775. },
  3776. {
  3777. "type": "openvino",
  3778. "target": "2018_R5_single-image-super-resolution-1011.xml",
  3779. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-1011/FP32/single-image-super-resolution-1011.xml",
  3780. "format": "OpenVINO IR",
  3781. "link": "https://download.01.org/openvinotoolkit"
  3782. },
  3783. {
  3784. "type": "openvino",
  3785. "target": "2018_R5_single-image-super-resolution-1021.xml",
  3786. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-1021/FP32/single-image-super-resolution-1021.xml",
  3787. "format": "OpenVINO IR",
  3788. "link": "https://download.01.org/openvinotoolkit"
  3789. },
  3790. {
  3791. "type": "openvino",
  3792. "target": "2018_R5_text-detection-0001.xml",
  3793. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/text-detection-0001/FP32/text-detection-0001.xml",
  3794. "format": "OpenVINO IR",
  3795. "link": "https://download.01.org/openvinotoolkit"
  3796. },
  3797. {
  3798. "type": "openvino",
  3799. "target": "2018_R5_vehicle-attributes-recognition-barrier-0039.xml",
  3800. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/vehicle-attributes-recognition-barrier-0039/FP32/vehicle-attributes-recognition-barrier-0039.xml",
  3801. "format": "OpenVINO IR",
  3802. "link": "https://download.01.org/openvinotoolkit"
  3803. },
  3804. {
  3805. "type": "openvino",
  3806. "target": "2018_R5_vehicle-detection-adas-0002.xml",
  3807. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/vehicle-detection-adas-0002/FP32/vehicle-detection-adas-0002.xml",
  3808. "format": "OpenVINO IR",
  3809. "link": "https://download.01.org/openvinotoolkit"
  3810. },
  3811. {
  3812. "type": "openvino",
  3813. "target": "2018_R5_vehicle-license-plate-detection-barrier-0106.xml",
  3814. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/vehicle-license-plate-detection-barrier-0106/FP32/vehicle-license-plate-detection-barrier-0106.xml",
  3815. "format": "OpenVINO IR",
  3816. "link": "https://download.01.org/openvinotoolkit"
  3817. },
  3818. {
  3819. "type": "openvino",
  3820. "target": "2019_R1_resnet50-binary-0001.bin,2019_R1_resnet50-binary-0001.xml",
  3821. "source": "https://download.01.org/opencv/2019/open_model_zoo/R1/models_bin/resnet50-binary-0001/resnet50-binary-0001.bin,https://download.01.org/opencv/2019/open_model_zoo/R1/models_bin/resnet50-binary-0001/resnet50-binary-0001.xml",
  3822. "format": "OpenVINO IR",
  3823. "link": "https://download.01.org/opencv"
  3824. },
  3825. {
  3826. "type": "openvino",
  3827. "target": "netron_issue_372.xml",
  3828. "source": "https://github.com/lutzroeder/netron/files/4447843/netron_issue_372.zip[netron_issue_372.xml]",
  3829. "format": "OpenVINO IR",
  3830. "link": "https://github.com/lutzroeder/netron/issues/372"
  3831. },
  3832. {
  3833. "type": "openvino",
  3834. "target": "netron_issue_484.xml,netron_issue_484.bin",
  3835. "source": "https://github.com/lutzroeder/netron/files/4569338/netron_issue_484.zip[netron_issue_484.xml,netron_issue_484.bin]",
  3836. "format": "OpenVINO IR",
  3837. "link": "https://github.com/lutzroeder/netron/issues/484"
  3838. },
  3839. {
  3840. "type": "openvino",
  3841. "target": "netron_issue_572.xml,netron_issue_572.bin",
  3842. "source": "https://github.com/lutzroeder/netron/files/5114040/netron_issue_572.zip[netron_issue_572.xml,netron_issue_572.bin]",
  3843. "format": "OpenVINO IR",
  3844. "link": "https://github.com/lutzroeder/netron/issues/572"
  3845. },
  3846. {
  3847. "type": "openvino",
  3848. "target": "with_pad_simple.xml",
  3849. "source": "https://github.com/lutzroeder/netron/files/2871673/with_pad_simple.xml.zip[with_pad_simple.xml]",
  3850. "format": "OpenVINO IR",
  3851. "link": "https://download.01.org/openvinotoolkit"
  3852. },
  3853. {
  3854. "type": "openvino",
  3855. "target": "with_nd_conv_simple.xml",
  3856. "source": "https://github.com/lutzroeder/netron/files/2871696/with_nd_conv_simple.xml.zip[with_nd_conv_simple.xml]",
  3857. "format": "OpenVINO IR",
  3858. "link": "https://download.01.org/openvinotoolkit"
  3859. },
  3860. {
  3861. "type": "openvino",
  3862. "target": "with_gather.xml",
  3863. "source": "https://github.com/lutzroeder/netron/files/2871676/with_gather.xml.zip[with_gather.xml]",
  3864. "format": "OpenVINO IR",
  3865. "link": "https://download.01.org/openvinotoolkit"
  3866. },
  3867. {
  3868. "type": "openvino",
  3869. "target": "ti_with_large_body.xml",
  3870. "source": "https://github.com/lutzroeder/netron/files/2871678/ti_with_large_body.xml.zip[ti_with_large_body.xml]",
  3871. "format": "OpenVINO IR",
  3872. "link": "https://download.01.org/openvinotoolkit"
  3873. },
  3874. {
  3875. "type": "openvino",
  3876. "target": "text-recognition-0012.xml,text-recognition-0012.bin",
  3877. "source": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-recognition-0012/FP16-INT8/text-recognition-0012.xml,https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-recognition-0012/FP16-INT8/text-recognition-0012.bin",
  3878. "format": "OpenVINO IR",
  3879. "link": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-recognition-0012/FP16-INT8"
  3880. },
  3881. {
  3882. "type": "openvino",
  3883. "target": "text-spotting-0002-recognizer-decoder.xml,text-spotting-0002-recognizer-decoder.bin",
  3884. "source": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-spotting-0002-recognizer-decoder/FP32/text-spotting-0002-recognizer-decoder.xml,https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-spotting-0002-recognizer-decoder/FP32/text-spotting-0002-recognizer-decoder.bin",
  3885. "format": "OpenVINO IR",
  3886. "link": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-spotting-0002-recognizer-decoder/FP32"
  3887. },
  3888. {
  3889. "type": "paddle",
  3890. "target": "assign.pbtxt",
  3891. "source": "https://github.com/lutzroeder/netron/files/5485296/assign.pbtxt.zip[assign.pbtxt]",
  3892. "format": "PaddlePaddle",
  3893. "link": "https://github.com/lutzroeder/netron/issues/198"
  3894. },
  3895. {
  3896. "type": "paddle",
  3897. "target": "PyramidBox_WiderFace.tar.gz",
  3898. "source": "http://paddlemodels.bj.bcebos.com/PyramidBox_WiderFace.tar.gz",
  3899. "format": "PaddlePaddle",
  3900. "link": "https://github.com/PaddlePaddle/models/tree/develop/PaddleCV/face_detection"
  3901. },
  3902. {
  3903. "type": "paddle",
  3904. "target": "recognize_digits_multilayer_perceptron_model.zip",
  3905. "source": "https://github.com/lutzroeder/netron/files/4985730/recognize_digits_multilayer_perceptron_model.zip",
  3906. "format": "PaddlePaddle",
  3907. "link": "https://github.com/lutzroeder/netron/issues/552"
  3908. },
  3909. {
  3910. "type": "paddle",
  3911. "target": "recognize_digits_multilayer_perceptron_weights.tar",
  3912. "source": "https://github.com/lutzroeder/netron/files/5551009/recognize_digits_multilayer_perceptron_weights.tar.zip[recognize_digits_multilayer_perceptron_weights.tar]",
  3913. "format": "PaddlePaddle Weights",
  3914. "link": "https://github.com/lutzroeder/netron/issues/198"
  3915. },
  3916. {
  3917. "type": "paddle",
  3918. "target": "tranformer_base.zip",
  3919. "source": "https://github.com/lutzroeder/netron/files/5160568/tranformer_base.zip",
  3920. "format": "PaddlePaddle",
  3921. "link": "https://github.com/lutzroeder/netron/issues/198"
  3922. },
  3923. {
  3924. "type": "paddle",
  3925. "target": "resnet50_int8_model.tar.gz",
  3926. "source": "http://paddle-inference-dist.bj.bcebos.com/int8/resnet50_int8_model.tar.gz",
  3927. "format": "PaddlePaddle",
  3928. "link": "https://github.com/lutzroeder/netron/issues/198"
  3929. },
  3930. {
  3931. "type": "paddle",
  3932. "target": "vgg_ilsvrc_16_fc_reduced.tar.gz",
  3933. "source": "http://paddlemodels.bj.bcebos.com/vgg_ilsvrc_16_fc_reduced.tar.gz",
  3934. "format": "PaddlePaddle",
  3935. "link": "https://github.com/PaddlePaddle/models/tree/develop/PaddleCV/face_detection"
  3936. },
  3937. {
  3938. "type": "paddle",
  3939. "target": "with_dummy_tensor_type.zip",
  3940. "source": "https://github.com/lutzroeder/netron/files/3021210/with_dummy_tensor_type.zip",
  3941. "format": "PaddlePaddle",
  3942. "link": "https://github.com/lutzroeder/netron/issues/246"
  3943. },
  3944. {
  3945. "type": "paddle",
  3946. "target": "without_tensor_type.zip",
  3947. "source": "https://github.com/lutzroeder/netron/files/3021211/without_tensor_type.zip",
  3948. "format": "PaddlePaddle",
  3949. "link": "https://github.com/lutzroeder/netron/issues/246"
  3950. },
  3951. {
  3952. "type": "pytorch",
  3953. "target": "alexnet.pkl.pth.zip",
  3954. "source": "https://github.com/lutzroeder/netron/files/5213453/alexnet.pkl.pth.zip",
  3955. "format": "PyTorch v0.1.10",
  3956. "link": "https://github.com/lutzroeder/netron/issues/133"
  3957. },
  3958. {
  3959. "type": "pytorch",
  3960. "target": "alexnet.zip.pth",
  3961. "script": "./tools/pytorch zoo",
  3962. "format": "PyTorch v1.6",
  3963. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  3964. },
  3965. {
  3966. "type": "pytorch",
  3967. "target": "alexnet.pt",
  3968. "script": "./tools/pytorch zoo",
  3969. "format": "TorchScript v1.6",
  3970. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  3971. },
  3972. {
  3973. "type": "pytorch",
  3974. "target": "alexnet_traced.pt",
  3975. "script": "./tools/pytorch zoo",
  3976. "format": "TorchScript v1.6",
  3977. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  3978. },
  3979. {
  3980. "type": "pytorch",
  3981. "target": "alexnet-owt-4df8aa71.pth",
  3982. "source": "https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth",
  3983. "format": "PyTorch v0.1.1",
  3984. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py"
  3985. },
  3986. {
  3987. "type": "pytorch",
  3988. "target": "blitz_neural_networks_tutorial_traced.pt",
  3989. "source": "https://github.com/lutzroeder/netron/files/3748989/blitz_neural_networks_tutorial.zip[blitz_neural_networks_tutorial_traced.pt]",
  3990. "format": "TorchScript v1.3",
  3991. "link": "https://github.com/lutzroeder/netron/issues/281"
  3992. },
  3993. {
  3994. "type": "pytorch",
  3995. "target": "blitz_neural_networks_tutorial.pt",
  3996. "source": "https://github.com/lutzroeder/netron/files/3748989/blitz_neural_networks_tutorial.zip[blitz_neural_networks_tutorial.pt]",
  3997. "format": "TorchScript v1.3",
  3998. "link": "https://github.com/lutzroeder/netron/issues/281"
  3999. },
  4000. {
  4001. "type": "pytorch",
  4002. "target": "blitz_cifar10_tutorial.pt",
  4003. "source": "https://github.com/lutzroeder/netron/files/3748500/blitz_cifar10_tutorial.zip[blitz_cifar10_tutorial.pt]",
  4004. "format": "TorchScript v1.3",
  4005. "link": "https://github.com/lutzroeder/netron/issues/281"
  4006. },
  4007. {
  4008. "type": "pytorch",
  4009. "target": "boolean.pkl.pth",
  4010. "source": "https://github.com/lutzroeder/netron/files/5435851/boolean.zip[boolean.pkl.pth]",
  4011. "format": "PyTorch v0.1.10",
  4012. "link": "https://github.com/lutzroeder/netron/issues/472"
  4013. },
  4014. {
  4015. "type": "pytorch",
  4016. "target": "boolean.zip.pth",
  4017. "source": "https://github.com/lutzroeder/netron/files/5435851/boolean.zip[boolean.pkl.pth]",
  4018. "format": "PyTorch v0.1.10",
  4019. "link": "https://github.com/lutzroeder/netron/issues/472"
  4020. },
  4021. {
  4022. "type": "pytorch",
  4023. "target": "bn_inception-9f5701afb96c8044.pth",
  4024. "source": "https://yjxiong.blob.core.windows.net/models/bn_inception-9f5701afb96c8044.pth",
  4025. "format": "PyTorch v0.1.1"
  4026. },
  4027. {
  4028. "type": "pytorch",
  4029. "target": "bvlc_googlenet.caffemodel.pth",
  4030. "source": "https://www.dropbox.com/s/2ljm35ztj6hllcu/bvlc_googlenet.caffemodel.pth?dl=1",
  4031. "format": "PyTorch v0.1.10",
  4032. "link": "https://sea-region.github.com/yuminsuh/part_bilinear_reid/issues/2"
  4033. },
  4034. {
  4035. "type": "pytorch",
  4036. "target": "ckpt.t7",
  4037. "source": "https://raw.githubusercontent.com/babajide07/Redundant-Feature-Pruning-Pytorch-Implementation/master/checkpoint/ckpt.t7",
  4038. "format": "PyTorch v0.1.10",
  4039. "link": "https://github.com/babajide07/Redundant-Feature-Pruning-Pytorch-Implementation"
  4040. },
  4041. {
  4042. "type": "pytorch",
  4043. "target": "cruise_cutin_vehicle_model.pt",
  4044. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/cruise_cutin_vehicle_model.pt",
  4045. "format": "TorchScript v1.0",
  4046. "link": "https://github.com/ApolloAuto/apollo"
  4047. },
  4048. {
  4049. "type": "pytorch",
  4050. "target": "cruise_go_vehicle_model.pt",
  4051. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/cruise_go_vehicle_model.pt",
  4052. "format": "TorchScript v1.0",
  4053. "link": "https://github.com/ApolloAuto/apollo"
  4054. },
  4055. {
  4056. "type": "pytorch",
  4057. "target": "densenet161.zip.pth",
  4058. "script": "./tools/pytorch zoo",
  4059. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4060. },
  4061. {
  4062. "type": "pytorch",
  4063. "target": "densenet161.pt",
  4064. "script": "./tools/pytorch zoo",
  4065. "action": "skip-render",
  4066. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4067. },
  4068. {
  4069. "type": "pytorch",
  4070. "target": "densenet161_traced.pt",
  4071. "script": "./tools/pytorch zoo",
  4072. "action": "skip-render",
  4073. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4074. },
  4075. {
  4076. "type": "pytorch",
  4077. "target": "densenet161-8d451a50.pth",
  4078. "source": "https://download.pytorch.org/models/densenet161-8d451a50.pth",
  4079. "format": "PyTorch v0.1.10"
  4080. },
  4081. {
  4082. "type": "pytorch",
  4083. "target": "DRNL4x_dual_model.pth",
  4084. "source": "https://github.com/lutzroeder/netron/files/5505677/DRNL4x_dual_model.pth.zip[DRNL4x_dual_model.pth]",
  4085. "format": "PyTorch v0.1.10",
  4086. "link": "https://github.com/lutzroeder/netron/issues/543"
  4087. },
  4088. {
  4089. "type": "pytorch",
  4090. "target": "ENet.pth",
  4091. "source": "https://github.com/lutzroeder/netron/files/5368544/ENet.pth.zip[ENet.pth]",
  4092. "format": "PyTorch v0.1.10",
  4093. "link": "https://github.com/lutzroeder/netron/issues/133"
  4094. },
  4095. {
  4096. "type": "pytorch",
  4097. "target": "gcn2_tiny_320x240.pb",
  4098. "source": "https://raw.githubusercontent.com/jiexiong2016/GCNv2_SLAM/master/GCN2/gcn2_tiny_320x240.pt",
  4099. "format": "TorchScript v1.0",
  4100. "link": "https://github.com/jiexiong2016/GCNv2_SLAM"
  4101. },
  4102. {
  4103. "type": "pytorch",
  4104. "target": "inception_v3_traced.pt",
  4105. "script": "./tools/pytorch zoo",
  4106. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4107. },
  4108. {
  4109. "type": "pytorch",
  4110. "target": "inception_v3.pkl.pth.zip",
  4111. "source": "https://github.com/lutzroeder/netron/files/5213454/inception_v3.pkl.pth.zip",
  4112. "format": "PyTorch v0.1.10",
  4113. "link": "https://github.com/lutzroeder/netron/issues/133"
  4114. },
  4115. {
  4116. "type": "pytorch",
  4117. "target": "inception_v3.pt",
  4118. "script": "./tools/pytorch zoo",
  4119. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4120. },
  4121. {
  4122. "type": "pytorch",
  4123. "target": "inception_v3.zip.pth",
  4124. "script": "./tools/pytorch zoo",
  4125. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4126. },
  4127. {
  4128. "type": "pytorch",
  4129. "target": "inception_v3_google-1a9a5a14.pth",
  4130. "format": "PyTorch v0.1.10",
  4131. "source": "https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth"
  4132. },
  4133. {
  4134. "type": "pytorch",
  4135. "target": "iv3_pertensor.pt",
  4136. "source": "https://github.com/lutzroeder/netron/files/5212009/iv3_pertensor.zip[iv3_pertensor.pt]",
  4137. "format": "TorchScript v1.5",
  4138. "link": "https://github.com/lutzroeder/netron/issues/546"
  4139. },
  4140. {
  4141. "type": "pytorch",
  4142. "target": "junction_mlp_vehicle_model.pt",
  4143. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/junction_mlp_vehicle_model.pt",
  4144. "format": "TorchScript v1.0",
  4145. "link": "https://github.com/ApolloAuto/apollo"
  4146. },
  4147. {
  4148. "type": "pytorch",
  4149. "target": "lane_scanning_vehicle_model.pt",
  4150. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/lane_scanning_vehicle_model.pt",
  4151. "format": "TorchScript v1.0",
  4152. "link": "https://github.com/ApolloAuto/apollo"
  4153. },
  4154. {
  4155. "type": "pytorch",
  4156. "target": "mask_r_cnn.pth",
  4157. "source": "https://raw.githubusercontent.com/facebookresearch/kill-the-bits/master/src/models/compressed/mask_r_cnn.pth",
  4158. "format": "PyTorch v0.1.10",
  4159. "link": "https://github.com/facebookresearch/kill-the-bits/tree/master/src/models/compressed"
  4160. },
  4161. {
  4162. "type": "pytorch",
  4163. "target": "mask_rcnn_r50_fpn_1x_20181010-069fa190.pth",
  4164. "source": "https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_1x_20181010-069fa190.pth",
  4165. "format": "PyTorch v0.1.10",
  4166. "link": "https://github.com/open-mmlab/mmdetection/blob/master/docs/MODEL_ZOO.md"
  4167. },
  4168. {
  4169. "type": "pytorch",
  4170. "target": "mnist_linear.ckpt",
  4171. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear.ckpt]",
  4172. "format": "PyTorch v0.1.10",
  4173. "link": "https://github.com/lutzroeder/netron/issues/281"
  4174. },
  4175. {
  4176. "type": "pytorch",
  4177. "target": "mnist_linear_dynamic_quantized.pt",
  4178. "source": "https://github.com/lutzroeder/netron/files/4774023/mnist_linear_dynamic_quantized.zip[mnist_linear_dynamic_quantized.pt]",
  4179. "format": "PyTorch v0.1.10",
  4180. "link": "https://github.com/lutzroeder/netron/issues/519"
  4181. },
  4182. {
  4183. "type": "pytorch",
  4184. "target": "mnist_linear_static_quantized.pt",
  4185. "source": "https://github.com/lutzroeder/netron/files/4774022/mnist_linear_static_quantized.zip[mnist_linear_static_quantized.pt]",
  4186. "format": "PyTorch v0.1.10",
  4187. "link": "https://github.com/lutzroeder/netron/issues/519"
  4188. },
  4189. {
  4190. "type": "pytorch",
  4191. "target": "mnist_linear_torchscript_1.pt",
  4192. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear_torchscript_1.pt]",
  4193. "format": "TorchScript v1.1",
  4194. "link": "https://github.com/lutzroeder/netron/issues/281"
  4195. },
  4196. {
  4197. "type": "pytorch",
  4198. "target": "mnist_linear_torchscript_2.pt",
  4199. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear_torchscript_2.pt]",
  4200. "format": "TorchScript v1.3",
  4201. "link": "https://github.com/lutzroeder/netron/issues/281"
  4202. },
  4203. {
  4204. "type": "pytorch",
  4205. "target": "mobilefacenet_scripted.pt",
  4206. "source": "https://github.com/foamliu/MobileFaceNet/releases/download/v1.0/mobilefacenet_scripted.pt",
  4207. "format": "TorchScript v1.3",
  4208. "link": "https://github.com/foamliu/MobileFaceNet"
  4209. },
  4210. {
  4211. "type": "pytorch",
  4212. "target": "Mobilenet_se_focal_121000.pb",
  4213. "source": "https://download.01.org/openvinotoolkit/open_model_zoo/training_toolbox_pytorch/models/fr/Mobilenet_se_focal_121000.pt",
  4214. "format": "PyTorch v0.1.10",
  4215. "link": "https://github.com/grib0ed0v/face_recognition.pytorch"
  4216. },
  4217. {
  4218. "type": "pytorch",
  4219. "target": "mobilenet_quantization_scripted_quantized_1.pth",
  4220. "source": "https://github.com/lutzroeder/netron/files/5394885/mobilenet_quantization_scripted_quantized.zip[mobilenet_quantization_scripted_quantized_1.pth]",
  4221. "format": "TorchScript v1.3",
  4222. "link": "https://github.com/lutzroeder/netron/issues/421"
  4223. },
  4224. {
  4225. "type": "pytorch",
  4226. "target": "mobilenet_quantization_scripted_quantized_2.pth",
  4227. "source": "https://github.com/lutzroeder/netron/files/5394885/mobilenet_quantization_scripted_quantized.zip[mobilenet_quantization_scripted_quantized_2.pth]",
  4228. "format": "TorchScript v1.6",
  4229. "link": "https://github.com/lutzroeder/netron/issues/421"
  4230. },
  4231. {
  4232. "type": "pytorch",
  4233. "target": "mobilenet_v2.pt",
  4234. "script": "./tools/pytorch zoo",
  4235. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4236. },
  4237. {
  4238. "type": "pytorch",
  4239. "target": "mobilenet_v2_traced.pt",
  4240. "script": "./tools/pytorch zoo",
  4241. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4242. },
  4243. {
  4244. "type": "pytorch",
  4245. "target": "model-reddit16-f140225004_2.pt1",
  4246. "source": "https://raw.githubusercontent.com/pytorch/android-demo-app/master/PyTorchDemoApp/app/src/main/assets/model-reddit16-f140225004_2.pt1",
  4247. "format": "TorchScript v1.3",
  4248. "link": "https://github.com/pytorch/android-demo-app"
  4249. },
  4250. {
  4251. "type": "pytorch",
  4252. "target": "mobilenetv2-quant_none-nnapi.pt",
  4253. "source": "https://github.com/lutzroeder/netron/files/5647823/mobilenetv2-quant_none-nnapi.pt.zip[mobilenetv2-quant_none-nnapi.pt]",
  4254. "format": "TorchScript v1.6",
  4255. "link": "https://github.com/lutzroeder/netron/issues/644"
  4256. },
  4257. {
  4258. "type": "pytorch",
  4259. "target": "netron_issue_313_v1.pt",
  4260. "source": "https://github.com/lutzroeder/netron/files/3721266/netron_issue_313.zip[netron_issue_313_v1.pt]",
  4261. "format": "TorchScript v1.0",
  4262. "link": "https://github.com/lutzroeder/netron/issues/313"
  4263. },
  4264. {
  4265. "type": "pytorch",
  4266. "target": "netron_issue_313_v2.pt",
  4267. "source": "https://github.com/lutzroeder/netron/files/3721266/netron_issue_313.zip[netron_issue_313_v2.pt]",
  4268. "format": "TorchScript v1.3",
  4269. "link": "https://github.com/lutzroeder/netron/issues/313"
  4270. },
  4271. {
  4272. "type": "pytorch",
  4273. "target": "netron_issue_432_activation.pth",
  4274. "source": "https://github.com/lutzroeder/netron/files/4226686/netron_issue_432_activation.pth.zip[netron_issue_432_activation.pth]",
  4275. "format": "TorchScript v1.3",
  4276. "link": "https://github.com/lutzroeder/netron/issues/432"
  4277. },
  4278. {
  4279. "type": "pytorch",
  4280. "target": "netron_issue_432_bmm.pth",
  4281. "source": "https://github.com/lutzroeder/netron/files/4226688/netron_issue_432_bmm.pth.zip[netron_issue_432_bmm.pth]",
  4282. "format": "TorchScript v1.3",
  4283. "link": "https://github.com/lutzroeder/netron/issues/432"
  4284. },
  4285. {
  4286. "type": "pytorch",
  4287. "target": "netron_issue_432_constant_pad_2d.pth",
  4288. "source": "https://github.com/lutzroeder/netron/files/4226690/netron_issue_432_constant_pad_2d.pth.zip[netron_issue_432_constant_pad_2d.pth]",
  4289. "format": "TorchScript v1.3",
  4290. "link": "https://github.com/lutzroeder/netron/issues/432"
  4291. },
  4292. {
  4293. "type": "pytorch",
  4294. "target": "netron_issue_529.pt",
  4295. "source": "https://github.com/lutzroeder/netron/files/4834633/netron_issue_529.zip[netron_issue_529.pt]",
  4296. "format": "TorchScript v1.5",
  4297. "link": "https://github.com/lutzroeder/netron/issues/529"
  4298. },
  4299. {
  4300. "type": "pytorch",
  4301. "target": "netron_issue_529_traced.pt",
  4302. "source": "https://github.com/lutzroeder/netron/files/4834633/netron_issue_529.zip[netron_issue_529_traced.pt]",
  4303. "format": "TorchScript v1.5",
  4304. "link": "https://github.com/lutzroeder/netron/issues/529"
  4305. },
  4306. {
  4307. "type": "pytorch",
  4308. "target": "netron_issue_547_1.pt",
  4309. "source": "https://github.com/lutzroeder/netron/files/5137393/netron_issue_547_1.zip[netron_issue_547_1.pt]",
  4310. "error": "Unknown torch.add expression type in 'netron_issue_547_1.pt'.",
  4311. "link": "https://github.com/lutzroeder/netron/issues/547"
  4312. },
  4313. {
  4314. "type": "pytorch",
  4315. "target": "netron_issue_609.pt",
  4316. "source": "https://github.com/lutzroeder/netron/files/5309279/netron_issue_609.pt.zip[netron_issue_609.pt]",
  4317. "format": "TorchScript v1.6",
  4318. "link": "https://github.com/lutzroeder/netron/issues/609"
  4319. },
  4320. {
  4321. "type": "pytorch",
  4322. "target": "norm_inplace.pt.zip",
  4323. "source": "https://github.com/lutzroeder/netron/files/4516621/norm_inplace.pt.zip",
  4324. "format": "TorchScript v1.3",
  4325. "link": "https://github.com/lutzroeder/netron/issues/473"
  4326. },
  4327. {
  4328. "type": "pytorch",
  4329. "target": "pedestrian_interaction_position_embedding.pt",
  4330. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_position_embedding.pt",
  4331. "format": "TorchScript v1.0",
  4332. "link": "https://github.com/ApolloAuto/apollo"
  4333. },
  4334. {
  4335. "type": "pytorch",
  4336. "target": "pedestrian_interaction_prediction_layer.pt",
  4337. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_prediction_layer.pt",
  4338. "format": "TorchScript v1.0",
  4339. "link": "https://github.com/ApolloAuto/apollo"
  4340. },
  4341. {
  4342. "type": "pytorch",
  4343. "target": "pedestrian_interaction_single_lstm.pt",
  4344. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_single_lstm.pt",
  4345. "format": "TorchScript v1.0",
  4346. "link": "https://github.com/ApolloAuto/apollo"
  4347. },
  4348. {
  4349. "type": "pytorch",
  4350. "target": "pedestrian_interaction_social_embedding.pt",
  4351. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_social_embedding.pt",
  4352. "format": "TorchScript v1.1",
  4353. "link": "https://github.com/ApolloAuto/apollo"
  4354. },
  4355. {
  4356. "type": "pytorch",
  4357. "target": "posemodel.pt",
  4358. "source": "https://github.com/lutzroeder/netron/files/5475350/posemodel.pt.zip[posemodel.pt]",
  4359. "format": "TorchScript v1.6",
  4360. "link": "https://github.com/lutzroeder/netron/issues/546"
  4361. },
  4362. {
  4363. "type": "pytorch",
  4364. "target": "pytorch_invalid_file.pth",
  4365. "source": "https://github.com/lutzroeder/netron/files/3269093/pytorch_invalid_file.zip[pytorch_invalid_file.pth]",
  4366. "error": "Could not find end of line in 'pytorch_invalid_file.pth'.",
  4367. "link": "https://github.com/lutzroeder/netron/issues/133"
  4368. },
  4369. {
  4370. "type": "pytorch",
  4371. "target": "r3d_18.zip.pth",
  4372. "script": "./tools/pytorch zoo",
  4373. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4374. },
  4375. {
  4376. "type": "pytorch",
  4377. "target": "r3d_18.pt",
  4378. "script": "./tools/pytorch zoo",
  4379. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4380. },
  4381. {
  4382. "type": "pytorch",
  4383. "target": "r3d_18_traced.pt",
  4384. "script": "./tools/pytorch zoo",
  4385. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4386. },
  4387. {
  4388. "type": "pytorch",
  4389. "target": "resnet18-5c106cde.pth",
  4390. "source": "https://download.pytorch.org/models/resnet18-5c106cde.pth",
  4391. "format": "PyTorch v0.1.1",
  4392. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py"
  4393. },
  4394. {
  4395. "type": "pytorch",
  4396. "target": "resnet18_fbgemm_16fa66dd.pth",
  4397. "source": "https://download.pytorch.org/models/quantized/resnet18_fbgemm_16fa66dd.pth",
  4398. "format": "PyTorch v0.1.10",
  4399. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/quantization/resnet.py"
  4400. },
  4401. {
  4402. "type": "pytorch",
  4403. "target": "resnet18_large_blocks.pth",
  4404. "source": "https://raw.githubusercontent.com/facebookresearch/kill-the-bits/master/src/models/compressed/resnet18_large_blocks.pth",
  4405. "format": "PyTorch v0.1.10",
  4406. "link": "https://github.com/facebookresearch/kill-the-bits/tree/master/src/models/compressed"
  4407. },
  4408. {
  4409. "type": "pytorch",
  4410. "target": "resnet-18-at-export.pth",
  4411. "source": "https://s3.amazonaws.com/modelzoo-networks/resnet-18-at-export.pth",
  4412. "format": "PyTorch v0.1.10",
  4413. "link": "https://github.com/szagoruyko/attention-transfer"
  4414. },
  4415. {
  4416. "type": "pytorch",
  4417. "target": "resnet34-333f7ec4.pth",
  4418. "source": "https://download.pytorch.org/models/resnet34-333f7ec4.pth",
  4419. "format": "PyTorch v0.1.1",
  4420. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py"
  4421. },
  4422. {
  4423. "type": "pytorch",
  4424. "target": "resnet50_pertensor.pt",
  4425. "source": "https://github.com/lutzroeder/netron/files/5212006/resnet50_pertensor.zip[resnet50_pertensor.pt]",
  4426. "format": "TorchScript v1.5",
  4427. "link": "https://github.com/lutzroeder/netron/issues/546"
  4428. },
  4429. {
  4430. "type": "pytorch",
  4431. "target": "resnet101.pkl.pth.zip",
  4432. "source": "https://github.com/lutzroeder/netron/files/5213455/resnet101.pkl.pth.zip",
  4433. "format": "PyTorch v0.1.10",
  4434. "link": "https://github.com/lutzroeder/netron/issues/133"
  4435. },
  4436. {
  4437. "type": "pytorch",
  4438. "target": "resnet101.pt",
  4439. "script": "./tools/pytorch zoo",
  4440. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4441. },
  4442. {
  4443. "type": "pytorch",
  4444. "target": "resnet101_traced.pt",
  4445. "script": "./tools/pytorch zoo",
  4446. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4447. },
  4448. {
  4449. "type": "pytorch",
  4450. "target": "resnet18.pt",
  4451. "source": "https://github.com/lutzroeder/netron/files/5212015/resnet18.zip[resnet18.pt]",
  4452. "format": "TorchScript v1.6",
  4453. "link": "https://github.com/lutzroeder/netron/issues/559"
  4454. },
  4455. {
  4456. "type": "pytorch",
  4457. "target": "resnet50_tucker.pth",
  4458. "source": "https://raw.githubusercontent.com/larry0123du/Decompose-CNN/master/models/resnet50_tucker.pth",
  4459. "format": "PyTorch v0.1.10",
  4460. "link": "https://github.com/larry0123du/Decompose-CNN"
  4461. },
  4462. {
  4463. "type": "pytorch",
  4464. "target": "resnet50_tucker_state.pth",
  4465. "source": "https://raw.githubusercontent.com/larry0123du/Decompose-CNN/master/models/resnet50_tucker_state.pth",
  4466. "format": "PyTorch v0.1.10",
  4467. "link": "https://github.com/larry0123du/Decompose-CNN"
  4468. },
  4469. {
  4470. "type": "pytorch",
  4471. "target": "resnet101-5d3b4d8f.pth",
  4472. "source": "https://download.pytorch.org/models/resnet101-5d3b4d8f.pth",
  4473. "format": "PyTorch v0.1.1",
  4474. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py"
  4475. },
  4476. {
  4477. "type": "pytorch",
  4478. "target": "semantic_lstm_vehicle_model.pt",
  4479. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/semantic_lstm_vehicle_model.pt",
  4480. "format": "TorchScript v1.1",
  4481. "link": "https://github.com/ApolloAuto/apollo"
  4482. },
  4483. {
  4484. "type": "pytorch",
  4485. "target": "SiamFC_50_model.pth",
  4486. "source": "https://raw.githubusercontent.com/HengLan/SiamFC-PyTorch/master/Train/model/SiamFC_50_model.pth",
  4487. "format": "PyTorch v0.1.10",
  4488. "link": "https://github.com/HengLan/SiamFC-PyTorch"
  4489. },
  4490. {
  4491. "type": "pytorch",
  4492. "target": "shufflenet_v2_x1_0.zip.pth",
  4493. "script": "./tools/pytorch zoo",
  4494. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4495. },
  4496. {
  4497. "type": "pytorch",
  4498. "target": "shufflenet_v2_x1_0.pt",
  4499. "script": "./tools/pytorch zoo",
  4500. "action": "skip-render",
  4501. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4502. },
  4503. {
  4504. "type": "pytorch",
  4505. "target": "squeezenet1_0-a815701f.pth",
  4506. "source": "https://download.pytorch.org/models/squeezenet1_0-a815701f.pth",
  4507. "format": "PyTorch v0.1.1"
  4508. },
  4509. {
  4510. "type": "pytorch",
  4511. "target": "squeezenet1_1.pkl.pth.zip",
  4512. "source": "https://github.com/lutzroeder/netron/files/5213456/squeezenet1_1.pkl.pth.zip",
  4513. "format": "PyTorch v0.1.10",
  4514. "link": "https://github.com/lutzroeder/netron/issues/133"
  4515. },
  4516. {
  4517. "type": "pytorch",
  4518. "target": "squeezenet1_1.pt",
  4519. "script": "./tools/pytorch zoo",
  4520. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4521. },
  4522. {
  4523. "type": "pytorch",
  4524. "target": "squeezenet1_1_traced.pt",
  4525. "script": "./tools/pytorch zoo",
  4526. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4527. },
  4528. {
  4529. "type": "pytorch",
  4530. "target": "squeezenet1_1-f364aa15.pth",
  4531. "source": "https://download.pytorch.org/models/squeezenet1_1-f364aa15.pth",
  4532. "format": "PyTorch v0.1.1"
  4533. },
  4534. {
  4535. "type": "pytorch",
  4536. "target": "superpoint_v1.pth",
  4537. "source": "https://raw.githubusercontent.com/MagicLeapResearch/SuperPointPretrainedNetwork/master/superpoint_v1.pth",
  4538. "format": "PyTorch v0.1.10",
  4539. "link": "https://github.com/MagicLeapResearch/SuperPointPretrainedNetwork"
  4540. },
  4541. {
  4542. "type": "pytorch",
  4543. "target": "superpoint.pt",
  4544. "source": "https://raw.githubusercontent.com/KinglittleQ/SuperPoint_SLAM/master/superpoint.pt",
  4545. "format": "TorchScript v1.0",
  4546. "link": "https://github.com/KinglittleQ/SuperPoint_SLAM"
  4547. },
  4548. {
  4549. "type": "pytorch",
  4550. "target": "traced_fft.pt",
  4551. "source": "https://github.com/lutzroeder/netron/files/5172197/traced_fft.zip[traced_fft.pt]",
  4552. "format": "TorchScript v1.3",
  4553. "link": "https://github.com/lutzroeder/netron/issues/546"
  4554. },
  4555. {
  4556. "type": "pytorch",
  4557. "target": "traced_online_lane_enc.pt",
  4558. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_lane_enc.pt",
  4559. "format": "TorchScript v1.0",
  4560. "link": "https://github.com/ApolloAuto/apollo"
  4561. },
  4562. {
  4563. "type": "pytorch",
  4564. "target": "traced_online_obs_enc.pt",
  4565. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_obs_enc.pt",
  4566. "format": "TorchScript v1.0",
  4567. "link": "https://github.com/ApolloAuto/apollo"
  4568. },
  4569. {
  4570. "type": "pytorch",
  4571. "target": "traced_online_pred_layer.pt",
  4572. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_pred_layer.pt",
  4573. "format": "TorchScript v1.0",
  4574. "link": "https://github.com/ApolloAuto/apollo"
  4575. },
  4576. {
  4577. "type": "pytorch",
  4578. "target": "test.8bit.pth",
  4579. "source": "https://github.com/lutzroeder/netron/files/5238524/test.8bit.pth.zip[test.8bit.pth]",
  4580. "format": "TorchScript v1.6",
  4581. "link": "https://github.com/lutzroeder/netron/issues/546"
  4582. },
  4583. {
  4584. "type": "pytorch",
  4585. "target": "tutorial_bidirectional_recurrent_neural_network.pth",
  4586. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_bidirectional_recurrent_neural_network.pth]",
  4587. "format": "PyTorch v0.1.10",
  4588. "link": "https://github.com/lutzroeder/netron/issues/133"
  4589. },
  4590. {
  4591. "type": "pytorch",
  4592. "target": "tutorial_convolutional_neural_network.pth",
  4593. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_convolutional_neural_network.pth]",
  4594. "format": "PyTorch v0.1.10",
  4595. "link": "https://github.com/lutzroeder/netron/issues/133"
  4596. },
  4597. {
  4598. "type": "pytorch",
  4599. "target": "tutorial_deep_residual_network.pth",
  4600. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_deep_residual_network.pth]",
  4601. "format": "PyTorch v0.1.10",
  4602. "link": "https://github.com/lutzroeder/netron/issues/133"
  4603. },
  4604. {
  4605. "type": "pytorch",
  4606. "target": "tutorial_logistic_regression.pth",
  4607. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_logistic_regression.pth]",
  4608. "format": "PyTorch v0.1.10",
  4609. "link": "https://github.com/lutzroeder/netron/issues/133"
  4610. },
  4611. {
  4612. "type": "pytorch",
  4613. "target": "tutorial_mnist.pth",
  4614. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_mnist.pth]",
  4615. "format": "PyTorch v0.1.10",
  4616. "link": "https://github.com/lutzroeder/netron/issues/133"
  4617. },
  4618. {
  4619. "type": "pytorch",
  4620. "target": "tutorial_recurrent_neural_network.pth",
  4621. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_recurrent_neural_network.pth]",
  4622. "format": "PyTorch v0.1.10",
  4623. "link": "https://github.com/lutzroeder/netron/issues/133"
  4624. },
  4625. {
  4626. "type": "pytorch",
  4627. "target": "tutorial_variational_autoencoder.pth.tar",
  4628. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_variational_autoencoder.pth]",
  4629. "format": "PyTorch v0.1.10",
  4630. "link": "https://github.com/lutzroeder/netron/issues/133"
  4631. },
  4632. {
  4633. "type": "pytorch",
  4634. "target": "valid-bert-base-uncased.pt",
  4635. "source": "https://github.com/lutzroeder/netron/files/4977150/valid-bert-base-uncased.zip[valid-bert-base-uncased.pt]",
  4636. "format": "PyTorch v0.1.10",
  4637. "link": "https://github.com/lutzroeder/netron/issues/133"
  4638. },
  4639. {
  4640. "type": "pytorch",
  4641. "target": "vgg-cifar10.pth.tar",
  4642. "source": "http://www.cs.unc.edu/~cyfu/cifar10/model_best.pth.tar",
  4643. "format": "PyTorch v0.1.10",
  4644. "link": "https://github.com/chengyangfu/pytorch-vgg-cifar10"
  4645. },
  4646. {
  4647. "type": "pytorch",
  4648. "target": "vgg11-bbd30ac9.pth",
  4649. "source": "https://download.pytorch.org/models/vgg11-bbd30ac9.pth",
  4650. "format": "PyTorch v0.1.10"
  4651. },
  4652. {
  4653. "type": "rknn",
  4654. "target": "autopilot.rknn",
  4655. "source": "https://github.com/lutzroeder/netron/files/5621074/autopilot.rknn.zip[autopilot.rknn]",
  4656. "format": "RKNN v1.3.0",
  4657. "link": "https://github.com/lutzroeder/netron/issues/639"
  4658. },
  4659. {
  4660. "type": "rknn",
  4661. "target": "deepfusion.rknn",
  4662. "source": "https://github.com/lutzroeder/netron/files/5621075/deepfusion.rknn.zip[deepfusion.rknn]",
  4663. "format": "RKNN v1.2.1",
  4664. "link": "https://github.com/lutzroeder/netron/issues/639"
  4665. },
  4666. {
  4667. "type": "rknn",
  4668. "target": "kindnet.rknn",
  4669. "source": "https://github.com/lutzroeder/netron/files/5621076/kindnet.rknn.zip[kindnet.rknn]",
  4670. "format": "RKNN v1.3.2",
  4671. "link": "https://github.com/lutzroeder/netron/issues/639"
  4672. },
  4673. {
  4674. "type": "rknn",
  4675. "target": "resnet_18.rknn",
  4676. "source": "https://github.com/lutzroeder/netron/files/5621078/resnet_18.rknn.zip[resnet_18.rknn]",
  4677. "format": "RKNN v1.3.2",
  4678. "link": "https://github.com/lutzroeder/netron/issues/639"
  4679. },
  4680. {
  4681. "type": "sklearn",
  4682. "target": "batches.meta",
  4683. "source": "https://raw.githubusercontent.com/MadryLab/cifar10_challenge/master/cifar10_data/batches.meta",
  4684. "format": "Pickle",
  4685. "link": "https://github.com/MadryLab/cifar10_challenge"
  4686. },
  4687. {
  4688. "type": "sklearn",
  4689. "target": "best_boston.pb",
  4690. "source": "https://github.com/lutzroeder/netron/files/3335715/xgboost_best_boston.zip[best_boston.pkl]",
  4691. "format": "scikit-learn v0.20.2",
  4692. "link": "https://github.com/lutzroeder/netron/issues/182"
  4693. },
  4694. {
  4695. "type": "sklearn",
  4696. "target": "binarizer.pkl",
  4697. "source": "https://github.com/lutzroeder/netron/files/2587902/binarizer.zip[binarizer.pkl]",
  4698. "format": "scikit-learn v0.19.1",
  4699. "link": "https://github.com/lutzroeder/netron/issues/182"
  4700. },
  4701. {
  4702. "type": "sklearn",
  4703. "target": "binarizer.joblib",
  4704. "source": "https://github.com/lutzroeder/netron/files/2587902/binarizer.zip[binarizer.joblib]",
  4705. "format": "scikit-learn v0.19.1",
  4706. "link": "https://github.com/lutzroeder/netron/issues/182"
  4707. },
  4708. {
  4709. "type": "sklearn",
  4710. "target": "curvrank.localization.dorsal.weights.pkl",
  4711. "source": "https://lev.cs.rpi.edu/public/models/curvrank.localization.dorsal.weights.pkl",
  4712. "format": "NumPy Weights"
  4713. },
  4714. {
  4715. "type": "sklearn",
  4716. "target": "column_pipeline.pkl",
  4717. "source": "https://github.com/lutzroeder/netron/files/4672437/column_pipeline.zip[column_pipeline.pkl]",
  4718. "format": "scikit-learn v0.22.1",
  4719. "link": "https://github.com/lutzroeder/netron/issues/498"
  4720. },
  4721. {
  4722. "type": "sklearn",
  4723. "target": "column_transformer_pipeline.pkl",
  4724. "source": "https://github.com/lutzroeder/netron/files/4672438/column_transformer_pipeline.zip[column_transformer_pipeline.pkl]",
  4725. "format": "scikit-learn v0.22.1",
  4726. "link": "https://github.com/lutzroeder/netron/issues/498"
  4727. },
  4728. {
  4729. "type": "sklearn",
  4730. "target": "d2v.model",
  4731. "source": "https://raw.githubusercontent.com/aseth99/doc2vec/master/d2v.model",
  4732. "format": "gensim"
  4733. },
  4734. {
  4735. "type": "sklearn",
  4736. "target": "mobilenet_v2_normal_72820.pkl",
  4737. "source": "https://data.megengine.org.cn/models/weights/mobilenet_v2_normal_72820.pkl",
  4738. "format": "NumPy Weights",
  4739. "link": "https://github.com/MegEngine/Models/tree/master/official/quantization"
  4740. },
  4741. {
  4742. "type": "sklearn",
  4743. "target": "LDA_model.pkl",
  4744. "source": "https://raw.githubusercontent.com/rainer85ah/DCS/master/Output/LDA_model.pkl",
  4745. "format": "scikit-learn",
  4746. "link": "https://github.com/rainer85ah/DCS"
  4747. },
  4748. {
  4749. "type": "sklearn",
  4750. "target": "phoenix_ml_classifier.pkl",
  4751. "source": "https://raw.githubusercontent.com/imeraj/Phoenix_Playground/master/1.4/phoenix_ml/lib/phoenix_ml/model/classifier.pkl",
  4752. "format": "scikit-learn v0.19.1",
  4753. "link": "https://github.com/imeraj/Phoenix_Playground/tree/master/1.4/phoenix_ml/lib/phoenix_ml/model"
  4754. },
  4755. {
  4756. "type": "sklearn",
  4757. "target": "forest_iris_ExtraTreesClassifier.pkl",
  4758. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_ExtraTreesClassifier.pkl]",
  4759. "format": "scikit-learn v0.19.2",
  4760. "link": "https://github.com/lutzroeder/netron/issues/182"
  4761. },
  4762. {
  4763. "type": "sklearn",
  4764. "target": "forest_iris_RandomForestClassifier.pkl",
  4765. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_RandomForestClassifier.pkl]",
  4766. "format": "scikit-learn v0.19.2",
  4767. "link": "https://github.com/lutzroeder/netron/issues/182"
  4768. },
  4769. {
  4770. "type": "sklearn",
  4771. "target": "forest_iris_AdaBoostClassifier.pkl",
  4772. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_AdaBoostClassifier.pkl]",
  4773. "format": "scikit-learn v0.19.2",
  4774. "link": "https://github.com/lutzroeder/netron/issues/182"
  4775. },
  4776. {
  4777. "type": "sklearn",
  4778. "target": "forest_iris_DecisionTreeClassifier.pkl",
  4779. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_DecisionTreeClassifier.pkl]",
  4780. "format": "scikit-learn v0.19.2",
  4781. "link": "https://github.com/lutzroeder/netron/issues/182"
  4782. },
  4783. {
  4784. "type": "sklearn",
  4785. "target": "net2.pkl",
  4786. "source": "https://raw.githubusercontent.com/Aabglov/LasaganeTest/master/results/net2.pkl",
  4787. "format": "Lasagne",
  4788. "link": "https://github.com/Aabglov/LasaganeTest"
  4789. },
  4790. {
  4791. "type": "sklearn",
  4792. "target": "pima.xgboost.joblib.pkl",
  4793. "source": "https://github.com/lutzroeder/netron/files/2656501/pima.xgboost.joblib.pkl.zip[pima.xgboost.joblib.pkl]",
  4794. "format": "XGBoost",
  4795. "link": "https://github.com/lutzroeder/netron/issues/182"
  4796. },
  4797. {
  4798. "type": "sklearn",
  4799. "target": "R-50.pkl",
  4800. "source": "https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl",
  4801. "format": "NumPy Weights",
  4802. "link": "https://github.com/facebookresearch/Detectron"
  4803. },
  4804. {
  4805. "type": "sklearn",
  4806. "target": "robinhood-portfolio_data_user.pkl.pkl",
  4807. "source": "https://raw.githubusercontent.com/omdv/robinhood-portfolio/4622dc61e0556a85ce52c4de178d01a9838acbc5/data/user.pkl",
  4808. "format": "Pickle",
  4809. "link": "https://github.com/omdv/robinhood-portfolio/tree/4622dc61e0556a85ce52c4de178d01a9838acbc5"
  4810. },
  4811. {
  4812. "type": "sklearn",
  4813. "target": "svc.joblib.pkl",
  4814. "source": "https://github.com/lutzroeder/netron/files/2592359/svc.zip[svc.joblib.pkl]",
  4815. "format": "scikit-learn v0.19.1",
  4816. "link": "https://github.com/lutzroeder/netron/issues/182"
  4817. },
  4818. {
  4819. "type": "sklearn",
  4820. "target": "svc.pkl",
  4821. "source": "https://github.com/lutzroeder/netron/files/2592359/svc.zip[svc.pkl]",
  4822. "format": "scikit-learn v0.19.1",
  4823. "link": "https://github.com/lutzroeder/netron/issues/182"
  4824. },
  4825. {
  4826. "type": "sklearn",
  4827. "target": "svm.pkl",
  4828. "source": "https://raw.githubusercontent.com/dfridovi/imagelib/master/svm.pkl",
  4829. "format": "scikit-learn",
  4830. "link": "https://github.com/dfridovi/imagelib/blob/master/svm.pkl"
  4831. },
  4832. {
  4833. "type": "sklearn",
  4834. "target": "wiki-aa-mlp.pkl",
  4835. "source": "https://github.com/lutzroeder/netron/files/2674319/wiki-aa-mlp.pkl.zip[wiki-aa-mlp.pkl]",
  4836. "format": "scikit-learn v0.19.0",
  4837. "link": "https://github.com/lutzroeder/netron/issues/182"
  4838. },
  4839. {
  4840. "type": "tengine",
  4841. "target": "detect_tflite.tmfile",
  4842. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/detect_tflite.tmfile",
  4843. "format": "Tengine v2.0",
  4844. "link": "https://github.com/pierricklee/tmfile-sample"
  4845. },
  4846. {
  4847. "type": "tengine",
  4848. "target": "detect_tflite_issue_466.tmfile",
  4849. "source": "https://github.com/lutzroeder/netron/files/4479142/detect_tflite_issue_466.zip[detect_tflite_issue_466.tmfile]",
  4850. "format": "Tengine v2.0",
  4851. "link": "https://github.com/lutzroeder/netron/issues/466"
  4852. },
  4853. {
  4854. "type": "tengine",
  4855. "target": "lighten_cnn.tmfile",
  4856. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/lighten_cnn.tmfile",
  4857. "format": "Tengine v2.0",
  4858. "link": "https://github.com/pierricklee/tmfile-sample"
  4859. },
  4860. {
  4861. "type": "tengine",
  4862. "target": "mobilenet.tmfile",
  4863. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet.tmfile",
  4864. "format": "Tengine v2.0",
  4865. "link": "https://github.com/pierricklee/tmfile-sample"
  4866. },
  4867. {
  4868. "type": "tengine",
  4869. "target": "mobilenet_quant_tflite.tmfile",
  4870. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_quant_tflite.tmfile",
  4871. "format": "Tengine v2.0",
  4872. "link": "https://github.com/pierricklee/tmfile-sample"
  4873. },
  4874. {
  4875. "type": "tengine",
  4876. "target": "mobolenet_ssd_v1_quant_tflite.tmfile",
  4877. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobolenet_ssd_v1_quant_tflite.tmfile",
  4878. "format": "Tengine v2.0",
  4879. "link": "https://github.com/pierricklee/tmfile-sample"
  4880. },
  4881. {
  4882. "type": "tengine",
  4883. "target": "mobilenet_v1_tf.tmfile",
  4884. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v1_tf.tmfile",
  4885. "format": "Tengine v2.0",
  4886. "link": "https://github.com/pierricklee/tmfile-sample"
  4887. },
  4888. {
  4889. "type": "tengine",
  4890. "target": "mobilenet_v2.tmfile",
  4891. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v2.tmfile",
  4892. "format": "Tengine v2.0",
  4893. "link": "https://github.com/pierricklee/tmfile-sample"
  4894. },
  4895. {
  4896. "type": "tengine",
  4897. "target": "mobilenet_v2_tf.tmfile",
  4898. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v2_tf.tmfile",
  4899. "format": "Tengine v2.0",
  4900. "link": "https://github.com/pierricklee/tmfile-sample"
  4901. },
  4902. {
  4903. "type": "tengine",
  4904. "target": "nasnet_tf.tmfile",
  4905. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/nasnet_tf.tmfile",
  4906. "format": "Tengine v2.0",
  4907. "link": "https://github.com/pierricklee/tmfile-sample"
  4908. },
  4909. {
  4910. "type": "tengine",
  4911. "target": "retinaface_benchmark.tmfile",
  4912. "source": "https://raw.githubusercontent.com/OAID/Tengine/master/models/retinaface_benchmark.tmfile",
  4913. "format": "Tengine v2.0",
  4914. "link": "https://github.com/OAID/Tengine"
  4915. },
  4916. {
  4917. "type": "tengine",
  4918. "target": "squeezenet.tmfile",
  4919. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/squeezenet.tmfile",
  4920. "format": "Tengine v2.0",
  4921. "link": "https://github.com/pierricklee/tmfile-sample"
  4922. },
  4923. {
  4924. "type": "tengine",
  4925. "target": "squeezenet_on.tmfile",
  4926. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/squeezenet_on.tmfile",
  4927. "format": "Tengine v2.0",
  4928. "link": "https://github.com/pierricklee/tmfile-sample"
  4929. },
  4930. {
  4931. "type": "tengine",
  4932. "target": "test_multi_input_output.tmfile",
  4933. "source": "https://github.com/lutzroeder/netron/files/5248932/test_multi_input_output.zip[test_multi_input_output.tmfile]",
  4934. "format": "Tengine v2.0",
  4935. "link": "https://github.com/lutzroeder/netron/issues/440"
  4936. },
  4937. {
  4938. "type": "tf",
  4939. "target": "bert_uncased_L-12_H-768_A-12.meta",
  4940. "source": "https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-12_H-768_A-12.zip[uncased_L-12_H-768_A-12/bert_model.ckpt.meta]",
  4941. "format": "TensorFlow MetaGraph", "producer": "TensorFlow v1.11.0-rc1",
  4942. "action": "skip-render",
  4943. "link": "https://github.com/google-research/bert#pre-trained-models"
  4944. },
  4945. {
  4946. "type": "tf",
  4947. "target": "bert_cased_L-24_H-1024_A-16.meta",
  4948. "source": "https://storage.googleapis.com/bert_models/2018_10_18/cased_L-24_H-1024_A-16.zip[cased_L-24_H-1024_A-16/bert_model.ckpt.meta]",
  4949. "format": "TensorFlow MetaGraph",
  4950. "action": "skip-render",
  4951. "link": "https://github.com/google-research/bert#pre-trained-models"
  4952. },
  4953. {
  4954. "type": "tf",
  4955. "target": "char-rnn-tensorflow.pb",
  4956. "source": "https://github.com/lutzroeder/netron/files/2592462/char-rnn-tensorflow.pb.zip[char-rnn-tensorflow.pb]",
  4957. "format": "TensorFlow Graph",
  4958. "action": "skip-render",
  4959. "link": "https://github.com/lutzroeder/netron/issues/187"
  4960. },
  4961. {
  4962. "type": "tf",
  4963. "target": "chessbot.pb",
  4964. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/chessbot.pb",
  4965. "format": "TensorFlow Graph",
  4966. "link": "https://github.com/srom/chessbot"
  4967. },
  4968. {
  4969. "type": "tf",
  4970. "target": "chessbot_estimator.pb",
  4971. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/estimator.pb",
  4972. "format": "TensorFlow Graph",
  4973. "link": "https://github.com/srom/chessbot"
  4974. },
  4975. {
  4976. "type": "tf",
  4977. "target": "chessbot_classifier.pb",
  4978. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/classifier.pb",
  4979. "format": "TensorFlow Graph",
  4980. "link": "https://github.com/srom/chessbot"
  4981. },
  4982. {
  4983. "type": "tf",
  4984. "target": "classify_image_graph_def.pb",
  4985. "source": "https://raw.githubusercontent.com/taey16/tf/master/imagenet/classify_image_graph_def.pb",
  4986. "format": "TensorFlow Graph",
  4987. "link": "https://github.com/taey16/tf"
  4988. },
  4989. {
  4990. "type": "tf",
  4991. "target": "conv-layers.pb.zip",
  4992. "source": "https://github.com/lutzroeder/netron/files/2592468/conv-layers.pb.zip",
  4993. "format": "TensorFlow Graph",
  4994. "link": "https://github.com/lutzroeder/netron/issues/187"
  4995. },
  4996. {
  4997. "type": "tf",
  4998. "target": "densenet.pb",
  4999. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/densenet_2018_04_27.tgz[densenet/densenet.pb]",
  5000. "format": "TensorFlow Graph",
  5001. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/guide/hosted_models.md"
  5002. },
  5003. {
  5004. "type": "tf",
  5005. "target": "events.out.tfevents.1606692323.b5c8f88cc7ee.58.2",
  5006. "source": "https://github.com/lutzroeder/netron/files/5613448/events.out.tfevents.1606692323.b5c8f88cc7ee.58.2.zip[events.out.tfevents.1606692323.b5c8f88cc7ee.58.2]",
  5007. "format": "TensorFlow Event File v2",
  5008. "link": "https://github.com/lutzroeder/netron/issues/638"
  5009. },
  5010. {
  5011. "type": "tf",
  5012. "target": "events.out.tfevents.1606696207.eba7c8084653.55.0",
  5013. "source": "https://github.com/lutzroeder/netron/files/5613451/events.out.tfevents.1606696207.eba7c8084653.55.0.zip[events.out.tfevents.1606696207.eba7c8084653.55.0]",
  5014. "format": "TensorFlow Event File v2",
  5015. "link": "https://github.com/lutzroeder/netron/issues/638"
  5016. },
  5017. {
  5018. "type": "tf",
  5019. "target": "events.out.tfevents.1606704213.784cbcc2d49a.55.162.v2",
  5020. "source": "https://github.com/lutzroeder/netron/files/5613605/events.out.tfevents.1606704213.784cbcc2d49a.55.162.v2.zip[events.out.tfevents.1606704213.784cbcc2d49a.55.162.v2]",
  5021. "format": "TensorFlow Event File v2",
  5022. "link": "https://github.com/lutzroeder/netron/issues/638"
  5023. },
  5024. {
  5025. "type": "tf",
  5026. "target": "exDeepFM-criteo.meta",
  5027. "source": "https://raw.githubusercontent.com/Leavingseason/xDeepFM/master/exdeepfm/checkpoint/epoch_0.meta",
  5028. "format": "TensorFlow MetaGraph",
  5029. "action": "skip-render",
  5030. "link": "https://github.com/Leavingseason/xDeepFM"
  5031. },
  5032. {
  5033. "type": "tf",
  5034. "target": "faster_rcnn_inception_resnet_v2_atrous_oid_2018_01_28.ckpt.meta",
  5035. "source": "http://download.tensorflow.org/models/object_detection/faster_rcnn_inception_resnet_v2_atrous_oid_2018_01_28.tar.gz[faster_rcnn_inception_resnet_v2_atrous_oid_2018_01_28/model.ckpt.meta]",
  5036. "format": "TensorFlow MetaGraph",
  5037. "action": "skip-render",
  5038. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  5039. },
  5040. {
  5041. "type": "tf",
  5042. "target": "faster_rcnn_resnet50_lowproposals_coco_2017_11_08.ckpt.meta",
  5043. "source": "http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet50_lowproposals_coco_2017_11_08.tar.gz[faster_rcnn_resnet50_lowproposals_coco_2017_11_08/model.ckpt.meta]",
  5044. "action": "skip-render",
  5045. "format": "TensorFlow MetaGraph"
  5046. },
  5047. {
  5048. "type": "tf",
  5049. "target": "faster_rcnn_resnet50_lowproposals_coco_2017_11_08_saved_model.pb",
  5050. "source": "http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet50_lowproposals_coco_2017_11_08.tar.gz[faster_rcnn_resnet50_lowproposals_coco_2017_11_08/saved_model/saved_model.pb]",
  5051. "action": "skip-render",
  5052. "format": "TensorFlow Saved Model v1"
  5053. },
  5054. {
  5055. "type": "tf",
  5056. "target": "graphdef_saved_model.pb",
  5057. "source": "https://github.com/lutzroeder/netron/files/2528688/saved_model.zip[saved_model.pb]",
  5058. "format": "TensorFlow Graph",
  5059. "link": "https://github.com/lutzroeder/netron/issues/171"
  5060. },
  5061. {
  5062. "type": "tf",
  5063. "target": "half_plus_two_saved_model.pb",
  5064. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two/00000123/saved_model.pb",
  5065. "format": "TensorFlow Saved Model v1",
  5066. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5067. },
  5068. {
  5069. "type": "tf",
  5070. "target": "half_plus_two_main_op_saved_model.pb",
  5071. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two_main_op/00000123/saved_model.pb",
  5072. "format": "TensorFlow Saved Model v1",
  5073. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5074. },
  5075. {
  5076. "type": "tf",
  5077. "target": "half_plus_two_pbtxt_saved_model.pbtxt",
  5078. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two_pbtxt/00000123/saved_model.pbtxt",
  5079. "format": "TensorFlow Saved Model v1",
  5080. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5081. },
  5082. {
  5083. "type": "tf",
  5084. "target": "inception_v1_2016_08_28_frozen.pb",
  5085. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception_resnet_v2_2016_08_30_frozen.pb.tar.gz[inception_resnet_v2_2016_08_30_frozen.pb]",
  5086. "format": "TensorFlow Graph",
  5087. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5088. },
  5089. {
  5090. "type": "tf",
  5091. "target": "inception_v1_2016_08_28_frozen.pb",
  5092. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception_v1_2016_08_28_frozen.pb.tar.gz[inception_v1_2016_08_28_frozen.pb]",
  5093. "format": "TensorFlow Graph",
  5094. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5095. },
  5096. {
  5097. "type": "tf",
  5098. "target": "inception_v2_2016_08_28_frozen.pb",
  5099. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception_v2_2016_08_28_frozen.pb.tar.gz[inception_v2_2016_08_28_frozen.pb]",
  5100. "format": "TensorFlow Graph",
  5101. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5102. },
  5103. {
  5104. "type": "tf",
  5105. "target": "inception_v3.pb",
  5106. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v3_2018_04_27.tgz[./inception_v3.pb]"
  5107. },
  5108. {
  5109. "type": "tf",
  5110. "target": "inception_v3_2016_08_28_frozen.pb",
  5111. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception_v3_2016_08_28_frozen.pb.tar.gz[inception_v3_2016_08_28_frozen.pb]",
  5112. "format": "TensorFlow Graph",
  5113. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5114. },
  5115. {
  5116. "type": "tf",
  5117. "target": "inception_v4.pb",
  5118. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v4_2018_04_27.tgz[./inception_v4.pb]"
  5119. },
  5120. {
  5121. "type": "tf",
  5122. "target": "inception5h.pb",
  5123. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip[tensorflow_inception_graph.pb]"
  5124. },
  5125. {
  5126. "type": "tf",
  5127. "target": "inception_resnet_v2.pb",
  5128. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_resnet_v2_2018_04_27.tgz[./inception_resnet_v2.pb]"
  5129. },
  5130. {
  5131. "type": "tf",
  5132. "target": "mask_rcnn_resnet50_atrous_coco_2018_01_28.ckpt.meta",
  5133. "source": "http://download.tensorflow.org/models/object_detection/mask_rcnn_resnet50_atrous_coco_2018_01_28.tar.gz[mask_rcnn_resnet50_atrous_coco_2018_01_28/model.ckpt.meta]",
  5134. "format": "TensorFlow MetaGraph",
  5135. "action": "skip-render"
  5136. },
  5137. {
  5138. "type": "tf",
  5139. "target": "mnist_model.pbtxt",
  5140. "source": "https://raw.githubusercontent.com/ShauralP/MobileML/master/SimpleMNIST/mnist_model.pbtxt",
  5141. "format": "TensorFlow Graph",
  5142. "link": "https://github.com/ShauralP/MobileML"
  5143. },
  5144. {
  5145. "type": "tf",
  5146. "target": "mobilenet_v1_1.0_224_frozen.pb",
  5147. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224_frozen.pb]",
  5148. "format": "TensorFlow Graph"
  5149. },
  5150. {
  5151. "type": "tf",
  5152. "target": "mobilenet_v1_1.0_224_eval.pbtxt",
  5153. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224_eval.pbtxt]",
  5154. "format": "TensorFlow Graph"
  5155. },
  5156. {
  5157. "type": "tf",
  5158. "target": "mobilenet_v1_1.0_224_quant_eval.pbtxt",
  5159. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz[./mobilenet_v1_1.0_224_quant_eval.pbtxt]",
  5160. "format": "TensorFlow Graph",
  5161. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5162. },
  5163. {
  5164. "type": "tf",
  5165. "target": "mobilenet_v1_1.0_224_quant_frozen.pb",
  5166. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz[./mobilenet_v1_1.0_224_quant_frozen.pb]",
  5167. "format": "TensorFlow Graph",
  5168. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5169. },
  5170. {
  5171. "type": "tf",
  5172. "target": "mobilenet_v1_1.0_224_quant.ckpt.meta",
  5173. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz[./mobilenet_v1_1.0_224_quant.ckpt.meta]",
  5174. "format": "TensorFlow MetaGraph",
  5175. "action": "skip-render",
  5176. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5177. },
  5178. {
  5179. "type": "tf",
  5180. "target": "mobilenet_v2_1.4_224_frozen.pb",
  5181. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224_frozen.pb]",
  5182. "format": "TensorFlow Graph",
  5183. "link": "https://www.tensorflow.org/lite/models"
  5184. },
  5185. {
  5186. "type": "tf",
  5187. "target": "mobilenet_v2_1.4_224.ckpt.meta",
  5188. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224.ckpt.meta]",
  5189. "format": "TensorFlow MetaGraph",
  5190. "action": "skip-render",
  5191. "link": "https://www.tensorflow.org/lite/models"
  5192. },
  5193. {
  5194. "type": "tf",
  5195. "target": "mobilenet_v2_1.4_224_eval.pbtxt",
  5196. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224_eval.pbtxt]",
  5197. "format": "TensorFlow Graph",
  5198. "link": "https://www.tensorflow.org/lite/models"
  5199. },
  5200. {
  5201. "type": "tf",
  5202. "target": "mnasnet_0.5_224.pb",
  5203. "source": "http://download.tensorflow.org/models/tflite/mnasnet_0.5_224_09_07_2018.tgz[mnasnet_0.5_224/mnasnet_0.5_224.pb]",
  5204. "format": "TensorFlow Graph",
  5205. "link": "https://www.tensorflow.org/lite/models"
  5206. },
  5207. {
  5208. "type": "tf",
  5209. "target": "mnasnet_1.3_224.pb",
  5210. "source": "http://download.tensorflow.org/models/tflite/mnasnet_1.3_224_09_07_2018.tgz[mnasnet_1.3_224/mnasnet_1.3_224.pb]",
  5211. "format": "TensorFlow Graph",
  5212. "link": "https://www.tensorflow.org/lite/models"
  5213. },
  5214. {
  5215. "type": "tf",
  5216. "target": "nasnet_mobile.pb",
  5217. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_mobile_2018_04_27.tgz[./nasnet_mobile.pb]",
  5218. "format": "TensorFlow Graph",
  5219. "link": "https://www.tensorflow.org/lite/models"
  5220. },
  5221. {
  5222. "type": "tf",
  5223. "target": "netron_issue_110.pb",
  5224. "source": "https://github.com/lutzroeder/netron/files/2592457/netron_issue_110.pb.zip[netron_issue_110.pb]",
  5225. "format": "TensorFlow Graph",
  5226. "link": "https://github.com/lutzroeder/netron/issues/110"
  5227. },
  5228. {
  5229. "type": "tf",
  5230. "target": "netron_issue_224.pbtxt",
  5231. "source": "https://github.com/lutzroeder/netron/files/2823959/netron_issue_224.zip[netron_issue_224.pbtxt]",
  5232. "format": "TensorFlow Graph",
  5233. "link": "https://github.com/lutzroeder/netron/issues/224"
  5234. },
  5235. {
  5236. "type": "tf",
  5237. "target": "netron_issue_291.pbtxt",
  5238. "source": "https://github.com/lutzroeder/netron/files/3336368/netron_issue_291.zip[netron_issue_291.pbtxt]",
  5239. "format": "TensorFlow Graph",
  5240. "link": "https://github.com/lutzroeder/netron/issues/291"
  5241. },
  5242. {
  5243. "type": "tf",
  5244. "target": "netron_issue_320.pb",
  5245. "source": "https://github.com/lutzroeder/netron/files/3499707/netron_issue_320.zip[netron_issue_320.pb]",
  5246. "format": "TensorFlow Graph",
  5247. "link": "https://github.com/lutzroeder/netron/issues/320"
  5248. },
  5249. {
  5250. "type": "tf",
  5251. "target": "netron_issue_320.pbtxt",
  5252. "source": "https://github.com/lutzroeder/netron/files/3499707/netron_issue_320.zip[netron_issue_320.pbtxt]",
  5253. "format": "TensorFlow Graph",
  5254. "link": "https://github.com/lutzroeder/netron/issues/320"
  5255. },
  5256. {
  5257. "type": "tf",
  5258. "target": "netron_issue_323.pbtxt",
  5259. "source": "https://github.com/lutzroeder/netron/files/3539403/graph.zip[graph.pbtxt]",
  5260. "action": "skip-render",
  5261. "format": "TensorFlow Graph",
  5262. "link": "https://github.com/lutzroeder/netron/issues/323"
  5263. },
  5264. {
  5265. "type": "tf",
  5266. "target": "netron_issue_342.zip",
  5267. "source": "https://github.com/lutzroeder/netron/files/3918584/netron_issue_342.zip",
  5268. "format": "TensorFlow Saved Model v1",
  5269. "link": "https://github.com/lutzroeder/netron/issues/342"
  5270. },
  5271. {
  5272. "type": "tf",
  5273. "target": "netron_issue_405.zip",
  5274. "source": "https://github.com/lutzroeder/netron/files/4017943/netron_issue_405.zip",
  5275. "format": "TensorFlow Tensor Bundle v2",
  5276. "link": "https://github.com/lutzroeder/netron/issues/405"
  5277. },
  5278. {
  5279. "type": "tf",
  5280. "target": "pose_estimation_for_mobile.pb",
  5281. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.pb",
  5282. "format": "TensorFlow Graph",
  5283. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  5284. },
  5285. {
  5286. "type": "tf",
  5287. "target": "readable_graph.meta",
  5288. "source": "https://github.com/lutzroeder/netron/files/2592463/readable_graph.meta.zip[readable_graph.meta]",
  5289. "format": "TensorFlow MetaGraph",
  5290. "link": "https://github.com/lutzroeder/netron/issues/187"
  5291. },
  5292. {
  5293. "type": "tf",
  5294. "target": "resnet_v1_50.pb",
  5295. "source": "https://deepdetect.com/models/tf/resnet_v1_50/resnet_v1_50.pb",
  5296. "format": "TensorFlow Graph",
  5297. "link": "https://deepdetect.com/models/tf"
  5298. },
  5299. {
  5300. "type": "tf",
  5301. "target": "resnet_v1_50.ckpt",
  5302. "source": "https://raw.githubusercontent.com/serre-lab/deeplabcut_mgh/master/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_50.ckpt",
  5303. "format": "TensorFlow Tensor Bundle v1",
  5304. "link": "https://github.com/lutzroeder/netron/issues/405"
  5305. },
  5306. {
  5307. "type": "tf",
  5308. "target": "resnet_v1_101.pb",
  5309. "source": "https://deepdetect.com/models/tf/resnet_v1_101/resnet_v1_101.pb",
  5310. "format": "TensorFlow Graph",
  5311. "link": "https://deepdetect.com/models/tf"
  5312. },
  5313. {
  5314. "type": "tf",
  5315. "target": "resnet_v1_152.pb",
  5316. "source": "https://deepdetect.com/models/tf/resnet_v1_152/resnet_v1_152.pb",
  5317. "format": "TensorFlow Graph",
  5318. "link": "https://deepdetect.com/models/tf"
  5319. },
  5320. {
  5321. "type": "tf",
  5322. "target": "resnet_v2_fp16_savedmodel_NHWC_saved_model.pb",
  5323. "source": "http://download.tensorflow.org/models/official/20181001_resnet/savedmodels/resnet_v2_fp16_savedmodel_NHWC.tar.gz[./resnet_v2_fp16_savedmodel_NHWC/1538686978/saved_model.pb]",
  5324. "format": "TensorFlow Saved Model v1",
  5325. "action": "skip-render",
  5326. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5327. },
  5328. {
  5329. "type": "tf",
  5330. "target": "resnet18_model_baseline.pbtxt",
  5331. "source": "https://github.com/lutzroeder/netron/files/2913372/resnet18_model_baseline.pbtxt.zip[resnet18_model_baseline.pbtxt]",
  5332. "format": "TensorFlow Graph",
  5333. "action": "skip-render",
  5334. "link": "https://github.com/lutzroeder/netron/issues/235"
  5335. },
  5336. {
  5337. "type": "tf",
  5338. "target": "speech_commands_v0.pb",
  5339. "source": "http://storage.googleapis.com/download.tensorflow.org/models/speech_commands_v0.01.zip[conv_actions_frozen.pb]",
  5340. "format": "TensorFlow Graph"
  5341. },
  5342. {
  5343. "type": "tf",
  5344. "target": "squeezenet.pb",
  5345. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/squeezenet_2018_04_27.tgz[./squeezenet.pb]"
  5346. },
  5347. {
  5348. "type": "tf",
  5349. "target": "ssd_mobilenet_v1_android_export.pb",
  5350. "source": "https://storage.googleapis.com/download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_android_export.zip[ssd_mobilenet_v1_android_export.pb]",
  5351. "format": "TensorFlow Graph",
  5352. "action": "skip-render",
  5353. "link": "https://www.tensorflow.org/lite/models"
  5354. },
  5355. {
  5356. "type": "tf",
  5357. "target": "ssd_mobilenet_v1_coco_11_06_2017_graph.pbtxt",
  5358. "source": "http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_11_06_2017.tar.gz[ssd_mobilenet_v1_coco_11_06_2017/graph.pbtxt]",
  5359. "format": "TensorFlow Graph",
  5360. "action": "skip-render",
  5361. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  5362. },
  5363. {
  5364. "type": "tf",
  5365. "target": "ssd_mobilenet_v1_coco_11_06_2017_frozen_inference.pb",
  5366. "source": "http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_11_06_2017.tar.gz[ssd_mobilenet_v1_coco_11_06_2017/frozen_inference_graph.pb]",
  5367. "format": "TensorFlow Graph",
  5368. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  5369. },
  5370. {
  5371. "type": "tf",
  5372. "target": "ssd_mobilenet_v1_coco_11_06_2017.ckpt.meta",
  5373. "source": "http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_11_06_2017.tar.gz[ssd_mobilenet_v1_coco_11_06_2017/model.ckpt.meta]",
  5374. "format": "TensorFlow MetaGraph",
  5375. "action": "skip-render",
  5376. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  5377. },
  5378. {
  5379. "type": "tf",
  5380. "target": "tensorflow_issue_9169_saved_model.pbtxt",
  5381. "source": "https://github.com/tensorflow/tensorflow/files/917065/sample.zip[sample/load/saved_model.pbtxt]",
  5382. "format": "TensorFlow Saved Model v1",
  5383. "link": "https://github.com/tensorflow/tensorflow/issues/9169"
  5384. },
  5385. {
  5386. "type": "tf",
  5387. "target": "vgg_16.ckpt",
  5388. "source": "http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz[vgg_16.ckpt]",
  5389. "format": "TensorFlow Tensor Bundle v1"
  5390. },
  5391. {
  5392. "type": "tf",
  5393. "target": "vgg_19.pb",
  5394. "source": "https://deepdetect.com/models/tf/vgg_19/vgg_19.pb",
  5395. "format": "TensorFlow Graph",
  5396. "link": "https://deepdetect.com/models/tf"
  5397. },
  5398. {
  5399. "type": "tfjs",
  5400. "target": "air-time-model/air-time-model.json",
  5401. "source": "https://github.com/lutzroeder/netron/files/3170424/air-time-model.json.zip[air-time-model.json]",
  5402. "format": "TensorFlow.js layers-model", "producer": "TensorFlow.js tfjs-layers v1.0.4",
  5403. "link": "https://github.com/lutzroeder/netron/issues/270"
  5404. },
  5405. {
  5406. "type": "tfjs",
  5407. "target": "age_gender_model/age_gender_model-weights_manifest.json,age_gender_model/age_gender_model-shard1",
  5408. "source": "https://raw.githubusercontent.com/justadudewhohacks/face-api.js-models/master/age_gender_model/age_gender_model-weights_manifest.json,https://raw.githubusercontent.com/justadudewhohacks/face-api.js-models/master/age_gender_model/age_gender_model-shard1",
  5409. "format": "TensorFlow.js Weights"
  5410. },
  5411. {
  5412. "type": "tfjs",
  5413. "target": "mnist_transfer_cnn_v1/model.json,mnist_transfer_cnn_v1/group1-shard1of1,mnist_transfer_cnn_v1/group2-shard1of1,mnist_transfer_cnn_v1/group3-shard1of1,mnist_transfer_cnn_v1/group4-shard1of1",
  5414. "source": "https://github.com/lutzroeder/netron/files/3361048/mnist_transfer_cnn_v1.zip[model.json,group1-shard1of1,group2-shard1of1,group3-shard1of1,group4-shard1of1]",
  5415. "format": "TensorFlow.js Keras v2.1.4",
  5416. "link": "https://github.com/tensorflow/tfjs-examples"
  5417. },
  5418. {
  5419. "type": "tfjs",
  5420. "target": "mobilenet_v1_0.25_224/model.json",
  5421. "source": "https://storage.googleapis.com/tfjs-models/tfjs/mobilenet_v1_0.25_224/model.json",
  5422. "format": "TensorFlow.js Keras v2.1.4",
  5423. "link": "https://github.com/tensorflow/tfjs-examples"
  5424. },
  5425. {
  5426. "type": "tfjs",
  5427. "target": "posenet_mobilenet_float_075/model-stride16.json,posenet_mobilenet_float_075/group1-shard1of2.bin,posenet_mobilenet_float_075/group1-shard2of2.bin",
  5428. "source": "https://github.com/lutzroeder/netron/files/3357629/posenet_mobilenet_float_075.zip[model-stride16.json,group1-shard1of2.bin,group1-shard2of2.bin]",
  5429. "format": "TensorFlow.js graph-model",
  5430. "link": "https://github.com/intel/webml-polyfill/issues/880"
  5431. },
  5432. {
  5433. "type": "tfjs",
  5434. "target": "sentiment_cnn_v1/model.json",
  5435. "source": "https://github.com/lutzroeder/netron/files/3361046/sentiment_cnn_v1.zip[model.json]",
  5436. "format": "TensorFlow.js Keras v2.1.4",
  5437. "link": "https://github.com/tensorflow/tfjs-examples"
  5438. },
  5439. {
  5440. "type": "tfjs",
  5441. "target": "translation_en_fr_v1/model.json",
  5442. "source": "https://storage.googleapis.com/tfjs-models/tfjs/translation_en_fr_v1/model.json",
  5443. "format": "TensorFlow.js Keras v2.1.4",
  5444. "link": "https://github.com/tensorflow/tfjs-examples"
  5445. },
  5446. {
  5447. "type": "tflite",
  5448. "target": "deeplab_mobilenetv2_513.tflite",
  5449. "source": "https://raw.githubusercontent.com/pinzhenx/webml-demo/master/examples/deeplab/model/deeplab_mobilenetv2_513.tflite",
  5450. "format": "TensorFlow Lite v3",
  5451. "link": "https://github.com/pinzhenx/webml-demo"
  5452. },
  5453. {
  5454. "type": "tflite",
  5455. "target": "deeplab_mobilenetv2_513_dilated.tflite",
  5456. "source": "https://raw.githubusercontent.com/pinzhenx/webml-demo/master/examples/deeplab/model/deeplab_mobilenetv2_513_dilated.tflite",
  5457. "format": "TensorFlow Lite v3",
  5458. "link": "https://github.com/pinzhenx/webml-demo"
  5459. },
  5460. {
  5461. "type": "tflite",
  5462. "target": "densenet.tflite",
  5463. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/densenet_2018_04_27.tgz[densenet/densenet.tflite]",
  5464. "format": "TensorFlow Lite v3"
  5465. },
  5466. {
  5467. "type": "tflite",
  5468. "target": "efficientnet-edgetpu-S_quant_edgetpu.tflite",
  5469. "source": "https://github.com/google-coral/edgetpu/raw/master/test_data/efficientnet-edgetpu-S_quant_edgetpu.tflite",
  5470. "format": "TensorFlow Lite v3",
  5471. "link": "https://github.com/lutzroeder/netron/issues/499"
  5472. },
  5473. {
  5474. "type": "tflite",
  5475. "target": "face_detection_front.json",
  5476. "source": "https://github.com/lutzroeder/netron/files/4606685/face_detection_front.zip[face_detection_front.json]",
  5477. "format": "TensorFlow Lite v3"
  5478. },
  5479. {
  5480. "type": "tflite",
  5481. "target": "face_detection_front.tflite",
  5482. "source": "https://github.com/lutzroeder/netron/files/4606685/face_detection_front.zip[face_detection_front.tflite]",
  5483. "format": "TensorFlow Lite v3",
  5484. "link": "https://github.com/lutzroeder/netron/issues/487"
  5485. },
  5486. {
  5487. "type": "tflite",
  5488. "target": "hair_segmentation.json",
  5489. "source": "https://github.com/lutzroeder/netron/files/4606715/hair_segmentation.zip[hair_segmentation.json]",
  5490. "format": "TensorFlow Lite v3",
  5491. "link": "https://github.com/lutzroeder/netron/issues/487"
  5492. },
  5493. {
  5494. "type": "tflite",
  5495. "target": "hair_segmentation.tflite",
  5496. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/models/hair_segmentation.tflite",
  5497. "format": "TensorFlow Lite v3",
  5498. "link": "https://github.com/google/mediapipe"
  5499. },
  5500. {
  5501. "type": "tflite",
  5502. "target": "hed_lite_model_quantize.tflite",
  5503. "source": "https://raw.githubusercontent.com/pqpo/SmartCropper/master/smartcropperlib/src/main/assets/models/hed_lite_model_quantize.tflite",
  5504. "format": "TensorFlow Lite v3",
  5505. "link": "https://github.com/pqpo/SmartCropper"
  5506. },
  5507. {
  5508. "type": "tflite",
  5509. "target": "inception_resnet_v2.tflite",
  5510. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_resnet_v2_2018_04_27.tgz[./inception_resnet_v2.tflite]",
  5511. "format": "TensorFlow Lite v3"
  5512. },
  5513. {
  5514. "type": "tflite",
  5515. "target": "inception_v3.tflite",
  5516. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v3_2018_04_27.tgz[./inception_v3.tflite]"
  5517. },
  5518. {
  5519. "type": "tflite",
  5520. "target": "inception_v3_quant.tflite",
  5521. "source": "http://download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz[inception_v3_quant.tflite]",
  5522. "format": "TensorFlow Lite v3",
  5523. "link": "https://www.tensorflow.org/lite/models"
  5524. },
  5525. {
  5526. "type": "tflite",
  5527. "target": "inception_v4_299_quant.tflite",
  5528. "source": "http://download.tensorflow.org/models/inception_v4_299_quant_20181026.tgz[inception_v4_299_quant.tflite]",
  5529. "format": "TensorFlow Lite v3",
  5530. "link": "https://www.tensorflow.org/lite/models"
  5531. },
  5532. {
  5533. "type": "tflite",
  5534. "target": "mobilenet_v1_1.0_224.tflite",
  5535. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224.tflite]",
  5536. "format": "TensorFlow Lite v3",
  5537. "link": "https://www.tensorflow.org/lite/models"
  5538. },
  5539. {
  5540. "type": "tflite",
  5541. "target": "mobilenet_v1_1.0_224_quant.tflite",
  5542. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz[./mobilenet_v1_1.0_224_quant.tflite]",
  5543. "format": "TensorFlow Lite v3",
  5544. "link": "https://www.tensorflow.org/lite/models"
  5545. },
  5546. {
  5547. "type": "tflite",
  5548. "target": "mobilenet_v1_0.75_160_quantized.tflite",
  5549. "source": "https://github.com/lutzroeder/netron/files/4569400/mobilenet_v1_0.75_160_quantized.zip[mobilenet_v1_0.75_160_quantized.tflite]",
  5550. "format": "TensorFlow Lite v3",
  5551. "link": "https://github.com/lutzroeder/netron/issues/481"
  5552. },
  5553. {
  5554. "type": "tflite",
  5555. "target": "mobilenet_v2_0.4_224.tflite",
  5556. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.0_224.tgz[./mobilenet_v2_1.0_224.tflite]",
  5557. "format": "TensorFlow Lite v3"
  5558. },
  5559. {
  5560. "type": "tflite",
  5561. "target": "mobilenet_v2_1.4_224.tflite",
  5562. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224.tflite]",
  5563. "format": "TensorFlow Lite v3"
  5564. },
  5565. {
  5566. "type": "tflite",
  5567. "target": "mnasnet_0.5_224.tflite",
  5568. "source": "http://download.tensorflow.org/models/tflite/mnasnet_0.5_224_09_07_2018.tgz[mnasnet_0.5_224/mnasnet_0.5_224.tflite]",
  5569. "format": "TensorFlow Lite v3",
  5570. "link": "https://www.tensorflow.org/lite/models"
  5571. },
  5572. {
  5573. "type": "tflite",
  5574. "target": "mnasnet_1.3_224.tflite",
  5575. "source": "http://download.tensorflow.org/models/tflite/mnasnet_1.3_224_09_07_2018.tgz[mnasnet_1.3_224/mnasnet_1.3_224.tflite]",
  5576. "format": "TensorFlow Lite v3",
  5577. "link": "https://www.tensorflow.org/lite/models"
  5578. },
  5579. {
  5580. "type": "tflite",
  5581. "target": "nasnet_mobile.tflite",
  5582. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_mobile_2018_04_27.tgz[./nasnet_mobile.tflite]",
  5583. "format": "TensorFlow Lite v3",
  5584. "link": "https://www.tensorflow.org/lite/models"
  5585. },
  5586. {
  5587. "type": "tflite",
  5588. "target": "nasnet_large.tflite",
  5589. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_large_2018_04_27.tgz[./nasnet_large.tflite]",
  5590. "format": "TensorFlow Lite v3",
  5591. "link": "https://www.tensorflow.org/lite/models"
  5592. },
  5593. {
  5594. "type": "tflite",
  5595. "target": "netron_issue_256.tflite",
  5596. "source": "https://github.com/lutzroeder/netron/files/3101992/test.zip[test.tflite]",
  5597. "format": "TensorFlow Lite v3",
  5598. "link": "https://github.com/lutzroeder/netron/issues/256"
  5599. },
  5600. {
  5601. "type": "tflite",
  5602. "target": "netron_issue_386.tflite",
  5603. "source": "https://github.com/lutzroeder/netron/files/3963415/netron_issue_386.zip[netron_issue_386.tflite]",
  5604. "format": "TensorFlow Lite v3",
  5605. "link": "https://github.com/lutzroeder/netron/issues/386"
  5606. },
  5607. {
  5608. "type": "tflite",
  5609. "target": "netron_issue_416.tflite",
  5610. "source": "https://github.com/lutzroeder/netron/files/4089319/netron_issue_416.zip[netron_issue_416.tflite]",
  5611. "format": "TensorFlow Lite v3",
  5612. "link": "https://github.com/lutzroeder/netron/issues/416"
  5613. },
  5614. {
  5615. "type": "tflite",
  5616. "target": "netron_issue_479.tflite",
  5617. "source": "https://github.com/lutzroeder/netron/files/4565988/netron_issue_479.zip[netron_issue_479.tflite]",
  5618. "format": "TensorFlow Lite v3",
  5619. "link": "https://github.com/lutzroeder/netron/issues/479"
  5620. },
  5621. {
  5622. "type": "tflite",
  5623. "target": "pose_estimation_for_mobile.tflite",
  5624. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.tflite",
  5625. "format": "TensorFlow Lite v3",
  5626. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  5627. },
  5628. {
  5629. "type": "tflite",
  5630. "target": "quicknet.tflite",
  5631. "source": "https://github.com/lutzroeder/netron/files/5184953/quicknet.zip[quicknet.tflite]",
  5632. "format": "TensorFlow Lite v3",
  5633. "link": "https://github.com/lutzroeder/netron/issues/499"
  5634. },
  5635. {
  5636. "type": "tflite",
  5637. "target": "resnet_v2_50.tflite",
  5638. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/resnet_v2_50_2018_03_27.zip[resnet_v2_50.tflite]",
  5639. "format": "TensorFlow Lite v3",
  5640. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/models.md"
  5641. },
  5642. {
  5643. "type": "tflite",
  5644. "target": "smartreply.tflite",
  5645. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip[smartreply.tflite]",
  5646. "format": "TensorFlow Lite v3"
  5647. },
  5648. {
  5649. "type": "tflite",
  5650. "target": "smartreply_1.0_2017_11_01.zip",
  5651. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip",
  5652. "format": "TensorFlow Lite v3"
  5653. },
  5654. {
  5655. "type": "tflite",
  5656. "target": "squeezenet.tflite",
  5657. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/squeezenet_2018_04_27.tgz[./squeezenet.tflite]",
  5658. "format": "TensorFlow Lite v3"
  5659. },
  5660. {
  5661. "type": "tflite",
  5662. "target": "speech_hotword_model_rank1_2017_11_14.tflite",
  5663. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank1_2017_11_14.tflite",
  5664. "format": "TensorFlow Lite v3"
  5665. },
  5666. {
  5667. "type": "tflite",
  5668. "target": "speech_hotword_model_rank2_2017_11_14.tflite",
  5669. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank2_2017_11_14.tflite",
  5670. "format": "TensorFlow Lite v3"
  5671. },
  5672. {
  5673. "type": "tflite",
  5674. "target": "speech_speakerid_model_2017_11_14.tflite",
  5675. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_speakerid_model_2017_11_14.tflite",
  5676. "format": "TensorFlow Lite v3"
  5677. },
  5678. {
  5679. "type": "tflite",
  5680. "target": "speech_tts_model_2017_11_14.tflite",
  5681. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_tts_model_2017_11_14.tflite",
  5682. "format": "TensorFlow Lite v3"
  5683. },
  5684. {
  5685. "type": "tflite",
  5686. "target": "speech_tts_model_2017_11_14.json",
  5687. "source": "https://github.com/lutzroeder/netron/files/4606719/speech_tts_model_2017_11_14.zip[speech_tts_model_2017_11_14.json]",
  5688. "format": "TensorFlow Lite v3",
  5689. "link": "https://github.com/lutzroeder/netron/issues/487"
  5690. },
  5691. {
  5692. "type": "tflite",
  5693. "target": "text_classification.tflite",
  5694. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/text_classification/text_classification.tflite",
  5695. "format": "TensorFlow Lite v3",
  5696. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/models/text_classification/overview.md"
  5697. },
  5698. {
  5699. "type": "tflite",
  5700. "target": "two_subgraphs.bin",
  5701. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/lite/testdata/two_subgraphs.bin",
  5702. "format": "TensorFlow Lite v3",
  5703. "link": "https://github.com/tensorflow/tensorflow"
  5704. },
  5705. {
  5706. "type": "tflite",
  5707. "target": "xorGate.lite",
  5708. "source": "https://raw.githubusercontent.com/kosslab-kr/Tizen-NN-Runtime/master/Xor/xorGate.lite",
  5709. "format": "TensorFlow Lite v3",
  5710. "link": "https://github.com/kosslab-kr/Tizen-NN-Runtime"
  5711. },
  5712. {
  5713. "type": "tnn",
  5714. "target": "instance_normalization.tnnproto,instance_normalization.tnnmodel",
  5715. "source": "https://github.com/lutzroeder/netron/files/5124180/instance_normalization.zip[instance_normalization.tnnproto,instance_normalization.tnnmodel]",
  5716. "format": "TNN",
  5717. "link": "https://github.com/lutzroeder/netron/pull/583"
  5718. },
  5719. {
  5720. "type": "tnn",
  5721. "target": "mobilenet_v2.onnx.opt.onnx.tnnproto",
  5722. "source": "https://gitee.com/darren3d/tnn-resource/raw/master/model/mobilenet_v2/mobilenet_v2.onnx.opt.onnx.tnnproto",
  5723. "format": "TNN",
  5724. "link": "https://gitee.com/darren3d/tnn-resource/tree/master/model/mobilenet_v2"
  5725. },
  5726. {
  5727. "type": "tnn",
  5728. "target": "squeezenet_v1.1.tnnmodel,squeezenet_v1.1.tnnproto",
  5729. "source": "https://raw.githubusercontent.com/Tencent/TNN/master/model/SqueezeNet/squeezenet_v1.1.tnnmodel,https://raw.githubusercontent.com/Tencent/TNN/master/model/SqueezeNet/squeezenet_v1.1.tnnproto",
  5730. "format": "TNN",
  5731. "link": "https://github.com/Tencent/TNN"
  5732. },
  5733. {
  5734. "type": "tnn",
  5735. "target": "version-slim-320_simplified.tnnproto,version-slim-320_simplified.tnnmodel",
  5736. "source": "https://gitee.com/darren3d/tnn-resource/raw/master/model/face-detector/version-slim-320_simplified.tnnproto,https://gitee.com/darren3d/tnn-resource/raw/master/model/face-detector/version-slim-320_simplified.tnnmodel",
  5737. "format": "TNN",
  5738. "link": "https://gitee.com/darren3d/tnn-resource/raw/master/model/face-detector"
  5739. },
  5740. {
  5741. "type": "tnn",
  5742. "target": "squeezenet_v1.1.tnnproto,squeezenet_v1.1.tnnmodel",
  5743. "source": "https://raw.githubusercontent.com/Tencent/TNN/master/model/SqueezeNet/squeezenet_v1.1.tnnproto,https://raw.githubusercontent.com/Tencent/TNN/master/model/SqueezeNet/squeezenet_v1.1.tnnmodel",
  5744. "format": "TNN",
  5745. "link": "https://github.com/Tencent/TNN"
  5746. },
  5747. {
  5748. "type": "torch",
  5749. "target": "2ch_notredame.t7",
  5750. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2ch/2ch_notredame.t7]",
  5751. "format": "Torch v7",
  5752. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  5753. },
  5754. {
  5755. "type": "torch",
  5756. "target": "2ch2stream_liberty.t7",
  5757. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2ch2stream/2ch2stream_liberty.t7]",
  5758. "format": "Torch v7",
  5759. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  5760. },
  5761. {
  5762. "type": "torch",
  5763. "target": "2chdeep_yosemite.t7",
  5764. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2chdeep/2chdeep_yosemite.t7]",
  5765. "format": "Torch v7",
  5766. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  5767. },
  5768. {
  5769. "type": "torch",
  5770. "target": "apple2orange.t7",
  5771. "source": "https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/models/apple2orange.t7",
  5772. "format": "Torch v7",
  5773. "link": "https://github.com/junyanz/CycleGAN"
  5774. },
  5775. {
  5776. "type": "torch",
  5777. "target": "bedrooms_4_net_G.t7",
  5778. "source": "https://github.com/soumith/lfs/raw/master/dcgan.torch/bedrooms_4_net_G.t7",
  5779. "format": "Torch v7",
  5780. "link": "https://github.com/soumith/dcgan.torch"
  5781. },
  5782. {
  5783. "type": "torch",
  5784. "target": "celebA_25_net_G.t7",
  5785. "source": "https://github.com/soumith/lfs/raw/master/dcgan.torch/celebA_25_net_G.t7",
  5786. "format": "Torch v7",
  5787. "link": "https://github.com/soumith/dcgan.torch"
  5788. },
  5789. {
  5790. "type": "torch",
  5791. "target": "composition_vii.t7",
  5792. "source": "https://cs.stanford.edu/people/jcjohns/fast-neural-style/models/eccv16/composition_vii.t7",
  5793. "format": "Torch v7",
  5794. "link": "https://github.com/jcjohnson/fast-neural-style"
  5795. },
  5796. {
  5797. "type": "torch",
  5798. "target": "cunet_art_14l_scale2.0x_model.t7",
  5799. "source": "https://raw.githubusercontent.com/nagadomi/waifu2x/master/models/cunet/art/noise0_model.t7",
  5800. "format": "Torch v7",
  5801. "link": "https://github.com/nagadomi/waifu2x"
  5802. },
  5803. {
  5804. "type": "torch",
  5805. "target": "facades_photo2label.t7",
  5806. "source": "https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/models/facades_photo2label.t7",
  5807. "format": "Torch v7",
  5808. "link": "https://github.com/junyanz/CycleGAN"
  5809. },
  5810. {
  5811. "type": "torch",
  5812. "target": "Helen_8x.t7",
  5813. "source": "https://raw.githubusercontent.com/tyshiwo/FSRNet/master/models/Helen_8x.t7",
  5814. "format": "Torch v7",
  5815. "link": "https://github.com/tyshiwo/FSRNet"
  5816. },
  5817. {
  5818. "type": "torch",
  5819. "target": "inception.t7",
  5820. "source": "https://raw.githubusercontent.com/cpra/fer-cnn-sota/master/models/inception.t7",
  5821. "format": "Torch v7",
  5822. "link": "https://github.com/cpra/fer-cnn-sota"
  5823. },
  5824. {
  5825. "type": "torch",
  5826. "target": "model-ende_epoch7_5.55_release.t7",
  5827. "source": "https://s3.amazonaws.com/opennmt-models/wmt-ende_l2-h1024-bpe32k_release.tar.gz[model-ende_epoch7_5.55_release.t7]",
  5828. "format": "Torch v7",
  5829. "link": "https://github.com/OpenNMT/opennmt.github.io/issues/22"
  5830. },
  5831. {
  5832. "type": "torch",
  5833. "target": "net_kitti2015_fast_-a_train_all.t7",
  5834. "source": "https://github.com/lutzroeder/netron/files/3165404/net_kitti2015_fast_-a_train_all.t7.zip[net_kitti2015_fast_-a_train_all.t7]",
  5835. "format": "Torch v7",
  5836. "link": "https://github.com/lutzroeder/netron/issues/269"
  5837. },
  5838. {
  5839. "type": "torch",
  5840. "target": "openface.nn4.small2.v1.t7",
  5841. "source": "https://raw.githubusercontent.com/pyannote/pyannote-data/master/openface.nn4.small2.v1.t7",
  5842. "format": "Torch v7",
  5843. "link": "https://github.com/pyannote/pyannote-data"
  5844. },
  5845. {
  5846. "type": "torch",
  5847. "target": "resnet.t7",
  5848. "source": "https://raw.githubusercontent.com/cpra/fer-cnn-sota/master/models/resnet.t7",
  5849. "format": "Torch v7",
  5850. "link": "https://github.com/cpra/fer-cnn-sota"
  5851. },
  5852. {
  5853. "type": "torch",
  5854. "target": "resnet-18.t7",
  5855. "source": "https://d2j0dndfm35trm.cloudfront.net/resnet-18.t7",
  5856. "format": "Torch v7",
  5857. "link": "https://github.com/facebook/fb.resnet.torch"
  5858. },
  5859. {
  5860. "type": "torch",
  5861. "target": "resnet-50.t7",
  5862. "source": "https://d2j0dndfm35trm.cloudfront.net/resnet-50.t7",
  5863. "format": "Torch v7",
  5864. "link": "https://github.com/facebook/fb.resnet.torch"
  5865. },
  5866. {
  5867. "type": "torch",
  5868. "target": "resnet_photo_14l_scale2.0x_model.t7",
  5869. "source": "https://raw.githubusercontent.com/nagadomi/waifu2x/master/models/resnet_14l/photo/scale2.0x_model.t7",
  5870. "format": "Torch v7",
  5871. "link": "https://github.com/nagadomi/waifu2x"
  5872. },
  5873. {
  5874. "type": "torch",
  5875. "target": "rnnTracker_r300_l1_n1_m1_d4.t7",
  5876. "source": "https://raw.githubusercontent.com/aghagol/minimal_rnntracking_deploy/master/bin/rnnTracker_r300_l1_n1_m1_d4.t7",
  5877. "format": "Torch v7",
  5878. "link": "https://github.com/aghagol"
  5879. },
  5880. {
  5881. "type": "torch",
  5882. "target": "siam_liberty.t7",
  5883. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[siam/siam_liberty.t7]",
  5884. "format": "Torch v7",
  5885. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  5886. },
  5887. {
  5888. "type": "torch",
  5889. "target": "siam2stream_notredame.t7",
  5890. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[siam2stream/siam2stream_notredame.t7]",
  5891. "format": "Torch v7",
  5892. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  5893. },
  5894. {
  5895. "type": "torch",
  5896. "target": "soundnet5_final.t7",
  5897. "source": "http://data.csail.mit.edu/soundnet/soundnet_models_public.zip[soundnet_models_public/soundnet5_final.t7]",
  5898. "format": "Torch v7",
  5899. "link": "https://github.com/afperezm/acoustic-images-distillation"
  5900. },
  5901. {
  5902. "type": "torch",
  5903. "target": "upconv_7l_photo_scale2.0x_model.t7",
  5904. "source": "https://raw.githubusercontent.com/nagadomi/waifu2x/master/models/upconv_7l/photo/scale2.0x_model.t7",
  5905. "format": "Torch v7",
  5906. "link": "https://github.com/nagadomi/waifu2x"
  5907. },
  5908. {
  5909. "type": "torch",
  5910. "target": "uni_image_np_50.t7",
  5911. "source": "https://polybox.ethz.ch/index.php/s/0SEdZqkn433dbEh/download",
  5912. "format": "Torch v7",
  5913. "link": "https://github.com/simonwsw/deep-soli"
  5914. },
  5915. {
  5916. "type": "torch",
  5917. "target": "vgg.t7",
  5918. "source": "https://raw.githubusercontent.com/cpra/fer-cnn-sota/master/models/vgg.t7",
  5919. "format": "Torch v7",
  5920. "link": "https://github.com/cpra/fer-cnn-sota"
  5921. },
  5922. {
  5923. "type": "uff",
  5924. "target": "tmp_v2_coco.pbtxt",
  5925. "source": "https://github.com/lutzroeder/netron/files/4741218/tmp_v2_coco.zip[tmp_v2_coco.pbtxt]",
  5926. "format": "UFF v1",
  5927. "link": "https://github.com/lutzroeder/netron/issues/511"
  5928. },
  5929. {
  5930. "type": "uff",
  5931. "target": "sample_unpruned_mobilenet_v2.tar.gz",
  5932. "source": "https://nvidia.box.com/shared/static/8oqvmd79llr6lq1fr43s4fu1ph37v8nt.gz",
  5933. "format": "UFF v1"
  5934. },
  5935. {
  5936. "type": "weka",
  5937. "target": "j48model.model",
  5938. "source": "https://raw.githubusercontent.com/PTaati/wekaTree2python/master/j48model.model",
  5939. "error": "Unsupported type 'weka.classifiers.trees.J48' in 'j48model.model'."
  5940. }
  5941. ]