2
0

models.json 284 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798991001011021031041051061071081091101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491501511521531541551561571581591601611621631641651661671681691701711721731741751761771781791801811821831841851861871881891901911921931941951961971981992002012022032042052062072082092102112122132142152162172182192202212222232242252262272282292302312322332342352362372382392402412422432442452462472482492502512522532542552562572582592602612622632642652662672682692702712722732742752762772782792802812822832842852862872882892902912922932942952962972982993003013023033043053063073083093103113123133143153163173183193203213223233243253263273283293303313323333343353363373383393403413423433443453463473483493503513523533543553563573583593603613623633643653663673683693703713723733743753763773783793803813823833843853863873883893903913923933943953963973983994004014024034044054064074084094104114124134144154164174184194204214224234244254264274284294304314324334344354364374384394404414424434444454464474484494504514524534544554564574584594604614624634644654664674684694704714724734744754764774784794804814824834844854864874884894904914924934944954964974984995005015025035045055065075085095105115125135145155165175185195205215225235245255265275285295305315325335345355365375385395405415425435445455465475485495505515525535545555565575585595605615625635645655665675685695705715725735745755765775785795805815825835845855865875885895905915925935945955965975985996006016026036046056066076086096106116126136146156166176186196206216226236246256266276286296306316326336346356366376386396406416426436446456466476486496506516526536546556566576586596606616626636646656666676686696706716726736746756766776786796806816826836846856866876886896906916926936946956966976986997007017027037047057067077087097107117127137147157167177187197207217227237247257267277287297307317327337347357367377387397407417427437447457467477487497507517527537547557567577587597607617627637647657667677687697707717727737747757767777787797807817827837847857867877887897907917927937947957967977987998008018028038048058068078088098108118128138148158168178188198208218228238248258268278288298308318328338348358368378388398408418428438448458468478488498508518528538548558568578588598608618628638648658668678688698708718728738748758768778788798808818828838848858868878888898908918928938948958968978988999009019029039049059069079089099109119129139149159169179189199209219229239249259269279289299309319329339349359369379389399409419429439449459469479489499509519529539549559569579589599609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959969979989991000100110021003100410051006100710081009101010111012101310141015101610171018101910201021102210231024102510261027102810291030103110321033103410351036103710381039104010411042104310441045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810891090109110921093109410951096109710981099110011011102110311041105110611071108110911101111111211131114111511161117111811191120112111221123112411251126112711281129113011311132113311341135113611371138113911401141114211431144114511461147114811491150115111521153115411551156115711581159116011611162116311641165116611671168116911701171117211731174117511761177117811791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240124112421243124412451246124712481249125012511252125312541255125612571258125912601261126212631264126512661267126812691270127112721273127412751276127712781279128012811282128312841285128612871288128912901291129212931294129512961297129812991300130113021303130413051306130713081309131013111312131313141315131613171318131913201321132213231324132513261327132813291330133113321333133413351336133713381339134013411342134313441345134613471348134913501351135213531354135513561357135813591360136113621363136413651366136713681369137013711372137313741375137613771378137913801381138213831384138513861387138813891390139113921393139413951396139713981399140014011402140314041405140614071408140914101411141214131414141514161417141814191420142114221423142414251426142714281429143014311432143314341435143614371438143914401441144214431444144514461447144814491450145114521453145414551456145714581459146014611462146314641465146614671468146914701471147214731474147514761477147814791480148114821483148414851486148714881489149014911492149314941495149614971498149915001501150215031504150515061507150815091510151115121513151415151516151715181519152015211522152315241525152615271528152915301531153215331534153515361537153815391540154115421543154415451546154715481549155015511552155315541555155615571558155915601561156215631564156515661567156815691570157115721573157415751576157715781579158015811582158315841585158615871588158915901591159215931594159515961597159815991600160116021603160416051606160716081609161016111612161316141615161616171618161916201621162216231624162516261627162816291630163116321633163416351636163716381639164016411642164316441645164616471648164916501651165216531654165516561657165816591660166116621663166416651666166716681669167016711672167316741675167616771678167916801681168216831684168516861687168816891690169116921693169416951696169716981699170017011702170317041705170617071708170917101711171217131714171517161717171817191720172117221723172417251726172717281729173017311732173317341735173617371738173917401741174217431744174517461747174817491750175117521753175417551756175717581759176017611762176317641765176617671768176917701771177217731774177517761777177817791780178117821783178417851786178717881789179017911792179317941795179617971798179918001801180218031804180518061807180818091810181118121813181418151816181718181819182018211822182318241825182618271828182918301831183218331834183518361837183818391840184118421843184418451846184718481849185018511852185318541855185618571858185918601861186218631864186518661867186818691870187118721873187418751876187718781879188018811882188318841885188618871888188918901891189218931894189518961897189818991900190119021903190419051906190719081909191019111912191319141915191619171918191919201921192219231924192519261927192819291930193119321933193419351936193719381939194019411942194319441945194619471948194919501951195219531954195519561957195819591960196119621963196419651966196719681969197019711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044204520462047204820492050205120522053205420552056205720582059206020612062206320642065206620672068206920702071207220732074207520762077207820792080208120822083208420852086208720882089209020912092209320942095209620972098209921002101210221032104210521062107210821092110211121122113211421152116211721182119212021212122212321242125212621272128212921302131213221332134213521362137213821392140214121422143214421452146214721482149215021512152215321542155215621572158215921602161216221632164216521662167216821692170217121722173217421752176217721782179218021812182218321842185218621872188218921902191219221932194219521962197219821992200220122022203220422052206220722082209221022112212221322142215221622172218221922202221222222232224222522262227222822292230223122322233223422352236223722382239224022412242224322442245224622472248224922502251225222532254225522562257225822592260226122622263226422652266226722682269227022712272227322742275227622772278227922802281228222832284228522862287228822892290229122922293229422952296229722982299230023012302230323042305230623072308230923102311231223132314231523162317231823192320232123222323232423252326232723282329233023312332233323342335233623372338233923402341234223432344234523462347234823492350235123522353235423552356235723582359236023612362236323642365236623672368236923702371237223732374237523762377237823792380238123822383238423852386238723882389239023912392239323942395239623972398239924002401240224032404240524062407240824092410241124122413241424152416241724182419242024212422242324242425242624272428242924302431243224332434243524362437243824392440244124422443244424452446244724482449245024512452245324542455245624572458245924602461246224632464246524662467246824692470247124722473247424752476247724782479248024812482248324842485248624872488248924902491249224932494249524962497249824992500250125022503250425052506250725082509251025112512251325142515251625172518251925202521252225232524252525262527252825292530253125322533253425352536253725382539254025412542254325442545254625472548254925502551255225532554255525562557255825592560256125622563256425652566256725682569257025712572257325742575257625772578257925802581258225832584258525862587258825892590259125922593259425952596259725982599260026012602260326042605260626072608260926102611261226132614261526162617261826192620262126222623262426252626262726282629263026312632263326342635263626372638263926402641264226432644264526462647264826492650265126522653265426552656265726582659266026612662266326642665266626672668266926702671267226732674267526762677267826792680268126822683268426852686268726882689269026912692269326942695269626972698269927002701270227032704270527062707270827092710271127122713271427152716271727182719272027212722272327242725272627272728272927302731273227332734273527362737273827392740274127422743274427452746274727482749275027512752275327542755275627572758275927602761276227632764276527662767276827692770277127722773277427752776277727782779278027812782278327842785278627872788278927902791279227932794279527962797279827992800280128022803280428052806280728082809281028112812281328142815281628172818281928202821282228232824282528262827282828292830283128322833283428352836283728382839284028412842284328442845284628472848284928502851285228532854285528562857285828592860286128622863286428652866286728682869287028712872287328742875287628772878287928802881288228832884288528862887288828892890289128922893289428952896289728982899290029012902290329042905290629072908290929102911291229132914291529162917291829192920292129222923292429252926292729282929293029312932293329342935293629372938293929402941294229432944294529462947294829492950295129522953295429552956295729582959296029612962296329642965296629672968296929702971297229732974297529762977297829792980298129822983298429852986298729882989299029912992299329942995299629972998299930003001300230033004300530063007300830093010301130123013301430153016301730183019302030213022302330243025302630273028302930303031303230333034303530363037303830393040304130423043304430453046304730483049305030513052305330543055305630573058305930603061306230633064306530663067306830693070307130723073307430753076307730783079308030813082308330843085308630873088308930903091309230933094309530963097309830993100310131023103310431053106310731083109311031113112311331143115311631173118311931203121312231233124312531263127312831293130313131323133313431353136313731383139314031413142314331443145314631473148314931503151315231533154315531563157315831593160316131623163316431653166316731683169317031713172317331743175317631773178317931803181318231833184318531863187318831893190319131923193319431953196319731983199320032013202320332043205320632073208320932103211321232133214321532163217321832193220322132223223322432253226322732283229323032313232323332343235323632373238323932403241324232433244324532463247324832493250325132523253325432553256325732583259326032613262326332643265326632673268326932703271327232733274327532763277327832793280328132823283328432853286328732883289329032913292329332943295329632973298329933003301330233033304330533063307330833093310331133123313331433153316331733183319332033213322332333243325332633273328332933303331333233333334333533363337333833393340334133423343334433453346334733483349335033513352335333543355335633573358335933603361336233633364336533663367336833693370337133723373337433753376337733783379338033813382338333843385338633873388338933903391339233933394339533963397339833993400340134023403340434053406340734083409341034113412341334143415341634173418341934203421342234233424342534263427342834293430343134323433343434353436343734383439344034413442344334443445344634473448344934503451345234533454345534563457345834593460346134623463346434653466346734683469347034713472347334743475347634773478347934803481348234833484348534863487348834893490349134923493349434953496349734983499350035013502350335043505350635073508350935103511351235133514351535163517351835193520352135223523352435253526352735283529353035313532353335343535353635373538353935403541354235433544354535463547354835493550355135523553355435553556355735583559356035613562356335643565356635673568356935703571357235733574357535763577357835793580358135823583358435853586358735883589359035913592359335943595359635973598359936003601360236033604360536063607360836093610361136123613361436153616361736183619362036213622362336243625362636273628362936303631363236333634363536363637363836393640364136423643364436453646364736483649365036513652365336543655365636573658365936603661366236633664366536663667366836693670367136723673367436753676367736783679368036813682368336843685368636873688368936903691369236933694369536963697369836993700370137023703370437053706370737083709371037113712371337143715371637173718371937203721372237233724372537263727372837293730373137323733373437353736373737383739374037413742374337443745374637473748374937503751375237533754375537563757375837593760376137623763376437653766376737683769377037713772377337743775377637773778377937803781378237833784378537863787378837893790379137923793379437953796379737983799380038013802380338043805380638073808380938103811381238133814381538163817381838193820382138223823382438253826382738283829383038313832383338343835383638373838383938403841384238433844384538463847384838493850385138523853385438553856385738583859386038613862386338643865386638673868386938703871387238733874387538763877387838793880388138823883388438853886388738883889389038913892389338943895389638973898389939003901390239033904390539063907390839093910391139123913391439153916391739183919392039213922392339243925392639273928392939303931393239333934393539363937393839393940394139423943394439453946394739483949395039513952395339543955395639573958395939603961396239633964396539663967396839693970397139723973397439753976397739783979398039813982398339843985398639873988398939903991399239933994399539963997399839994000400140024003400440054006400740084009401040114012401340144015401640174018401940204021402240234024402540264027402840294030403140324033403440354036403740384039404040414042404340444045404640474048404940504051405240534054405540564057405840594060406140624063406440654066406740684069407040714072407340744075407640774078407940804081408240834084408540864087408840894090409140924093409440954096409740984099410041014102410341044105410641074108410941104111411241134114411541164117411841194120412141224123412441254126412741284129413041314132413341344135413641374138413941404141414241434144414541464147414841494150415141524153415441554156415741584159416041614162416341644165416641674168416941704171417241734174417541764177417841794180418141824183418441854186418741884189419041914192419341944195419641974198419942004201420242034204420542064207420842094210421142124213421442154216421742184219422042214222422342244225422642274228422942304231423242334234423542364237423842394240424142424243424442454246424742484249425042514252425342544255425642574258425942604261426242634264426542664267426842694270427142724273427442754276427742784279428042814282428342844285428642874288428942904291429242934294429542964297429842994300430143024303430443054306430743084309431043114312431343144315431643174318431943204321432243234324432543264327432843294330433143324333433443354336433743384339434043414342434343444345434643474348434943504351435243534354435543564357435843594360436143624363436443654366436743684369437043714372437343744375437643774378437943804381438243834384438543864387438843894390439143924393439443954396439743984399440044014402440344044405440644074408440944104411441244134414441544164417441844194420442144224423442444254426442744284429443044314432443344344435443644374438443944404441444244434444444544464447444844494450445144524453445444554456445744584459446044614462446344644465446644674468446944704471447244734474447544764477447844794480448144824483448444854486448744884489449044914492449344944495449644974498449945004501450245034504450545064507450845094510451145124513451445154516451745184519452045214522452345244525452645274528452945304531453245334534453545364537453845394540454145424543454445454546454745484549455045514552455345544555455645574558455945604561456245634564456545664567456845694570457145724573457445754576457745784579458045814582458345844585458645874588458945904591459245934594459545964597459845994600460146024603460446054606460746084609461046114612461346144615461646174618461946204621462246234624462546264627462846294630463146324633463446354636463746384639464046414642464346444645464646474648464946504651465246534654465546564657465846594660466146624663466446654666466746684669467046714672467346744675467646774678467946804681468246834684468546864687468846894690469146924693469446954696469746984699470047014702470347044705470647074708470947104711471247134714471547164717471847194720472147224723472447254726472747284729473047314732473347344735473647374738473947404741474247434744474547464747474847494750475147524753475447554756475747584759476047614762476347644765476647674768476947704771477247734774477547764777477847794780478147824783478447854786478747884789479047914792479347944795479647974798479948004801480248034804480548064807480848094810481148124813481448154816481748184819482048214822482348244825482648274828482948304831483248334834483548364837483848394840484148424843484448454846484748484849485048514852485348544855485648574858485948604861486248634864486548664867486848694870487148724873487448754876487748784879488048814882488348844885488648874888488948904891489248934894489548964897489848994900490149024903490449054906490749084909491049114912491349144915491649174918491949204921492249234924492549264927492849294930493149324933493449354936493749384939494049414942494349444945494649474948494949504951495249534954495549564957495849594960496149624963496449654966496749684969497049714972497349744975497649774978497949804981498249834984498549864987498849894990499149924993499449954996499749984999500050015002500350045005500650075008500950105011501250135014501550165017501850195020502150225023502450255026502750285029503050315032503350345035503650375038503950405041504250435044504550465047504850495050505150525053505450555056505750585059506050615062506350645065506650675068506950705071507250735074507550765077507850795080508150825083508450855086508750885089509050915092509350945095509650975098509951005101510251035104510551065107510851095110511151125113511451155116511751185119512051215122512351245125512651275128512951305131513251335134513551365137513851395140514151425143514451455146514751485149515051515152515351545155515651575158515951605161516251635164516551665167516851695170517151725173517451755176517751785179518051815182518351845185518651875188518951905191519251935194519551965197519851995200520152025203520452055206520752085209521052115212521352145215521652175218521952205221522252235224522552265227522852295230523152325233523452355236523752385239524052415242524352445245524652475248524952505251525252535254525552565257525852595260526152625263526452655266526752685269527052715272527352745275527652775278527952805281528252835284528552865287528852895290529152925293529452955296529752985299530053015302530353045305530653075308530953105311531253135314531553165317531853195320532153225323532453255326532753285329533053315332533353345335533653375338533953405341534253435344534553465347534853495350535153525353535453555356535753585359536053615362536353645365536653675368536953705371537253735374537553765377537853795380538153825383538453855386538753885389539053915392539353945395539653975398539954005401540254035404540554065407540854095410541154125413541454155416541754185419542054215422542354245425542654275428542954305431543254335434543554365437543854395440544154425443544454455446544754485449545054515452545354545455545654575458545954605461546254635464546554665467546854695470547154725473547454755476547754785479548054815482548354845485548654875488548954905491549254935494549554965497549854995500550155025503550455055506550755085509551055115512551355145515551655175518551955205521552255235524552555265527552855295530553155325533553455355536553755385539554055415542554355445545554655475548554955505551555255535554555555565557555855595560556155625563556455655566556755685569557055715572557355745575557655775578557955805581558255835584558555865587558855895590559155925593559455955596559755985599560056015602560356045605560656075608560956105611561256135614561556165617561856195620562156225623562456255626562756285629563056315632563356345635563656375638563956405641564256435644564556465647564856495650565156525653565456555656565756585659566056615662566356645665566656675668566956705671567256735674567556765677567856795680568156825683568456855686568756885689569056915692569356945695569656975698569957005701570257035704570557065707570857095710571157125713571457155716571757185719572057215722572357245725572657275728572957305731573257335734573557365737573857395740574157425743574457455746574757485749575057515752575357545755575657575758575957605761576257635764576557665767576857695770577157725773577457755776577757785779578057815782578357845785578657875788578957905791579257935794579557965797579857995800580158025803580458055806580758085809581058115812581358145815581658175818581958205821582258235824582558265827582858295830583158325833583458355836583758385839584058415842584358445845584658475848584958505851585258535854585558565857585858595860586158625863586458655866586758685869587058715872587358745875587658775878587958805881588258835884588558865887588858895890589158925893589458955896589758985899590059015902590359045905590659075908590959105911591259135914591559165917591859195920592159225923592459255926592759285929593059315932593359345935593659375938593959405941594259435944594559465947594859495950595159525953595459555956595759585959596059615962596359645965596659675968596959705971597259735974597559765977597859795980598159825983598459855986598759885989599059915992599359945995599659975998599960006001600260036004600560066007600860096010601160126013601460156016601760186019602060216022602360246025602660276028602960306031603260336034603560366037603860396040604160426043604460456046604760486049605060516052605360546055605660576058605960606061606260636064606560666067606860696070607160726073607460756076607760786079608060816082608360846085608660876088608960906091609260936094609560966097609860996100610161026103610461056106610761086109611061116112611361146115611661176118611961206121612261236124612561266127612861296130613161326133613461356136613761386139614061416142614361446145614661476148614961506151615261536154615561566157615861596160616161626163616461656166616761686169617061716172617361746175617661776178617961806181618261836184618561866187618861896190619161926193619461956196619761986199620062016202620362046205620662076208620962106211621262136214621562166217621862196220622162226223622462256226622762286229623062316232623362346235623662376238623962406241624262436244624562466247624862496250625162526253625462556256625762586259626062616262626362646265626662676268626962706271627262736274627562766277627862796280628162826283628462856286628762886289629062916292629362946295629662976298629963006301630263036304630563066307630863096310631163126313631463156316631763186319632063216322632363246325632663276328632963306331633263336334633563366337633863396340634163426343634463456346634763486349635063516352635363546355635663576358635963606361636263636364636563666367636863696370637163726373637463756376637763786379638063816382638363846385638663876388638963906391639263936394639563966397639863996400640164026403640464056406640764086409641064116412641364146415641664176418641964206421642264236424642564266427642864296430643164326433643464356436643764386439644064416442644364446445644664476448644964506451645264536454645564566457645864596460646164626463646464656466646764686469647064716472647364746475647664776478647964806481648264836484648564866487648864896490649164926493649464956496649764986499650065016502650365046505650665076508650965106511651265136514651565166517651865196520652165226523652465256526652765286529653065316532653365346535653665376538653965406541654265436544654565466547654865496550655165526553655465556556655765586559656065616562656365646565656665676568656965706571657265736574657565766577657865796580658165826583658465856586658765886589659065916592659365946595659665976598659966006601660266036604660566066607660866096610661166126613661466156616661766186619662066216622662366246625662666276628
  1. [
  2. {
  3. "type": "_",
  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 configuration.",
  7. "link": "https://github.com/lutzroeder/netron/issues/458"
  8. },
  9. {
  10. "type": "_",
  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": "_",
  18. "target": "coreml_invalid_file.mlmodel",
  19. "source": "https://github.com/lutzroeder/netron/files/3219681/coreml_invalid_file.mlmodel.zip",
  20. "error": "Archive contains no model files in 'coreml_invalid_file.mlmodel'.",
  21. "format": "Core ML v1",
  22. "link": "https://github.com/lutzroeder/netron/issues/193"
  23. },
  24. {
  25. "type": "_",
  26. "target": "empty.zip",
  27. "source": "https://github.com/lutzroeder/netron/files/5581087/empty.zip",
  28. "error": "Archive contains no model files in 'empty.zip'.",
  29. "link": "https://github.com/lutzroeder/netron/issues/458"
  30. },
  31. {
  32. "type": "_",
  33. "target": "haarcascade_mcs_nose.xml",
  34. "source": "https://github.com/lutzroeder/netron/files/7403702/haarcascade_mcs_nose.xml.zip[haarcascade_mcs_nose.xml]",
  35. "error": "Invalid file content. File contains OpenCV storage data.",
  36. "link": "https://github.com/lutzroeder/netron/issues/458"
  37. },
  38. {
  39. "type": "_",
  40. "target": "imagenet_2012_challenge_label_map_proto.pbtxt",
  41. "source": "https://raw.githubusercontent.com/dmlc/web-data/master/tensorflow/models/InceptionV1/imagenet_2012_challenge_label_map_proto.pbtxt",
  42. "error": "Invalid file content. File contains ImageNet LabelMap data."
  43. },
  44. {
  45. "type": "_",
  46. "target": "keras_metadata.pb",
  47. "source": "https://github.com/lutzroeder/netron/files/6751650/keras_metadata.pb.zip[keras_metadata.pb]",
  48. "error": "The file 'saved_model.pb' does not exist in 'keras_metadata.pb'.",
  49. "link": "https://github.com/lutzroeder/netron/issues/458"
  50. },
  51. {
  52. "type": "_",
  53. "target": "knift_index.pb",
  54. "error": "Invalid file content. File contains mediapipe.BoxDetectorIndex data.",
  55. "source": "https://github.com/lutzroeder/netron/files/6308301/knift_index.pb.zip[knift_index.pb]"
  56. },
  57. {
  58. "type": "_",
  59. "target": "labelmap.pbtxt",
  60. "source": "https://github.com/lutzroeder/netron/files/5398649/labelmap.zip[labelmap.pbtxt]",
  61. "error": "Invalid file content. File contains StringIntLabelMapProto data.",
  62. "link": "https://github.com/lutzroeder/netron/issues/458"
  63. },
  64. {
  65. "type": "_",
  66. "target": "gzip_invalid_archive.tar.gz",
  67. "source": "https://github.com/lutzroeder/netron/files/5468427/gzip_invalid_archive.tar.gz",
  68. "error": "Unsupported file content (ff000000000000000000000000000000) for extension '.gz' in 'gzip_invalid_archive.tar.gz'.",
  69. "link": "https://github.com/lutzroeder/netron/issues/249"
  70. },
  71. {
  72. "type": "_",
  73. "target": "gzip_invalid_compression.tar.gz",
  74. "source": "https://github.com/lutzroeder/netron/files/3027193/gzip_invalid_compression.tar.gz",
  75. "error": "Invalid compression method '1' in 'gzip_invalid_compression.tar.gz'.",
  76. "link": "https://github.com/lutzroeder/netron/issues/249"
  77. },
  78. {
  79. "type": "_",
  80. "target": "invalid_git_lfs.mlmodel",
  81. "source": "https://github.com/lutzroeder/netron/files/4432767/invalid_git_lfs.mlmodel.zip[invalid_git_lfs.mlmodel]",
  82. "error": "Invalid file content. File contains Git LFS header.",
  83. "link": "https://github.com/lutzroeder/netron/issues/458"
  84. },
  85. {
  86. "type": "_",
  87. "target": "invalid_html.mlmodel.zip",
  88. "source": "https://github.com/lutzroeder/netron/files/4432768/invalid_html.mlmodel.zip",
  89. "error": "Invalid file content. File contains HTML markup.",
  90. "link": "https://github.com/lutzroeder/netron/issues/458"
  91. },
  92. {
  93. "type": "_",
  94. "target": "invalid_html.tflite",
  95. "source": "https://github.com/lutzroeder/netron/files/4432789/invalid_html.tflite.zip[invalid_html.tflite]",
  96. "error": "Invalid file content. File contains HTML markup.",
  97. "link": "https://github.com/lutzroeder/netron/issues/458"
  98. },
  99. {
  100. "type": "_",
  101. "target": "onnx-metadata.json",
  102. "source": "https://raw.githubusercontent.com/lutzroeder/netron/main/source/onnx-metadata.json",
  103. "error": "Invalid file content. File contains Netron metadata.",
  104. "link": "https://github.com/lutzroeder/netron/blob/main/source/onnx-metadata.json"
  105. },
  106. {
  107. "type": "_",
  108. "target": "ops.pbtxt",
  109. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/core/ops/ops.pbtxt",
  110. "error": "Invalid file content. File contains TensorFlow OpList data.",
  111. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/ops.pbtxt"
  112. },
  113. {
  114. "type": "_",
  115. "target": "random.onnx",
  116. "source": "https://github.com/lutzroeder/netron/files/7449479/random.onnx.zip[random.onnx]",
  117. "error": "Unsupported file content (746d6c20786d6c6e733d22687474703a) for extension '.onnx' in 'random.onnx'.",
  118. "link": "https://github.com/lutzroeder/netron/issues/458"
  119. },
  120. {
  121. "type": "_",
  122. "target": "spm_char.model",
  123. "source": "https://github.com/lutzroeder/netron/files/6611189/covost2_en_asr_vocab_char.zip[spm_char.model]",
  124. "error": "Invalid file content. File contains sentencepiece.ModelProto data.",
  125. "link": "https://github.com/lutzroeder/netron/issues/748"
  126. },
  127. {
  128. "type": "_",
  129. "target": "vk_swiftshader_icd.json",
  130. "source": "https://github.com/lutzroeder/netron/files/5398770/vk_swiftshader_icd.json.zip[vk_swiftshader_icd.json]",
  131. "error": "Invalid file content. File contains Vulkan SwiftShader ICD manifest.",
  132. "link": "https://github.com/lutzroeder/netron/issues/458"
  133. },
  134. {
  135. "type": "_",
  136. "target": "yolo-1c.meta",
  137. "source": "https://github.com/lutzroeder/netron/files/5398632/yolo-1c.meta.zip[yolo-1c.meta]",
  138. "error": "Invalid file content. File contains Darkflow metadata.",
  139. "link": "https://github.com/lutzroeder/netron/issues/458"
  140. },
  141. {
  142. "type": "_",
  143. "target": "universal_encoder_8k_spm.model.model",
  144. "source": "https://github.com/lutzroeder/netron/files/7232403/universal_encoder_8k_spm.model.zip[universal_encoder_8k_spm.model]",
  145. "error": "Invalid file content. File contains sentencepiece.ModelProto data.",
  146. "link": "https://github.com/lutzroeder/netron/issues/748"
  147. },
  148. {
  149. "type": "_",
  150. "target": "zip_invalid_archive.zip",
  151. "source": "https://github.com/lutzroeder/netron/files/5468425/zip_invalid_archive.zip",
  152. "error": "Unsupported file content (ff000000000000000000000000000000) for extension '.zip' in 'zip_invalid_archive.zip'.",
  153. "link": "https://github.com/lutzroeder/netron/issues/250"
  154. },
  155. {
  156. "type": "acuity",
  157. "target": "inception_v1.json",
  158. "source": "https://raw.githubusercontent.com/VeriSilicon/acuity-models/master/models/inception_v1/inception_v1.json",
  159. "link": "https://github.com/VeriSilicon/acuity-models"
  160. },
  161. {
  162. "type": "armnn",
  163. "target": "simple_network.armnn",
  164. "source": "https://github.com/lutzroeder/netron/files/4951689/simple_network.zip[simple_network.armnn]",
  165. "format": "Arm NN",
  166. "link": "https://github.com/lutzroeder/netron/issues/515"
  167. },
  168. {
  169. "type": "armnn",
  170. "target": "ssd_mobilenet_v1.armnn",
  171. "source": "https://raw.githubusercontent.com/ARM-software/armnn/master/samples/serialized/ssd_mobilenet_v1.armnn",
  172. "format": "Arm NN",
  173. "link": "https://github.com/ARM-software/armnn"
  174. },
  175. {
  176. "type": "armnn",
  177. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q8.armnn",
  178. "source": "https://github.com/lutzroeder/netron/files/3839429/samples.zip[ssd_mobilenet_v3_small_coco_2019_08_14_q8.armnn]",
  179. "format": "Arm NN",
  180. "link": "https://github.com/lutzroeder/netron/issues/515"
  181. },
  182. {
  183. "type": "armnn",
  184. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q8.json",
  185. "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]",
  186. "format": "Arm NN",
  187. "link": "https://github.com/lutzroeder/netron/issues/515"
  188. },
  189. {
  190. "type": "armnn",
  191. "target": "ssd_mobilenet_v3_small_coco_2019_08_14_q16.armnn",
  192. "source": "https://github.com/lutzroeder/netron/files/3839429/samples.zip[ssd_mobilenet_v3_small_coco_2019_08_14_q16.armnn]",
  193. "format": "Arm NN",
  194. "link": "https://github.com/lutzroeder/netron/issues/515"
  195. },
  196. {
  197. "type": "barracuda",
  198. "target": "3DBallHardLearning.nn",
  199. "source": "https://raw.githubusercontent.com/reinforcement-learning-kr/rl_bootcamp/master/UnitySDK/Assets/ML-Agents/Examples/3DBall/TFModels/3DBallHardLearning.nn",
  200. "format": "Barracuda v16",
  201. "link": "https://github.com/reinforcement-learning-kr/rl_bootcamp"
  202. },
  203. {
  204. "type": "barracuda",
  205. "target": "mobilenet_v2.nn",
  206. "source": "https://raw.githubusercontent.com/Syn-McJ/TFClassify-Unity-Barracuda/master/Assets/Resources/mobilenet_v2.nn",
  207. "format": "Barracuda v16",
  208. "link": "https://github.com/Syn-McJ/TFClassify-Unity-Barracuda"
  209. },
  210. {
  211. "type": "barracuda",
  212. "target": "HighQualityTrainedModel.nn",
  213. "source": "https://digital-standard.com/threedpose/models/HighQualityTrainedModel.nn",
  214. "format": "Barracuda v16",
  215. "link": "https://github.com/digista-tanaka/ThreeDPoseTracker"
  216. },
  217. {
  218. "type": "bigdl",
  219. "target": "analytics-zoo_squeezenet-quantize_imagenet_0.1.0.model",
  220. "source": "https://github.com/lutzroeder/netron/files/5891323/analytics-zoo_squeezenet-quantize_imagenet_0.1.0.model.zip[analytics-zoo_squeezenet-quantize_imagenet_0.1.0.model]",
  221. "format": "BigDL v0.5.0",
  222. "link": "https://github.com/lutzroeder/netron/issues/355"
  223. },
  224. {
  225. "type": "caffe",
  226. "target": "1D_lstm.prototxt",
  227. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/1D_lstm.prototxt",
  228. "format": "Caffe v2",
  229. "link": "https://github.com/cwlacewe/netscope"
  230. },
  231. {
  232. "type": "caffe",
  233. "target": "age_net.caffemodel",
  234. "source": "https://raw.githubusercontent.com/eveningglow/age-and-gender-classification/master/model/age_net.caffemodel",
  235. "format": "Caffe v1",
  236. "link": "https://github.com/eveningglow/age-and-gender-classification"
  237. },
  238. {
  239. "type": "caffe",
  240. "target": "alexnet.prototxt",
  241. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/alexnet.prototxt",
  242. "format": "Caffe v2",
  243. "link": "https://github.com/cwlacewe/netscope"
  244. },
  245. {
  246. "type": "caffe",
  247. "target": "AlexNet_SalObjSub_deploy.prototxt",
  248. "source": "https://raw.githubusercontent.com/natanielruiz/net-archive/master/salient-object-alexnet/deploy.prototxt",
  249. "format": "Caffe v1",
  250. "link": "https://github.com/natanielruiz/net-archive/tree/master/salient-object-alexnet"
  251. },
  252. {
  253. "type": "caffe",
  254. "target": "autocolorize.prototxt",
  255. "source": "https://github.com/lutzroeder/netron/files/4923194/autocolorize.zip[autocolorize.prototxt]",
  256. "format": "Caffe v2",
  257. "link": "https://github.com/lutzroeder/netron/issues/276"
  258. },
  259. {
  260. "type": "caffe",
  261. "target": "bvlc_alexnet.caffemodel",
  262. "source": "http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel",
  263. "format": "Caffe v1",
  264. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_alexnet"
  265. },
  266. {
  267. "type": "caffe",
  268. "target": "bvlc_caffenet_full_conv.prototxt",
  269. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/net_surgery/bvlc_caffenet_full_conv.prototxt",
  270. "format": "Caffe v2",
  271. "link": "https://github.com/BVLC/caffe/tree/master/examples/net_surgery"
  272. },
  273. {
  274. "type": "caffe",
  275. "target": "bvlc_alexnet_deploy.prototxt",
  276. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/models/bvlc_alexnet/deploy.prototxt",
  277. "format": "Caffe v2",
  278. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_alexnet"
  279. },
  280. {
  281. "type": "caffe",
  282. "target": "bvlc_googlenet.caffemodel",
  283. "source": "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel",
  284. "format": "Caffe v1",
  285. "link": "https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet"
  286. },
  287. {
  288. "type": "caffe",
  289. "target": "caffe_array.prototxt",
  290. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_array.prototxt]",
  291. "format": "Caffe v2",
  292. "link": "https://github.com/lutzroeder/netron/issues/276"
  293. },
  294. {
  295. "type": "caffe",
  296. "target": "caffe_invalid_file.caffemodel",
  297. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_invalid_file.caffemodel]",
  298. "error": "File format is not caffe.NetParameter (Invalid type 4 at offset 11) in 'caffe_invalid_file.caffemodel'.",
  299. "link": "https://github.com/lutzroeder/netron/issues/276"
  300. },
  301. {
  302. "type": "caffe",
  303. "target": "caffe_invalid_semicolon.prototxt",
  304. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_invalid_semicolon.prototxt]",
  305. "error": "File text format is not caffe.NetParameter (Unexpected token ';' at 7:18) in 'caffe_invalid_semicolon.prototxt'.",
  306. "link": "https://github.com/lutzroeder/netron/issues/276"
  307. },
  308. {
  309. "type": "caffe",
  310. "target": "caffe_semicolon.prototxt",
  311. "source": "https://github.com/lutzroeder/netron/files/3288816/caffe_examples.zip[caffe_semicolon.prototxt]",
  312. "format": "Caffe v2",
  313. "link": "https://github.com/lutzroeder/netron/issues/276"
  314. },
  315. {
  316. "type": "caffe",
  317. "target": "caffenet.prototxt",
  318. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/caffenet.prototxt",
  319. "format": "Caffe v2",
  320. "link": "https://github.com/cwlacewe/netscope"
  321. },
  322. {
  323. "type": "caffe",
  324. "target": "cifar10_full_sigmoid_solver_bn.prototxt,cifar10_full_sigmoid_train_test_bn.prototxt",
  325. "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",
  326. "format": "Caffe v2",
  327. "link": "https://github.com/BVLC/caffe/tree/master/examples/cifar10"
  328. },
  329. {
  330. "type": "caffe",
  331. "target": "cityscapes_713_pspnet.prototxt",
  332. "source": "https://github.com/lutzroeder/netron/files/6543206/cityscapes_713_pspnet.prototxt.zip[cityscapes_713_pspnet.prototxt]",
  333. "format": "Caffe v2",
  334. "link": "https://github.com/lutzroeder/netron/issues/276"
  335. },
  336. {
  337. "type": "caffe",
  338. "target": "conv.prototxt",
  339. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/net_surgery/conv.prototxt",
  340. "format": "Caffe v2",
  341. "link": "https://github.com/BVLC/caffe/tree/master/examples/net_surgery"
  342. },
  343. {
  344. "type": "caffe",
  345. "target": "deepyeast.caffemodel",
  346. "source": "https://kodu.ut.ee/~leopoldp/2016_DeepYeast/code/caffe_model/HOwt_png_vgg_A_bn_iter_130000.caffemodel",
  347. "format": "Caffe v2",
  348. "link": "https://github.com/BVLC/caffe/wiki/Model-Zoo#deepyeast"
  349. },
  350. {
  351. "type": "caffe",
  352. "target": "DenseNet_169.prototxt",
  353. "source": "https://raw.githubusercontent.com/shicai/DenseNet-Caffe/master/DenseNet_169.prototxt",
  354. "format": "Caffe v2",
  355. "link": "https://github.com/shicai/DenseNet-Caffe"
  356. },
  357. {
  358. "type": "caffe",
  359. "target": "deploy_iResNet_ROB.tpl.prototxt",
  360. "source": "https://raw.githubusercontent.com/leonzfa/iResNet/master/models/model/deploy_iResNet_ROB.tpl.prototxt",
  361. "error": "File text format is not caffe.NetParameter (Couldn't parse float '$SCALE_WIDTH' at 727:47) in 'deploy_iResNet_ROB.tpl.prototxt'.",
  362. "link": "https://github.com/leonzfa/iResNet"
  363. },
  364. {
  365. "type": "caffe",
  366. "target": "faster_rcnn_train_test_21cls.pt",
  367. "source": "https://raw.githubusercontent.com/sanghoon/pva-faster-rcnn/master/models/pvanet/pva9.1/faster_rcnn_train_test_21cls.pt",
  368. "format": "Caffe v2",
  369. "link": "https://github.com/sanghoon/pva-faster-rcnn"
  370. },
  371. {
  372. "type": "caffe",
  373. "target": "fasterRCNN_AlexNet.prototxt",
  374. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_AlexNet.prototxt",
  375. "format": "Caffe v2",
  376. "link": "https://github.com/cwlacewe/netscope"
  377. },
  378. {
  379. "type": "caffe",
  380. "target": "fasterRCNN_ResNet.prototxt",
  381. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_ResNet.prototxt",
  382. "format": "Caffe v2",
  383. "link": "https://github.com/cwlacewe/netscope"
  384. },
  385. {
  386. "type": "caffe",
  387. "target": "fasterRCNN_VGG.prototxt",
  388. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_VGG.prototxt",
  389. "format": "Caffe v2",
  390. "link": "https://github.com/cwlacewe/netscope"
  391. },
  392. {
  393. "type": "caffe",
  394. "target": "fasterRCNN_ZynqNet.prototxt",
  395. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fasterRCNN_ZynqNet.prototxt",
  396. "format": "Caffe v2",
  397. "link": "https://github.com/cwlacewe/netscope"
  398. },
  399. {
  400. "type": "caffe",
  401. "target": "fcn-16s.prototxt",
  402. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/fcn-16s.prototxt",
  403. "format": "Caffe v1",
  404. "link": "https://github.com/cwlacewe/netscope"
  405. },
  406. {
  407. "type": "caffe",
  408. "target": "fcn-8s-pascal-deploy.prototxt",
  409. "source": "https://raw.githubusercontent.com/HyeonwooNoh/DeconvNet/master/model/FCN/fcn-8s-pascal-deploy.prototxt",
  410. "format": "Caffe v1",
  411. "link": "https://github.com/HyeonwooNoh/DeconvNet"
  412. },
  413. {
  414. "type": "caffe",
  415. "target": "feat_ext_C3D_examples_imagenet_alexnet_train.prototxt",
  416. "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]",
  417. "format": "Caffe v1",
  418. "link": "https://github.com/lutzroeder/netron/issues/276"
  419. },
  420. {
  421. "type": "caffe",
  422. "target": "googlenet.prototxt",
  423. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/googlenet.prototxt",
  424. "format": "Caffe v2",
  425. "link": "https://github.com/cwlacewe/netscope"
  426. },
  427. {
  428. "type": "caffe",
  429. "target": "inceptionv3.prototxt",
  430. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv3.prototxt",
  431. "format": "Caffe v2",
  432. "link": "https://github.com/cwlacewe/netscope"
  433. },
  434. {
  435. "type": "caffe",
  436. "target": "inceptionv3_orig.prototxt",
  437. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv3_orig.prototxt",
  438. "format": "Caffe v2",
  439. "link": "https://github.com/cwlacewe/netscope"
  440. },
  441. {
  442. "type": "caffe",
  443. "target": "inceptionv4.prototxt",
  444. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4.prototxt",
  445. "format": "Caffe v2",
  446. "link": "https://github.com/cwlacewe/netscope"
  447. },
  448. {
  449. "type": "caffe",
  450. "target": "inceptionv4_resnet.prototxt",
  451. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4_resnet.prototxt",
  452. "format": "Caffe v2",
  453. "link": "https://github.com/cwlacewe/netscope"
  454. },
  455. {
  456. "type": "caffe",
  457. "target": "inceptionv4_resnet.prototxt",
  458. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/inceptionv4_resnet.prototxt",
  459. "format": "Caffe v2",
  460. "link": "https://github.com/cwlacewe/netscope"
  461. },
  462. {
  463. "type": "caffe",
  464. "target": "lenet_consolidated_solver.prototxt",
  465. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/mnist/lenet_consolidated_solver.prototxt",
  466. "format": "Caffe v1",
  467. "link": "https://github.com/BVLC/caffe/tree/master/examples/mnist"
  468. },
  469. {
  470. "type": "caffe",
  471. "target": "lenet.prototxt",
  472. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/mnist/lenet.prototxt",
  473. "format": "Caffe v2",
  474. "link": "https://github.com/BVLC/caffe/tree/master/examples/mnist"
  475. },
  476. {
  477. "type": "caffe",
  478. "target": "linreg.prototxt",
  479. "source": "https://raw.githubusercontent.com/BVLC/caffe/master/examples/pycaffe/linreg.prototxt",
  480. "format": "Caffe v2",
  481. "link": "https://github.com/BVLC/caffe/tree/master/examples/pycaffe"
  482. },
  483. {
  484. "type": "caffe",
  485. "target": "lstm.prototxt",
  486. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/lstm.prototxt",
  487. "format": "Caffe v2",
  488. "link": "https://github.com/cwlacewe/netscope"
  489. },
  490. {
  491. "type": "caffe",
  492. "target": "mobilenet.caffemodel",
  493. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet.caffemodel",
  494. "format": "Caffe v2",
  495. "link": "https://github.com/shicai/MobileNet-Caffe"
  496. },
  497. {
  498. "type": "caffe",
  499. "target": "mobilenet_deploy.prototxt",
  500. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_deploy.prototxt",
  501. "format": "Caffe v2",
  502. "link": "https://github.com/shicai/MobileNet-Caffe"
  503. },
  504. {
  505. "type": "caffe",
  506. "target": "mobilenet_yolov3_lite_train.prototxt",
  507. "source": "https://raw.githubusercontent.com/eric612/Caffe-YOLOv3-Windows/master/models/yolov3/mobilenet_yolov3_lite_train.prototxt",
  508. "format": "Caffe v2",
  509. "link": "https://github.com/eric612/Caffe-YOLOv3-Windows"
  510. },
  511. {
  512. "type": "caffe",
  513. "target": "mobilenet_yolov3_solver.prototxt,mobilenet_yolov3_train.prototxt",
  514. "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",
  515. "format": "Caffe v2",
  516. "link": "https://github.com/eric612/Caffe-YOLOv3-Windows"
  517. },
  518. {
  519. "type": "caffe",
  520. "target": "mobilenet_v2.caffemodel",
  521. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_v2.caffemodel",
  522. "format": "Caffe v2",
  523. "link": "https://github.com/shicai/MobileNet-Caffe"
  524. },
  525. {
  526. "type": "caffe",
  527. "target": "mobilenet_v2_deploy.prototxt",
  528. "source": "https://raw.githubusercontent.com/shicai/MobileNet-Caffe/master/mobilenet_v2_deploy.prototxt",
  529. "format": "Caffe v2",
  530. "link": "https://github.com/shicai/MobileNet-Caffe"
  531. },
  532. {
  533. "type": "caffe",
  534. "target": "MobileNetSSD_train.prototxt",
  535. "source": "https://github.com/lutzroeder/netron/files/3771164/MobileNetSSD_train.prototxt.txt",
  536. "format": "Caffe v2",
  537. "link": "https://github.com/lutzroeder/netron/issues/358"
  538. },
  539. {
  540. "type": "caffe",
  541. "target": "MobileNetSSD_train_template.prototxt",
  542. "source": "https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/master/template/MobileNetSSD_train_template.prototxt",
  543. "format": "Caffe v2",
  544. "link": "https://github.com/chuanqi305/MobileNet-SSD"
  545. },
  546. {
  547. "type": "caffe",
  548. "target": "mnist_siamese_solver.prototxt,mnist_siamese_train_test.prototxt",
  549. "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",
  550. "format": "Caffe v2",
  551. "link": "https://github.com/BVLC/caffe/tree/master/examples/siamese"
  552. },
  553. {
  554. "type": "caffe",
  555. "target": "netron_issue_306.prototxt",
  556. "source": "https://github.com/lutzroeder/netron/files/3440457/netron_issue_306.zip[netron_issue_306.pbtxt]",
  557. "format": "Caffe v2",
  558. "link": "https://github.com/lutzroeder/netron/issues/306"
  559. },
  560. {
  561. "type": "caffe",
  562. "target": "nin.prototxt",
  563. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/nin.prototxt",
  564. "format": "Caffe v1",
  565. "link": "https://github.com/cwlacewe/netscope"
  566. },
  567. {
  568. "type": "caffe",
  569. "target": "ORION_extended_trainval.prototxt",
  570. "source": "https://raw.githubusercontent.com/lmb-freiburg/orion/master/net_archs/modelnet10/ORION_extended_trainval.prototxt",
  571. "format": "Caffe v2",
  572. "link": "https://github.com/lmb-freiburg/orion"
  573. },
  574. {
  575. "type": "caffe",
  576. "target": "panoramic_object_detection_deploy_crop.prototxt.prototxt",
  577. "source": "https://raw.githubusercontent.com/gdlg/panoramic-object-detection/master/examples/inference/deploy_crop.prototxt",
  578. "format": "Caffe v2",
  579. "link": "https://github.com/gdlg/panoramic-object-detection/tree/master/examples/inference"
  580. },
  581. {
  582. "type": "caffe",
  583. "target": "ResNet-18-deploy.prototxt",
  584. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-18-deploy.prototxt",
  585. "format": "Caffe v2",
  586. "link": "https://github.com/cwlacewe/netscope"
  587. },
  588. {
  589. "type": "caffe",
  590. "target": "ResNet-34.prototxt",
  591. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-34.prototxt",
  592. "format": "Caffe v2",
  593. "link": "https://github.com/cwlacewe/netscope"
  594. },
  595. {
  596. "type": "caffe",
  597. "target": "resnet-50.prototxt",
  598. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/resnet-50.prototxt",
  599. "format": "Caffe v2",
  600. "link": "https://github.com/cwlacewe/netscope"
  601. },
  602. {
  603. "type": "caffe",
  604. "target": "ResNet-50-deploy.prototxt",
  605. "source": "https://deepdetect.com/models/resnet/ResNet-50-deploy.prototxt",
  606. "format": "Caffe v2",
  607. "link": "https://deepdetect.com/models/resnet/"
  608. },
  609. {
  610. "type": "caffe",
  611. "target": "ResNet-50_merged.qconv.winograd.cwl.prototxt",
  612. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/ResNet-50_merged.qconv.winograd.cwl.prototxt",
  613. "link": "https://github.com/cwlacewe/netscope"
  614. },
  615. {
  616. "type": "caffe",
  617. "target": "ResNet-152-deploy.prototxt",
  618. "source": "https://deepdetect.com/models/resnet/ResNet-152-deploy.prototxt",
  619. "format": "Caffe v2",
  620. "link": "https://deepdetect.com/models/resnet/"
  621. },
  622. {
  623. "type": "caffe",
  624. "target": "resnet-152.prototxt",
  625. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/resnet-152.prototxt",
  626. "format": "Caffe v2",
  627. "link": "https://github.com/cwlacewe/netscope"
  628. },
  629. {
  630. "type": "caffe",
  631. "target": "seq2seq_train_ep7_tar.prototxt",
  632. "source": "https://raw.githubusercontent.com/jasjeetIM/Seq2Seq/master/models/s2s/train_ep7_tar.prototxt",
  633. "format": "Caffe v2",
  634. "link": "https://github.com/jasjeetIM/Seq2Seq"
  635. },
  636. {
  637. "type": "caffe",
  638. "target": "se_resnet_50_v1_deploy.prototxt",
  639. "source": "https://raw.githubusercontent.com/shicai/SENet-Caffe/master/se_resnet_50_v1_deploy.prototxt",
  640. "format": "Caffe v2",
  641. "link": "https://github.com/shicai/SENet-Caffe"
  642. },
  643. {
  644. "type": "caffe",
  645. "target": "segnet_basic_inference.prototxt",
  646. "source": "https://raw.githubusercontent.com/alexgkendall/SegNet-Tutorial/master/Models/segnet_basic_inference.prototxt",
  647. "format": "Caffe v2",
  648. "link": "https://github.com/alexgkendall/SegNet-Tutorial"
  649. },
  650. {
  651. "type": "caffe",
  652. "target": "shufflenet_1x_g3_train.prototxt",
  653. "source": "https://raw.githubusercontent.com/Ewenwan/ShuffleNet-2/master/shufflenet_1x_g3_train.prototxt",
  654. "format": "Caffe v2",
  655. "link": "https://github.com/Ewenwan/ShuffleNet-2"
  656. },
  657. {
  658. "type": "caffe",
  659. "target": "squeezenet_v1.1.caffemodel",
  660. "source": "https://raw.githubusercontent.com/DeepScale/SqueezeNet/master/SqueezeNet_v1.1/squeezenet_v1.1.caffemodel",
  661. "format": "Caffe v2",
  662. "link": "https://github.com/DeepScale/SqueezeNet"
  663. },
  664. {
  665. "type": "caffe",
  666. "target": "sq11b2a_e3.prototxt",
  667. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/sq11b2a_e3.prototxt",
  668. "format": "Caffe v2",
  669. "link": "https://github.com/cwlacewe/netscope"
  670. },
  671. {
  672. "type": "caffe",
  673. "target": "squeezenet.prototxt",
  674. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/squeezenet.prototxt",
  675. "format": "Caffe v2",
  676. "link": "https://github.com/cwlacewe/netscope"
  677. },
  678. {
  679. "type": "caffe",
  680. "target": "squeezenet_v11.prototxt",
  681. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/squeezenet_v11.prototxt",
  682. "format": "Caffe v2",
  683. "link": "https://github.com/cwlacewe/netscope"
  684. },
  685. {
  686. "type": "caffe",
  687. "target": "ssd_16nodes_512_batch_train.prototxt",
  688. "source": "https://raw.githubusercontent.com/intel/caffe/master/models/intel_optimized_models/multinode/ssd_16nodes_512_batch/train.prototxt",
  689. "format": "Caffe v2",
  690. "link": "https://github.com/intel/caffe"
  691. },
  692. {
  693. "type": "caffe",
  694. "target": "SSD300.prototxt",
  695. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/SSD300.prototxt",
  696. "format": "Caffe v2",
  697. "link": "https://github.com/cwlacewe/netscope"
  698. },
  699. {
  700. "type": "caffe",
  701. "target": "tsn_bn_inception_flow_deploy.prototxt",
  702. "source": "https://raw.githubusercontent.com/yjxiong/temporal-segment-networks/master/models/hmdb51/tsn_bn_inception_flow_deploy.prototxt",
  703. "format": "Caffe v2",
  704. "link": "https://github.com/yjxiong/temporal-segment-networks"
  705. },
  706. {
  707. "type": "caffe",
  708. "target": "vanillaCNN.caffemodel",
  709. "source": "https://raw.githubusercontent.com/ishay2b/VanillaCNN/master/ZOO/vanillaCNN.caffemodel",
  710. "format": "Caffe v2",
  711. "link": "https://gist.github.com/ishay2b/58248e5f3c3bf575ac40"
  712. },
  713. {
  714. "type": "caffe",
  715. "target": "vgg-16.prototxt",
  716. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/vgg-16.prototxt",
  717. "format": "Caffe v1",
  718. "link": "https://github.com/cwlacewe/netscope"
  719. },
  720. {
  721. "type": "caffe",
  722. "target": "VGG_CNN_M_2048_deploy.prototxt",
  723. "source": "https://raw.githubusercontent.com/natanielruiz/net-archive/master/vgg_cnn_m_2048/VGG_CNN_M_2048_deploy.prototxt",
  724. "format": "Caffe v1",
  725. "link": "https://github.com/natanielruiz/net-archive"
  726. },
  727. {
  728. "type": "caffe",
  729. "target": "VGG_VOC0712Plus_SSD_300x300_ft_deploy.prototxt",
  730. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/VGG_VOC0712Plus_SSD_300x300_ft_deploy.prototxt",
  731. "format": "Caffe v2",
  732. "link": "https://github.com/cwlacewe/netscope"
  733. },
  734. {
  735. "type": "caffe",
  736. "target": "YOLO.prototxt",
  737. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/YOLO.prototxt",
  738. "format": "Caffe v2",
  739. "link": "https://github.com/cwlacewe/netscope"
  740. },
  741. {
  742. "type": "caffe",
  743. "target": "yolov3_gen.prototext.txt",
  744. "source": "https://github.com/lutzroeder/netron/files/5615031/yolov3_gen.prototext.txt.zip[yolov3_gen.prototext.txt]",
  745. "format": "Caffe v2",
  746. "link": "https://github.com/lutzroeder/netron/issues/276"
  747. },
  748. {
  749. "type": "caffe",
  750. "target": "yolov3-tiny.prototxt",
  751. "source": "https://raw.githubusercontent.com/eric612/MobileNet-YOLO/master/models/darknet_yolov3/yolov3-tiny.prototxt",
  752. "format": "Caffe v2",
  753. "link": "https://github.com/eric612/MobileNet-YOLO/tree/master/models/darknet_yolov3"
  754. },
  755. {
  756. "type": "caffe",
  757. "target": "yolov3-spp.prototxt",
  758. "source": "https://raw.githubusercontent.com/eric612/MobileNet-YOLO/master/models/darknet_yolov3/yolov3-spp.prototxt",
  759. "format": "Caffe v2",
  760. "link": "https://github.com/eric612/MobileNet-YOLO/tree/master/models/darknet_yolov3"
  761. },
  762. {
  763. "type": "caffe",
  764. "target": "zynqnet.prototxt",
  765. "source": "https://raw.githubusercontent.com/cwlacewe/netscope/master/presets/zynqnet.prototxt",
  766. "format": "Caffe v2",
  767. "link": "https://github.com/cwlacewe/netscope"
  768. },
  769. {
  770. "type": "caffe2",
  771. "target": "bvlc_alexnet/predict_net.pb,bvlc_alexnet/init_net.pb",
  772. "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",
  773. "format": "Caffe2",
  774. "link": "https://github.com/caffe2/models"
  775. },
  776. {
  777. "type": "caffe2",
  778. "target": "bvlc_alexnet/init_net.pb",
  779. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/bvlc_alexnet/init_net.pb",
  780. "format": "Caffe2",
  781. "link": "https://github.com/caffe2/models"
  782. },
  783. {
  784. "type": "caffe2",
  785. "target": "bvlc_alexnet/predict_net.pbtxt,bvlc_alexnet/init_net.pb",
  786. "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",
  787. "format": "Caffe2",
  788. "link": "https://github.com/caffe2/models"
  789. },
  790. {
  791. "type": "caffe2",
  792. "target": "bvlc_googlenet/predict_net.pb,bvlc_googlenet/init_net.pb",
  793. "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",
  794. "format": "Caffe2",
  795. "link": "https://github.com/caffe2/models"
  796. },
  797. {
  798. "type": "caffe2",
  799. "target": "densenet121/predict_net.pb,densenet121/init_net.pb",
  800. "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",
  801. "format": "Caffe2",
  802. "link": "https://github.com/caffe2/models"
  803. },
  804. {
  805. "type": "caffe2",
  806. "target": "FBNet-A-int8/model.pbtxt,FBNet-A-int8/model_init.pb",
  807. "source": "https://dl.fbaipublicfiles.com/fbnet/models/FBNet_caffe2.zip[FBNet/FBNet-A/int8/model.pbtxt,FBNet/FBNet-A/int8/model_init.pb]",
  808. "format": "Caffe2",
  809. "link": "https://github.com/facebookresearch/mobile-vision"
  810. },
  811. {
  812. "type": "caffe2",
  813. "target": "generalized_rcnn/net.pbtxt",
  814. "source": "https://github.com/lutzroeder/netron/files/2801714/net.pbtxt.txt",
  815. "format": "Caffe2",
  816. "action": "skip-render",
  817. "link": "https://github.com/lutzroeder/netron/issues/223"
  818. },
  819. {
  820. "type": "caffe2",
  821. "target": "generalized_rcnn/predict_net.pbtxt",
  822. "source": "https://github.com/lutzroeder/netron/files/2802044/predict_net.pbtxt.txt",
  823. "format": "Caffe2",
  824. "link": "https://github.com/lutzroeder/netron/issues/223"
  825. },
  826. {
  827. "type": "caffe2",
  828. "target": "inception_v2/predict_net.pb,inception_v2/init_net.pb",
  829. "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",
  830. "format": "Caffe2",
  831. "link": "https://github.com/caffe2/models"
  832. },
  833. {
  834. "type": "caffe2",
  835. "target": "lenet/predict_net.pbtxt,lenet/init_net.pbtxt",
  836. "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",
  837. "format": "Caffe2",
  838. "link": "https://github.com/jolibrain/deepdetect/tree/master/templates/caffe2"
  839. },
  840. {
  841. "type": "caffe2",
  842. "target": "mask_rcnn_2go/model.pbtxt",
  843. "source": "https://raw.githubusercontent.com/caffe2/models/master/mask_rcnn_2go/model/fp32/model.pbtxt",
  844. "format": "Caffe2",
  845. "link": "https://github.com/lutzroeder/netron/issues/168"
  846. },
  847. {
  848. "type": "caffe2",
  849. "target": "mobilenet_v2/predict_net.pb,mobilenet_v2/init_net.pb",
  850. "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",
  851. "format": "Caffe2",
  852. "link": "https://github.com/caffe2/models"
  853. },
  854. {
  855. "type": "caffe2",
  856. "target": "mobilenet_v2/predict_net.pb",
  857. "source": "https://s3.amazonaws.com/download.caffe2.ai/models/mobilenet_v2/predict_net.pb",
  858. "format": "Caffe2",
  859. "link": "https://github.com/caffe2/models"
  860. },
  861. {
  862. "type": "caffe2",
  863. "target": "mobilenet_v2_quantized/predict_net.pb,mobilenet_v2_quantized/init_net.pb",
  864. "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",
  865. "format": "Caffe2",
  866. "link": "https://github.com/caffe2/models"
  867. },
  868. {
  869. "type": "caffe2",
  870. "target": "resnet50_quantized/resnet50_quantized_predict_net.pb,resnet50_quantized/resnet50_quantized_init_net.pb",
  871. "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",
  872. "format": "Caffe2",
  873. "link": "https://github.com/caffe2/models/tree/master/resnet50_quantized"
  874. },
  875. {
  876. "type": "caffe2",
  877. "target": "onnx_while/predict_net.pb,onnx_while/inits_net.pb",
  878. "source": "https://github.com/lutzroeder/netron/files/2522635/onnxwhile.zip[predict_net.pb,init_net.pb]",
  879. "format": "Caffe2",
  880. "link": "https://github.com/lutzroeder/netron/issues/168"
  881. },
  882. {
  883. "type": "caffe2",
  884. "target": "resnet50/predict_net.pb,resnet50/init_net.pb",
  885. "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",
  886. "format": "Caffe2",
  887. "link": "https://github.com/caffe2/models"
  888. },
  889. {
  890. "type": "caffe2",
  891. "target": "squeezenet/squeezenet.pb,squeezenet/init_net.pb",
  892. "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",
  893. "format": "Caffe2",
  894. "link": "https://github.com/caffe2/models"
  895. },
  896. {
  897. "type": "circle",
  898. "target": "ArgMax_001.circle",
  899. "source": "https://github.com/lutzroeder/netron/files/7489768/circle_model_samples.zip[ArgMax_001.circle]",
  900. "format": "Circle v0",
  901. "link": "https://github.com/lutzroeder/netron/issues/790"
  902. },
  903. {
  904. "type": "circle",
  905. "target": "FullyConnected_002.circle",
  906. "source": "https://github.com/lutzroeder/netron/files/7489768/circle_model_samples.zip[FullyConnected_002.circle]",
  907. "format": "Circle v0",
  908. "link": "https://github.com/lutzroeder/netron/issues/790"
  909. },
  910. {
  911. "type": "cntk",
  912. "target": "01_OneHidden.dnn",
  913. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tests/UnitTests/NetworkTests/Models/01_OneHidden.dnn",
  914. "format": "CNTK v1.18",
  915. "link": "https://github.com/Microsoft/CNTK"
  916. },
  917. {
  918. "type": "cntk",
  919. "target": "cifar10.pretrained.cmf",
  920. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/ImageHandsOn/cifar10.pretrained.cmf",
  921. "format": "CNTK v1.14",
  922. "link": "https://github.com/Microsoft/CNTK"
  923. },
  924. {
  925. "type": "cntk",
  926. "target": "cifar10.ResNet.cmf",
  927. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/ImageHandsOn/cifar10.ResNet.cmf",
  928. "format": "CNTK v1.10",
  929. "link": "https://github.com/Microsoft/CNTK"
  930. },
  931. {
  932. "type": "cntk",
  933. "target": "cntkSpeechFF.dnn",
  934. "source": "https://github.com/lutzroeder/netron/files/3243442/cntkSpeechFF.dnn.zip[cntkSpeechFF.dnn]",
  935. "format": "CNTK v1.31",
  936. "link": "https://github.com/lutzroeder/netron/issues/153"
  937. },
  938. {
  939. "type": "cntk",
  940. "target": "ResNet_18.model",
  941. "source": "https://www.cntk.ai/Models/ResNet/ResNet_18.model",
  942. "format": "CNTK v1.17"
  943. },
  944. {
  945. "type": "cntk",
  946. "target": "ResNet20_CIFAR10_DataAug.dnn",
  947. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tests/UnitTests/NetworkTests/Models/ResNet20_CIFAR10_DataAug.dnn",
  948. "format": "CNTK v1.18",
  949. "link": "https://github.com/Microsoft/CNTK"
  950. },
  951. {
  952. "type": "cntk",
  953. "target": "slu.forward.backward.cmf",
  954. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.backward.cmf",
  955. "format": "CNTK v1.14",
  956. "link": "https://github.com/Microsoft/CNTK"
  957. },
  958. {
  959. "type": "cntk",
  960. "target": "slu.forward.cmf",
  961. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.cmf",
  962. "format": "CNTK v1.14",
  963. "link": "https://github.com/Microsoft/CNTK"
  964. },
  965. {
  966. "type": "cntk",
  967. "target": "slu.forward.nobn.cmf",
  968. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.nobn.cmf",
  969. "format": "CNTK v1.14",
  970. "link": "https://github.com/Microsoft/CNTK"
  971. },
  972. {
  973. "type": "cntk",
  974. "target": "slu.forward.lookahead.cmf",
  975. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/Tutorials/SLUHandsOn/slu.forward.lookahead.cmf",
  976. "format": "CNTK v1.14",
  977. "link": "https://github.com/Microsoft/CNTK"
  978. },
  979. {
  980. "type": "cntk",
  981. "target": "Bean.cntk",
  982. "source": "https://media.githubusercontent.com/media/Microsoft/ELL-models/master/models/ILSVRC2012/Bean/Bean.cntk.zip[Bean.cntk]",
  983. "format": "CNTK v2",
  984. "link": "https://github.com/Microsoft/ELL-models"
  985. },
  986. {
  987. "type": "cntk",
  988. "target": "BNInception_ImageNet_Caffe.model",
  989. "source": "https://www.cntk.ai/Models/Caffe_Converted/BNInception_ImageNet_Caffe.model",
  990. "format": "CNTK v2",
  991. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/download_model.py"
  992. },
  993. {
  994. "type": "cntk",
  995. "target": "d_I160x160x3CMCMCMCMCMCMC1AS.model",
  996. "source": "https://media.githubusercontent.com/media/Microsoft/ELL-models/master/models/ILSVRC2012/d_I160x160x3CMCMCMCMCMCMC1AS/d_I160x160x3CMCMCMCMCMCMC1AS.cntk.zip[d_I160x160x3CMCMCMCMCMCMC1AS.cntk]",
  997. "format": "CNTK v2",
  998. "link": "https://github.com/Microsoft/ELL-models/tree/master/models/ILSVRC2012/d_I160x160x3CMCMCMCMCMCMC1AS"
  999. },
  1000. {
  1001. "type": "cntk",
  1002. "target": "DRNN.model",
  1003. "source": "https://www.cntk.ai/Models/SuperResolution/DRNN.model",
  1004. "format": "CNTK v2",
  1005. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1006. },
  1007. {
  1008. "type": "cntk",
  1009. "target": "initial_policy_network.dnn",
  1010. "source": "https://raw.githubusercontent.com/Microsoft/CNTK/master/bindings/python/cntk/contrib/deeprl/tests/data/initial_policy_network.dnn",
  1011. "format": "CNTK v2",
  1012. "link": "https://github.com/Microsoft/CNTK"
  1013. },
  1014. {
  1015. "type": "cntk",
  1016. "target": "InceptionV3_ImageNet_CNTK.model",
  1017. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/InceptionV3_ImageNet_CNTK.model",
  1018. "format": "CNTK v2",
  1019. "link": "https://github.com/Microsoft/MMdnn/blob/master/mmdnn/conversion/examples/cntk/extract_model.py"
  1020. },
  1021. {
  1022. "type": "cntk",
  1023. "target": "ResNet18_ImageNet_CNTK.model",
  1024. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet18_ImageNet_CNTK.model",
  1025. "format": "CNTK v2",
  1026. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1027. },
  1028. {
  1029. "type": "cntk",
  1030. "target": "ResNet20_CIFAR10_CNTK.model",
  1031. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet20_CIFAR10_CNTK.model",
  1032. "format": "CNTK v2",
  1033. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1034. },
  1035. {
  1036. "type": "cntk",
  1037. "target": "ResNet110_CIFAR10_CNTK.model",
  1038. "source": "https://www.cntk.ai/Models/CNTK_Pretrained/ResNet110_CIFAR10_CNTK.model",
  1039. "format": "CNTK v2",
  1040. "link": "https://github.com/Microsoft/CNTK/blob/master/PretrainedModels/Image.md"
  1041. },
  1042. {
  1043. "type": "cntk",
  1044. "target": "SRGAN.model",
  1045. "source": "https://www.cntk.ai/Models/SuperResolution/SRGAN.model",
  1046. "format": "CNTK v2",
  1047. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1048. },
  1049. {
  1050. "type": "cntk",
  1051. "target": "tutorial_103b_mnist.model",
  1052. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103b_mnist.model]",
  1053. "format": "CNTK v2",
  1054. "link": "https://github.com/lutzroeder/netron/issues/153"
  1055. },
  1056. {
  1057. "type": "cntk",
  1058. "target": "tutorial_103c_mnist.model",
  1059. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103c_mnist.model]",
  1060. "format": "CNTK v2",
  1061. "link": "https://github.com/lutzroeder/netron/issues/153"
  1062. },
  1063. {
  1064. "type": "cntk",
  1065. "target": "tutorial_103d_mnist.model",
  1066. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_103d_mnist.model]",
  1067. "format": "CNTK v2",
  1068. "link": "https://github.com/lutzroeder/netron/issues/153"
  1069. },
  1070. {
  1071. "type": "cntk",
  1072. "target": "tutorial_106a_lstm.model",
  1073. "source": "https://github.com/lutzroeder/netron/files/2591620/tutorial_models.zip[tutorial_106a_lstm.model]",
  1074. "format": "CNTK v2",
  1075. "link": "https://github.com/lutzroeder/netron/issues/153"
  1076. },
  1077. {
  1078. "type": "cntk",
  1079. "target": "VDSR.model",
  1080. "source": "https://www.cntk.ai/Models/SuperResolution/VDSR.model",
  1081. "format": "CNTK v2",
  1082. "link": "https://cntk.ai/pythondocs/CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.html"
  1083. },
  1084. {
  1085. "type": "coreml",
  1086. "target": "BERTSQUADFP16.mlmodel",
  1087. "source": "https://docs-assets.developer.apple.com/coreml/models/Text/QuestionAnswering/BERT_SQUAD/BERTSQUADFP16.mlmodel",
  1088. "format": "Core ML v4",
  1089. "link": "https://developer.apple.com/machine-learning/models"
  1090. },
  1091. {
  1092. "type": "coreml",
  1093. "target": "DocumentClassification.mlmodel",
  1094. "source": "https://raw.githubusercontent.com/toddkramer/DocumentClassifier/master/Sources/DocumentClassification.mlmodel",
  1095. "format": "Core ML v1",
  1096. "link": "https://github.com/toddkramer/DocumentClassifier"
  1097. },
  1098. {
  1099. "type": "coreml",
  1100. "target": "DeepLabV3.pb",
  1101. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageSegmentation/DeepLabV3/DeepLabV3.mlmodel",
  1102. "format": "Core ML v3",
  1103. "link": "https://developer.apple.com/machine-learning/models"
  1104. },
  1105. {
  1106. "type": "coreml",
  1107. "target": "EfficientNetB0.mlpackage,EfficientNetB0.mlpackage/Manifest.json,EfficientNetB0.mlpackage/Data/com.apple.CoreML/model.mlmodel,EfficientNetB0.mlpackage/Data/com.apple.CoreML/weights/weight.bin",
  1108. "source": "https://github.com/lutzroeder/netron/files/6636195/EfficientNetB0.mlpackage.zip[.,EfficientNetB0.mlpackage/Manifest.json,EfficientNetB0.mlpackage/Data/com.apple.CoreML/model.mlmodel,EfficientNetB0.mlpackage/Data/com.apple.CoreML/weights/weight.bin]",
  1109. "format": "Core ML Package v6",
  1110. "link": "https://github.com/lutzroeder/netron/issues/751"
  1111. },
  1112. {
  1113. "type": "coreml",
  1114. "target": "EfficientNetB0.mlpackage.zip",
  1115. "source": "https://github.com/lutzroeder/netron/files/6636195/EfficientNetB0.mlpackage.zip",
  1116. "format": "Core ML Package v6",
  1117. "link": "https://github.com/lutzroeder/netron/issues/751"
  1118. },
  1119. {
  1120. "type": "coreml",
  1121. "target": "EnvSceneClassification.mlmodel",
  1122. "source": "https://raw.githubusercontent.com/anujdutt9/iOS-Audio-Classification/cdf5b72dc351a83168369d0afbd0eeba9ecae448/RealTimeSoundClassifier/RealTimeSoundClassifier/EnvSceneClassification.mlmodel",
  1123. "format": "Core ML v3",
  1124. "link": "https://github.com/anujdutt9/iOS-Audio-Classification"
  1125. },
  1126. {
  1127. "type": "coreml",
  1128. "target": "Exermote.mlmodel",
  1129. "source": "https://raw.githubusercontent.com/Lausbert/Exermote/master/ExermoteInference/ExermoteCoreML/ExermoteCoreML/Model/Exermote.mlmodel",
  1130. "format": "Core ML v1"
  1131. },
  1132. {
  1133. "type": "coreml",
  1134. "target": "faces_model.mlmodel",
  1135. "source": "https://github.com/NovaTecConsulting/FaceRecognition-in-ARKit/files/1526806/faces_model.mlmodel.zip[faces_model.mlmodel]",
  1136. "format": "Core ML v1",
  1137. "link": "https://github.com/NovaTecConsulting/FaceRecognition-in-ARKit/issues/3"
  1138. },
  1139. {
  1140. "type": "coreml",
  1141. "target": "float16.mlmodel",
  1142. "source": "https://github.com/lutzroeder/netron/files/2382815/model.zip[model.mlmodel]",
  1143. "format": "Core ML v2",
  1144. "link": "https://github.com/lutzroeder/netron/issues/149"
  1145. },
  1146. {
  1147. "type": "coreml",
  1148. "target": "FNS-Candy.mlmodel",
  1149. "source": "https://raw.githubusercontent.com/ileafsolutions/StyleArt/master/StyleArt/CoreMLModels/FNS-Candy.mlmodel",
  1150. "link": "https://github.com/ileafsolutions/StyleArt"
  1151. },
  1152. {
  1153. "type": "coreml",
  1154. "target": "food.mlmodel",
  1155. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food.mlmodel",
  1156. "format": "Core ML v1",
  1157. "link": "https://github.com/kingreza/quantization"
  1158. },
  1159. {
  1160. "type": "coreml",
  1161. "target": "food_kmeans_1.mlmodel",
  1162. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_1.mlmodel",
  1163. "format": "Core ML v3",
  1164. "link": "https://github.com/kingreza/quantization"
  1165. },
  1166. {
  1167. "type": "coreml",
  1168. "target": "food_kmeans_2.mlmodel",
  1169. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_2.mlmodel",
  1170. "format": "Core ML v3",
  1171. "link": "https://github.com/kingreza/quantization"
  1172. },
  1173. {
  1174. "type": "coreml",
  1175. "target": "food_kmeans_3.mlmodel",
  1176. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_3.mlmodel",
  1177. "format": "Core ML v3",
  1178. "link": "https://github.com/kingreza/quantization"
  1179. },
  1180. {
  1181. "type": "coreml",
  1182. "target": "food_kmeans_4.mlmodel",
  1183. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_4.mlmodel",
  1184. "format": "Core ML v3",
  1185. "link": "https://github.com/kingreza/quantization"
  1186. },
  1187. {
  1188. "type": "coreml",
  1189. "target": "food_kmeans_5.mlmodel",
  1190. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_5.mlmodel",
  1191. "format": "Core ML v3",
  1192. "link": "https://github.com/kingreza/quantization"
  1193. },
  1194. {
  1195. "type": "coreml",
  1196. "target": "food_kmeans_6.mlmodel",
  1197. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_6.mlmodel",
  1198. "format": "Core ML v3",
  1199. "link": "https://github.com/kingreza/quantization"
  1200. },
  1201. {
  1202. "type": "coreml",
  1203. "target": "food_kmeans_7.mlmodel",
  1204. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_7.mlmodel",
  1205. "format": "Core ML v3",
  1206. "link": "https://github.com/kingreza/quantization"
  1207. },
  1208. {
  1209. "type": "coreml",
  1210. "target": "food_kmeans_8.mlmodel",
  1211. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_8.mlmodel",
  1212. "format": "Core ML v3",
  1213. "link": "https://github.com/kingreza/quantization"
  1214. },
  1215. {
  1216. "type": "coreml",
  1217. "target": "food_kmeans_16.mlmodel",
  1218. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_kmeans_16.mlmodel",
  1219. "format": "Core ML v2",
  1220. "link": "https://github.com/kingreza/quantization"
  1221. },
  1222. {
  1223. "type": "coreml",
  1224. "target": "food_linear_1.mlmodel",
  1225. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_1.mlmodel",
  1226. "format": "Core ML v3",
  1227. "link": "https://github.com/kingreza/quantization"
  1228. },
  1229. {
  1230. "type": "coreml",
  1231. "target": "food_linear_2.mlmodel",
  1232. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_2.mlmodel",
  1233. "format": "Core ML v3",
  1234. "link": "https://github.com/kingreza/quantization"
  1235. },
  1236. {
  1237. "type": "coreml",
  1238. "target": "food_linear_3.mlmodel",
  1239. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_3.mlmodel",
  1240. "format": "Core ML v3",
  1241. "link": "https://github.com/kingreza/quantization"
  1242. },
  1243. {
  1244. "type": "coreml",
  1245. "target": "food_linear_4.mlmodel",
  1246. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_4.mlmodel",
  1247. "format": "Core ML v3",
  1248. "link": "https://github.com/kingreza/quantization"
  1249. },
  1250. {
  1251. "type": "coreml",
  1252. "target": "food_linear_5.mlmodel",
  1253. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_5.mlmodel",
  1254. "format": "Core ML v3",
  1255. "link": "https://github.com/kingreza/quantization"
  1256. },
  1257. {
  1258. "type": "coreml",
  1259. "target": "food_linear_6.mlmodel",
  1260. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_6.mlmodel",
  1261. "format": "Core ML v3",
  1262. "link": "https://github.com/kingreza/quantization"
  1263. },
  1264. {
  1265. "type": "coreml",
  1266. "target": "food_linear_7.mlmodel",
  1267. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_7.mlmodel",
  1268. "format": "Core ML v3",
  1269. "link": "https://github.com/kingreza/quantization"
  1270. },
  1271. {
  1272. "type": "coreml",
  1273. "target": "food_linear_8.mlmodel",
  1274. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_8.mlmodel",
  1275. "format": "Core ML v3",
  1276. "link": "https://github.com/kingreza/quantization"
  1277. },
  1278. {
  1279. "type": "coreml",
  1280. "target": "food_linear_16.mlmodel",
  1281. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_16.mlmodel",
  1282. "format": "Core ML v2",
  1283. "link": "https://github.com/kingreza/quantization"
  1284. },
  1285. {
  1286. "type": "coreml",
  1287. "target": "food_linear_lut_1.mlmodel",
  1288. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_1.mlmodel",
  1289. "format": "Core ML v3",
  1290. "link": "https://github.com/kingreza/quantization"
  1291. },
  1292. {
  1293. "type": "coreml",
  1294. "target": "food_linear_lut_2.mlmodel",
  1295. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_2.mlmodel",
  1296. "format": "Core ML v3",
  1297. "link": "https://github.com/kingreza/quantization"
  1298. },
  1299. {
  1300. "type": "coreml",
  1301. "target": "food_linear_lut_3.mlmodel",
  1302. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_3.mlmodel",
  1303. "format": "Core ML v3",
  1304. "link": "https://github.com/kingreza/quantization"
  1305. },
  1306. {
  1307. "type": "coreml",
  1308. "target": "food_linear_lut_4.mlmodel",
  1309. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_4.mlmodel",
  1310. "format": "Core ML v3",
  1311. "link": "https://github.com/kingreza/quantization"
  1312. },
  1313. {
  1314. "type": "coreml",
  1315. "target": "food_linear_lut_5.mlmodel",
  1316. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_5.mlmodel",
  1317. "format": "Core ML v3",
  1318. "link": "https://github.com/kingreza/quantization"
  1319. },
  1320. {
  1321. "type": "coreml",
  1322. "target": "food_linear_lut_6.mlmodel",
  1323. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_6.mlmodel",
  1324. "format": "Core ML v3",
  1325. "link": "https://github.com/kingreza/quantization"
  1326. },
  1327. {
  1328. "type": "coreml",
  1329. "target": "food_linear_lut_7.mlmodel",
  1330. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_7.mlmodel",
  1331. "format": "Core ML v3",
  1332. "link": "https://github.com/kingreza/quantization"
  1333. },
  1334. {
  1335. "type": "coreml",
  1336. "target": "food_linear_lut_8.mlmodel",
  1337. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_8.mlmodel",
  1338. "format": "Core ML v3",
  1339. "link": "https://github.com/kingreza/quantization"
  1340. },
  1341. {
  1342. "type": "coreml",
  1343. "target": "food_linear_lut_16.mlmodel",
  1344. "source": "https://raw.githubusercontent.com/kingreza/quantization/master/food_linear_lut_16.mlmodel",
  1345. "format": "Core ML v2",
  1346. "link": "https://github.com/kingreza/quantization"
  1347. },
  1348. {
  1349. "type": "coreml",
  1350. "target": "GoogLeNetPlaces.mlmodel",
  1351. "source": "https://docs-assets.developer.apple.com/coreml/models/GoogLeNetPlaces.mlmodel"
  1352. },
  1353. {
  1354. "type": "coreml",
  1355. "target": "HED_so.mlmodel",
  1356. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_so.mlmodel",
  1357. "link": "https://github.com/s1ddok/HED-CoreML"
  1358. },
  1359. {
  1360. "type": "coreml",
  1361. "target": "HED_so3.mlmodel",
  1362. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_so3.mlmodel",
  1363. "link": "https://github.com/s1ddok/HED-CoreML"
  1364. },
  1365. {
  1366. "type": "coreml",
  1367. "target": "HED_fuse.mlmodel",
  1368. "source": "https://raw.githubusercontent.com/s1ddok/HED-CoreML/master/HED-CoreML/Models/HED_fuse.mlmodel",
  1369. "link": "https://github.com/s1ddok/HED-CoreML"
  1370. },
  1371. {
  1372. "type": "coreml",
  1373. "target": "imdb_lstm.mlmodel",
  1374. "source": "https://github.com/lutzroeder/netron/files/2591614/imdb_lstm.mlmodel.zip[imdb_lstm.mlmodel]",
  1375. "format": "Core ML v1",
  1376. "link": "https://github.com/lutzroeder/netron/issues/149"
  1377. },
  1378. {
  1379. "type": "coreml",
  1380. "target": "imdb_bidirectional_lstm.mlmodel",
  1381. "source": "https://github.com/lutzroeder/netron/files/2591615/imdb_bidirectional_lstm.mlmodel.zip[imdb_bidirectional_lstm.mlmodel]",
  1382. "format": "Core ML v1",
  1383. "link": "https://github.com/lutzroeder/netron/issues/149"
  1384. },
  1385. {
  1386. "type": "coreml",
  1387. "target": "Inceptionv3.mlmodel",
  1388. "source": "https://docs-assets.developer.apple.com/coreml/models/Inceptionv3.mlmodel"
  1389. },
  1390. {
  1391. "type": "coreml",
  1392. "target": "iris.mlmodel",
  1393. "source": "https://raw.githubusercontent.com/gavi/Iris/master/Iris/iris.mlmodel",
  1394. "format": "Core ML v1",
  1395. "link": "https://github.com/gavi/Iris"
  1396. },
  1397. {
  1398. "type": "coreml",
  1399. "target": "LinkedUpdatableTinyDrawingClassifier.mlmodel",
  1400. "source": "https://github.com/lutzroeder/netron/files/4500539/LinkedUpdatableTinyDrawingClassifier.zip[LinkedUpdatableTinyDrawingClassifier.mlmodel]",
  1401. "format": "Core ML v4",
  1402. "link": "https://github.com/lutzroeder/netron/issues/193"
  1403. },
  1404. {
  1405. "type": "coreml",
  1406. "target": "lstm_model.mlpackage.zip",
  1407. "source": "https://github.com/lutzroeder/netron/files/7406821/lstm_model.mlpackage.zip",
  1408. "format": "Core ML Package v6",
  1409. "link": "https://github.com/lutzroeder/netron/issues/832"
  1410. },
  1411. {
  1412. "type": "coreml",
  1413. "target": "MessageClassifier.mlmodel",
  1414. "source": "https://raw.githubusercontent.com/llSourcell/A_guide_to_coreML/master/MessageClassifier.mlmodel",
  1415. "link": "https://github.com/llSourcell/A_guide_to_coreML"
  1416. },
  1417. {
  1418. "type": "coreml",
  1419. "target": "MNIST.mlmodel",
  1420. "source": "https://github.com/ph1ps/MNIST-CoreML/raw/master/MNISTPrediction/MNIST.mlmodel",
  1421. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1422. },
  1423. {
  1424. "type": "coreml",
  1425. "target": "MNISTClassifier.mlmodel",
  1426. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/DrawingClassification/MNISTClassifier/MNISTClassifier.mlmodel",
  1427. "format": "Core ML v1",
  1428. "link": "https://developer.apple.com/machine-learning/models"
  1429. },
  1430. {
  1431. "type": "coreml",
  1432. "target": "MobileNet.mlmodel",
  1433. "source": "https://docs-assets.developer.apple.com/coreml/models/MobileNet.mlmodel"
  1434. },
  1435. {
  1436. "type": "coreml",
  1437. "target": "mobilenet_v2_1.4_224.mlmodel",
  1438. "source": "https://github.com/tf-coreml/tf-coreml/files/2575260/mobilenet_v2_1.4_224.mlmodel.zip[mobilenet_v2_1.4_224.mlmodel]",
  1439. "format": "Core ML v1",
  1440. "link": "https://github.com/tf-coreml/tf-coreml/issues/252"
  1441. },
  1442. {
  1443. "type": "coreml",
  1444. "target": "mobilenet_v2_not_working_netron.mlpackage.zip",
  1445. "source": "https://github.com/lutzroeder/netron/files/7197761/mobilenet_v2_not_working_netron.mlpackage.zip",
  1446. "format": "Core ML Package v6",
  1447. "link": "https://github.com/lutzroeder/netron/issues/812"
  1448. },
  1449. {
  1450. "type": "coreml",
  1451. "target": "MovieRecommender.mlmodel",
  1452. "source": "https://raw.githubusercontent.com/anupamchugh/iowncode/master/CoreMLRecommender/CoreMLRecommender/MovieRecommender.mlmodel",
  1453. "format": "Core ML v4",
  1454. "link": "https://github.com/anupamchugh/iowncode/tree/master/CoreMLRecommender"
  1455. },
  1456. {
  1457. "type": "coreml",
  1458. "target": "NamesDT.mlmodel",
  1459. "source": "https://github.com/cocoa-ai/NamesCoreMLDemo/raw/master/Names/Resources/NamesDT.mlmodel",
  1460. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1461. },
  1462. {
  1463. "type": "coreml",
  1464. "target": "onehot_simple.mlmodel",
  1465. "source": "https://raw.githubusercontent.com/onnx/onnxmltools/master/tests/data/onehot_simple.mlmodel",
  1466. "link": "https://github.com/onnx/onnxmltools/tree/master/tests/data"
  1467. },
  1468. {
  1469. "type": "coreml",
  1470. "target": "PoseEstimationForMobile.mlmodel",
  1471. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.mlmodel",
  1472. "format": "Core ML v1",
  1473. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  1474. },
  1475. {
  1476. "type": "coreml",
  1477. "target": "ProductTagger.mlmodel",
  1478. "source": "https://raw.githubusercontent.com/aidev1065/CustomEntityRecognition/master/ProductTagger.mlmodel",
  1479. "format": "Core ML v3",
  1480. "link": "https://github.com/aidev1065/CustomEntityRecognition"
  1481. },
  1482. {
  1483. "type": "coreml",
  1484. "target": "ProgrammingLanguageClassifier.mlmodel",
  1485. "source": "https://raw.githubusercontent.com/Flight-School/Programming-Language-Classifier/master/ProgrammingLanguageClassifier.mlmodel",
  1486. "format": "Core ML v3",
  1487. "link": "https://github.com/Flight-School/Programming-Language-Classifier"
  1488. },
  1489. {
  1490. "type": "coreml",
  1491. "target": "ReadTheRoom.mlmodel",
  1492. "source": "https://raw.githubusercontent.com/CapTechMobile/blogfest-coreml/d8e8c15d33e9591c9e81cb18e5ea4b2fb6972503/ReadTheRoom/ReadTheRoom.mlmodel",
  1493. "format": "Core ML v4",
  1494. "link": "https://github.com/CapTechMobile/blogfest-coreml"
  1495. },
  1496. {
  1497. "type": "coreml",
  1498. "target": "Resnet50.mlmodel",
  1499. "source": "https://docs-assets.developer.apple.com/coreml/models/Resnet50.mlmodel"
  1500. },
  1501. {
  1502. "type": "coreml",
  1503. "target": "SentimentPolarity.mlmodel",
  1504. "source": "https://github.com/cocoa-ai/SentimentCoreMLDemo/raw/master/SentimentPolarity/Resources/SentimentPolarity.mlmodel",
  1505. "link": "https://github.com/SwiftBrain/awesome-CoreML-models"
  1506. },
  1507. {
  1508. "type": "coreml",
  1509. "target": "sentiment_model.mlmodel",
  1510. "source": "https://github.com/lutzroeder/netron/files/2591618/sentiment_model.mlmodel.zip[sentiment_model.mlmodel]",
  1511. "format": "Core ML v1",
  1512. "link": "https://github.com/lutzroeder/netron/issues/149"
  1513. },
  1514. {
  1515. "type": "coreml",
  1516. "target": "SqueezeNet.mlmodel",
  1517. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNet.mlmodel",
  1518. "format": "Core ML v1",
  1519. "link": "https://developer.apple.com/machine-learning/models"
  1520. },
  1521. {
  1522. "type": "coreml",
  1523. "target": "SqueezeNetFP16.mlmodel",
  1524. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNetFP16.mlmodel",
  1525. "format": "Core ML v2",
  1526. "link": "https://developer.apple.com/machine-learning/models"
  1527. },
  1528. {
  1529. "type": "coreml",
  1530. "target": "SqueezeNetInt8LUT.mlmodel",
  1531. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ImageClassification/SqueezeNet/SqueezeNetInt8LUT.mlmodel",
  1532. "format": "Core ML v3",
  1533. "link": "https://developer.apple.com/machine-learning/models"
  1534. },
  1535. {
  1536. "type": "coreml",
  1537. "target": "test_categorical_imputer.mlmodel",
  1538. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_categorical_imputer.mlmodel]",
  1539. "format": "Core ML v1",
  1540. "link": "https://github.com/lutzroeder/netron/issues/193"
  1541. },
  1542. {
  1543. "type": "coreml",
  1544. "target": "test_keras_embedding_model.mlmodel",
  1545. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_keras_embedding_model.mlmodel]",
  1546. "format": "Core ML v1",
  1547. "link": "https://github.com/lutzroeder/netron/issues/193"
  1548. },
  1549. {
  1550. "type": "coreml",
  1551. "target": "test_linear_regressor.mlmodel",
  1552. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_linear_regressor.mlmodel]",
  1553. "format": "Core ML v1",
  1554. "link": "https://github.com/lutzroeder/netron/issues/193"
  1555. },
  1556. {
  1557. "type": "coreml",
  1558. "target": "test_normalizer_boston.mlmodel",
  1559. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_normalizer_boston.mlmodel]",
  1560. "format": "Core ML v1",
  1561. "link": "https://github.com/lutzroeder/netron/issues/193"
  1562. },
  1563. {
  1564. "type": "coreml",
  1565. "target": "test_normalizer_random.mlmodel",
  1566. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_normalizer_random.mlmodel]",
  1567. "format": "Core ML v1",
  1568. "link": "https://github.com/lutzroeder/netron/issues/193"
  1569. },
  1570. {
  1571. "type": "coreml",
  1572. "target": "test_one_hot_encoder_many_columns.mlmodel",
  1573. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_many_columns.mlmodel]",
  1574. "format": "Core ML v1",
  1575. "link": "https://github.com/lutzroeder/netron/issues/193"
  1576. },
  1577. {
  1578. "type": "coreml",
  1579. "target": "test_one_hot_encoder_one_column_of_several.mlmodel",
  1580. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_one_column_of_several.mlmodel]",
  1581. "format": "Core ML v1",
  1582. "link": "https://github.com/lutzroeder/netron/issues/193"
  1583. },
  1584. {
  1585. "type": "coreml",
  1586. "target": "test_one_hot_encoder_pipeline.mlmodel",
  1587. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_one_hot_encoder_pipeline.mlmodel]",
  1588. "format": "Core ML v1",
  1589. "link": "https://github.com/lutzroeder/netron/issues/193"
  1590. },
  1591. {
  1592. "type": "coreml",
  1593. "target": "test_random_forest_classifier.mlmodel",
  1594. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_random_forest_classifier.mlmodel]",
  1595. "format": "Core ML v1",
  1596. "link": "https://github.com/lutzroeder/netron/issues/193"
  1597. },
  1598. {
  1599. "type": "coreml",
  1600. "target": "test_random_forest_regressor.mlmodel",
  1601. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_random_forest_regressor.mlmodel]",
  1602. "format": "Core ML v1",
  1603. "link": "https://github.com/lutzroeder/netron/issues/193"
  1604. },
  1605. {
  1606. "type": "coreml",
  1607. "target": "test_support_vector_classifier.mlmodel",
  1608. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_support_vector_classifier.mlmodel]",
  1609. "format": "Core ML v1",
  1610. "link": "https://github.com/lutzroeder/netron/issues/193"
  1611. },
  1612. {
  1613. "type": "coreml",
  1614. "target": "test_support_vector_regressor.mlmodel",
  1615. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_support_vector_regressor.mlmodel]",
  1616. "format": "Core ML v1",
  1617. "link": "https://github.com/lutzroeder/netron/issues/193"
  1618. },
  1619. {
  1620. "type": "coreml",
  1621. "target": "test_tree_regressor.mlmodel",
  1622. "source": "https://github.com/lutzroeder/netron/files/3268269/coreml_models.zip[test_tree_regressor.mlmodel]",
  1623. "format": "Core ML v1",
  1624. "link": "https://github.com/lutzroeder/netron/issues/193"
  1625. },
  1626. {
  1627. "type": "coreml",
  1628. "target": "UpdatableKNN.mlmodel",
  1629. "source": "https://github.com/lutzroeder/netron/files/3424578/UpdatableKNN.zip[UpdatableKNN.mlmodel]",
  1630. "format": "Core ML v4",
  1631. "link": "https://github.com/lutzroeder/netron/issues/193"
  1632. },
  1633. {
  1634. "type": "coreml",
  1635. "target": "UpdatableMNISTDigitClassifier.mlmodel",
  1636. "source": "https://github.com/lutzroeder/netron/files/3424579/UpdatableMNISTDigitClassifier.zip[UpdatableMNISTDigitClassifier.mlmodel]",
  1637. "format": "Core ML v1",
  1638. "link": "https://github.com/lutzroeder/netron/issues/193"
  1639. },
  1640. {
  1641. "type": "coreml",
  1642. "target": "wave.mlmodel",
  1643. "source": "https://raw.githubusercontent.com/UnusualWolf/coreML/master/StyleArt-master/StyleArt/CoreMLModels/wave.mlmodel",
  1644. "format": "Core ML v1",
  1645. "link": "https://github.com/UnusualWolf/coreML"
  1646. },
  1647. {
  1648. "type": "coreml",
  1649. "target": "YOLOv3Tiny.mlmodel",
  1650. "source": "https://docs-assets.developer.apple.com/coreml/models/Image/ObjectDetection/YOLOv3Tiny/YOLOv3Tiny.mlmodel",
  1651. "format": "Core ML v3",
  1652. "link": "https://developer.apple.com/machine-learning/models"
  1653. },
  1654. {
  1655. "type": "darknet",
  1656. "target": "alexnet.cfg",
  1657. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/alexnet.cfg",
  1658. "format": "Darknet",
  1659. "link": "https://pjreddie.com/darknet/imagenet"
  1660. },
  1661. {
  1662. "type": "darknet",
  1663. "target": "csresnext50-panet-spp.cfg",
  1664. "source": "https://raw.githubusercontent.com/WongKinYiu/CrossStagePartialNetworks/master/cfg/csresnext50-panet-spp.cfg",
  1665. "format": "Darknet",
  1666. "link": "https://github.com/lutzroeder/netron/issues/381"
  1667. },
  1668. {
  1669. "type": "darknet",
  1670. "target": "darknet_invalid_file.cfg",
  1671. "source": "https://github.com/lutzroeder/netron/files/3219696/darknet_invalid_file.cfg.zip[darknet_invalid_file.cfg]",
  1672. "error": "Invalid cfg 'xxxx' at line 4 in 'darknet_invalid_file.cfg'.",
  1673. "link": "https://github.com/lutzroeder/netron/issues/277"
  1674. },
  1675. {
  1676. "type": "darknet",
  1677. "target": "darknet53_448.weights,darknet53_448.cfg",
  1678. "source": "https://pjreddie.com/media/files/darknet53_448.weights,https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/darknet53_448.cfg",
  1679. "format": "Darknet",
  1680. "link": "https://pjreddie.com/darknet/imagenet"
  1681. },
  1682. {
  1683. "type": "darknet",
  1684. "target": "enet-coco.model",
  1685. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/enet-coco.cfg",
  1686. "format": "Darknet",
  1687. "link": "https://github.com/lutzroeder/netron/issues/381"
  1688. },
  1689. {
  1690. "type": "darknet",
  1691. "target": "face_small_3.cfg",
  1692. "source": "https://raw.githubusercontent.com/zlmo/Face-Detection/master/cfg/face_small_3.cfg",
  1693. "format": "Darknet",
  1694. "link": "https://github.com/zlmo/Face-Detection"
  1695. },
  1696. {
  1697. "type": "darknet",
  1698. "target": "Gaussian_yolov3_BDD.cfg",
  1699. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/Gaussian_yolov3_BDD.cfg",
  1700. "format": "Darknet",
  1701. "link": "https://github.com/AlexeyAB/darknet"
  1702. },
  1703. {
  1704. "type": "darknet",
  1705. "target": "go.cfg,go.weights",
  1706. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/go.cfg,https://pjreddie.com/media/files/go.weights",
  1707. "format": "Darknet",
  1708. "link": "https://pjreddie.com/darknet/darkgo-go-in-darknet"
  1709. },
  1710. {
  1711. "type": "darknet",
  1712. "target": "grrm.cfg,grrm.weights",
  1713. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/rnn.cfg,https://pjreddie.com/media/files/grrm.weights",
  1714. "format": "Darknet",
  1715. "link": "https://pjreddie.com/darknet/rnns-in-darknet"
  1716. },
  1717. {
  1718. "type": "darknet",
  1719. "target": "gru.cfg",
  1720. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/gru.cfg",
  1721. "format": "Darknet",
  1722. "link": "https://pjreddie.com/darknet"
  1723. },
  1724. {
  1725. "type": "darknet",
  1726. "target": "jnet-conv.cfg,jnet-conv.weights",
  1727. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/jnet-conv.cfg,https://pjreddie.com/media/files/jnet-conv.weights",
  1728. "format": "Darknet",
  1729. "link": "https://pjreddie.com/darknet/nightmare"
  1730. },
  1731. {
  1732. "type": "darknet",
  1733. "target": "lstm.train.cfg",
  1734. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/lstm.train.cfg",
  1735. "format": "Darknet",
  1736. "link": "https://github.com/AlexeyAB/darknet"
  1737. },
  1738. {
  1739. "type": "darknet",
  1740. "target": "mixnet_m_gpu.cfg",
  1741. "source": "https://github.com/lutzroeder/netron/files/3935529/mixnet_m_gpu.cfg.txt",
  1742. "format": "Darknet",
  1743. "link": "https://github.com/lutzroeder/netron/issues/381"
  1744. },
  1745. {
  1746. "type": "darknet",
  1747. "target": "netron_issue_539_1.cfg",
  1748. "source": "https://github.com/lutzroeder/netron/files/5048435/netron_issue_539_1.zip[netron_issue_539_1.cfg]",
  1749. "format": "Darknet",
  1750. "link": "https://github.com/lutzroeder/netron/issues/539"
  1751. },
  1752. {
  1753. "type": "darknet",
  1754. "target": "netron_issue_539_2.cfg",
  1755. "source": "https://github.com/lutzroeder/netron/files/5048436/netron_issue_539_2.zip[netron_issue_539_2.cfg]",
  1756. "format": "Darknet",
  1757. "link": "https://github.com/lutzroeder/netron/issues/539"
  1758. },
  1759. {
  1760. "type": "darknet",
  1761. "target": "netron_issue_539_3.cfg",
  1762. "source": "https://github.com/lutzroeder/netron/files/5612917/netron_issue_539_3.zip[netron_issue_539_3.cfg]",
  1763. "format": "Darknet",
  1764. "link": "https://github.com/lutzroeder/netron/issues/539"
  1765. },
  1766. {
  1767. "type": "darknet",
  1768. "target": "netron_issue_541.cfg",
  1769. "source": "https://github.com/lutzroeder/netron/files/4968181/netron_issue_541.zip[netron_issue_541.cfg]",
  1770. "format": "Darknet",
  1771. "link": "https://github.com/lutzroeder/netron/issues/541"
  1772. },
  1773. {
  1774. "type": "darknet",
  1775. "target": "netron_issue_569.cfg",
  1776. "source": "https://github.com/lutzroeder/netron/files/5025566/netron_issue_569.zip[netron_issue_569.cfg]",
  1777. "format": "Darknet",
  1778. "link": "https://github.com/lutzroeder/netron/issues/569"
  1779. },
  1780. {
  1781. "type": "darknet",
  1782. "target": "resnet18.cfg,resnet18.weights",
  1783. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/resnet18.cfg,https://pjreddie.com/media/files/resnet18.weights",
  1784. "format": "Darknet",
  1785. "link": "https://pjreddie.com/darknet/imagenet"
  1786. },
  1787. {
  1788. "type": "darknet",
  1789. "target": "tiny.cfg,tiny.weights",
  1790. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/tiny.cfg,https://pjreddie.com/media/files/tiny.weights",
  1791. "format": "Darknet",
  1792. "link": "https://pjreddie.com/darknet/tiny-darknet"
  1793. },
  1794. {
  1795. "type": "darknet",
  1796. "target": "vgg_bn_ssd300.cfg",
  1797. "source": "https://github.com/lutzroeder/netron/files/5287397/vgg_bn_ssd300.cfg.zip[vgg_bn_ssd300.cfg]",
  1798. "error": "Unexpected '[convolutional]' section. First section must be [net] or [network] in 'vgg_bn_ssd300.cfg'.",
  1799. "link": "https://github.com/lutzroeder/netron/issues/277"
  1800. },
  1801. {
  1802. "type": "darknet",
  1803. "target": "xyolo.test.cfg",
  1804. "source": "https://github.com/lutzroeder/netron/files/6026689/xyolo.test.cfg.zip[xyolo.test.cfg]",
  1805. "format": "Darknet",
  1806. "link": "https://github.com/lutzroeder/netron/issues/277"
  1807. },
  1808. {
  1809. "type": "darknet",
  1810. "target": "yolo-coco.cfg",
  1811. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov1/yolo-coco.cfg",
  1812. "format": "Darknet",
  1813. "link": "https://github.com/AlexeyAB/darknet"
  1814. },
  1815. {
  1816. "type": "darknet",
  1817. "target": "yolo-voc.cfg",
  1818. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo-voc.cfg",
  1819. "format": "Darknet",
  1820. "link": "https://github.com/AlexeyAB/darknet"
  1821. },
  1822. {
  1823. "type": "darknet",
  1824. "target": "yolo.cfg",
  1825. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo.cfg",
  1826. "format": "Darknet",
  1827. "link": "https://github.com/AlexeyAB/darknet"
  1828. },
  1829. {
  1830. "type": "darknet",
  1831. "target": "yolo_v3_tiny_pan3_aa_ae_mixup_scale_giou.cfg",
  1832. "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]",
  1833. "format": "Darknet",
  1834. "link": "https://github.com/lutzroeder/netron/issues/277"
  1835. },
  1836. {
  1837. "type": "darknet",
  1838. "target": "yolo_v3_tiny_lstm.cfg",
  1839. "source": "https://github.com/lutzroeder/netron/files/4999065/yolo_v3_tiny_lstm.zip[yolo_v3_tiny_lstm.cfg]",
  1840. "format": "Darknet",
  1841. "link": "https://github.com/lutzroeder/netron/issues/562"
  1842. },
  1843. {
  1844. "type": "darknet",
  1845. "target": "yolov3-tiny.cfg,yolov3-tiny.weights",
  1846. "source": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3-tiny.cfg,https://pjreddie.com/media/files/yolov3-tiny.weights",
  1847. "format": "Darknet",
  1848. "link": "https://github.com/AlexeyAB/darknet"
  1849. },
  1850. {
  1851. "type": "darknet",
  1852. "target": "yolov3-tiny_default.cfg.txt",
  1853. "source": "https://github.com/lutzroeder/netron/files/5615015/yolov3-tiny_default.cfg.txt.zip[yolov3-tiny_default.cfg.txt]",
  1854. "format": "Darknet",
  1855. "link": "https://github.com/lutzroeder/netron/issues/277"
  1856. },
  1857. {
  1858. "type": "darknet",
  1859. "target": "yolov3-tiny_3l_shortcut_multilayer_per_feature_softmax.cfg",
  1860. "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]",
  1861. "format": "Darknet",
  1862. "link": "https://github.com/lutzroeder/netron/issues/410"
  1863. },
  1864. {
  1865. "type": "darknet",
  1866. "target": "yolov3_1088x608.cfg",
  1867. "source": "https://github.com/lutzroeder/netron/files/4391007/yolov3_1088x608.cfg.zip[yolov3_1088x608.cfg]",
  1868. "format": "Darknet",
  1869. "link": "https://github.com/lutzroeder/netron/issues/277"
  1870. },
  1871. {
  1872. "type": "darknet",
  1873. "target": "yolov4-tiny.cfg,yolov4-tiny.weights",
  1874. "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",
  1875. "format": "Darknet",
  1876. "link": "https://github.com/lutzroeder/netron/issues/531"
  1877. },
  1878. {
  1879. "type": "darknet",
  1880. "target": "yolo9000.cfg",
  1881. "source": "https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolo9000.cfg",
  1882. "format": "Darknet",
  1883. "link": "https://github.com/AlexeyAB/darknet"
  1884. },
  1885. {
  1886. "type": "darknet",
  1887. "target": "yolor_p6.cfg",
  1888. "source": "https://github.com/lutzroeder/netron/files/6767257/yolor_p6.cfg.zip[yolor_p6.cfg]",
  1889. "format": "Darknet",
  1890. "link": "https://github.com/lutzroeder/netron/issues/765"
  1891. },
  1892. {
  1893. "type": "dl4j",
  1894. "target": "lenet_dl4j_mnist_inference.zip",
  1895. "source": "https://dl4jdata.blob.core.windows.net/models/lenet_dl4j_mnist_inference.zip",
  1896. "format": "Deeplearning4j",
  1897. "link": "https://github.com/eclipse/deeplearning4j"
  1898. },
  1899. {
  1900. "type": "dl4j",
  1901. "target": "nasnetmobile_dl4j_inference.v1.zip",
  1902. "source": "https://dl4jdata.blob.core.windows.net/models/nasnetmobile_dl4j_inference.v1.zip",
  1903. "format": "Deeplearning4j",
  1904. "link": "https://github.com/eclipse/deeplearning4j"
  1905. },
  1906. {
  1907. "type": "dl4j",
  1908. "target": "squeezenet_dl4j_inference.v2.zip",
  1909. "source": "https://dl4jdata.blob.core.windows.net/models/squeezenet_dl4j_inference.v2.zip",
  1910. "format": "Deeplearning4j",
  1911. "link": "https://github.com/eclipse/deeplearning4j"
  1912. },
  1913. {
  1914. "type": "dl4j",
  1915. "target": "tiny-yolo-voc_dl4j_inference.v2.zip",
  1916. "source": "https://dl4jdata.blob.core.windows.net/models/tiny-yolo-voc_dl4j_inference.v2.zip",
  1917. "format": "Deeplearning4j",
  1918. "link": "https://github.com/eclipse/deeplearning4j"
  1919. },
  1920. {
  1921. "type": "dl4j",
  1922. "target": "unet_dl4j_segment_inference.v1.zip",
  1923. "source": "https://dl4jdata.blob.core.windows.net/models/unet_dl4j_segment_inference.v1.zip",
  1924. "format": "Deeplearning4j",
  1925. "link": "https://github.com/eclipse/deeplearning4j"
  1926. },
  1927. {
  1928. "type": "dl4j",
  1929. "target": "xception_dl4j_inference.v2.zip",
  1930. "source": "https://dl4jdata.blob.core.windows.net/models/xception_dl4j_inference.v2.zip",
  1931. "format": "Deeplearning4j",
  1932. "link": "https://github.com/eclipse/deeplearning4j"
  1933. },
  1934. {
  1935. "type": "dlc",
  1936. "target": "dmonitoring_model_q/model,dmonitoring_model_q/model.params",
  1937. "source": "https://github.com/lutzroeder/netron/files/8767267/dmonitoring_model_q.zip[model,model.params]",
  1938. "error": "File contains undocumented 'NETD' data in 'model'.",
  1939. "link": "https://github.com/lutzroeder/netron/issues/640"
  1940. },
  1941. {
  1942. "type": "dlc",
  1943. "target": "dmonitoring_model_q.dlc",
  1944. "source": "https://github.com/lutzroeder/netron/files/8767255/dmonitoring_model_q.dlc.zip[dmonitoring_model_q.dlc]",
  1945. "error": "File contains undocumented 'NETD' data in 'dmonitoring_model_q.dlc'.",
  1946. "link": "https://github.com/lutzroeder/netron/issues/640"
  1947. },
  1948. {
  1949. "type": "dlc",
  1950. "target": "inception_v3_quantized.dlc",
  1951. "source": "https://github.com/lutzroeder/netron/files/5615377/inception_v3_quantized.dlc.zip[inception_v3_quantized.dlc]",
  1952. "error": "File contains undocumented 'NETD' data in 'inception_v3_quantized.dlc'.",
  1953. "link": "https://github.com/lutzroeder/netron/issues/640"
  1954. },
  1955. {
  1956. "type": "dlc",
  1957. "target": "model_front_mibokeh_video.dlc",
  1958. "source": "https://github.com/lutzroeder/netron/files/8767521/model_front_mibokeh_video.dlc.zip[model_front_mibokeh_video.dlc]",
  1959. "error": "File contains undocumented 'NETD' data in 'model_front_mibokeh_video.dlc'.",
  1960. "link": "https://github.com/lutzroeder/netron/issues/640"
  1961. },
  1962. {
  1963. "type": "dlc",
  1964. "target": "mobile_mosaic_hta/model.params",
  1965. "source": "https://github.com/lutzroeder/netron/files/8767531/mobile_mosaic_hta.zip[model.params]",
  1966. "error": "File contains undocumented 'NETP' data in 'model.params'.",
  1967. "link": "https://github.com/lutzroeder/netron/issues/640"
  1968. },
  1969. {
  1970. "type": "dnn",
  1971. "target": "brows_model.dnn",
  1972. "source": "https://github.com/lutzroeder/netron/files/5118426/brows_model.zip[brows_model.dnn]",
  1973. "format": "SnapML v1",
  1974. "link": "https://github.com/lutzroeder/netron/issues/581"
  1975. },
  1976. {
  1977. "type": "flax",
  1978. "target": "flax_model.msgpack",
  1979. "source": "https://github.com/lutzroeder/netron/files/8567810/flax_model.msgpack.zip[flax_model.msgpack]",
  1980. "format": "Flax",
  1981. "link": "https://github.com/lutzroeder/netron/issues/850"
  1982. },
  1983. {
  1984. "type": "flux",
  1985. "target": "helloworld.bson",
  1986. "source": "https://github.com/lutzroeder/netron/files/3638212/helloworld.zip[helloworld.bson]",
  1987. "format": "Flux",
  1988. "link": "https://github.com/lutzroeder/netron/issues/334"
  1989. },
  1990. {
  1991. "type": "keras",
  1992. "target": "5_model_fold_0.h5",
  1993. "source": "https://github.com/lutzroeder/netron/files/6174822/5_model_fold_0.h5.zip[5_model_fold_0.h5]",
  1994. "format": "Keras v2.4.0",
  1995. "link": "https://github.com/lutzroeder/netron/issues/540"
  1996. },
  1997. {
  1998. "type": "keras",
  1999. "target": "babi_rnn.h5",
  2000. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[babi_rnn.h5]",
  2001. "format": "Keras v2.1.2",
  2002. "link": "https://github.com/lutzroeder/netron/issues/57"
  2003. },
  2004. {
  2005. "type": "keras",
  2006. "target": "betago.hdf5",
  2007. "source": "https://raw.githubusercontent.com/maxpumperla/deep_learning_and_the_game_of_go/master/code/agents/betago.hdf5",
  2008. "format": "Keras v2.0.8",
  2009. "link": "https://github.com/lutzroeder/netron/issues/57"
  2010. },
  2011. {
  2012. "type": "keras",
  2013. "target": "bidirectional_lstm.h5",
  2014. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[bidirectional_lstm.h5]",
  2015. "format": "Keras v2.1.2",
  2016. "link": "https://github.com/lutzroeder/netron/issues/57"
  2017. },
  2018. {
  2019. "type": "keras",
  2020. "target": "cats_and_dogs_small_1.h5",
  2021. "source": "https://raw.githubusercontent.com/wwells/CUNY_DATA_698/master/DL_Coursework/DLR/cats_and_dogs_small_1.h5",
  2022. "format": "Keras v2.1.5",
  2023. "link": "https://github.com/wwells/CUNY_DATA_698/tree/master/DL_Coursework/DLR"
  2024. },
  2025. {
  2026. "type": "keras",
  2027. "target": "cats_and_dogs_small_2.h5",
  2028. "source": "https://raw.githubusercontent.com/kylehamilton/deep-learning-with-r-notebooks/master/cats_and_dogs_small_2.h5",
  2029. "format": "Keras v2.0.9",
  2030. "link": "https://github.com/kylehamilton/deep-learning-with-r-notebooks"
  2031. },
  2032. {
  2033. "type": "keras",
  2034. "target": "cats_and_dogs_2_activation.h5",
  2035. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[cats_and_dogs_2_activation.h5]",
  2036. "format": "Keras v2.1.3",
  2037. "link": "https://github.com/lutzroeder/netron/issues/57"
  2038. },
  2039. {
  2040. "type": "keras",
  2041. "target": "cifar10_m4_iter_70000.caffemodel.h5",
  2042. "source": "https://raw.githubusercontent.com/ARM-software/ML-examples/d229d37863d69963f36e9da92dfd25f592925b9d/cmsisnn-cifar10/models/cifar10_m4_iter_70000.caffemodel.h5",
  2043. "format": "HDF5 Weights",
  2044. "link": "https://github.com/ARM-software/ML-examples"
  2045. },
  2046. {
  2047. "type": "keras",
  2048. "target": "CNN_SN_flaw1_v1.h5",
  2049. "source": "https://github.com/lutzroeder/netron/files/2452413/CNN_SN_flaw1_v1.h5.zip[CNN_SN_flaw1_v1.h5]",
  2050. "format": "Keras v2.2.3",
  2051. "link": "https://github.com/lutzroeder/netron/issues/157"
  2052. },
  2053. {
  2054. "type": "keras",
  2055. "target": "data_prediction.hdf5",
  2056. "source": "https://github.com/lutzroeder/netron/files/8694214/data_prediction.hdf5.zip[data_prediction.hdf5]",
  2057. "format": "HDF5 Weights",
  2058. "link": "https://github.com/lutzroeder/netron/issues/467"
  2059. },
  2060. {
  2061. "type": "keras",
  2062. "target": "DenseNet121.h5.zip",
  2063. "source": "https://github.com/lutzroeder/netron/files/6251712/DenseNet121.h5.zip",
  2064. "format": "Keras v2.4.0",
  2065. "link": "https://github.com/lutzroeder/netron/issues/57"
  2066. },
  2067. {
  2068. "type": "keras",
  2069. "target": "generating_images_with_vaes.h5",
  2070. "source": "https://github.com/lutzroeder/netron/files/2592326/generating_images_with_vaes.h5.zip[generating_images_with_vaes.h5]",
  2071. "format": "Keras v2.1.3",
  2072. "link": "https://github.com/fchollet/deep-learning-with-python-notebooks/blob/master/8.4-generating-images-with-vaes.ipynb"
  2073. },
  2074. {
  2075. "type": "keras",
  2076. "target": "generator_model.h5",
  2077. "source": "https://raw.githubusercontent.com/mattya/chainer-DCGAN/master/generator_model.h5",
  2078. "format": "HDF5 Weights",
  2079. "link": "https://github.com/mattya/chainer-DCGAN"
  2080. },
  2081. {
  2082. "type": "keras",
  2083. "target": "imdb_embedding.h5",
  2084. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[imdb_embedding.h5]",
  2085. "format": "Keras v2.1.3",
  2086. "link": "https://github.com/lutzroeder/netron/issues/57"
  2087. },
  2088. {
  2089. "type": "keras",
  2090. "target": "imdb_simplernn.h5",
  2091. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[imdb_simplernn.h5]",
  2092. "format": "Keras v2.1.3",
  2093. "link": "https://github.com/lutzroeder/netron/issues/57"
  2094. },
  2095. {
  2096. "type": "keras",
  2097. "target": "InceptionResNetV2.h5.zip",
  2098. "source": "https://github.com/lutzroeder/netron/files/6098150/InceptionResNetV2.h5.zip",
  2099. "format": "Keras v2.4.0",
  2100. "link": "https://github.com/lutzroeder/netron/issues/57"
  2101. },
  2102. {
  2103. "type": "keras",
  2104. "target": "InceptionV3.h5.zip",
  2105. "source": "https://github.com/lutzroeder/netron/files/6098151/InceptionV3.h5.zip",
  2106. "format": "Keras v2.4.0",
  2107. "link": "https://github.com/lutzroeder/netron/issues/57"
  2108. },
  2109. {
  2110. "type": "keras",
  2111. "target": "lstm_seq2seq.h5",
  2112. "source": "https://github.com/lutzroeder/netron/files/2592328/lstm_seq2seq.zip[lstm_seq2seq.h5]",
  2113. "format": "Keras v2.1.2",
  2114. "link": "https://github.com/lutzroeder/netron/issues/57"
  2115. },
  2116. {
  2117. "type": "keras",
  2118. "target": "lstm_seq2seq.json",
  2119. "source": "https://github.com/lutzroeder/netron/files/2592328/lstm_seq2seq.zip[lstm_seq2seq.json] ",
  2120. "format": "Keras",
  2121. "link": "https://github.com/lutzroeder/netron/issues/57"
  2122. },
  2123. {
  2124. "type": "keras",
  2125. "target": "mlp.h5",
  2126. "source": "https://github.com/lutzroeder/netron/files/3666244/mlp.zip[mlp.h5]",
  2127. "format": "HDF5 Weights",
  2128. "link": "https://github.com/lutzroeder/netron/issues/337"
  2129. },
  2130. {
  2131. "type": "keras",
  2132. "target": "mimo.h5",
  2133. "source": "https://github.com/lutzroeder/netron/files/2565761/mimo.h5.zip[mimo.h5]",
  2134. "format": "Keras v2.2.0",
  2135. "link": "https://github.com/lutzroeder/netron/issues/138"
  2136. },
  2137. {
  2138. "type": "keras",
  2139. "target": "mnist_float16.h5",
  2140. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float16.h5]",
  2141. "format": "Keras v2.1.2",
  2142. "link": "https://github.com/lutzroeder/netron/issues/57"
  2143. },
  2144. {
  2145. "type": "keras",
  2146. "target": "mnist_float32.h5",
  2147. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float32.h5]",
  2148. "format": "Keras v2.1.2",
  2149. "link": "https://github.com/lutzroeder/netron/issues/57"
  2150. },
  2151. {
  2152. "type": "keras",
  2153. "target": "mnist_float64.h5",
  2154. "source": "https://github.com/lutzroeder/netron/files/2592324/mnist.zip[mnist_float64.h5]",
  2155. "format": "Keras v2.1.2",
  2156. "link": "https://github.com/lutzroeder/netron/issues/57"
  2157. },
  2158. {
  2159. "type": "keras",
  2160. "target": "mobilenet.h5",
  2161. "source": "https://raw.githubusercontent.com/aio-libs/aiohttp-demos/master/demos/imagetagger/tests/data/mobilenet.h5",
  2162. "format": "Keras v2.2.2",
  2163. "link": "https://github.com/aio-libs/aiohttp-demos/tree/master/demos/imagetagger/tests/data"
  2164. },
  2165. {
  2166. "type": "keras",
  2167. "target": "mobilenet_v1_1.0_224_quant.hdf5",
  2168. "source": "https://github.com/lutzroeder/netron/files/4484451/mobilenet_v1_1.0_224_quant.zip[mobilenet_v1_1.0_224_quant.hdf5]",
  2169. "format": "HDF5 Weights",
  2170. "link": "https://github.com/lutzroeder/netron/issues/467"
  2171. },
  2172. {
  2173. "type": "keras",
  2174. "target": "MobileNetV2.h5.zip",
  2175. "source": "https://github.com/lutzroeder/netron/files/6098152/MobileNetV2.h5.zip",
  2176. "link": "https://github.com/lutzroeder/netron/issues/57"
  2177. },
  2178. {
  2179. "type": "keras",
  2180. "target": "model_denoise.h5",
  2181. "source": "https://github.com/lutzroeder/netron/files/8452765/model_denoise.h5.zip[model_denoise.h5]",
  2182. "format": "Keras v2.4.0",
  2183. "link": "https://github.com/lutzroeder/netron/issues/900"
  2184. },
  2185. {
  2186. "type": "keras",
  2187. "target": "model_float32.h5",
  2188. "source": "https://github.com/lutzroeder/netron/files/7759357/model_float32.h5.zip[model_float32.h5]",
  2189. "format": "Keras v2.7.0",
  2190. "link": "https://github.com/lutzroeder/netron/issues/540"
  2191. },
  2192. {
  2193. "type": "keras",
  2194. "target": "NASNetMobile.h5.zip",
  2195. "source": "https://github.com/lutzroeder/netron/files/6098153/NASNetMobile.h5.zip",
  2196. "format": "Keras v2.4.0",
  2197. "link": "https://github.com/lutzroeder/netron/issues/57"
  2198. },
  2199. {
  2200. "type": "keras",
  2201. "target": "nested_bidrectional.h5",
  2202. "source": "https://github.com/lutzroeder/netron/files/4304644/nested_bidrectional.zip[nested_bidrectional.h5]",
  2203. "format": "Keras v2.3.1",
  2204. "link": "https://github.com/lutzroeder/netron/issues/428"
  2205. },
  2206. {
  2207. "type": "keras",
  2208. "target": "nested_bidrectional.weights",
  2209. "source": "https://github.com/lutzroeder/netron/files/4304644/nested_bidrectional.zip[nested_bidrectional_weights.h5]",
  2210. "format": "Keras Weights v2.3.1",
  2211. "link": "https://github.com/lutzroeder/netron/issues/428"
  2212. },
  2213. {
  2214. "type": "keras",
  2215. "target": "netron_issue_326.json",
  2216. "source": "https://github.com/lutzroeder/netron/files/3563087/netron_issue_326.zip[netron_issue_326.json]",
  2217. "format": "Keras v2.2.4-tf",
  2218. "link": "https://github.com/lutzroeder/netron/issues/326"
  2219. },
  2220. {
  2221. "type": "keras",
  2222. "target": "netron_issue_428.h5",
  2223. "source": "https://github.com/lutzroeder/netron/files/4221535/netron_issue_428.zip[netron_issue_428.h5]",
  2224. "format": "Keras v2.2.4-tf",
  2225. "link": "https://github.com/lutzroeder/netron/issues/428"
  2226. },
  2227. {
  2228. "type": "keras",
  2229. "target": "netron_issue_435.h5",
  2230. "source": "https://github.com/lutzroeder/netron/files/4269953/netron_issue_435.zip[netron_issue_435.h5]",
  2231. "format": "Keras v2.2.4",
  2232. "link": "https://github.com/lutzroeder/netron/issues/435"
  2233. },
  2234. {
  2235. "type": "keras",
  2236. "target": "netron_issue_553.h5",
  2237. "source": "https://github.com/lutzroeder/netron/files/4979486/netron_issue_553.zip[netron_issue_553.h5]",
  2238. "format": "Keras v2.2.4-tf",
  2239. "link": "https://github.com/lutzroeder/netron/issues/553"
  2240. },
  2241. {
  2242. "type": "keras",
  2243. "target": "netron_issue_855.h5",
  2244. "source": "https://github.com/lutzroeder/netron/files/7729736/netron_issue_855.h5.zip[netron_issue_855.h5]",
  2245. "format": "Keras v2.7.0",
  2246. "link": "https://github.com/lutzroeder/netron/issues/855"
  2247. },
  2248. {
  2249. "type": "keras",
  2250. "target": "nietzsche.h5",
  2251. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[nietzsche.h5]",
  2252. "format": "Keras v2.1.3",
  2253. "link": "https://github.com/lutzroeder/netron/issues/57"
  2254. },
  2255. {
  2256. "type": "keras",
  2257. "target": "residual_cnn.h5",
  2258. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[residual_cnn.h5]",
  2259. "format": "Keras v2.1.2",
  2260. "link": "https://github.com/lutzroeder/netron/issues/57"
  2261. },
  2262. {
  2263. "type": "keras",
  2264. "target": "resnet50_weights_tf_dim_ordering_tf_kernels.h5",
  2265. "source": "https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels.h5",
  2266. "format": "Keras Weights"
  2267. },
  2268. {
  2269. "type": "keras",
  2270. "target": "resnet50_csv_16.json",
  2271. "source": "https://github.com/lutzroeder/netron/files/4202466/resnet50_csv_16.json.zip[resnet50_csv_16.json]",
  2272. "format": "Keras",
  2273. "link": "https://github.com/lutzroeder/netron/issues/426"
  2274. },
  2275. {
  2276. "type": "keras",
  2277. "target": "sentiment_model.h5",
  2278. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[sentiment_model.h5]",
  2279. "format": "Keras v2.1.3",
  2280. "link": "https://github.com/lutzroeder/netron/issues/57"
  2281. },
  2282. {
  2283. "type": "keras",
  2284. "target": "siamese_net.json",
  2285. "source": "https://github.com/lutzroeder/netron/files/2592353/siamese_net.json.zip[siamese_net.json]",
  2286. "format": "Keras",
  2287. "link": "https://github.com/lutzroeder/netron/issues/130"
  2288. },
  2289. {
  2290. "type": "keras",
  2291. "target": "snapshot_parent_0097.h5",
  2292. "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",
  2293. "error": "File format is not HDF5 Weights in 'snapshot_parent_0097.h5'.",
  2294. "link": "https://github.com/uber-research/deep-neuroevolution"
  2295. },
  2296. {
  2297. "type": "keras",
  2298. "target": "tecogan_model.h5",
  2299. "source": "https://nnabla.org/pretrained-models/nnabla-examples/GANs/tecogan/tecogan_model.h5",
  2300. "format": "HDF5 Weights",
  2301. "link": "https://github.com/sony/nnabla-examples/issues/192"
  2302. },
  2303. {
  2304. "type": "keras",
  2305. "target": "time_distributed.h5",
  2306. "source": "https://github.com/lutzroeder/netron/files/2592329/keras_models.zip[time_distributed.h5]",
  2307. "format": "Keras v2.1.2",
  2308. "link": "https://github.com/lutzroeder/netron/issues/57"
  2309. },
  2310. {
  2311. "type": "keras",
  2312. "target": "thisnotworks.h5",
  2313. "source": "https://github.com/lutzroeder/netron/files/7764266/thisnotworks.h5.zip[thisnotworks.h5]",
  2314. "format": "Keras v2.4.0",
  2315. "runtime": "tensorflow",
  2316. "link": "https://github.com/lutzroeder/netron/issues/540"
  2317. },
  2318. {
  2319. "type": "keras",
  2320. "target": "tiny-yolo-voc.h5",
  2321. "source": "https://raw.githubusercontent.com/hollance/YOLO-CoreML-MPSNNGraph/master/Convert/yad2k/model_data/tiny-yolo-voc.h5",
  2322. "format": "Keras v1.2.2",
  2323. "link": "https://github.com/hollance/YOLO-CoreML-MPSNNGraph/tree/master/Convert/yad2k/model_data"
  2324. },
  2325. {
  2326. "type": "keras",
  2327. "target": "yolov3-tiny.h5",
  2328. "source": "https://github.com/lutzroeder/netron/files/5823763/yolov3-tiny.h5.zip[yolov3-tiny.h5]",
  2329. "format": "Keras v2.4.0",
  2330. "runtime": "tensorflow",
  2331. "link": "https://github.com/lutzroeder/netron/issues/540"
  2332. },
  2333. {
  2334. "type": "keras",
  2335. "target": "test11.h5",
  2336. "source": "https://github.com/lutzroeder/netron/files/7874228/test11.h5.zip[test11.h5]",
  2337. "format": "HDF5 Weights",
  2338. "link": "https://github.com/lutzroeder/netron/issues/467"
  2339. },
  2340. {
  2341. "type": "keras",
  2342. "target": "tiramisu_fc_dense103_model.json",
  2343. "source": "https://raw.githubusercontent.com/0bserver07/One-Hundred-Layers-Tiramisu/master/tiramisu_fc_dense103_model.json",
  2344. "format": "Keras v2.0.2",
  2345. "runtime": "tensorflow",
  2346. "link": "https://github.com/0bserver07/One-Hundred-Layers-Tiramisu"
  2347. },
  2348. {
  2349. "type": "keras",
  2350. "target": "VGG19.h5.zip",
  2351. "source": "https://github.com/lutzroeder/netron/files/6098155/VGG19.h5.zip",
  2352. "link": "https://github.com/lutzroeder/netron/issues/57"
  2353. },
  2354. {
  2355. "type": "kmodel",
  2356. "target": "cifar10.kmodel",
  2357. "source": "https://github.com/lutzroeder/netron/files/7965167/cifar10.kmodel.zip[cifar10.kmodel]",
  2358. "format": "kmodel v3",
  2359. "link": "https://github.com/lutzroeder/netron/issues/871"
  2360. },
  2361. {
  2362. "type": "kmodel",
  2363. "target": "iris.kmodel",
  2364. "source": "https://github.com/lutzroeder/netron/files/8111178/iris.kmodel.zip[iris.kmodel]",
  2365. "format": "kmodel v4",
  2366. "link": "https://github.com/lutzroeder/netron/issues/871"
  2367. },
  2368. {
  2369. "type": "kmodel",
  2370. "target": "LPbox_1_branch.kmodel",
  2371. "source": "https://github.com/lutzroeder/netron/files/8402871/LPbox_1_branch.kmodel.zip[LPbox_1_branch.kmodel]",
  2372. "format": "kmodel v4",
  2373. "link": "https://github.com/lutzroeder/netron/issues/871"
  2374. },
  2375. {
  2376. "type": "kmodel",
  2377. "target": "mbnetv1.kmodel",
  2378. "source": "https://github.com/lutzroeder/netron/files/8111310/mbnetv1.kmodel.zip[mbnetv1.kmodel]",
  2379. "format": "kmodel v3",
  2380. "link": "https://github.com/lutzroeder/netron/issues/871"
  2381. },
  2382. {
  2383. "type": "kmodel",
  2384. "target": "mobilenet_v2.kmodel",
  2385. "source": "https://github.com/lutzroeder/netron/files/7965168/mobilenet_v2.kmodel.zip[mobilenet_v2.kmodel]",
  2386. "format": "kmodel v5",
  2387. "link": "https://github.com/lutzroeder/netron/issues/871"
  2388. },
  2389. {
  2390. "type": "kmodel",
  2391. "target": "model.kmodel",
  2392. "source": "https://github.com/lutzroeder/netron/files/8111371/model.kmodel.zip[model.kmodel]",
  2393. "format": "kmodel v4",
  2394. "link": "https://github.com/lutzroeder/netron/issues/871"
  2395. },
  2396. {
  2397. "type": "kmodel",
  2398. "target": "mnist.kmodel",
  2399. "source": "https://github.com/lutzroeder/netron/files/8111312/mnist.kmodel.zip[mnist.kmodel]",
  2400. "format": "kmodel v5",
  2401. "link": "https://github.com/lutzroeder/netron/issues/871"
  2402. },
  2403. {
  2404. "type": "kmodel",
  2405. "target": "RFB-320.kmodel",
  2406. "source": "https://github.com/lutzroeder/netron/files/7965166/RFB-320.kmodel.zip[RFB-320.kmodel]",
  2407. "format": "kmodel v4",
  2408. "link": "https://github.com/lutzroeder/netron/issues/871"
  2409. },
  2410. {
  2411. "type": "kmodel",
  2412. "target": "test1.kmodel",
  2413. "source": "https://github.com/lutzroeder/netron/files/8568261/test1.kmodel.zip[test1.kmodel]",
  2414. "format": "kmodel v4",
  2415. "link": "https://github.com/lutzroeder/netron/issues/871"
  2416. },
  2417. {
  2418. "type": "kmodel",
  2419. "target": "ulffd_landmark.kmodel",
  2420. "source": "https://github.com/lutzroeder/netron/files/8111629/ulffd_landmark.kmodel.zip[ulffd_landmark.kmodel]",
  2421. "format": "kmodel v4",
  2422. "link": "https://github.com/lutzroeder/netron/issues/871"
  2423. },
  2424. {
  2425. "type": "kmodel",
  2426. "target": "yolofast.kmodel",
  2427. "source": "https://github.com/lutzroeder/netron/files/8758983/yolofast.kmodel.zip[yolofast.kmodel]",
  2428. "format": "kmodel v5",
  2429. "link": "https://github.com/lutzroeder/netron/issues/871"
  2430. },
  2431. {
  2432. "type": "kmodel",
  2433. "target": "yolox_nano_224.kmodel",
  2434. "source": "https://github.com/lutzroeder/netron/files/8695383/yolox_nano_224.kmodel.zip[yolox_nano_224.kmodel]",
  2435. "format": "kmodel v5",
  2436. "link": "https://github.com/lutzroeder/netron/issues/871"
  2437. },
  2438. {
  2439. "type": "lasagne",
  2440. "target": "net2.pkl",
  2441. "source": "https://raw.githubusercontent.com/Aabglov/LasaganeTest/master/results/net2.pkl",
  2442. "format": "Lasagne",
  2443. "link": "https://github.com/Aabglov/LasaganeTest"
  2444. },
  2445. {
  2446. "type": "lightgbm",
  2447. "target": "rf_classifier.model",
  2448. "source": "https://github.com/lutzroeder/netron/files/6329766/rf_classifier.model.zip[rf_classifier.model]",
  2449. "format": "LightGBM v3",
  2450. "link": "https://github.com/lutzroeder/netron/issues/669"
  2451. },
  2452. {
  2453. "type": "lightgbm",
  2454. "target": "simple_example.pkl",
  2455. "source": "https://github.com/lutzroeder/netron/files/5978325/simple_example.pkl.zip[simple_example.pkl]",
  2456. "format": "LightGBM Pickle v2",
  2457. "link": "https://github.com/lutzroeder/netron/issues/669"
  2458. },
  2459. {
  2460. "type": "lightgbm",
  2461. "target": "simple_example.txt",
  2462. "source": "https://github.com/lutzroeder/netron/files/5832361/simple_example.txt.zip[simple_example.txt]",
  2463. "format": "LightGBM v3",
  2464. "link": "https://github.com/lutzroeder/netron/issues/669"
  2465. },
  2466. {
  2467. "type": "mediapipe",
  2468. "target": "clipped_images_from_file_at_24fps.pbtxt",
  2469. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/media_sequence/clipped_images_from_file_at_24fps.pbtxt",
  2470. "format": "MediaPipe",
  2471. "link": "https://github.com/google/mediapipe"
  2472. },
  2473. {
  2474. "type": "mediapipe",
  2475. "target": "cpu_oss_hairsegment.pbtxt",
  2476. "source": "https://github.com/lutzroeder/netron/files/5760736/cpu_oss_hairsegment.pbtxt.zip[cpu_oss_hairsegment.pbtxt]",
  2477. "format": "MediaPipe",
  2478. "link": "https://github.com/lutzroeder/netron/issues/423"
  2479. },
  2480. {
  2481. "type": "mediapipe",
  2482. "target": "face_detection_mobile_cpu.pbtxt",
  2483. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/face_detection/face_detection_mobile_cpu.pbtxt",
  2484. "format": "MediaPipe",
  2485. "link": "https://github.com/google/mediapipe"
  2486. },
  2487. {
  2488. "type": "mediapipe",
  2489. "target": "face_landmarks_from_pose_cpu.pbtxt",
  2490. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/modules/holistic_landmark/face_landmarks_from_pose_cpu.pbtxt",
  2491. "format": "MediaPipe",
  2492. "link": "https://github.com/lutzroeder/netron/issues/550"
  2493. },
  2494. {
  2495. "type": "mediapipe",
  2496. "target": "hand_detection_mobile.pbtxt",
  2497. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/hand_tracking/hand_detection_mobile.pbtxt",
  2498. "format": "MediaPipe",
  2499. "link": "https://github.com/google/mediapipe"
  2500. },
  2501. {
  2502. "type": "mediapipe",
  2503. "target": "hand_tracking.pbtxt",
  2504. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/modules/holistic_landmark/hand_tracking.pbtxt",
  2505. "format": "MediaPipe",
  2506. "link": "https://github.com/lutzroeder/netron/issues/550"
  2507. },
  2508. {
  2509. "type": "mediapipe",
  2510. "target": "hand_tracking_mobile.pbtxt",
  2511. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/hand_tracking/hand_tracking_mobile.pbtxt",
  2512. "format": "MediaPipe",
  2513. "link": "https://github.com/google/mediapipe"
  2514. },
  2515. {
  2516. "type": "mediapipe",
  2517. "target": "object_detection_desktop_live.pbtxt",
  2518. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/examples/coral/graphs/object_detection_desktop_live.pbtxt",
  2519. "format": "MediaPipe",
  2520. "link": "https://github.com/google/mediapipe"
  2521. },
  2522. {
  2523. "type": "mediapipe",
  2524. "target": "object_occlusion_tracking.pbtxt",
  2525. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/object_detection_3d/object_occlusion_tracking.pbtxt",
  2526. "format": "MediaPipe",
  2527. "link": "https://github.com/lutzroeder/netron/issues/444"
  2528. },
  2529. {
  2530. "type": "mediapipe",
  2531. "target": "tvl1_flow_and_rgb_from_file.pbtxt",
  2532. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/media_sequence/tvl1_flow_and_rgb_from_file.pbtxt",
  2533. "format": "MediaPipe",
  2534. "link": "https://github.com/google/mediapipe"
  2535. },
  2536. {
  2537. "type": "mediapipe",
  2538. "target": "yt8m_dataset_model_inference.pbtxt",
  2539. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/graphs/youtube8m/yt8m_dataset_model_inference.pbtxt",
  2540. "format": "MediaPipe",
  2541. "link": "https://github.com/google/mediapipe"
  2542. },
  2543. {
  2544. "type": "mlnet",
  2545. "target": "BinaryClassification_AutoML_SentimentModel.zip",
  2546. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/BinaryClassification_AutoML/SentimentAnalysis/MLModels/SentimentModel.zip",
  2547. "format": "ML.NET v1.0.27701.1",
  2548. "link": "https://github.com/dotnet/machinelearning-samples"
  2549. },
  2550. {
  2551. "type": "mlnet",
  2552. "target": "BikeDemandForecasting.zip",
  2553. "source": "https://github.com/lutzroeder/netron/files/4042150/MLModel.zip",
  2554. "format": "ML.NET v1.4.28305.1",
  2555. "link": "https://github.com/dotnet/machinelearning-samples"
  2556. },
  2557. {
  2558. "type": "mlnet",
  2559. "target": "ep_model1.zip",
  2560. "source": "https://github.com/lutzroeder/netron/files/4216033/ep_model1.zip",
  2561. "format": "ML.NET v1.0.0.0",
  2562. "link": "https://github.com/lutzroeder/netron/issues/170"
  2563. },
  2564. {
  2565. "type": "mlnet",
  2566. "target": "ep_model3.zip",
  2567. "source": "https://github.com/lutzroeder/netron/files/4216304/ep_model3.zip",
  2568. "format": "ML.NET v1.0.0.0",
  2569. "link": "https://github.com/lutzroeder/netron/issues/170"
  2570. },
  2571. {
  2572. "type": "mlnet",
  2573. "target": "FastTreeModel.zip",
  2574. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/FastTreeModel.zip",
  2575. "format": "ML.NET v1.0.0.0",
  2576. "link": "https://github.com/dotnet/machinelearning-samples"
  2577. },
  2578. {
  2579. "type": "mlnet",
  2580. "target": "FastTreeTweedieModel.zip",
  2581. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/FastTreeTweedieModel.zip",
  2582. "format": "ML.NET v1.0.0.0",
  2583. "link": "https://github.com/dotnet/machinelearning-samples"
  2584. },
  2585. {
  2586. "type": "mlnet",
  2587. "target": "GitHubLabelerModel.zip",
  2588. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/MulticlassClassification-GitHubLabeler/GitHubLabeler/MLModels/GitHubLabelerModel.zip",
  2589. "format": "ML.NET v1.0.27701.1",
  2590. "link": "https://github.com/dotnet/machinelearning-samples"
  2591. },
  2592. {
  2593. "type": "mlnet",
  2594. "target": "ImageClassification.Predict.imageClassifier.zip",
  2595. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/MLNETModel/imageClassifier.zip",
  2596. "format": "ML.NET v1.4.28230.4",
  2597. "link": "https://github.com/dotnet/machinelearning-samples"
  2598. },
  2599. {
  2600. "type": "mlnet",
  2601. "target": "IrisClassificationModel.zip",
  2602. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/MulticlassClassification_Iris/IrisClassification/MLModels/IrisClassificationModel.zip",
  2603. "format": "ML.NET v1.0.0.0",
  2604. "link": "https://github.com/dotnet/machinelearning-samples"
  2605. },
  2606. {
  2607. "type": "mlnet",
  2608. "target": "MovieRecommender_Model.zip",
  2609. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/Recommendation-MovieRecommender/MovieRecommender_Model/Model/model.zip",
  2610. "format": "ML.NET v1.4.28230.4",
  2611. "link": "https://github.com/dotnet/machinelearning-samples"
  2612. },
  2613. {
  2614. "type": "mlnet",
  2615. "target": "ngram.zip",
  2616. "source": "https://github.com/lutzroeder/netron/files/4216079/ngram.zip?raw=true",
  2617. "format": "ML.NET v3.10.29.504",
  2618. "link": "https://github.com/lutzroeder/netron/issues/170"
  2619. },
  2620. {
  2621. "type": "mlnet",
  2622. "target": "PoissonModel.zip",
  2623. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/PoissonModel.zip",
  2624. "format": "ML.NET v1.0.0.0",
  2625. "link": "https://github.com/dotnet/machinelearning-samples"
  2626. },
  2627. {
  2628. "type": "mlnet",
  2629. "target": "product_month_fastTreeTweedie.zip",
  2630. "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",
  2631. "format": "ML.NET v1.3.28006.10",
  2632. "link": "https://github.com/dotnet/machinelearning-samples"
  2633. },
  2634. {
  2635. "type": "mlnet",
  2636. "target": "ProductSalesChangePointModel.zip",
  2637. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/AnomalyDetection-Sales/SpikeDetectionE2EApp/MLModels/ProductSalesChangePointModel.zip",
  2638. "format": "ML.NET v1.4.28305.1",
  2639. "link": "https://github.com/dotnet/machinelearning-samples"
  2640. },
  2641. {
  2642. "type": "mlnet",
  2643. "target": "ProductSalesSpikeModel.zip",
  2644. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/end-to-end-apps/AnomalyDetection-Sales/SpikeDetectionE2EApp/MLModels/ProductSalesSpikeModel.zip",
  2645. "format": "ML.NET v1.4.28305.1",
  2646. "link": "https://github.com/dotnet/machinelearning-samples"
  2647. },
  2648. {
  2649. "type": "mlnet",
  2650. "target": "randomizedPca.zip",
  2651. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/AnomalyDetection_CreditCardFraudDetection/CreditCardFraudDetection.Predictor/assets/input/randomizedPca.zip",
  2652. "format": "ML.NET v1.2.27902.10",
  2653. "link": "https://github.com/dotnet/machinelearning-samples"
  2654. },
  2655. {
  2656. "type": "mlnet",
  2657. "target": "retailClustering.zip",
  2658. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Clustering_CustomerSegmentation/CustomerSegmentation.Train/assets/outputs/retailClustering.zip",
  2659. "format": "ML.NET v1.0.27701.1",
  2660. "link": "https://github.com/dotnet/machinelearning-samples"
  2661. },
  2662. {
  2663. "type": "mlnet",
  2664. "target": "SDCAModel.zip",
  2665. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_BikeSharingDemand/BikeSharingDemand/MLModels/SDCAModel.zip",
  2666. "format": "ML.NET v1.0.0.0",
  2667. "link": "https://github.com/dotnet/machinelearning-samples"
  2668. },
  2669. {
  2670. "type": "mlnet",
  2671. "target": "TaxiFareModel.zip",
  2672. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/master/samples/csharp/getting-started/Regression_AutoML/TaxiFarePrediction/MLModels/TaxiFareModel.zip",
  2673. "format": "ML.NET v1.5.28926.5",
  2674. "link": "https://github.com/dotnet/machinelearning-samples"
  2675. },
  2676. {
  2677. "type": "mlnet",
  2678. "target": "termlookup_with_key.zip",
  2679. "source": "https://github.com/lutzroeder/netron/files/4216237/termlookup_with_key.zip?raw=true",
  2680. "format": "ML.NET v1.0.0.0",
  2681. "link": "https://github.com/lutzroeder/netron/issues/170"
  2682. },
  2683. {
  2684. "type": "mlnet",
  2685. "target": "TinyYoloModel.zip",
  2686. "source": "https://raw.githubusercontent.com/dotnet/machinelearning-samples/61b428c746f39069a9d1d92f9e0f819e6beb30f3/samples/csharp/end-to-end-apps/DeepLearning_ObjectDetection_Onnx/OnnxObjectDetectionE2EAPP/ML/MLNETModel/TinyYoloModel.zip",
  2687. "format": "ML.NET v1.0.27701.1"
  2688. },
  2689. {
  2690. "type": "mnn",
  2691. "target": "blazeface.mnn",
  2692. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/blazeface/tensorflow/jni/blazeface.mnn",
  2693. "format": "MNN v2",
  2694. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2695. },
  2696. {
  2697. "type": "mnn",
  2698. "target": "blazeface_quant.mnn",
  2699. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/blazeface/tensorflow/jni/blazeface_quant.mnn",
  2700. "format": "MNN v2",
  2701. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2702. },
  2703. {
  2704. "type": "mnn",
  2705. "target": "face_det.mnn",
  2706. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/mssd/tflite/jni/face_det.mnn",
  2707. "format": "MNN v2",
  2708. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2709. },
  2710. {
  2711. "type": "mnn",
  2712. "target": "Kmeans.mnn",
  2713. "source": "https://github.com/lutzroeder/netron/files/5405963/Kmeans.mnn.zip[Kmeans.mnn]",
  2714. "format": "MNN v2",
  2715. "link": "https://github.com/lutzroeder/netron/issues/341"
  2716. },
  2717. {
  2718. "type": "mnn",
  2719. "target": "inception-v3.mnn",
  2720. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/inception-v3.mnn",
  2721. "format": "MNN v2",
  2722. "link": "https://github.com/alibaba/MNN"
  2723. },
  2724. {
  2725. "type": "mnn",
  2726. "target": "inception-v3.mnn",
  2727. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/inception-v3.mnn",
  2728. "format": "MNN v2",
  2729. "link": "https://github.com/alibaba/MNN"
  2730. },
  2731. {
  2732. "type": "mnn",
  2733. "target": "mobilenet-v1-1.0.mnn",
  2734. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/mobilenet-v1-1.0.mnn",
  2735. "format": "MNN v2",
  2736. "link": "https://github.com/alibaba/MNN"
  2737. },
  2738. {
  2739. "type": "mnn",
  2740. "target": "MobileNetV2_224.mnn",
  2741. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/MobileNetV2_224.mnn",
  2742. "format": "MNN v2",
  2743. "link": "https://github.com/alibaba/MNN"
  2744. },
  2745. {
  2746. "type": "mnn",
  2747. "target": "resnet-v2-50.mnn",
  2748. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/resnet-v2-50.mnn",
  2749. "format": "MNN v2",
  2750. "link": "https://github.com/alibaba/MNN"
  2751. },
  2752. {
  2753. "type": "mnn",
  2754. "target": "simple.mnn",
  2755. "source": "https://github.com/lutzroeder/netron/files/3698466/simple.mnn.zip[simple.mnn]",
  2756. "format": "MNN v2",
  2757. "link": "https://github.com/lutzroeder/netron/issues/341"
  2758. },
  2759. {
  2760. "type": "mnn",
  2761. "target": "SqueezeNetV1.0.mnn",
  2762. "source": "https://raw.githubusercontent.com/alibaba/MNN/master/benchmark/models/SqueezeNetV1.0.mnn",
  2763. "format": "MNN v2",
  2764. "link": "https://github.com/alibaba/MNN"
  2765. },
  2766. {
  2767. "type": "mnn",
  2768. "target": "tf_body_det.mnn",
  2769. "source": "https://raw.githubusercontent.com/xindongzhang/MNN-APPLICATIONS/master/applications/mssd/tensorflow/jni/tf_body_det.mnn",
  2770. "format": "MNN v2",
  2771. "link": "https://github.com/xindongzhang/MNN-APPLICATIONS"
  2772. },
  2773. {
  2774. "type": "mslite",
  2775. "target": "blazeface_quant.ms",
  2776. "source": "https://github.com/lutzroeder/netron/files/6097966/blazeface_quant.ms.zip[blazeface_quant.ms]",
  2777. "error": "MSL0 format is deprecated.",
  2778. "link": "https://github.com/lutzroeder/netron/issues/600"
  2779. },
  2780. {
  2781. "type": "mslite",
  2782. "target": "control_flow_ut_while_0122.ms",
  2783. "source": "https://github.com/lutzroeder/netron/files/6097971/control_flow_ut_while_0122.ms.zip[control_flow_ut_while_0122.ms]",
  2784. "error": "MSL1 format is deprecated.",
  2785. "link": "https://github.com/lutzroeder/netron/issues/600"
  2786. },
  2787. {
  2788. "type": "mslite",
  2789. "target": "mnist.ms",
  2790. "source": "https://github.com/lutzroeder/netron/files/6128484/mnist.ms.zip[mnist.ms]",
  2791. "format": "MindSpore Lite v1.2.0",
  2792. "link": "https://github.com/lutzroeder/netron/issues/600"
  2793. },
  2794. {
  2795. "type": "mslite",
  2796. "target": "squeezenet1.1.ms",
  2797. "source": "https://github.com/lutzroeder/netron/files/6128485/squeezenet1.1.ms.zip[squeezenet1.1.ms]",
  2798. "format": "MindSpore Lite v1.2.0",
  2799. "link": "https://github.com/lutzroeder/netron/issues/600"
  2800. },
  2801. {
  2802. "type": "mxnet",
  2803. "target": "bvlc_alexnet-symbol.json,bvlc_alexnet-0000.params",
  2804. "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",
  2805. "format": "MXNet v0.10.0",
  2806. "link": "https://github.com/rai-project/mxnet/blob/master/builtin_models/BVLC-AlexNet.yml"
  2807. },
  2808. {
  2809. "type": "mxnet",
  2810. "target": "crepe.mar",
  2811. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/crepe.mar",
  2812. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2813. },
  2814. {
  2815. "type": "mxnet",
  2816. "target": "conv_weights_sharing.json",
  2817. "source": "https://github.com/lutzroeder/netron/files/3016064/conv_weights_sharing.json.zip[conv_weights_sharing.json]",
  2818. "format": "MXNet v1.3.0",
  2819. "link": "https://github.com/lutzroeder/netron/issues/245"
  2820. },
  2821. {
  2822. "type": "mxnet",
  2823. "target": "deep3d-symbol.json",
  2824. "source": "https://raw.githubusercontent.com/dmlc/mxnet-gtc-tutorial/master/deep3d/deep3d-symbol.json",
  2825. "format": "MXNet",
  2826. "link": "https://github.com/dmlc/mxnet-gtc-tutorial/tree/master/deep3d"
  2827. },
  2828. {
  2829. "type": "mxnet",
  2830. "target": "dpn68-symbol.json",
  2831. "source": "http://s3.amazonaws.com/store.carml.org/models/mxnet/dpn68/dpn68-symbol.json",
  2832. "format": "MXNet",
  2833. "link": "https://github.com/rai-project/mxnet/blob/master/builtin_models/DPN68.yml"
  2834. },
  2835. {
  2836. "type": "mxnet",
  2837. "target": "ferplus.model",
  2838. "source": "https://s3.amazonaws.com/model-server/models/FERPlus/ferplus.model",
  2839. "format": "MXNet Model Server v0.2",
  2840. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2841. },
  2842. {
  2843. "type": "mxnet",
  2844. "target": "inception_resnet_v2-symbol.json",
  2845. "source": "https://raw.githubusercontent.com/soeaver/mxnet-model/master/cls/inception/inception_resnet_v2-symbol.json",
  2846. "format": "MXNet v1.0.1",
  2847. "link": "https://github.com/soeaver/mxnet-model/tree/master/cls"
  2848. },
  2849. {
  2850. "type": "mxnet",
  2851. "target": "inception_v1.model",
  2852. "source": "https://s3.amazonaws.com/model-server/models/onnx-inception_v1/inception_v1.model",
  2853. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2854. },
  2855. {
  2856. "type": "mxnet",
  2857. "target": "inception_v3-symbol.json",
  2858. "source": "https://raw.githubusercontent.com/soeaver/mxnet-model/master/cls/inception/inception_v3-symbol.json",
  2859. "format": "MXNet v0.11.0",
  2860. "link": "https://github.com/soeaver/mxnet-model/tree/master/cls"
  2861. },
  2862. {
  2863. "type": "mxnet",
  2864. "target": "Inception-7-symbol.json",
  2865. "source": "https://raw.githubusercontent.com/bzshang/yelp-photo-classification/master/mxnet_model/inception_v3/Inception-7-symbol.json",
  2866. "format": "MXNet",
  2867. "link": "https://github.com/bzshang/yelp-photo-classification/tree/master/mxnet_model/inception_v3"
  2868. },
  2869. {
  2870. "type": "mxnet",
  2871. "target": "Inception-BN.model",
  2872. "source": "https://s3.amazonaws.com/model-server/models/inception-bn/Inception-BN.model"
  2873. },
  2874. {
  2875. "type": "mxnet",
  2876. "target": "Inception-BN-0126.params,Inception-BN-symbol.json",
  2877. "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",
  2878. "format": "MXNet",
  2879. "link": "https://mxnet.apache.org/model_zoo/index.html"
  2880. },
  2881. {
  2882. "type": "mxnet",
  2883. "target": "lstm_ptb.model",
  2884. "source": "https://s3.amazonaws.com/model-server/models/lstm_ptb/lstm_ptb.model",
  2885. "format": "MXNet Model Server v0.1",
  2886. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2887. },
  2888. {
  2889. "type": "mxnet",
  2890. "target": "lstm_ptb-symbol.json",
  2891. "source": "https://s3.amazonaws.com/model-server/models/lstm_ptb/lstm_ptb-symbol.json",
  2892. "format": "MXNet v0.11.0",
  2893. "link": "https://github.com/awslabs/mxnet-model-server/tree/master/examples/lstm_ptb"
  2894. },
  2895. {
  2896. "type": "mxnet",
  2897. "target": "mobilenet-v1-tvm.json",
  2898. "source": "https://github.com/lutzroeder/netron/files/2636924/mobilenet-v1-tvm.json.zip[mobilenet-v1-tvm.json]",
  2899. "format": "MXNet",
  2900. "producer": "TVM",
  2901. "link": "https://github.com/lutzroeder/netron/issues/199"
  2902. },
  2903. {
  2904. "type": "mxnet",
  2905. "target": "nin.model",
  2906. "source": "https://s3.amazonaws.com/model-server/models/nin/nin.model",
  2907. "format": "MXNet Model Server v0.1",
  2908. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2909. },
  2910. {
  2911. "type": "mxnet",
  2912. "target": "resnet-18.model",
  2913. "source": "https://s3.amazonaws.com/model-server/models/resnet-18/resnet-18.model",
  2914. "format": "MXNet Model Server v0.1",
  2915. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2916. },
  2917. {
  2918. "type": "mxnet",
  2919. "target": "resnet-50-0000.params",
  2920. "source": "http://data.mxnet.io/models/imagenet/resnet/50-layers/resnet-50-0000.params",
  2921. "format": "MXNet",
  2922. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2923. },
  2924. {
  2925. "type": "mxnet",
  2926. "target": "resnet-101-symbol.json",
  2927. "source": "http://data.mxnet.io/models/imagenet/resnet/101-layers/resnet-101-symbol.json",
  2928. "format": "MXNet",
  2929. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2930. },
  2931. {
  2932. "type": "mxnet",
  2933. "target": "resnet-152-symbol.json",
  2934. "source": "http://data.mxnet.io/models/imagenet/resnet/152-layers/resnet-152-symbol.json",
  2935. "format": "MXNet",
  2936. "link": "https://github.com/awslabs/deeplearning-benchmark/blob/master/image_classification/common/modelzoo.py"
  2937. },
  2938. {
  2939. "type": "mxnet",
  2940. "target": "resnext-101-64x4d.model",
  2941. "source": "https://github.com/lutzroeder/netron/files/6179250/resnext-101-64x4d.model.zip[resnext-101-64x4d.model]",
  2942. "format": "MXNet Model Server v0.1",
  2943. "runtime": "MXNet v0.12",
  2944. "link": "https://github.com/lutzroeder/netron/issues/286"
  2945. },
  2946. {
  2947. "type": "mxnet",
  2948. "target": "squeezenet_v1.1.model",
  2949. "source": "https://s3.amazonaws.com/model-server/models/squeezenet_v1.1/squeezenet_v1.1.model"
  2950. },
  2951. {
  2952. "type": "mxnet",
  2953. "target": "squeezenet_v1.1.mar",
  2954. "source": "https://s3.amazonaws.com/model-server/model_archive_1.0/squeezenet_v1.1.mar",
  2955. "format": "MXNet Model Archive v1.0",
  2956. "link": "https://github.com/awslabs/mxnet-model-server/blob/master/docs/model_zoo.md"
  2957. },
  2958. {
  2959. "type": "mxnet",
  2960. "target": "vgg16.mar",
  2961. "source": "https://github.com/lutzroeder/netron/files/6179223/vgg16.mar.zip[vgg16.mar]",
  2962. "format": "MXNet Model Archive v1.0",
  2963. "link": "https://github.com/lutzroeder/netron/issues/286"
  2964. },
  2965. {
  2966. "type": "ncnn",
  2967. "target": "centerface.param,centerface.bin",
  2968. "source": "https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/centerface.param,https://raw.githubusercontent.com/MirrorYuChen/ncnn_example/798f64b7d5f0b883e05cb994258d43658b0661b6/models/centerface.bin",
  2969. "format": "ncnn",
  2970. "link": "https://github.com/MirrorYuChen/ncnn_example"
  2971. },
  2972. {
  2973. "type": "ncnn",
  2974. "target": "darknet_yolov2.cfg.ncnn,darknet_yolov2.weights.ncnn",
  2975. "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",
  2976. "format": "ncnn",
  2977. "link": "https://github.com/00liujj/gen-ncnn-models"
  2978. },
  2979. {
  2980. "type": "ncnn",
  2981. "target": "faces_wider_squeezenet.param,faces_wider_squeezenet.bin",
  2982. "source": "https://deepdetect.com/models/init/embedded/images/detection/squeezenet_ssd_faces_ncnn.tar.gz[faces_wider_squeezenet.param,faces_wider_squeezenet.bin]",
  2983. "format": "ncnn",
  2984. "link": "https://www.deepdetect.com/models/faces_embedded_ncnn"
  2985. },
  2986. {
  2987. "type": "ncnn",
  2988. "target": "frozen.pb.cfg.ncnn,frozen.pb.weights.ncnn",
  2989. "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",
  2990. "format": "ncnn",
  2991. "link": "https://github.com/00liujj/gen-ncnn-models"
  2992. },
  2993. {
  2994. "type": "ncnn",
  2995. "target": "googlenet.param",
  2996. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/googlenet.param",
  2997. "format": "ncnn",
  2998. "link": "https://github.com/Tencent/ncnn"
  2999. },
  3000. {
  3001. "type": "ncnn",
  3002. "target": "mnet-opt.param,mnet-opt.bin",
  3003. "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",
  3004. "format": "ncnn",
  3005. "link": "https://github.com/MirrorYuChen/ncnn_example"
  3006. },
  3007. {
  3008. "type": "ncnn",
  3009. "target": "mnet.25.zip",
  3010. "source": "https://github.com/lutzroeder/netron/files/6813063/mnet.25.zip",
  3011. "format": "ncnn",
  3012. "link": "https://github.com/MirrorYuChen/ncnn_example"
  3013. },
  3014. {
  3015. "type": "ncnn",
  3016. "target": "mobilefacenet.bin,mobilefacenet.param",
  3017. "source": "https://raw.githubusercontent.com/GRAYKEY/mobilefacenet_ncnn/master/models/mobilefacenet.bin,https://raw.githubusercontent.com/GRAYKEY/mobilefacenet_ncnn/master/models/mobilefacenet.param",
  3018. "format": "ncnn",
  3019. "link": "https://github.com/GRAYKEY/mobilefacenet_ncnn"
  3020. },
  3021. {
  3022. "type": "ncnn",
  3023. "target": "mobilenetv2_yolov3.param",
  3024. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/mobilenetv2_yolov3.param",
  3025. "format": "ncnn",
  3026. "link": "https://github.com/Tencent/ncnn"
  3027. },
  3028. {
  3029. "type": "ncnn",
  3030. "target": "MobileNetSSD_deploy.param.bin,MobileNetSSD_deploy.bin",
  3031. "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",
  3032. "format": "ncnn",
  3033. "link": "https://github.com/chehongshu/ncnnforandroid_objectiondetection_Mobilenetssd"
  3034. },
  3035. {
  3036. "type": "ncnn",
  3037. "target": "ncnn_yolo2_det3.bin,ncnn_yolo2_det3.param",
  3038. "source": "https://raw.githubusercontent.com/kyo055/ncnn_yolo2/master/models/det3.bin,https://raw.githubusercontent.com/kyo055/ncnn_yolo2/master/models/det3.param",
  3039. "format": "ncnn",
  3040. "link": "https://github.com/kyo055/ncnn_yolo2"
  3041. },
  3042. {
  3043. "type": "ncnn",
  3044. "target": "netron_issue_397.param",
  3045. "source": "https://github.com/lutzroeder/netron/files/3981934/det.txt",
  3046. "format": "ncnn",
  3047. "link": "https://github.com/lutzroeder/netron/issues/397"
  3048. },
  3049. {
  3050. "type": "ncnn",
  3051. "target": "proxylessnasnet.param",
  3052. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/proxylessnasnet.param",
  3053. "format": "ncnn",
  3054. "link": "https://github.com/Tencent/ncnn"
  3055. },
  3056. {
  3057. "type": "ncnn",
  3058. "target": "resnet18_int8.param",
  3059. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/resnet18_int8.param",
  3060. "format": "ncnn",
  3061. "link": "https://github.com/Tencent/ncnn"
  3062. },
  3063. {
  3064. "type": "ncnn",
  3065. "target": "rnn-lstm-gru.param,rnn-lstm-gru.bin",
  3066. "source": "https://github.com/lutzroeder/netron/files/5800011/rnn-lstm-gru.zip[rnn-lstm-gru.param,rnn-lstm-gru.bin]",
  3067. "format": "ncnn",
  3068. "link": "https://github.com/lutzroeder/netron/issues/296"
  3069. },
  3070. {
  3071. "type": "ncnn",
  3072. "target": "shufflenet.param",
  3073. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/shufflenet.param",
  3074. "format": "ncnn",
  3075. "link": "https://github.com/Tencent/ncnn"
  3076. },
  3077. {
  3078. "type": "ncnn",
  3079. "target": "squeezenet.param",
  3080. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/squeezenet.param",
  3081. "format": "ncnn",
  3082. "link": "https://github.com/Tencent/ncnn"
  3083. },
  3084. {
  3085. "type": "ncnn",
  3086. "target": "squeezenet_v1.1.param.bin,squeezenet_v1.1.bin",
  3087. "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",
  3088. "format": "ncnn",
  3089. "link": "https://github.com/Tencent/ncnn"
  3090. },
  3091. {
  3092. "type": "ncnn",
  3093. "target": "squeezenet_v1.1.bin",
  3094. "source": "https://raw.githubusercontent.com/nihui/ncnn-android-squeezenet/master/app/src/main/assets/squeezenet_v1.1.bin",
  3095. "format": "ncnn",
  3096. "link": "https://github.com/Tencent/ncnn"
  3097. },
  3098. {
  3099. "type": "ncnn",
  3100. "target": "ssdmobilenet.param",
  3101. "source": "https://github.com/lutzroeder/netron/files/5165601/ssdmobilenet.zip[ssdmobilenet.param]",
  3102. "format": "ncnn",
  3103. "link": "https://github.com/lutzroeder/netron/issues/296"
  3104. },
  3105. {
  3106. "type": "ncnn",
  3107. "target": "test_nn_Conv1d.ncnn.param,test_nn_Conv1d.ncnn.bin",
  3108. "source": "https://github.com/lutzroeder/netron/files/7796942/ncnn-20211231.zip[test_nn_Conv3d.ncnn.param,test_nn_Conv3d.ncnn.bin]",
  3109. "format": "ncnn",
  3110. "link": "https://github.com/lutzroeder/netron/issues/296"
  3111. },
  3112. {
  3113. "type": "ncnn",
  3114. "target": "test_nn_Conv3d.ncnn.param,test_nn_Conv3d.ncnn.bin",
  3115. "source": "https://github.com/lutzroeder/netron/files/7796942/ncnn-20211231.zip[test_nn_Conv3d.ncnn.param,test_nn_Conv3d.ncnn.bin]",
  3116. "format": "ncnn",
  3117. "link": "https://github.com/lutzroeder/netron/issues/296"
  3118. },
  3119. {
  3120. "type": "ncnn",
  3121. "target": "test_nn_MultiheadAttention.ncnn.param,test_nn_MultiheadAttention.ncnn.bin",
  3122. "source": "https://github.com/lutzroeder/netron/files/7796942/ncnn-20211231.zip[test_nn_MultiheadAttention.ncnn.param,test_nn_MultiheadAttention.ncnn.bin]",
  3123. "format": "ncnn",
  3124. "link": "https://github.com/lutzroeder/netron/issues/296"
  3125. },
  3126. {
  3127. "type": "ncnn",
  3128. "target": "vgg16.param",
  3129. "source": "https://raw.githubusercontent.com/Tencent/ncnn/master/benchmark/vgg16.param",
  3130. "format": "ncnn",
  3131. "link": "https://github.com/Tencent/ncnn"
  3132. },
  3133. {
  3134. "type": "nnabla",
  3135. "target": "Resnet-18.nnp",
  3136. "source": "https://nnabla.org/pretrained-models/nnp_models/imagenet/Resnet-18/Resnet-18.nnp",
  3137. "format": "nnabla v0.1",
  3138. "link": "https://nnabla.readthedocs.io/en/latest/python/api/models/imagenet.html"
  3139. },
  3140. {
  3141. "type": "nnabla",
  3142. "target": "MobileNet-v2.nnp",
  3143. "source": "https://nnabla.org/pretrained-models/nnp_models/imagenet/MobileNet-v2/MobileNet-v2.nnp",
  3144. "format": "nnabla v0.1",
  3145. "link": "https://nnabla.readthedocs.io/en/latest/python/api/models/imagenet.html"
  3146. },
  3147. {
  3148. "type": "nnabla",
  3149. "target": "SqueezeNet-1.1.nnp",
  3150. "source": "https://nnabla.org/pretrained-models/nnp_models/imagenet/SqueezeNet-1.1/SqueezeNet-1.1.nnp",
  3151. "format": "nnabla v0.1",
  3152. "link": "https://nnabla.readthedocs.io/en/latest/python/api/models/imagenet.html"
  3153. },
  3154. {
  3155. "type": "nnabla",
  3156. "target": "NIN.nnp",
  3157. "source": "https://nnabla.org/pretrained-models/nnp_models/imagenet/NIN/NIN.nnp",
  3158. "format": "nnabla v0.1",
  3159. "link": "https://nnabla.readthedocs.io/en/latest/python/api/models/imagenet.html"
  3160. },
  3161. {
  3162. "type": "nnabla",
  3163. "target": "ShuffleNet-0.5x.nnp",
  3164. "source": "https://nnabla.org/pretrained-models/nnp_models/imagenet/ShuffleNet-0.5x/ShuffleNet-0.5x.nnp",
  3165. "format": "nnabla v0.1",
  3166. "link": "https://nnabla.readthedocs.io/en/latest/python/api/models/imagenet.html"
  3167. },
  3168. {
  3169. "type": "numpy",
  3170. "target": "cifar10-1w-1a.npz",
  3171. "source": "https://raw.githubusercontent.com/Xilinx/BNN-PYNQ/master/bnn/src/training/cifar10-1w-1a.npz",
  3172. "format": "NumPy Zip",
  3173. "link": "https://github.com/Xilinx/BNN-PYNQ"
  3174. },
  3175. {
  3176. "type": "numpy",
  3177. "target": "mlp.npz",
  3178. "source": "https://github.com/lutzroeder/netron/files/6225731/mlp.zip[mlp.npz]",
  3179. "format": "NumPy Zip",
  3180. "link": "https://github.com/lutzroeder/netron/issues/711"
  3181. },
  3182. {
  3183. "type": "numpy",
  3184. "target": "mobilenet_v2_normal_72820.pkl",
  3185. "source": "https://data.megengine.org.cn/models/weights/mobilenet_v2_normal_72820.pkl",
  3186. "format": "NumPy Weights",
  3187. "link": "https://github.com/MegEngine/Models/tree/master/official/quantization"
  3188. },
  3189. {
  3190. "type": "numpy",
  3191. "target": "numpy.array.pkl",
  3192. "source": "https://github.com/lutzroeder/netron/files/6233588/numpy.array.pkl.zip[numpy.array.pkl]",
  3193. "format": "NumPy NDArray",
  3194. "link": "https://github.com/lutzroeder/netron/issues/711"
  3195. },
  3196. {
  3197. "type": "numpy",
  3198. "target": "R-50.pkl",
  3199. "source": "https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl",
  3200. "format": "NumPy Weights",
  3201. "link": "https://github.com/facebookresearch/Detectron"
  3202. },
  3203. {
  3204. "type": "numpy",
  3205. "target": "tensor.npy",
  3206. "source": "https://github.com/lutzroeder/netron/files/6225732/tensor.npy.zip[tensor.npy]",
  3207. "format": "NumPy Array",
  3208. "link": "https://github.com/lutzroeder/netron/issues/711"
  3209. },
  3210. {
  3211. "type": "onnx",
  3212. "target": "arcface-resnet100.onnx",
  3213. "source": "https://s3.amazonaws.com/onnx-model-zoo/arcface/resnet100/resnet100.onnx",
  3214. "format": "ONNX v3",
  3215. "link": "https://github.com/onnx/models/tree/main/models/face_recognition/ArcFace"
  3216. },
  3217. {
  3218. "type": "onnx",
  3219. "target": "bidaf-9.onnx.zip",
  3220. "source": "https://github.com/lutzroeder/netron/files/6572387/bidaf-9.onnx.zip",
  3221. "format": "ONNX v4",
  3222. "producer": "CNTK 2.7",
  3223. "link": "https://github.com/lutzroeder/netron/issues/6"
  3224. },
  3225. {
  3226. "type": "onnx",
  3227. "target": "bert-base-uncased.onnx.zip",
  3228. "source": "https://github.com/lutzroeder/netron/files/7705191/bert-base-uncased.onnx.zip",
  3229. "format": "ONNX v7",
  3230. "link": "https://github.com/lutzroeder/netron/issues/6"
  3231. },
  3232. {
  3233. "type": "onnx",
  3234. "target": "bertsquad-10.zip",
  3235. "source": "https://github.com/lutzroeder/netron/files/5251086/bertsquad-10.zip",
  3236. "format": "ONNX v5",
  3237. "producer": "tf2onnx 1.5.2",
  3238. "link": "https://github.com/onnx/models/blob/master/text/machine_comprehension/bert-squad/README.md"
  3239. },
  3240. {
  3241. "type": "onnx",
  3242. "target": "mnist_bfloat16.onnx",
  3243. "source": "https://github.com/lutzroeder/netron/files/8556399/mnist_bfloat16.onnx.zip[mnist_bfloat16.onnx]",
  3244. "format": "ONNX v4",
  3245. "producer": "pytorch 1.12.0",
  3246. "link": "https://github.com/lutzroeder/netron/issues/6"
  3247. },
  3248. {
  3249. "type": "onnx",
  3250. "target": "bvlc_alexnet_opset_3.onnx.zip",
  3251. "source": "https://github.com/lutzroeder/netron/files/5296267/bvlc_alexnet_opset_3.onnx.zip",
  3252. "format": "ONNX v3",
  3253. "link": "https://github.com/lutzroeder/netron/issues/6"
  3254. },
  3255. {
  3256. "type": "onnx",
  3257. "target": "bvlc_googlenet_opset_9.onnx",
  3258. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/bvlc_googlenet.tar.gz[bvlc_googlenet/model.onnx]",
  3259. "link": "https://github.com/onnx/models/tree/main/bvlc_googlenet"
  3260. },
  3261. {
  3262. "type": "onnx",
  3263. "target": "candy.onnx",
  3264. "source": "https://raw.githubusercontent.com/Microsoft/Windows-Machine-Learning/master/Samples/FNSCandyStyleTransfer/UWP/cs/Assets/candy.onnx",
  3265. "format": "ONNX v3",
  3266. "link": "https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/FNSCandyStyleTransfer/UWP/cs/Assets"
  3267. },
  3268. {
  3269. "type": "onnx",
  3270. "target": "candy.ort",
  3271. "source": "https://github.com/lutzroeder/netron/files/6844795/candy.ort.zip[candy.ort]",
  3272. "format": "ONNX Runtime v3",
  3273. "link": "https://github.com/lutzroeder/netron/issues/767"
  3274. },
  3275. {
  3276. "type": "onnx",
  3277. "target": "cnn.onnx",
  3278. "source": "https://github.com/lutzroeder/netron/files/7148909/cnn.onnx.zip[cnn.onnx]",
  3279. "format": "ONNX v6",
  3280. "action": "skip-render",
  3281. "link": "https://github.com/lutzroeder/netron/issues/589"
  3282. },
  3283. {
  3284. "type": "onnx",
  3285. "target": "complex_init.onnx",
  3286. "source": "https://github.com/lutzroeder/netron/files/8582128/complex_init.onnx.zip[complex_init.onnx]",
  3287. "format": "ONNX v4",
  3288. "link": "https://github.com/lutzroeder/netron/issues/905"
  3289. },
  3290. {
  3291. "type": "onnx",
  3292. "target": "conv_autopad.onnx",
  3293. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/conv_autopad.onnx",
  3294. "format": "ONNX v3",
  3295. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3296. },
  3297. {
  3298. "type": "onnx",
  3299. "target": "coo_normal_sparse.onnx",
  3300. "source": "https://github.com/lutzroeder/netron/files/6080534/coo_normal_sparse.onnx.zip[coo_normal_sparse.onnx]",
  3301. "format": "ONNX v7",
  3302. "link": "https://github.com/lutzroeder/netron/issues/693"
  3303. },
  3304. {
  3305. "type": "onnx",
  3306. "target": "denotation_Add_ImageNet1920WithImageMetadataBgr8_SRGB_0_255.onnx",
  3307. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataBgr8_SRGB_0_255.onnx]",
  3308. "format": "ONNX v3",
  3309. "assert": [ "model.graphs[0].nodes[0].outputs[0].arguments[0].type.denotation = Image(Bgr8,SRGB,NominalRange_0_255)" ],
  3310. "link": "https://github.com/lutzroeder/netron/issues/183"
  3311. },
  3312. {
  3313. "type": "onnx",
  3314. "target": "denotation_Add_ImageNet1920WithImageMetadataBgra8_SRGB_0_255.onnx",
  3315. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataBgra8_SRGB_0_255.onnx]",
  3316. "format": "ONNX v3",
  3317. "link": "https://github.com/lutzroeder/netron/issues/183"
  3318. },
  3319. {
  3320. "type": "onnx",
  3321. "target": "denotation_Add_ImageNet1920WithImageMetadataRgb8_SRGB_0_255.onnx",
  3322. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataRgb8_SRGB_0_255.onnx]",
  3323. "format": "ONNX v3",
  3324. "link": "https://github.com/lutzroeder/netron/issues/183"
  3325. },
  3326. {
  3327. "type": "onnx",
  3328. "target": "denotation_Add_ImageNet1920WithImageMetadataRgba8_SRGB_0_255.onnx",
  3329. "source": "https://github.com/lutzroeder/netron/files/2587943/onnx_denotation_models.zip[denotation_Add_ImageNet1920WithImageMetadataRgba8_SRGB_0_255.onnx]",
  3330. "format": "ONNX v3",
  3331. "link": "https://github.com/lutzroeder/netron/issues/183"
  3332. },
  3333. {
  3334. "type": "onnx",
  3335. "target": "densenet121_opset_9.onnx",
  3336. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/densenet121.tar.gz[densenet121/model.onnx]"
  3337. },
  3338. {
  3339. "type": "onnx",
  3340. "target": "DocumentClassification.onnx",
  3341. "source": "https://github.com/lutzroeder/netron/files/2592479/DocumentClassification.onnx.zip[DocumentClassification.onnx]",
  3342. "format": "ONNX v3",
  3343. "link": "https://github.com/lutzroeder/netron/issues/6"
  3344. },
  3345. {
  3346. "type": "onnx",
  3347. "target": "EfficientDet-d0.onnx.zip",
  3348. "source": "https://github.com/lutzroeder/netron/files/7786937/EfficientDet-d0.onnx.zip",
  3349. "format": "ONNX v6",
  3350. "link": "https://github.com/lutzroeder/netron/issues/589"
  3351. },
  3352. {
  3353. "type": "onnx",
  3354. "target": "eisber_model3.pbtxt",
  3355. "source": "https://github.com/lutzroeder/netron/files/4209090/eisber_model3.pbtxt.zip[eisber_model3.pbtxt]",
  3356. "format": "ONNX v3",
  3357. "link": "https://github.com/lutzroeder/netron/issues/139"
  3358. },
  3359. {
  3360. "type": "onnx",
  3361. "target": "eisber_model3.pbtxt.gz",
  3362. "source": "https://github.com/lutzroeder/netron/files/6490172/eisber_model3.pbtxt.gz",
  3363. "format": "ONNX v3",
  3364. "link": "https://github.com/lutzroeder/netron/issues/249"
  3365. },
  3366. {
  3367. "type": "onnx",
  3368. "target": "eisber_model3_invalid.pbtxt",
  3369. "source": "https://github.com/lutzroeder/netron/files/5011185/eisber_model3_invalid.pbtxt.zip[eisber_model3_invalid.pbtxt]",
  3370. "error": "File text format is not onnx.ModelProto (Unexpected '}' instead of ':' at 6:3) in 'eisber_model3_invalid.pbtxt'.",
  3371. "link": "https://github.com/lutzroeder/netron/issues/139"
  3372. },
  3373. {
  3374. "type": "onnx",
  3375. "target": "emotion-ferplus-8.onnx",
  3376. "source": "https://github.com/onnx/models/raw/main/vision/body_analysis/emotion_ferplus/model/emotion-ferplus-8.onnx",
  3377. "format": "ONNX v3",
  3378. "link": "https://github.com/onnx/models/tree/main/vision/body_analysis/emotion_ferplus"
  3379. },
  3380. {
  3381. "type": "onnx",
  3382. "target": "end2end_tfc_w1a1_oqnt_streamlined.onnx",
  3383. "source": "https://github.com/lutzroeder/netron/files/4885362/end2end_tfc_w1a1_oqnt_streamlined.zip[end2end_tfc_w1a1_oqnt_streamlined.onnx]",
  3384. "format": "ONNX v4",
  3385. "link": "https://github.com/lutzroeder/netron/issues/532"
  3386. },
  3387. {
  3388. "type": "onnx",
  3389. "target": "Exermote.onnx",
  3390. "source": "https://github.com/lutzroeder/netron/files/2592478/Exermote.onnx.zip[Exermote.onnx]",
  3391. "format": "ONNX v3",
  3392. "link": "https://github.com/lutzroeder/netron/issues/6"
  3393. },
  3394. {
  3395. "type": "onnx",
  3396. "target": "FastStyleNet.onnx",
  3397. "source": "https://raw.githubusercontent.com/tkat0/chainer-nnvm-example/master/models/chainer-fast-neuralstyle/FastStyleNet.onnx",
  3398. "format": "ONNX v1",
  3399. "producer": "Chainer 3.2.0"
  3400. },
  3401. {
  3402. "type": "onnx",
  3403. "target": "FCLayer_graph.onnx",
  3404. "source": "https://raw.githubusercontent.com/Xilinx/finn/master/notebooks/FCLayer_graph.onnx",
  3405. "format": "ONNX v6",
  3406. "link": "https://github.com/Xilinx/finn/tree/master/notebooks"
  3407. },
  3408. {
  3409. "type": "onnx",
  3410. "target": "gpt2-10.onnx.zip",
  3411. "source": "https://github.com/lutzroeder/netron/files/7786929/gpt2-10.onnx.zip",
  3412. "format": "ONNX v6",
  3413. "link": "https://github.com/lutzroeder/netron/issues/6"
  3414. },
  3415. {
  3416. "type": "onnx",
  3417. "target": "input_0.pb",
  3418. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/shufflenet.tar.gz[shufflenet/test_data_set_0/input_0.pb]",
  3419. "format": "ONNX Tensor",
  3420. "link": "https://github.com/lutzroeder/netron/issues/550"
  3421. },
  3422. {
  3423. "type": "onnx",
  3424. "target": "inception_v1_opset_9.onnx",
  3425. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/inception_v1.tar.gz[inception_v1/model.onnx]"
  3426. },
  3427. {
  3428. "type": "onnx",
  3429. "target": "inception_v2_opset_6.onnx.zip",
  3430. "source": "https://github.com/lutzroeder/netron/files/6572388/inception_v2_opset_6.onnx.zip",
  3431. "format": "ONNX v3",
  3432. "link": "https://github.com/lutzroeder/netron/issues/6"
  3433. },
  3434. {
  3435. "type": "onnx",
  3436. "target": "inception_v2_opset_9.onnx.zip",
  3437. "source": "https://github.com/lutzroeder/netron/files/6572391/inception_v2_opset_9.onnx.zip",
  3438. "format": "ONNX v3",
  3439. "link": "https://github.com/lutzroeder/netron/issues/6"
  3440. },
  3441. {
  3442. "type": "onnx",
  3443. "target": "keras2onnx.onnx",
  3444. "source": "https://github.com/lutzroeder/netron/files/5738366/keras2onnx.onnx.zip[keras2onnx.onnx]",
  3445. "error": "File format is not onnx.ModelProto (Unexpected end of file) in 'keras2onnx.onnx'.",
  3446. "link": "https://github.com/lutzroeder/netron/issues/6"
  3447. },
  3448. {
  3449. "type": "onnx",
  3450. "target": "Kmeans.onnx",
  3451. "source": "https://github.com/lutzroeder/netron/files/2592495/Kmeans.onnx.zip[Kmeans.onnx]",
  3452. "format": "ONNX v3",
  3453. "producer": "ML.NET 0.7.27009.0",
  3454. "link": "https://github.com/lutzroeder/netron/issues/6"
  3455. },
  3456. {
  3457. "type": "onnx",
  3458. "target": "Kmeans.pbtxt",
  3459. "source": "https://github.com/lutzroeder/netron/files/4209089/Kmeans.pbtxt.zip[Kmeans.pbtxt]",
  3460. "format": "ONNX v3",
  3461. "producer": "ML.NET 0.7.27009.0",
  3462. "link": "https://github.com/lutzroeder/netron/issues/139"
  3463. },
  3464. {
  3465. "type": "onnx",
  3466. "target": "LabelEncoder.onnx",
  3467. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/LabelEncoder.onnx",
  3468. "format": "ONNX v3",
  3469. "link": "https://github.com/Microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3470. },
  3471. {
  3472. "type": "onnx",
  3473. "target": "last_hidden_state_crf_jud.onnx",
  3474. "source": "https://github.com/lutzroeder/netron/files/7148912/last_hidden_state_crf_jud.onnx.zip[last_hidden_state_crf_jud.onnx]",
  3475. "format": "ONNX v6",
  3476. "action": "skip-render",
  3477. "link": "https://github.com/lutzroeder/netron/issues/589"
  3478. },
  3479. {
  3480. "type": "onnx",
  3481. "target": "maskDet_opt.onnx",
  3482. "source": "https://github.com/lutzroeder/netron/files/8238283/maskDet_opt.onnx.zip[maskDet_opt.onnx]",
  3483. "format": "ONNX v4",
  3484. "link": "https://github.com/lutzroeder/netron/issues/6"
  3485. },
  3486. {
  3487. "type": "onnx",
  3488. "target": "maskrcnn.onnx.zip",
  3489. "source": "https://github.com/lutzroeder/netron/files/5322320/maskrcnn.onnx.zip",
  3490. "format": "ONNX v6",
  3491. "link": "https://github.com/lutzroeder/netron/issues/6"
  3492. },
  3493. {
  3494. "type": "onnx",
  3495. "target": "mnist.onnx",
  3496. "source": "https://raw.githubusercontent.com/Microsoft/Windows-Machine-Learning/master/Samples/MNIST/Tutorial/cs/Assets/mnist.onnx",
  3497. "format": "ONNX v3",
  3498. "link": "https://github.com/Microsoft/Windows-Machine-Learning/tree/master/Samples/MNIST/Tutorial/cs/Assets"
  3499. },
  3500. {
  3501. "type": "onnx",
  3502. "target": "mlnet_encoder.onnx",
  3503. "source": "https://raw.githubusercontent.com/Microsoft/onnxruntime/master/onnxruntime/test/testdata/mlnet_encoder.onnx",
  3504. "format": "ONNX v3",
  3505. "link": "https://github.com/Microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3506. },
  3507. {
  3508. "type": "onnx",
  3509. "target": "model_local_func_test.onnx",
  3510. "source": "https://github.com/lutzroeder/netron/files/6845111/model_local_func_test.onnx.zip[model_local_func_test.onnx]",
  3511. "format": "ONNX v8",
  3512. "link": "https://github.com/lutzroeder/netron/issues/773"
  3513. },
  3514. {
  3515. "type": "onnx",
  3516. "target": "netron_issue_119.onnx",
  3517. "source": "https://github.com/lutzroeder/netron/files/4260629/netron_issue_119.zip[netron_issue_119.onnx]",
  3518. "format": "ONNX v4",
  3519. "link": "https://github.com/lutzroeder/netron/issues/119"
  3520. },
  3521. {
  3522. "type": "onnx",
  3523. "target": "netron_issue168_onnx_if.pbtxt",
  3524. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_if.pbtxt]",
  3525. "format": "ONNX v3",
  3526. "link": "https://github.com/lutzroeder/netron/issues/168"
  3527. },
  3528. {
  3529. "type": "onnx",
  3530. "target": "netron_issue168_onnx_loop.pbtxt",
  3531. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_loop.pbtxt]",
  3532. "format": "ONNX v3",
  3533. "link": "https://github.com/lutzroeder/netron/issues/168"
  3534. },
  3535. {
  3536. "type": "onnx",
  3537. "target": "netron_issue168_onnx_scan.pbtxt",
  3538. "source": "https://github.com/lutzroeder/netron/files/3239859/netron_issue168_onnx.zip[netron_issue168_onnx_scan.pbtxt]",
  3539. "format": "ONNX v3",
  3540. "link": "https://github.com/lutzroeder/netron/issues/168"
  3541. },
  3542. {
  3543. "type": "onnx",
  3544. "target": "netron_issue_845.onnx",
  3545. "source": "https://github.com/lutzroeder/netron/files/7604948/netron_issue_845.onnx.zip[netron_issue_845.onnx]",
  3546. "format": "ONNX v4",
  3547. "link": "https://github.com/lutzroeder/netron/issues/6"
  3548. },
  3549. {
  3550. "type": "onnx",
  3551. "target": "optional_1.onnx",
  3552. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/optional_1.onnx",
  3553. "format": "ONNX v3",
  3554. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3555. },
  3556. {
  3557. "type": "onnx",
  3558. "target": "optional_type.onnx",
  3559. "source": "https://github.com/lutzroeder/netron/files/8746170/optional_type.onnx.zip[optional_type.onnx]",
  3560. "format": "ONNX v8",
  3561. "link": "https://github.com/lutzroeder/netron/issues/914"
  3562. },
  3563. {
  3564. "type": "onnx",
  3565. "target": "ort_github_issue_4031.onnx.ort",
  3566. "source": "https://github.com/lutzroeder/netron/files/8191468/ort_github_issue_4031.onnx.ort.zip[ort_github_issue_4031.onnx.ort]",
  3567. "format": "ONNX Runtime v7",
  3568. "link": "https://github.com/lutzroeder/netron/issues/767"
  3569. },
  3570. {
  3571. "type": "onnx",
  3572. "target": "resnet50_opset_9.onnx.zip",
  3573. "source": "https://github.com/lutzroeder/netron/files/5296268/resnet50_opset_9.onnx.zip",
  3574. "format": "ONNX v3",
  3575. "link": "https://github.com/lutzroeder/netron/issues/6"
  3576. },
  3577. {
  3578. "type": "onnx",
  3579. "target": "reshape_opset_4.pb",
  3580. "source": "https://github.com/lutzroeder/netron/files/2592375/reshape_opset.zip[reshape_opset_4.pb]",
  3581. "format": "ONNX v3",
  3582. "link": "https://github.com/lutzroeder/netron/pull/97"
  3583. },
  3584. {
  3585. "type": "onnx",
  3586. "target": "reshape_opset_6.pb",
  3587. "source": "https://github.com/lutzroeder/netron/files/2592375/reshape_opset.zip[reshape_opset_6.pb]",
  3588. "format": "ONNX v3",
  3589. "link": "https://github.com/lutzroeder/netron/pull/97"
  3590. },
  3591. {
  3592. "type": "onnx",
  3593. "target": "s2.onnx",
  3594. "source": "https://github.com/lutzroeder/netron/files/6191354/s2.onnx.zip[s2.onnx]",
  3595. "format": "ONNX v6",
  3596. "link": "https://github.com/lutzroeder/netron/issues/647"
  3597. },
  3598. {
  3599. "type": "onnx",
  3600. "target": "shufflenet_float16.onnx",
  3601. "source": "https://github.com/lutzroeder/netron/files/2592368/shufflenet_float16.onnx.zip[shufflenet_float16.onnx]",
  3602. "format": "ONNX v3",
  3603. "link": "https://github.com/lutzroeder/netron/issues/186"
  3604. },
  3605. {
  3606. "type": "onnx",
  3607. "target": "shufflenet_opset_9.onnx",
  3608. "source": "https://s3.amazonaws.com/download.onnx/models/opset_9/shufflenet.tar.gz[shufflenet/model.onnx]",
  3609. "format": "ONNX v3",
  3610. "link": "https://github.com/onnx/models/tree/main/shufflenet"
  3611. },
  3612. {
  3613. "type": "onnx",
  3614. "target": "sklearn_bin_voting_classifier_soft.ort",
  3615. "source": "https://github.com/lutzroeder/netron/files/8191675/sklearn_bin_voting_classifier_soft.ort.zip[sklearn_bin_voting_classifier_soft.ort]",
  3616. "format": "ONNX Runtime v6",
  3617. "link": "https://github.com/lutzroeder/netron/issues/767"
  3618. },
  3619. {
  3620. "type": "onnx",
  3621. "target": "sparse_const.onnx",
  3622. "source": "https://github.com/lutzroeder/netron/files/5198627/sparse_const.zip[sparse_const.onnx]",
  3623. "format": "ONNX v7",
  3624. "link": "https://github.com/lutzroeder/netron/issues/6"
  3625. },
  3626. {
  3627. "type": "onnx",
  3628. "target": "sparse_initializer_as_output.onnx",
  3629. "source": "https://github.com/lutzroeder/netron/files/6512243/sparse_initializer_as_output.onnx.zip[sparse_initializer_as_output.onnx]",
  3630. "format": "ONNX v7",
  3631. "link": "https://github.com/lutzroeder/netron/issues/741"
  3632. },
  3633. {
  3634. "type": "onnx",
  3635. "target": "squeezenet.onnx",
  3636. "source": "https://raw.githubusercontent.com/onnx/tutorials/master/tutorials/assets/squeezenet.onnx",
  3637. "format": "ONNX v1",
  3638. "producer": "pytorch 0.2"
  3639. },
  3640. {
  3641. "type": "onnx",
  3642. "target": "squeezenet1.1.onnx",
  3643. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.onnx",
  3644. "format": "ONNX v3",
  3645. "link": "https://github.com/onnx/models/tree/main/vision/classification/squeezenet"
  3646. },
  3647. {
  3648. "type": "onnx",
  3649. "target": "squeezenet1.1_shape.onnx",
  3650. "source": "https://github.com/lutzroeder/netron/files/3935903/squeezenet1.1_shape.onnx.zip[squeezenet1.1_shape.onnx]",
  3651. "format": "ONNX v3",
  3652. "link": "https://github.com/lutzroeder/netron/issues/6"
  3653. },
  3654. {
  3655. "type": "onnx",
  3656. "target": "squeezenet1.1.pb",
  3657. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.onnx",
  3658. "format": "ONNX v3",
  3659. "link": "https://github.com/onnx/models/tree/main/models/image_classification/squeezenet"
  3660. },
  3661. {
  3662. "type": "onnx",
  3663. "target": "squeezenet1.1.tgz",
  3664. "source": "https://s3.amazonaws.com/onnx-model-zoo/squeezenet/squeezenet1.1/squeezenet1.1.tar.gz",
  3665. "format": "ONNX v3",
  3666. "link": "https://github.com/onnx/models/tree/main/models/image_classification/squeezenet"
  3667. },
  3668. {
  3669. "type": "onnx",
  3670. "target": "ssd.onnx.zip",
  3671. "source": "https://github.com/lutzroeder/netron/files/5296269/ssd.onnx.zip",
  3672. "format": "ONNX v4",
  3673. "link": "https://github.com/lutzroeder/netron/issues/6"
  3674. },
  3675. {
  3676. "type": "onnx",
  3677. "target": "super_resolution.onnx",
  3678. "source": "https://gist.github.com/zhreshold/bcda4716699ac97ea44f791c24310193/raw/b385b1b242dc89a35dd808235b885ed8a19aedc1/super_resolution.onnx",
  3679. "format": "ONNX",
  3680. "link": "https://gist.github.com/zhreshold/bcda4716699ac97ea44f791c24310193"
  3681. },
  3682. {
  3683. "type": "onnx",
  3684. "target": "super-resolution-10.onnx",
  3685. "source": "https://media.githubusercontent.com/media/onnx/models/main/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx",
  3686. "format": "ONNX v4",
  3687. "producer": "pytorch 1.1",
  3688. "link": "https://github.com/onnx/models/tree/main/vision/super_resolution/sub_pixel_cnn_2016"
  3689. },
  3690. {
  3691. "type": "onnx",
  3692. "target": "super_resolution_0.2.onnx",
  3693. "source": "https://gist.github.com/zhreshold/bcda4716699ac97ea44f791c24310193/raw/93672b029103648953c4e5ad3ac3aadf346a4cdc/super_resolution_0.2.onnx",
  3694. "format": "ONNX v1",
  3695. "producer": "pytorch 0.2",
  3696. "link": "https://gist.github.com/zhreshold/bcda4716699ac97ea44f791c24310193"
  3697. },
  3698. {
  3699. "type": "onnx",
  3700. "target": "test_LSTM_tanh_bidirectional.onnx",
  3701. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/CNTK/test_LSTM.tanh.bidirectional//model.onnx",
  3702. "format": "ONNX v3",
  3703. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3704. },
  3705. {
  3706. "type": "onnx",
  3707. "target": "test_RNN_bidirectional_one_layer_relu.onnx",
  3708. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/CNTK/test_RNN.bidirectional.one_layer.relu//model.onnx",
  3709. "format": "ONNX v3",
  3710. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3711. },
  3712. {
  3713. "type": "onnx",
  3714. "target": "test_lstm_with_peepholes.onnx",
  3715. "source": "https://raw.githubusercontent.com/onnx/onnx/master/onnx/backend/test/data/node/test_lstm_with_peepholes/model.onnx",
  3716. "format": "ONNX v7",
  3717. "link": "https://github.com/onnx/onnx/tree/master/onnx/backend/test/data"
  3718. },
  3719. {
  3720. "type": "onnx",
  3721. "target": "text_constant.txt",
  3722. "source": "https://github.com/lutzroeder/netron/files/8189630/text_constant.txt.zip[text_constant.txt]",
  3723. "format": "ONNX Text v0",
  3724. "link": "https://github.com/lutzroeder/netron/issues/884"
  3725. },
  3726. {
  3727. "type": "onnx",
  3728. "target": "text_function.txt",
  3729. "source": "https://github.com/lutzroeder/netron/files/8189629/text_function.txt.zip[text_function.txt]",
  3730. "format": "ONNX Text v8",
  3731. "link": "https://github.com/lutzroeder/netron/issues/884"
  3732. },
  3733. {
  3734. "type": "onnx",
  3735. "target": "text_example.txt",
  3736. "source": "https://github.com/lutzroeder/netron/files/8190032/text_example.txt.zip[text_example.txt]",
  3737. "format": "ONNX Text v7",
  3738. "link": "https://github.com/lutzroeder/netron/issues/884"
  3739. },
  3740. {
  3741. "type": "onnx",
  3742. "target": "yolov3.onnx",
  3743. "source": "https://github.com/lutzroeder/netron/files/5581031/yolov3.onnx.zip[yolov3.onnx]",
  3744. "format": "ONNX v5",
  3745. "producer": "keras2onnx 1.5.1",
  3746. "link": "https://github.com/lutzroeder/netron/issues/6"
  3747. },
  3748. {
  3749. "type": "onnx",
  3750. "target": "vgg19.onnx.zip",
  3751. "source": "https://github.com/lutzroeder/netron/files/6558105/vgg19.onnx.zip",
  3752. "format": "ONNX v3",
  3753. "link": "https://github.com/lutzroeder/netron/issues/6"
  3754. },
  3755. {
  3756. "type": "onnx",
  3757. "target": "zipmap_int64float.onnx",
  3758. "source": "https://raw.githubusercontent.com/microsoft/onnxruntime/master/onnxruntime/test/testdata/zipmap_int64float.onnx",
  3759. "format": "ONNX v3",
  3760. "link": "https://github.com/microsoft/onnxruntime/tree/master/onnxruntime/test/testdata"
  3761. },
  3762. {
  3763. "type": "om",
  3764. "target": "hwhiaimodel-subgraph.om",
  3765. "source": "https://github.com/lutzroeder/netron/files/7114899/hwhiaimodel-subgraph.om.zip[hwhiaimodel-subgraph.om]",
  3766. "format": "DaVinci OM",
  3767. "link": "https://github.com/lutzroeder/netron/issues/799"
  3768. },
  3769. {
  3770. "type": "om",
  3771. "target": "netron_issue_788.om",
  3772. "source": "https://github.com/lutzroeder/netron/files/7104677/netron_issue_788.om.zip[netron_issue_788.om]",
  3773. "format": "DaVinci OM",
  3774. "link": "https://github.com/lutzroeder/netron/issues/799"
  3775. },
  3776. {
  3777. "type": "om",
  3778. "target": "netron_issue_798.om",
  3779. "source": "https://github.com/lutzroeder/netron/files/7104598/netron_issue_798.om.zip[netron_issue_798.om]",
  3780. "format": "DaVinci OM",
  3781. "link": "https://github.com/lutzroeder/netron/issues/799"
  3782. },
  3783. {
  3784. "type": "om",
  3785. "target": "resnet50v1_framework_tensorflow_aipp_0_batch_1_input_fp16_output_FP32.om",
  3786. "source": "https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/turing/resourcecenter/model/Resnet50V1/zh/1.1/ATC_Resnet50_V1_from_Tensorflow_Ascend310.zip[resnet50v1_framework_tensorflow_aipp_0_batch_1_input_fp16_output_FP32.om]",
  3787. "format": "DaVinci OM",
  3788. "link": "https://www.hiascend.com/zh/software/modelzoo/detail/1/7548422b6b9c4a809114435f6b128bb6"
  3789. },
  3790. {
  3791. "type": "openvino",
  3792. "target": "2018_R3_age-gender-recognition-retail-0013.xml,2018_R3_age-gender-recognition-retail-0013.bin",
  3793. "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",
  3794. "format": "OpenVINO IR",
  3795. "link": "https://download.01.org/openvinotoolkit"
  3796. },
  3797. {
  3798. "type": "openvino",
  3799. "target": "2018_R3_rm_cnn4a.xml",
  3800. "source": "https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/rm_cnn4a_smbr/rm_cnn4a.xml",
  3801. "format": "OpenVINO IR",
  3802. "link": "https://download.01.org/openvinotoolkit"
  3803. },
  3804. {
  3805. "type": "openvino",
  3806. "target": "2018_R3_rm_lstm4f.xml,2018_R3_rm_lstm4f.bin",
  3807. "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",
  3808. "format": "OpenVINO IR",
  3809. "link": "https://download.01.org/openvinotoolkit"
  3810. },
  3811. {
  3812. "type": "openvino",
  3813. "target": "2018_R3_wsj_dnn5b.xml",
  3814. "source": "https://download.01.org/openvinotoolkit/2018_R3/models_contrib/GNA/wsj_dnn5b_smbr/wsj_dnn5b.xml",
  3815. "format": "OpenVINO IR",
  3816. "link": "https://download.01.org/openvinotoolkit"
  3817. },
  3818. {
  3819. "type": "openvino",
  3820. "target": "2018_R4_emotions-recognition-retail-0003.bin,2018_R4_emotions-recognition-retail-0003.xml",
  3821. "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",
  3822. "format": "OpenVINO IR",
  3823. "link": "https://download.01.org/openvinotoolkit"
  3824. },
  3825. {
  3826. "type": "openvino",
  3827. "target": "2018_R4_face-detection-adas-0001.xml",
  3828. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-detection-adas-0001/FP32/face-detection-adas-0001.xml",
  3829. "format": "OpenVINO IR",
  3830. "link": "https://download.01.org/openvinotoolkit"
  3831. },
  3832. {
  3833. "type": "openvino",
  3834. "target": "2018_R4_face-detection-retail-0004.xml",
  3835. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-detection-retail-0004/FP32/face-detection-retail-0004.xml",
  3836. "format": "OpenVINO IR",
  3837. "link": "https://download.01.org/openvinotoolkit"
  3838. },
  3839. {
  3840. "type": "openvino",
  3841. "target": "2018_R4_face-person-detection-retail-0002.xml",
  3842. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-person-detection-retail-0002/FP32/face-person-detection-retail-0002.xml",
  3843. "format": "OpenVINO IR",
  3844. "link": "https://download.01.org/openvinotoolkit"
  3845. },
  3846. {
  3847. "type": "openvino",
  3848. "target": "2018_R4_face-reidentification-retail-0071.xml",
  3849. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/face-reidentification-retail-0071/FP32/face-reidentification-retail-0071.xml",
  3850. "format": "OpenVINO IR",
  3851. "link": "https://download.01.org/openvinotoolkit"
  3852. },
  3853. {
  3854. "type": "openvino",
  3855. "target": "2018_R4_facial-landmarks-35-adas-0001.xml",
  3856. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/facial-landmarks-35-adas-0001/FP32/facial-landmarks-35-adas-0001.xml",
  3857. "format": "OpenVINO IR",
  3858. "link": "https://download.01.org/openvinotoolkit"
  3859. },
  3860. {
  3861. "type": "openvino",
  3862. "target": "2018_R4_head-pose-estimation-adas-0001.xml",
  3863. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml",
  3864. "format": "OpenVINO IR",
  3865. "link": "https://download.01.org/openvinotoolkit"
  3866. },
  3867. {
  3868. "type": "openvino",
  3869. "target": "2018_R4_human-pose-estimation-0001.xml",
  3870. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml",
  3871. "format": "OpenVINO IR",
  3872. "link": "https://download.01.org/openvinotoolkit"
  3873. },
  3874. {
  3875. "type": "openvino",
  3876. "target": "2018_R4_landmarks-regression-retail-0009.xml",
  3877. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml",
  3878. "format": "OpenVINO IR",
  3879. "link": "https://download.01.org/openvinotoolkit"
  3880. },
  3881. {
  3882. "type": "openvino",
  3883. "target": "2018_R4_person-attributes-recognition-crossroad-0031.xml",
  3884. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-attributes-recognition-crossroad-0031/FP32/person-attributes-recognition-crossroad-0031.xml",
  3885. "format": "OpenVINO IR",
  3886. "link": "https://download.01.org/openvinotoolkit"
  3887. },
  3888. {
  3889. "type": "openvino",
  3890. "target": "2018_R4_pedestrian-detection-adas-0002.xml",
  3891. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/pedestrian-detection-adas-0002/FP32/pedestrian-detection-adas-0002.xml",
  3892. "format": "OpenVINO IR",
  3893. "link": "https://download.01.org/openvinotoolkit"
  3894. },
  3895. {
  3896. "type": "openvino",
  3897. "target": "2018_R4_person-detection-retail-0001.xml",
  3898. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-retail-0001/FP32/person-detection-retail-0001.xml",
  3899. "format": "OpenVINO IR",
  3900. "link": "https://download.01.org/openvinotoolkit"
  3901. },
  3902. {
  3903. "type": "openvino",
  3904. "target": "2018_R4_person-detection-retail-0013.xml",
  3905. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-retail-0013/FP32/person-detection-retail-0013.xml",
  3906. "format": "OpenVINO IR",
  3907. "link": "https://download.01.org/openvinotoolkit"
  3908. },
  3909. {
  3910. "type": "openvino",
  3911. "target": "2018_R4_person-reidentification-retail-0031.xml",
  3912. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0031/FP32/person-reidentification-retail-0031.xml",
  3913. "format": "OpenVINO IR",
  3914. "link": "https://download.01.org/openvinotoolkit"
  3915. },
  3916. {
  3917. "type": "openvino",
  3918. "target": "2018_R4_person-reidentification-retail-0076.xml",
  3919. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0076/FP32/person-reidentification-retail-0076.xml",
  3920. "format": "OpenVINO IR",
  3921. "link": "https://download.01.org/openvinotoolkit"
  3922. },
  3923. {
  3924. "type": "openvino",
  3925. "target": "2018_R4_person-detection-action-recognition-0003.xml",
  3926. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-detection-action-recognition-0003/FP32/person-detection-action-recognition-0003.xml",
  3927. "format": "OpenVINO IR",
  3928. "link": "https://download.01.org/openvinotoolkit"
  3929. },
  3930. {
  3931. "type": "openvino",
  3932. "target": "2018_R4_person-reidentification-retail-0079.xml",
  3933. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/person-reidentification-retail-0079/FP32/person-reidentification-retail-0079.xml",
  3934. "format": "OpenVINO IR",
  3935. "link": "https://download.01.org/openvinotoolkit"
  3936. },
  3937. {
  3938. "type": "openvino",
  3939. "target": "2018_R4_person-vehicle-bike-detection-crossroad-0078.xml",
  3940. "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",
  3941. "format": "OpenVINO IR",
  3942. "link": "https://download.01.org/openvinotoolkit"
  3943. },
  3944. {
  3945. "type": "openvino",
  3946. "target": "2018_R4_road-segmentation-adas-0001.xml",
  3947. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/road-segmentation-adas-0001/FP32/road-segmentation-adas-0001.xml",
  3948. "format": "OpenVINO IR",
  3949. "link": "https://download.01.org/openvinotoolkit"
  3950. },
  3951. {
  3952. "type": "openvino",
  3953. "target": "2018_R5_age-gender-recognition-retail-0013.xml",
  3954. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml",
  3955. "format": "OpenVINO IR",
  3956. "link": "https://download.01.org/openvinotoolkit"
  3957. },
  3958. {
  3959. "type": "openvino",
  3960. "target": "2018_R5_emotions-recognition-retail-0003.xml,2018_R5_emotions-recognition-retail-0003.bin",
  3961. "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",
  3962. "format": "OpenVINO IR",
  3963. "link": "https://download.01.org/openvinotoolkit"
  3964. },
  3965. {
  3966. "type": "openvino",
  3967. "target": "2018_R5_face-detection-adas-0001.xml",
  3968. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-detection-adas-0001/FP32/face-detection-adas-0001.xml",
  3969. "format": "OpenVINO IR",
  3970. "link": "https://download.01.org/openvinotoolkit"
  3971. },
  3972. {
  3973. "type": "openvino",
  3974. "target": "2018_R5_face-detection-retail-0004.xml",
  3975. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-detection-retail-0004/FP32/face-detection-retail-0004.xml",
  3976. "format": "OpenVINO IR",
  3977. "link": "https://download.01.org/openvinotoolkit"
  3978. },
  3979. {
  3980. "type": "openvino",
  3981. "target": "2018_R5_face-person-detection-retail-0002.xml",
  3982. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-person-detection-retail-0002/FP32/face-person-detection-retail-0002.xml",
  3983. "format": "OpenVINO IR",
  3984. "link": "https://download.01.org/openvinotoolkit"
  3985. },
  3986. {
  3987. "type": "openvino",
  3988. "target": "2018_R5_face-reidentification-retail-0095.xml",
  3989. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/face-reidentification-retail-0095/FP32/face-reidentification-retail-0095.xml",
  3990. "format": "OpenVINO IR",
  3991. "link": "https://download.01.org/openvinotoolkit"
  3992. },
  3993. {
  3994. "type": "openvino",
  3995. "target": "2018_R5_facial-landmarks-35-adas-0001.xml",
  3996. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/facial-landmarks-35-adas-0001/FP32/facial-landmarks-35-adas-0001.xml",
  3997. "format": "OpenVINO IR",
  3998. "link": "https://download.01.org/openvinotoolkit"
  3999. },
  4000. {
  4001. "type": "openvino",
  4002. "target": "2018_R5_head-pose-estimation-adas-0001.xml",
  4003. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml",
  4004. "format": "OpenVINO IR",
  4005. "link": "https://download.01.org/openvinotoolkit"
  4006. },
  4007. {
  4008. "type": "openvino",
  4009. "target": "2018_R5_human-pose-estimation-0001.xml",
  4010. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml",
  4011. "format": "OpenVINO IR",
  4012. "link": "https://download.01.org/openvinotoolkit"
  4013. },
  4014. {
  4015. "type": "openvino",
  4016. "target": "2018_R5_landmarks-regression-retail-0009.xml",
  4017. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml",
  4018. "format": "OpenVINO IR",
  4019. "link": "https://download.01.org/openvinotoolkit"
  4020. },
  4021. {
  4022. "type": "openvino",
  4023. "target": "2018_R4_landmarks-regression-retail-0009-fp16.xml,2018_R4_landmarks-regression-retail-0009-fp16.bin",
  4024. "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",
  4025. "format": "OpenVINO IR",
  4026. "link": "https://download.01.org/openvinotoolkit"
  4027. },
  4028. {
  4029. "type": "openvino",
  4030. "target": "2018_R4_license-plate-recognition-barrier-0001.xml",
  4031. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/license-plate-recognition-barrier-0001/FP32/license-plate-recognition-barrier-0001.xml",
  4032. "format": "OpenVINO IR",
  4033. "link": "https://download.01.org/openvinotoolkit"
  4034. },
  4035. {
  4036. "type": "openvino",
  4037. "target": "2018_R4_pedestrian-and-vehicle-detector-adas-0001.xml",
  4038. "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",
  4039. "format": "OpenVINO IR",
  4040. "link": "https://download.01.org/openvinotoolkit"
  4041. },
  4042. {
  4043. "type": "openvino",
  4044. "target": "2018_R4_semantic-segmentation-adas-0001.xml",
  4045. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/semantic-segmentation-adas-0001/FP32/semantic-segmentation-adas-0001.xml",
  4046. "format": "OpenVINO IR",
  4047. "link": "https://download.01.org/openvinotoolkit"
  4048. },
  4049. {
  4050. "type": "openvino",
  4051. "target": "2018_R4_single-image-super-resolution-0034.xml",
  4052. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/single-image-super-resolution-0034/FP32/single-image-super-resolution-0034.xml",
  4053. "format": "OpenVINO IR",
  4054. "link": "https://download.01.org/openvinotoolkit"
  4055. },
  4056. {
  4057. "type": "openvino",
  4058. "target": "2018_R4_vehicle-attributes-recognition-barrier-0039.xml",
  4059. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/vehicle-attributes-recognition-barrier-0039/FP32/vehicle-attributes-recognition-barrier-0039.xml",
  4060. "format": "OpenVINO IR",
  4061. "link": "https://download.01.org/openvinotoolkit"
  4062. },
  4063. {
  4064. "type": "openvino",
  4065. "target": "2018_R4_vehicle-detection-adas-0002.xml",
  4066. "source": "https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo/vehicle-detection-adas-0002/FP32/vehicle-detection-adas-0002.xml",
  4067. "format": "OpenVINO IR",
  4068. "link": "https://download.01.org/openvinotoolkit"
  4069. },
  4070. {
  4071. "type": "openvino",
  4072. "target": "2018_R4_vehicle-license-plate-detection-barrier-0106.xml",
  4073. "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",
  4074. "format": "OpenVINO IR",
  4075. "link": "https://download.01.org/openvinotoolkit"
  4076. },
  4077. {
  4078. "type": "openvino",
  4079. "target": "2018_R5_license-plate-recognition-barrier-0001.xml",
  4080. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/license-plate-recognition-barrier-0001/FP32/license-plate-recognition-barrier-0001.xml",
  4081. "format": "OpenVINO IR",
  4082. "link": "https://download.01.org/openvinotoolkit"
  4083. },
  4084. {
  4085. "type": "openvino",
  4086. "target": "2018_R5_pedestrian-and-vehicle-detector-adas-0001.xml",
  4087. "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",
  4088. "format": "OpenVINO IR",
  4089. "link": "https://download.01.org/openvinotoolkit"
  4090. },
  4091. {
  4092. "type": "openvino",
  4093. "target": "2018_R5_pedestrian-detection-adas-0002.xml",
  4094. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/pedestrian-detection-adas-0002/FP32/pedestrian-detection-adas-0002.xml",
  4095. "format": "OpenVINO IR",
  4096. "link": "https://download.01.org/openvinotoolkit"
  4097. },
  4098. {
  4099. "type": "openvino",
  4100. "target": "2018_R5_person-attributes-recognition-crossroad-0200.xml",
  4101. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-attributes-recognition-crossroad-0200/FP32/person-attributes-recognition-crossroad-0200.xml",
  4102. "format": "OpenVINO IR",
  4103. "link": "https://download.01.org/openvinotoolkit"
  4104. },
  4105. {
  4106. "type": "openvino",
  4107. "target": "2018_R5_person-detection-action-recognition-0004.xml",
  4108. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-action-recognition-0004/FP32/person-detection-action-recognition-0004.xml",
  4109. "format": "OpenVINO IR",
  4110. "link": "https://download.01.org/openvinotoolkit"
  4111. },
  4112. {
  4113. "type": "openvino",
  4114. "target": "2018_R5_person-detection-retail-0002.xml",
  4115. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-retail-0002/FP32/person-detection-retail-0002.xml",
  4116. "format": "OpenVINO IR",
  4117. "link": "https://download.01.org/openvinotoolkit"
  4118. },
  4119. {
  4120. "type": "openvino",
  4121. "target": "2018_R5_person-detection-retail-0013.xml",
  4122. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-detection-retail-0013/FP32/person-detection-retail-0013.xml",
  4123. "format": "OpenVINO IR",
  4124. "link": "https://download.01.org/openvinotoolkit"
  4125. },
  4126. {
  4127. "type": "openvino",
  4128. "target": "2018_R5_person-reidentification-retail-0031.xml",
  4129. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0031/FP32/person-reidentification-retail-0031.xml",
  4130. "format": "OpenVINO IR",
  4131. "link": "https://download.01.org/openvinotoolkit"
  4132. },
  4133. {
  4134. "type": "openvino",
  4135. "target": "2018_R5_person-reidentification-retail-0076.xml",
  4136. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0076/FP32/person-reidentification-retail-0076.xml",
  4137. "format": "OpenVINO IR",
  4138. "link": "https://download.01.org/openvinotoolkit"
  4139. },
  4140. {
  4141. "type": "openvino",
  4142. "target": "2018_R5_person-reidentification-retail-0079.xml",
  4143. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-reidentification-retail-0079/FP32/person-reidentification-retail-0079.xml",
  4144. "format": "OpenVINO IR",
  4145. "link": "https://download.01.org/openvinotoolkit"
  4146. },
  4147. {
  4148. "type": "openvino",
  4149. "target": "2018_R5_person-vehicle-bike-detection-crossroad-0078.xml",
  4150. "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",
  4151. "format": "OpenVINO IR",
  4152. "link": "https://download.01.org/openvinotoolkit"
  4153. },
  4154. {
  4155. "type": "openvino",
  4156. "target": "2018_R5_road-segmentation-adas-0001.xml",
  4157. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/road-segmentation-adas-0001/FP32/road-segmentation-adas-0001.xml",
  4158. "format": "OpenVINO IR",
  4159. "link": "https://download.01.org/openvinotoolkit"
  4160. },
  4161. {
  4162. "type": "openvino",
  4163. "target": "2018_R5_semantic-segmentation-adas-0001.xml",
  4164. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/semantic-segmentation-adas-0001/FP32/semantic-segmentation-adas-0001.xml",
  4165. "format": "OpenVINO IR",
  4166. "link": "https://download.01.org/openvinotoolkit"
  4167. },
  4168. {
  4169. "type": "openvino",
  4170. "target": "2018_R5_single-image-super-resolution-0063.xml",
  4171. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-0063/FP32/single-image-super-resolution-0063.xml",
  4172. "format": "OpenVINO IR",
  4173. "link": "https://download.01.org/openvinotoolkit"
  4174. },
  4175. {
  4176. "type": "openvino",
  4177. "target": "2018_R5_single-image-super-resolution-1011.xml",
  4178. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-1011/FP32/single-image-super-resolution-1011.xml",
  4179. "format": "OpenVINO IR",
  4180. "link": "https://download.01.org/openvinotoolkit"
  4181. },
  4182. {
  4183. "type": "openvino",
  4184. "target": "2018_R5_single-image-super-resolution-1021.xml",
  4185. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/single-image-super-resolution-1021/FP32/single-image-super-resolution-1021.xml",
  4186. "format": "OpenVINO IR",
  4187. "link": "https://download.01.org/openvinotoolkit"
  4188. },
  4189. {
  4190. "type": "openvino",
  4191. "target": "2018_R5_text-detection-0001.xml",
  4192. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/text-detection-0001/FP32/text-detection-0001.xml",
  4193. "format": "OpenVINO IR",
  4194. "link": "https://download.01.org/openvinotoolkit"
  4195. },
  4196. {
  4197. "type": "openvino",
  4198. "target": "2018_R5_vehicle-attributes-recognition-barrier-0039.xml",
  4199. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/vehicle-attributes-recognition-barrier-0039/FP32/vehicle-attributes-recognition-barrier-0039.xml",
  4200. "format": "OpenVINO IR",
  4201. "link": "https://download.01.org/openvinotoolkit"
  4202. },
  4203. {
  4204. "type": "openvino",
  4205. "target": "2018_R5_vehicle-detection-adas-0002.xml",
  4206. "source": "https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/vehicle-detection-adas-0002/FP32/vehicle-detection-adas-0002.xml",
  4207. "format": "OpenVINO IR",
  4208. "link": "https://download.01.org/openvinotoolkit"
  4209. },
  4210. {
  4211. "type": "openvino",
  4212. "target": "2018_R5_vehicle-license-plate-detection-barrier-0106.xml",
  4213. "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",
  4214. "format": "OpenVINO IR",
  4215. "link": "https://download.01.org/openvinotoolkit"
  4216. },
  4217. {
  4218. "type": "openvino",
  4219. "target": "2019_R1_resnet50-binary-0001.bin,2019_R1_resnet50-binary-0001.xml",
  4220. "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",
  4221. "format": "OpenVINO IR",
  4222. "link": "https://download.01.org/opencv"
  4223. },
  4224. {
  4225. "type": "openvino",
  4226. "target": "int4-model.xml,int4-model.bin",
  4227. "source": "https://github.com/lutzroeder/netron/files/6273773/int4-model.zip[int4-model.xml,int4-model.bin]",
  4228. "format": "OpenVINO IR",
  4229. "link": "https://github.com/lutzroeder/netron/pull/715"
  4230. },
  4231. {
  4232. "type": "openvino",
  4233. "target": "netron_issue_372.xml",
  4234. "source": "https://github.com/lutzroeder/netron/files/4447843/netron_issue_372.zip[netron_issue_372.xml]",
  4235. "format": "OpenVINO IR",
  4236. "link": "https://github.com/lutzroeder/netron/issues/372"
  4237. },
  4238. {
  4239. "type": "openvino",
  4240. "target": "netron_issue_484.xml,netron_issue_484.bin",
  4241. "source": "https://github.com/lutzroeder/netron/files/4569338/netron_issue_484.zip[netron_issue_484.xml,netron_issue_484.bin]",
  4242. "format": "OpenVINO IR",
  4243. "link": "https://github.com/lutzroeder/netron/issues/484"
  4244. },
  4245. {
  4246. "type": "openvino",
  4247. "target": "netron_issue_572.xml,netron_issue_572.bin",
  4248. "source": "https://github.com/lutzroeder/netron/files/5114040/netron_issue_572.zip[netron_issue_572.xml,netron_issue_572.bin]",
  4249. "format": "OpenVINO IR",
  4250. "link": "https://github.com/lutzroeder/netron/issues/572"
  4251. },
  4252. {
  4253. "type": "openvino",
  4254. "target": "text-recognition-0012.xml,text-recognition-0012.bin",
  4255. "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",
  4256. "format": "OpenVINO IR",
  4257. "link": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-recognition-0012/FP16-INT8"
  4258. },
  4259. {
  4260. "type": "openvino",
  4261. "target": "text-spotting-0002-recognizer-decoder.xml,text-spotting-0002-recognizer-decoder.bin",
  4262. "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",
  4263. "format": "OpenVINO IR",
  4264. "link": "https://download.01.org/opencv/2020/openvinotoolkit/2020.2/open_model_zoo/models_bin/3/text-spotting-0002-recognizer-decoder/FP32"
  4265. },
  4266. {
  4267. "type": "openvino",
  4268. "target": "ti_with_large_body.xml",
  4269. "source": "https://github.com/lutzroeder/netron/files/2871678/ti_with_large_body.xml.zip[ti_with_large_body.xml]",
  4270. "format": "OpenVINO IR",
  4271. "link": "https://download.01.org/openvinotoolkit"
  4272. },
  4273. {
  4274. "type": "openvino",
  4275. "target": "with_gather.xml",
  4276. "source": "https://github.com/lutzroeder/netron/files/2871676/with_gather.xml.zip[with_gather.xml]",
  4277. "format": "OpenVINO IR",
  4278. "link": "https://download.01.org/openvinotoolkit"
  4279. },
  4280. {
  4281. "type": "openvino",
  4282. "target": "with_nd_conv_simple.xml",
  4283. "source": "https://github.com/lutzroeder/netron/files/2871696/with_nd_conv_simple.xml.zip[with_nd_conv_simple.xml]",
  4284. "format": "OpenVINO IR",
  4285. "link": "https://download.01.org/openvinotoolkit"
  4286. },
  4287. {
  4288. "type": "openvino",
  4289. "target": "with_pad_simple.xml",
  4290. "source": "https://github.com/lutzroeder/netron/files/2871673/with_pad_simple.xml.zip[with_pad_simple.xml]",
  4291. "format": "OpenVINO IR",
  4292. "link": "https://download.01.org/openvinotoolkit"
  4293. },
  4294. {
  4295. "type": "paddle",
  4296. "target": "assign.pbtxt",
  4297. "source": "https://github.com/lutzroeder/netron/files/5485296/assign.pbtxt.zip[assign.pbtxt]",
  4298. "format": "PaddlePaddle",
  4299. "link": "https://github.com/lutzroeder/netron/issues/903"
  4300. },
  4301. {
  4302. "type": "paddle",
  4303. "target": "ch_ppocr_mobile_v2.0_det_infer.zip",
  4304. "source": "https://github.com/lutzroeder/netron/files/8748319/ch_ppocr_mobile_v2.0_det_infer.zip",
  4305. "format": "PaddlePaddle",
  4306. "link": "https://github.com/lutzroeder/netron/issues/552"
  4307. },
  4308. {
  4309. "type": "paddle",
  4310. "target": "ch_ppocr_mobile_v2.0_det_infer.pdiparams",
  4311. "source": "https://github.com/lutzroeder/netron/files/8748319/ch_ppocr_mobile_v2.0_det_infer.zip[inference.pdiparams]",
  4312. "format": "PaddlePaddle Inference Weights",
  4313. "link": "https://github.com/lutzroeder/netron/issues/552"
  4314. },
  4315. {
  4316. "type": "paddle",
  4317. "target": "critic.pdparams",
  4318. "source": "https://github.com/lutzroeder/netron/files/8748332/critic.pdparams.zip[critic.pdparams]",
  4319. "format": "PaddlePaddle Pickle",
  4320. "link": "https://github.com/lutzroeder/netron/issues/552"
  4321. },
  4322. {
  4323. "type": "paddle",
  4324. "target": "lite_naive_model_opt.nb.tar.gz",
  4325. "source": "https://github.com/lutzroeder/netron/files/7084134/lite_naive_model_opt.nb.tar.gz",
  4326. "error": "Paddle Lite naive buffer format is deprecated in '__model__.nb'.",
  4327. "format": "Paddle Lite",
  4328. "link": "https://github.com/lutzroeder/netron/issues/797"
  4329. },
  4330. {
  4331. "type": "paddle",
  4332. "target": "paddle_example.zip",
  4333. "source": "https://github.com/lutzroeder/netron/files/8548969/paddle_example.zip",
  4334. "format": "PaddlePaddle v2.2",
  4335. "link": "https://github.com/lutzroeder/netron/issues/903"
  4336. },
  4337. {
  4338. "type": "paddle",
  4339. "target": "recognize_digits_multilayer_perceptron_model.zip",
  4340. "source": "https://github.com/lutzroeder/netron/files/4985730/recognize_digits_multilayer_perceptron_model.zip",
  4341. "format": "PaddlePaddle v1.8",
  4342. "link": "https://github.com/lutzroeder/netron/issues/552"
  4343. },
  4344. {
  4345. "type": "paddle",
  4346. "target": "recognize_digits_multilayer_perceptron_weights.tar",
  4347. "source": "https://github.com/lutzroeder/netron/files/5551009/recognize_digits_multilayer_perceptron_weights.tar.zip[recognize_digits_multilayer_perceptron_weights.tar]",
  4348. "format": "PaddlePaddle Weights",
  4349. "link": "https://github.com/lutzroeder/netron/issues/903"
  4350. },
  4351. {
  4352. "type": "paddle",
  4353. "target": "tranformer_base.zip",
  4354. "source": "https://github.com/lutzroeder/netron/files/5160568/tranformer_base.zip",
  4355. "format": "PaddlePaddle v1.8.3",
  4356. "link": "https://github.com/lutzroeder/netron/issues/903"
  4357. },
  4358. {
  4359. "type": "paddle",
  4360. "target": "squeezenet1.1.nb",
  4361. "source": "https://github.com/lutzroeder/netron/files/7272515/squeezenet1.1.nb.zip[squeezenet1.1.nb]",
  4362. "format": "Paddle Lite v2.9.1",
  4363. "link": "https://github.com/lutzroeder/netron/issues/797"
  4364. },
  4365. {
  4366. "type": "paddle",
  4367. "target": "vgg_ilsvrc_16_fc_reduced.tar.gz",
  4368. "source": "http://paddlemodels.bj.bcebos.com/vgg_ilsvrc_16_fc_reduced.tar.gz",
  4369. "format": "PaddlePaddle",
  4370. "link": "https://github.com/PaddlePaddle/models/tree/develop/PaddleCV/face_detection"
  4371. },
  4372. {
  4373. "type": "paddle",
  4374. "target": "with_dummy_tensor_type.zip",
  4375. "source": "https://github.com/lutzroeder/netron/files/3021210/with_dummy_tensor_type.zip",
  4376. "format": "PaddlePaddle",
  4377. "link": "https://github.com/lutzroeder/netron/issues/246"
  4378. },
  4379. {
  4380. "type": "paddle",
  4381. "target": "without_tensor_type.zip",
  4382. "source": "https://github.com/lutzroeder/netron/files/3021211/without_tensor_type.zip",
  4383. "format": "PaddlePaddle",
  4384. "link": "https://github.com/lutzroeder/netron/issues/246"
  4385. },
  4386. {
  4387. "type": "pickle",
  4388. "target": "batches.meta",
  4389. "source": "https://raw.githubusercontent.com/MadryLab/cifar10_challenge/master/cifar10_data/batches.meta",
  4390. "format": "Pickle",
  4391. "error": "Unsupported Pickle object in 'batches.meta'.",
  4392. "link": "https://github.com/MadryLab/cifar10_challenge"
  4393. },
  4394. {
  4395. "type": "pickle",
  4396. "target": "myModel.model",
  4397. "source": "https://github.com/lutzroeder/netron/files/8506779/myModel.model.zip[myModel.model]",
  4398. "format": "cuML",
  4399. "link": "https://github.com/lutzroeder/netron/issues/901"
  4400. },
  4401. {
  4402. "type": "pickle",
  4403. "target": "net.pkl",
  4404. "source": "https://github.com/lutzroeder/netron/files/8506780/net.pkl.zip[net.pkl]",
  4405. "format": "Pickle",
  4406. "error": "Unsupported Pickle type '__main__.LeNetConvPoolLayer' in 'net.pkl'.",
  4407. "link": "https://github.com/lutzroeder/netron/issues/901"
  4408. },
  4409. {
  4410. "type": "pickle",
  4411. "target": "robinhood-portfolio_data_user.pkl.pkl",
  4412. "source": "https://raw.githubusercontent.com/omdv/robinhood-portfolio/4622dc61e0556a85ce52c4de178d01a9838acbc5/data/user.pkl",
  4413. "format": "Pickle",
  4414. "error": "Unsupported Pickle object in 'robinhood-portfolio_data_user.pkl.pkl'.",
  4415. "link": "https://github.com/omdv/robinhood-portfolio/tree/4622dc61e0556a85ce52c4de178d01a9838acbc5"
  4416. },
  4417. {
  4418. "type": "pytorch",
  4419. "target": "alexnet_traced.pt.zip",
  4420. "source": "https://github.com/lutzroeder/netron/files/6096602/alexnet_traced.pt.zip",
  4421. "format": "TorchScript v1.6",
  4422. "link": "https://github.com/lutzroeder/netron/issues/281"
  4423. },
  4424. {
  4425. "type": "pytorch",
  4426. "target": "alexnet.pkl.pth.zip",
  4427. "source": "https://github.com/lutzroeder/netron/files/5213453/alexnet.pkl.pth.zip",
  4428. "format": "PyTorch v0.1.10",
  4429. "link": "https://github.com/lutzroeder/netron/issues/133"
  4430. },
  4431. {
  4432. "type": "pytorch",
  4433. "target": "alexnet.pt.zip",
  4434. "source": "https://github.com/lutzroeder/netron/files/6096605/alexnet.pt.zip",
  4435. "format": "TorchScript v1.6",
  4436. "link": "https://github.com/lutzroeder/netron/issues/281"
  4437. },
  4438. {
  4439. "type": "pytorch",
  4440. "target": "alexnet.ptl",
  4441. "source": "https://github.com/lutzroeder/netron/files/7340000/alexnet.ptl.zip[alexnet.ptl]",
  4442. "format": "TorchScript v1.6",
  4443. "link": "https://github.com/lutzroeder/netron/issues/827"
  4444. },
  4445. {
  4446. "type": "pytorch",
  4447. "target": "alexnet.zip.pth",
  4448. "source": "https://github.com/lutzroeder/netron/files/6096607/alexnet.zip.pth.zip[alexnet.zip.pth]",
  4449. "format": "PyTorch v1.6",
  4450. "link": "https://github.com/lutzroeder/netron/issues/133"
  4451. },
  4452. {
  4453. "type": "pytorch",
  4454. "target": "bert-base-uncased.pt",
  4455. "source": "https://github.com/lutzroeder/netron/files/7705212/bert-base-uncased.pt.zip[bert-base-uncased.pt]",
  4456. "format": "TorchScript v1.6",
  4457. "link": "https://github.com/lutzroeder/netron/issues/842"
  4458. },
  4459. {
  4460. "type": "pytorch",
  4461. "target": "blitz_neural_networks_tutorial_traced.pt",
  4462. "source": "https://github.com/lutzroeder/netron/files/3748989/blitz_neural_networks_tutorial.zip[blitz_neural_networks_tutorial_traced.pt]",
  4463. "format": "TorchScript v1.3",
  4464. "link": "https://github.com/lutzroeder/netron/issues/281"
  4465. },
  4466. {
  4467. "type": "pytorch",
  4468. "target": "blitz_neural_networks_tutorial.pt",
  4469. "source": "https://github.com/lutzroeder/netron/files/3748989/blitz_neural_networks_tutorial.zip[blitz_neural_networks_tutorial.pt]",
  4470. "format": "TorchScript v1.3",
  4471. "link": "https://github.com/lutzroeder/netron/issues/281"
  4472. },
  4473. {
  4474. "type": "pytorch",
  4475. "target": "blitz_cifar10_tutorial.pt",
  4476. "source": "https://github.com/lutzroeder/netron/files/3748500/blitz_cifar10_tutorial.zip[blitz_cifar10_tutorial.pt]",
  4477. "format": "TorchScript v1.3",
  4478. "link": "https://github.com/lutzroeder/netron/issues/281"
  4479. },
  4480. {
  4481. "type": "pytorch",
  4482. "target": "boolean.pkl.pth",
  4483. "source": "https://github.com/lutzroeder/netron/files/5435851/boolean.zip[boolean.pkl.pth]",
  4484. "format": "PyTorch v0.1.10",
  4485. "link": "https://github.com/lutzroeder/netron/issues/472"
  4486. },
  4487. {
  4488. "type": "pytorch",
  4489. "target": "boolean.zip.pth",
  4490. "source": "https://github.com/lutzroeder/netron/files/5435851/boolean.zip[boolean.pkl.pth]",
  4491. "format": "PyTorch v0.1.10",
  4492. "link": "https://github.com/lutzroeder/netron/issues/472"
  4493. },
  4494. {
  4495. "type": "pytorch",
  4496. "target": "bvlc_googlenet.caffemodel.pth",
  4497. "source": "https://www.dropbox.com/s/2ljm35ztj6hllcu/bvlc_googlenet.caffemodel.pth?dl=1",
  4498. "format": "PyTorch v0.1.10",
  4499. "link": "https://sea-region.github.com/yuminsuh/part_bilinear_reid/issues/2"
  4500. },
  4501. {
  4502. "type": "pytorch",
  4503. "target": "ckpt.t7",
  4504. "source": "https://raw.githubusercontent.com/babajide07/Redundant-Feature-Pruning-Pytorch-Implementation/master/checkpoint/ckpt.t7",
  4505. "format": "PyTorch v0.1.10",
  4506. "link": "https://github.com/babajide07/Redundant-Feature-Pruning-Pytorch-Implementation"
  4507. },
  4508. {
  4509. "type": "pytorch",
  4510. "target": "cruise_cutin_vehicle_model.pt",
  4511. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/cruise_cutin_vehicle_model.pt",
  4512. "format": "TorchScript v1.0",
  4513. "link": "https://github.com/ApolloAuto/apollo"
  4514. },
  4515. {
  4516. "type": "pytorch",
  4517. "target": "cruise_go_vehicle_model.pt",
  4518. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/cruise_go_vehicle_model.pt",
  4519. "format": "TorchScript v1.0",
  4520. "link": "https://github.com/ApolloAuto/apollo"
  4521. },
  4522. {
  4523. "type": "pytorch",
  4524. "target": "d2go.pt",
  4525. "source": "https://github.com/lutzroeder/netron/files/6370675/d2go.pt.zip[d2go.pt]",
  4526. "format": "TorchScript v1.7",
  4527. "link": "https://github.com/lutzroeder/netron/issues/732"
  4528. },
  4529. {
  4530. "type": "pytorch",
  4531. "target": "deeplabv3_scripted.pt",
  4532. "source": "https://github.com/lutzroeder/netron/files/5604999/deeplabv3_scripted.pt.zip[deeplabv3_scripted.pt]",
  4533. "format": "TorchScript v1.6",
  4534. "link": "https://github.com/lutzroeder/netron/issues/630"
  4535. },
  4536. {
  4537. "type": "pytorch",
  4538. "target": "densenet161_traced.pt",
  4539. "source": "https://github.com/lutzroeder/netron/files/6096613/densenet161_traced.pt.zip[densenet161_traced.pt]",
  4540. "action": "skip-render",
  4541. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4542. },
  4543. {
  4544. "type": "pytorch",
  4545. "target": "densenet161.pt",
  4546. "source": "https://github.com/lutzroeder/netron/files/6096614/densenet161.pt.zip[densenet161.pt]",
  4547. "action": "skip-render",
  4548. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4549. },
  4550. {
  4551. "type": "pytorch",
  4552. "target": "densenet161.zip.pth",
  4553. "source": "https://github.com/lutzroeder/netron/files/6096621/densenet161.zip.pth.zip[densenet161.zip.pth]",
  4554. "link": "https://pytorch.org/docs/stable/torchvision/models.html"
  4555. },
  4556. {
  4557. "type": "pytorch",
  4558. "target": "densenet161.mar",
  4559. "source": "https://torchserve.pytorch.org/mar_files/densenet161.mar",
  4560. "format": "PyTorch v0.1.10",
  4561. "link": "https://github.com/lutzroeder/netron/issues/286"
  4562. },
  4563. {
  4564. "type": "pytorch",
  4565. "target": "DRNL4x_dual_model.pth",
  4566. "source": "https://github.com/lutzroeder/netron/files/5505677/DRNL4x_dual_model.pth.zip[DRNL4x_dual_model.pth]",
  4567. "format": "PyTorch v0.1.10",
  4568. "link": "https://github.com/lutzroeder/netron/issues/543"
  4569. },
  4570. {
  4571. "type": "pytorch",
  4572. "target": "ENet.pth",
  4573. "source": "https://github.com/lutzroeder/netron/files/5368544/ENet.pth.zip[ENet.pth]",
  4574. "format": "PyTorch v0.1.10",
  4575. "link": "https://github.com/lutzroeder/netron/issues/133"
  4576. },
  4577. {
  4578. "type": "pytorch",
  4579. "target": "fasterrcnn_resnet50_fpn.pt",
  4580. "source": "https://github.com/lutzroeder/netron/files/7677467/fasterrcnn_resnet50_fpn.pt.zip[fasterrcnn_resnet50_fpn.pt]",
  4581. "error": "Unsupported torch.add expression type in 'fasterrcnn_resnet50_fpn.pt'.",
  4582. "link": "https://github.com/lutzroeder/netron/issues/689"
  4583. },
  4584. {
  4585. "type": "pytorch",
  4586. "target": "gcn2_tiny_320x240.pb",
  4587. "source": "https://raw.githubusercontent.com/jiexiong2016/GCNv2_SLAM/master/GCN2/gcn2_tiny_320x240.pt",
  4588. "format": "TorchScript v1.0",
  4589. "link": "https://github.com/jiexiong2016/GCNv2_SLAM"
  4590. },
  4591. {
  4592. "type": "pytorch",
  4593. "target": "inception_v3_traced.pt",
  4594. "source": "https://github.com/lutzroeder/netron/files/6096627/inception_v3_traced.pt.zip[inception_v3_traced.pt]",
  4595. "link": "https://github.com/lutzroeder/netron/issues/281"
  4596. },
  4597. {
  4598. "type": "pytorch",
  4599. "target": "inception_v3.pt",
  4600. "source": "https://github.com/lutzroeder/netron/files/6096628/inception_v3.pt.zip[inception_v3.pt]",
  4601. "link": "https://github.com/lutzroeder/netron/issues/281"
  4602. },
  4603. {
  4604. "type": "pytorch",
  4605. "target": "inception_v3.pkl.pth.zip",
  4606. "source": "https://github.com/lutzroeder/netron/files/5213454/inception_v3.pkl.pth.zip",
  4607. "format": "PyTorch v0.1.10",
  4608. "link": "https://github.com/lutzroeder/netron/issues/133"
  4609. },
  4610. {
  4611. "type": "pytorch",
  4612. "target": "inception_v3.zip.pth",
  4613. "source": "https://github.com/lutzroeder/netron/files/6096630/inception_v3.zip.pth.zip[inception_v3.zip.pth]",
  4614. "link": "https://github.com/lutzroeder/netron/issues/133"
  4615. },
  4616. {
  4617. "type": "pytorch",
  4618. "target": "iv3_pertensor.pt",
  4619. "source": "https://github.com/lutzroeder/netron/files/5212009/iv3_pertensor.zip[iv3_pertensor.pt]",
  4620. "format": "TorchScript v1.5",
  4621. "link": "https://github.com/lutzroeder/netron/issues/546"
  4622. },
  4623. {
  4624. "type": "pytorch",
  4625. "target": "junction_mlp_vehicle_model.pt",
  4626. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/junction_mlp_vehicle_model.pt",
  4627. "format": "TorchScript v1.0",
  4628. "link": "https://github.com/ApolloAuto/apollo"
  4629. },
  4630. {
  4631. "type": "pytorch",
  4632. "target": "labels.pth",
  4633. "source": "https://github.com/lutzroeder/netron/files/7350657/labels.pth.zip[labels.pth]",
  4634. "format": "PyTorch v1.6",
  4635. "link": "https://github.com/lutzroeder/netron/issues/720"
  4636. },
  4637. {
  4638. "type": "pytorch",
  4639. "target": "lane_scanning_vehicle_model.pt",
  4640. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/lane_scanning_vehicle_model.pt",
  4641. "format": "TorchScript v1.0",
  4642. "link": "https://github.com/ApolloAuto/apollo"
  4643. },
  4644. {
  4645. "type": "pytorch",
  4646. "target": "LMModel1.pt",
  4647. "source": "https://github.com/lutzroeder/netron/files/7726055/LMModel1.zip[LMModel1.pt]",
  4648. "format": "TorchScript v1.6",
  4649. "link": "https://github.com/lutzroeder/netron/issues/842"
  4650. },
  4651. {
  4652. "type": "pytorch",
  4653. "target": "mask_depthwise_conv.pt",
  4654. "source": "https://github.com/lutzroeder/netron/files/6186157/mask_depthwise_conv.pt.zip[mask_depthwise_conv.pt]",
  4655. "format": "TorchScript v1.3",
  4656. "link": "https://github.com/lutzroeder/netron/issues/281"
  4657. },
  4658. {
  4659. "type": "pytorch",
  4660. "target": "mask_r_cnn.pth",
  4661. "source": "https://raw.githubusercontent.com/facebookresearch/kill-the-bits/master/src/models/compressed/mask_r_cnn.pth",
  4662. "format": "PyTorch v0.1.10",
  4663. "link": "https://github.com/facebookresearch/kill-the-bits/tree/master/src/models/compressed"
  4664. },
  4665. {
  4666. "type": "pytorch",
  4667. "target": "mnist_bfloat16.pt",
  4668. "source": "https://github.com/lutzroeder/netron/files/8556403/mnist_bfloat16.pt.zip[mnist_bfloat16.pt]",
  4669. "format": "PyTorch v1.6",
  4670. "link": "https://github.com/lutzroeder/netron/issues/720"
  4671. },
  4672. {
  4673. "type": "pytorch",
  4674. "target": "mnist_linear.ckpt",
  4675. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear.ckpt]",
  4676. "format": "PyTorch v0.1.10",
  4677. "link": "https://github.com/lutzroeder/netron/issues/281"
  4678. },
  4679. {
  4680. "type": "pytorch",
  4681. "target": "mnist_linear_dynamic_quantized.pt",
  4682. "source": "https://github.com/lutzroeder/netron/files/4774023/mnist_linear_dynamic_quantized.zip[mnist_linear_dynamic_quantized.pt]",
  4683. "format": "PyTorch v0.1.10",
  4684. "link": "https://github.com/lutzroeder/netron/issues/519"
  4685. },
  4686. {
  4687. "type": "pytorch",
  4688. "target": "mnist_linear_static_quantized.pt",
  4689. "source": "https://github.com/lutzroeder/netron/files/4774022/mnist_linear_static_quantized.zip[mnist_linear_static_quantized.pt]",
  4690. "format": "PyTorch v0.1.10",
  4691. "link": "https://github.com/lutzroeder/netron/issues/519"
  4692. },
  4693. {
  4694. "type": "pytorch",
  4695. "target": "mnist_linear_torchscript_1.pt",
  4696. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear_torchscript_1.pt]",
  4697. "format": "TorchScript v1.1",
  4698. "link": "https://github.com/lutzroeder/netron/issues/281"
  4699. },
  4700. {
  4701. "type": "pytorch",
  4702. "target": "mnist_linear_torchscript_2.pt",
  4703. "source": "https://github.com/lutzroeder/netron/files/3585288/mnist_linear_torchscript.zip[mnist_linear_torchscript_2.pt]",
  4704. "format": "TorchScript v1.3",
  4705. "link": "https://github.com/lutzroeder/netron/issues/281"
  4706. },
  4707. {
  4708. "type": "pytorch",
  4709. "target": "mobilefacenet_scripted.pt",
  4710. "source": "https://github.com/foamliu/MobileFaceNet/releases/download/v1.0/mobilefacenet_scripted.pt",
  4711. "format": "TorchScript v1.3",
  4712. "link": "https://github.com/foamliu/MobileFaceNet"
  4713. },
  4714. {
  4715. "type": "pytorch",
  4716. "target": "Mobilenet_se_focal_121000.pb",
  4717. "source": "https://download.01.org/openvinotoolkit/open_model_zoo/training_toolbox_pytorch/models/fr/Mobilenet_se_focal_121000.pt",
  4718. "format": "PyTorch v0.1.10",
  4719. "link": "https://github.com/grib0ed0v/face_recognition.pytorch"
  4720. },
  4721. {
  4722. "type": "pytorch",
  4723. "target": "mobilenet_quantization_scripted_quantized_1.pth",
  4724. "source": "https://github.com/lutzroeder/netron/files/5394885/mobilenet_quantization_scripted_quantized.zip[mobilenet_quantization_scripted_quantized_1.pth]",
  4725. "format": "TorchScript v1.3",
  4726. "link": "https://github.com/lutzroeder/netron/issues/421"
  4727. },
  4728. {
  4729. "type": "pytorch",
  4730. "target": "mobilenet_quantization_scripted_quantized_2.pth",
  4731. "source": "https://github.com/lutzroeder/netron/files/5394885/mobilenet_quantization_scripted_quantized.zip[mobilenet_quantization_scripted_quantized_2.pth]",
  4732. "format": "TorchScript v1.6",
  4733. "link": "https://github.com/lutzroeder/netron/issues/421"
  4734. },
  4735. {
  4736. "type": "pytorch",
  4737. "target": "mobilenet_v2.pt",
  4738. "source": "https://github.com/lutzroeder/netron/files/6096624/mobilenet_v2.pt.zip[mobilenet_v2.pt]",
  4739. "link": "https://github.com/lutzroeder/netron/issues/281"
  4740. },
  4741. {
  4742. "type": "pytorch",
  4743. "target": "mobilenet_v2_traced.pt",
  4744. "source": "https://github.com/lutzroeder/netron/files/6096623/mobilenet_v2_traced.pt.zip[mobilenet_v2_traced.pt]",
  4745. "link": "https://github.com/lutzroeder/netron/issues/281"
  4746. },
  4747. {
  4748. "type": "pytorch",
  4749. "target": "model_0_epochs.pt",
  4750. "source": "https://github.com/lutzroeder/netron/files/6765569/model_0_epochs.pt.zip[model_0_epochs.pt]",
  4751. "format": "TorchScript v1.6",
  4752. "link": "https://github.com/lutzroeder/netron/issues/647"
  4753. },
  4754. {
  4755. "type": "pytorch",
  4756. "target": "model_fnet.pt",
  4757. "source": "https://github.com/lutzroeder/netron/files/8457286/model_fnet.pt.zip[model_fnet.pt]",
  4758. "format": "TorchScript v1.6",
  4759. "link": "https://github.com/lutzroeder/netron/issues/882"
  4760. },
  4761. {
  4762. "type": "pytorch",
  4763. "target": "model-reddit16-f140225004_2.pt1",
  4764. "source": "https://raw.githubusercontent.com/pytorch/android-demo-app/master/PyTorchDemoApp/app/src/main/assets/model-reddit16-f140225004_2.pt1",
  4765. "format": "TorchScript v1.3",
  4766. "link": "https://github.com/pytorch/android-demo-app"
  4767. },
  4768. {
  4769. "type": "pytorch",
  4770. "target": "mobilenetv2-quant_full-nnapi.pt",
  4771. "source": "https://github.com/lutzroeder/netron/files/7406443/mobilenetv2-quant_full.zip[mobilenetv2-quant_full/mobilenetv2-quant_full-nnapi.pt]",
  4772. "format": "TorchScript v1.6",
  4773. "link": "https://github.com/lutzroeder/netron/issues/644"
  4774. },
  4775. {
  4776. "type": "pytorch",
  4777. "target": "mobilenetv2-quant_full-cpu.pt",
  4778. "source": "https://github.com/lutzroeder/netron/files/7406443/mobilenetv2-quant_full.zip[mobilenetv2-quant_full/mobilenetv2-quant_full-cpu.pt]",
  4779. "format": "TorchScript v1.6",
  4780. "link": "https://github.com/lutzroeder/netron/issues/644"
  4781. },
  4782. {
  4783. "type": "pytorch",
  4784. "target": "mtcnn.pt",
  4785. "source": "https://raw.githubusercontent.com/deepware/dFace/master/models/mtcnn.pt",
  4786. "format": "PyTorch v0.1.10",
  4787. "link": "https://github.com/deepware/dface/tree/master/dface"
  4788. },
  4789. {
  4790. "type": "pytorch",
  4791. "target": "netron_issue_313_v1.pt",
  4792. "source": "https://github.com/lutzroeder/netron/files/3721266/netron_issue_313.zip[netron_issue_313_v1.pt]",
  4793. "format": "TorchScript v1.0",
  4794. "link": "https://github.com/lutzroeder/netron/issues/313"
  4795. },
  4796. {
  4797. "type": "pytorch",
  4798. "target": "netron_issue_313_v2.pt",
  4799. "source": "https://github.com/lutzroeder/netron/files/3721266/netron_issue_313.zip[netron_issue_313_v2.pt]",
  4800. "format": "TorchScript v1.3",
  4801. "link": "https://github.com/lutzroeder/netron/issues/313"
  4802. },
  4803. {
  4804. "type": "pytorch",
  4805. "target": "netron_issue_432_activation.pth",
  4806. "source": "https://github.com/lutzroeder/netron/files/4226686/netron_issue_432_activation.pth.zip[netron_issue_432_activation.pth]",
  4807. "format": "TorchScript v1.3",
  4808. "link": "https://github.com/lutzroeder/netron/issues/432"
  4809. },
  4810. {
  4811. "type": "pytorch",
  4812. "target": "netron_issue_432_bmm.pth",
  4813. "source": "https://github.com/lutzroeder/netron/files/4226688/netron_issue_432_bmm.pth.zip[netron_issue_432_bmm.pth]",
  4814. "format": "TorchScript v1.3",
  4815. "link": "https://github.com/lutzroeder/netron/issues/432"
  4816. },
  4817. {
  4818. "type": "pytorch",
  4819. "target": "netron_issue_432_constant_pad_2d.pth",
  4820. "source": "https://github.com/lutzroeder/netron/files/4226690/netron_issue_432_constant_pad_2d.pth.zip[netron_issue_432_constant_pad_2d.pth]",
  4821. "format": "TorchScript v1.3",
  4822. "link": "https://github.com/lutzroeder/netron/issues/432"
  4823. },
  4824. {
  4825. "type": "pytorch",
  4826. "target": "netron_issue_529.pt",
  4827. "source": "https://github.com/lutzroeder/netron/files/4834633/netron_issue_529.zip[netron_issue_529.pt]",
  4828. "format": "TorchScript v1.5",
  4829. "link": "https://github.com/lutzroeder/netron/issues/529"
  4830. },
  4831. {
  4832. "type": "pytorch",
  4833. "target": "netron_issue_529_traced.pt",
  4834. "source": "https://github.com/lutzroeder/netron/files/4834633/netron_issue_529.zip[netron_issue_529_traced.pt]",
  4835. "format": "TorchScript v1.5",
  4836. "link": "https://github.com/lutzroeder/netron/issues/529"
  4837. },
  4838. {
  4839. "type": "pytorch",
  4840. "target": "netron_issue_545_caffe2.pt",
  4841. "source": "https://github.com/lutzroeder/netron/files/5690362/netron_issue_545_caffe2.pt.zip[netron_issue_545_caffe2.pt]",
  4842. "format": "TorchScript v1.6",
  4843. "link": "https://github.com/lutzroeder/netron/issues/545"
  4844. },
  4845. {
  4846. "type": "pytorch",
  4847. "target": "netron_issue_547_1.pt",
  4848. "source": "https://github.com/lutzroeder/netron/files/5137393/netron_issue_547_1.zip[netron_issue_547_1.pt]",
  4849. "error": "Unsupported torch.add expression type in 'netron_issue_547_1.pt'.",
  4850. "link": "https://github.com/lutzroeder/netron/issues/547"
  4851. },
  4852. {
  4853. "type": "pytorch",
  4854. "target": "netron_issue_609.pt",
  4855. "source": "https://github.com/lutzroeder/netron/files/5309279/netron_issue_609.pt.zip[netron_issue_609.pt]",
  4856. "format": "TorchScript v1.6",
  4857. "link": "https://github.com/lutzroeder/netron/issues/609"
  4858. },
  4859. {
  4860. "type": "pytorch",
  4861. "target": "netron_issue_677.pt",
  4862. "source": "https://github.com/lutzroeder/netron/files/5923252/netron_issue_677.pt.zip[netron_issue_677.pt]",
  4863. "format": "TorchScript v1.6",
  4864. "link": "https://github.com/lutzroeder/netron/issues/677"
  4865. },
  4866. {
  4867. "type": "pytorch",
  4868. "target": "norm_inplace.pt.zip",
  4869. "source": "https://github.com/lutzroeder/netron/files/4516621/norm_inplace.pt.zip",
  4870. "format": "TorchScript v1.3",
  4871. "link": "https://github.com/lutzroeder/netron/issues/473"
  4872. },
  4873. {
  4874. "type": "pytorch",
  4875. "target": "opt_xx.pt",
  4876. "source": "https://github.com/lutzroeder/netron/files/8747908/opt_xx.pt.zip[opt_xx.pt]",
  4877. "format": "TorchScript v1.6",
  4878. "error": "Slicing expected array in 'opt_xx.pt'.",
  4879. "link": "https://github.com/lutzroeder/netron/issues/913"
  4880. },
  4881. {
  4882. "type": "pytorch",
  4883. "target": "pedestrian_interaction_position_embedding.pt",
  4884. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_position_embedding.pt",
  4885. "format": "TorchScript v1.0",
  4886. "link": "https://github.com/ApolloAuto/apollo"
  4887. },
  4888. {
  4889. "type": "pytorch",
  4890. "target": "pedestrian_interaction_prediction_layer.pt",
  4891. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_prediction_layer.pt",
  4892. "format": "TorchScript v1.0",
  4893. "link": "https://github.com/ApolloAuto/apollo"
  4894. },
  4895. {
  4896. "type": "pytorch",
  4897. "target": "pedestrian_interaction_single_lstm.pt",
  4898. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_single_lstm.pt",
  4899. "format": "TorchScript v1.0",
  4900. "link": "https://github.com/ApolloAuto/apollo"
  4901. },
  4902. {
  4903. "type": "pytorch",
  4904. "target": "pedestrian_interaction_social_embedding.pt",
  4905. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/pedestrian_interaction_social_embedding.pt",
  4906. "format": "TorchScript v1.1",
  4907. "link": "https://github.com/ApolloAuto/apollo"
  4908. },
  4909. {
  4910. "type": "pytorch",
  4911. "target": "posemodel.pt",
  4912. "source": "https://github.com/lutzroeder/netron/files/5475350/posemodel.pt.zip[posemodel.pt]",
  4913. "format": "TorchScript v1.6",
  4914. "link": "https://github.com/lutzroeder/netron/issues/546"
  4915. },
  4916. {
  4917. "type": "pytorch",
  4918. "target": "pytorch_invalid_file.pth",
  4919. "source": "https://github.com/lutzroeder/netron/files/3269093/pytorch_invalid_file.zip[pytorch_invalid_file.pth]",
  4920. "error": "Could not find end of line in 'pytorch_invalid_file.pth'.",
  4921. "link": "https://github.com/lutzroeder/netron/issues/133"
  4922. },
  4923. {
  4924. "type": "pytorch",
  4925. "target": "quant_3d.pt",
  4926. "source": "https://github.com/lutzroeder/netron/files/5877566/quant_3d.pt.zip[quant_3d.pt]",
  4927. "format": "TorchScript v1.6",
  4928. "link": "https://github.com/lutzroeder/netron/issues/546"
  4929. },
  4930. {
  4931. "type": "pytorch",
  4932. "target": "r3d_18_traced.pt",
  4933. "source": "https://github.com/lutzroeder/netron/files/6096649/r3d_18_traced.pt.zip[r3d_18_traced.pt]",
  4934. "link": "https://github.com/lutzroeder/netron/issues/281"
  4935. },
  4936. {
  4937. "type": "pytorch",
  4938. "target": "r3d_18.pt",
  4939. "source": "https://github.com/lutzroeder/netron/files/6096650/r3d_18.pt.zip[r3d_18.pt]",
  4940. "link": "https://github.com/lutzroeder/netron/issues/281"
  4941. },
  4942. {
  4943. "type": "pytorch",
  4944. "target": "r3d_18.zip.pth",
  4945. "source": "https://github.com/lutzroeder/netron/files/6096655/r3d_18.zip.pth.zip[r3d_18.zip.pth]",
  4946. "link": "https://github.com/lutzroeder/netron/issues/133"
  4947. },
  4948. {
  4949. "type": "pytorch",
  4950. "target": "refine_model.pt",
  4951. "source": "https://github.com/lutzroeder/netron/files/6186158/refine_model.pt.zip[refine_model.pt]",
  4952. "format": "TorchScript v1.3",
  4953. "link": "https://github.com/lutzroeder/netron/issues/281"
  4954. },
  4955. {
  4956. "type": "pytorch",
  4957. "target": "resnet18_fbgemm_16fa66dd.pth",
  4958. "source": "https://download.pytorch.org/models/quantized/resnet18_fbgemm_16fa66dd.pth",
  4959. "format": "PyTorch v0.1.10",
  4960. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/quantization/resnet.py"
  4961. },
  4962. {
  4963. "type": "pytorch",
  4964. "target": "resnet18_large_blocks.pth",
  4965. "source": "https://raw.githubusercontent.com/facebookresearch/kill-the-bits/master/src/models/compressed/resnet18_large_blocks.pth",
  4966. "format": "PyTorch v0.1.10",
  4967. "link": "https://github.com/facebookresearch/kill-the-bits/tree/master/src/models/compressed"
  4968. },
  4969. {
  4970. "type": "pytorch",
  4971. "target": "resnet18_quantized_cifar10.pt.zip",
  4972. "source": "https://github.com/lutzroeder/netron/files/7610907/resnet18_quantized_cifar10.pt.zip[resnet18_quantized_cifar10.pt]",
  4973. "format": "TorchScript v1.6",
  4974. "link": "https://github.com/lutzroeder/netron/issues/842"
  4975. },
  4976. {
  4977. "type": "pytorch",
  4978. "target": "resnet18-5c106cde.pth",
  4979. "source": "https://download.pytorch.org/models/resnet18-5c106cde.pth",
  4980. "format": "PyTorch v0.1.1",
  4981. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py"
  4982. },
  4983. {
  4984. "type": "pytorch",
  4985. "target": "resnet-18-at-export.pth",
  4986. "source": "https://s3.amazonaws.com/modelzoo-networks/resnet-18-at-export.pth",
  4987. "format": "PyTorch v0.1.10",
  4988. "link": "https://github.com/szagoruyko/attention-transfer"
  4989. },
  4990. {
  4991. "type": "pytorch",
  4992. "target": "resnet34-333f7ec4.pth",
  4993. "source": "https://download.pytorch.org/models/resnet34-333f7ec4.pth",
  4994. "format": "PyTorch v0.1.1",
  4995. "link": "https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py"
  4996. },
  4997. {
  4998. "type": "pytorch",
  4999. "target": "resnet50_pertensor.pt",
  5000. "source": "https://github.com/lutzroeder/netron/files/5212006/resnet50_pertensor.zip[resnet50_pertensor.pt]",
  5001. "format": "TorchScript v1.5",
  5002. "link": "https://github.com/lutzroeder/netron/issues/546"
  5003. },
  5004. {
  5005. "type": "pytorch",
  5006. "target": "resnet101.pkl.pth.zip",
  5007. "source": "https://github.com/lutzroeder/netron/files/5213455/resnet101.pkl.pth.zip",
  5008. "format": "PyTorch v0.1.10",
  5009. "link": "https://github.com/lutzroeder/netron/issues/133"
  5010. },
  5011. {
  5012. "type": "pytorch",
  5013. "target": "resnet101.pt",
  5014. "source": "https://github.com/lutzroeder/netron/files/6096666/resnet101_traced.pt.zip[resnet101_traced.pt]",
  5015. "format": "TorchScript v1.6",
  5016. "link": "https://github.com/lutzroeder/netron/issues/281"
  5017. },
  5018. {
  5019. "type": "pytorch",
  5020. "target": "resnet101_traced.pt",
  5021. "source": "https://github.com/lutzroeder/netron/files/6096671/shufflenet_v2_x1_0.pt.zip[shufflenet_v2_x1_0.pt]",
  5022. "format": "TorchScript v1.6",
  5023. "link": "https://github.com/lutzroeder/netron/issues/281"
  5024. },
  5025. {
  5026. "type": "pytorch",
  5027. "target": "resnet18.ot",
  5028. "source": "https://github.com/lutzroeder/netron/files/7664092/resnet18.ot.zip[resnet18.ot]",
  5029. "format": "TorchScript v1.0",
  5030. "link": "https://github.com/lutzroeder/netron/issues/686"
  5031. },
  5032. {
  5033. "type": "pytorch",
  5034. "target": "resnet18.pt",
  5035. "source": "https://github.com/lutzroeder/netron/files/5212015/resnet18.zip[resnet18.pt]",
  5036. "format": "TorchScript v1.6",
  5037. "link": "https://github.com/lutzroeder/netron/issues/559"
  5038. },
  5039. {
  5040. "type": "pytorch",
  5041. "target": "resnet18_fx_graph_mode_quantized.pth",
  5042. "source": "https://github.com/lutzroeder/netron/files/6716842/resnet18_fx_graph_mode_quantized.pth.zip[resnet18_fx_graph_mode_quantized.pth]",
  5043. "format": "TorchScript v1.6",
  5044. "link": "https://github.com/lutzroeder/netron/issues/758"
  5045. },
  5046. {
  5047. "type": "pytorch",
  5048. "target": "resnet50_tucker.pth",
  5049. "source": "https://raw.githubusercontent.com/larry0123du/Decompose-CNN/master/models/resnet50_tucker.pth",
  5050. "format": "PyTorch v0.1.10",
  5051. "link": "https://github.com/larry0123du/Decompose-CNN"
  5052. },
  5053. {
  5054. "type": "pytorch",
  5055. "target": "resnet50_tucker_state.pth",
  5056. "source": "https://raw.githubusercontent.com/larry0123du/Decompose-CNN/master/models/resnet50_tucker_state.pth",
  5057. "format": "PyTorch v0.1.10",
  5058. "link": "https://github.com/larry0123du/Decompose-CNN"
  5059. },
  5060. {
  5061. "type": "pytorch",
  5062. "target": "rpn_model.pt",
  5063. "source": "https://github.com/lutzroeder/netron/files/6186159/rpn_model.pt.zip[rpn_model.pt]",
  5064. "format": "TorchScript v1.3",
  5065. "link": "https://github.com/lutzroeder/netron/issues/281"
  5066. },
  5067. {
  5068. "type": "pytorch",
  5069. "target": "rvm_mobilenetv3_fp16.torchscript",
  5070. "source": "https://github.com/PeterL1n/RobustVideoMatting/releases/download/v1.0.0/rvm_mobilenetv3_fp16.torchscript",
  5071. "format": "TorchScript v1.6",
  5072. "link": "https://github.com/PeterL1n/RobustVideoMatting"
  5073. },
  5074. {
  5075. "type": "pytorch",
  5076. "target": "segmentor.pt",
  5077. "source": "https://github.com/lutzroeder/netron/files/7663953/segmentor.pt.zip[segmentor.pt]",
  5078. "format": "TorchScript v1.6",
  5079. "link": "https://github.com/lutzroeder/netron/issues/686"
  5080. },
  5081. {
  5082. "type": "pytorch",
  5083. "target": "semantic_lstm_vehicle_model.pt",
  5084. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/semantic_lstm_vehicle_model.pt",
  5085. "format": "TorchScript v1.1",
  5086. "link": "https://github.com/ApolloAuto/apollo"
  5087. },
  5088. {
  5089. "type": "pytorch",
  5090. "target": "SiamFC_50_model.pth",
  5091. "source": "https://raw.githubusercontent.com/HengLan/SiamFC-PyTorch/master/Train/model/SiamFC_50_model.pth",
  5092. "format": "PyTorch v0.1.10",
  5093. "link": "https://github.com/HengLan/SiamFC-PyTorch"
  5094. },
  5095. {
  5096. "type": "pytorch",
  5097. "target": "shufflenet_v2_x1_0.zip.pth",
  5098. "source": "https://github.com/lutzroeder/netron/files/6096673/shufflenet_v2_x1_0.zip.pth.zip[shufflenet_v2_x1_0.zip.pth]",
  5099. "format": "PyTorch v1.6",
  5100. "link": "https://github.com/lutzroeder/netron/issues/133"
  5101. },
  5102. {
  5103. "type": "pytorch",
  5104. "target": "shufflenet_v2_x1_0.pt",
  5105. "source": "https://github.com/lutzroeder/netron/files/6096671/shufflenet_v2_x1_0.pt.zip[shufflenet_v2_x1_0.pt]",
  5106. "format": "TorchScript v1.6",
  5107. "link": "https://github.com/lutzroeder/netron/issues/281"
  5108. },
  5109. {
  5110. "type": "pytorch",
  5111. "target": "squeezenet1_0-a815701f.pth",
  5112. "source": "https://download.pytorch.org/models/squeezenet1_0-a815701f.pth",
  5113. "format": "PyTorch v0.1.1"
  5114. },
  5115. {
  5116. "type": "pytorch",
  5117. "target": "squeezenet1_1_traced.pt",
  5118. "source": "https://github.com/lutzroeder/netron/files/6096661/squeezenet1_1_traced.pt.zip[squeezenet1_1_traced.pt]",
  5119. "format": "TorchScript v1.6",
  5120. "link": "https://github.com/lutzroeder/netron/issues/281"
  5121. },
  5122. {
  5123. "type": "pytorch",
  5124. "target": "squeezenet1_1.pt",
  5125. "source": "https://github.com/lutzroeder/netron/files/6096662/squeezenet1_1.pt.zip[squeezenet1_1.pt]",
  5126. "format": "TorchScript v1.6",
  5127. "link": "https://github.com/lutzroeder/netron/issues/281"
  5128. },
  5129. {
  5130. "type": "pytorch",
  5131. "target": "squeezenet1_1.pkl.pth.zip",
  5132. "source": "https://github.com/lutzroeder/netron/files/5213456/squeezenet1_1.pkl.pth.zip",
  5133. "format": "PyTorch v0.1.10",
  5134. "link": "https://github.com/lutzroeder/netron/issues/133"
  5135. },
  5136. {
  5137. "type": "pytorch",
  5138. "target": "squeezenet1_1-f364aa15.pth",
  5139. "source": "https://download.pytorch.org/models/squeezenet1_1-f364aa15.pth",
  5140. "format": "PyTorch v0.1.1"
  5141. },
  5142. {
  5143. "type": "pytorch",
  5144. "target": "ssdlite320_mobilenet_v3_large.pt",
  5145. "source": "https://github.com/lutzroeder/netron/files/7677468/ssdlite320_mobilenet_v3_large.pt.zip[ssdlite320_mobilenet_v3_large.pt]",
  5146. "format": "TorchScript v1.6",
  5147. "link": "https://github.com/lutzroeder/netron/issues/842"
  5148. },
  5149. {
  5150. "type": "pytorch",
  5151. "target": "superpoint_v1.pth",
  5152. "source": "https://raw.githubusercontent.com/MagicLeapResearch/SuperPointPretrainedNetwork/master/superpoint_v1.pth",
  5153. "format": "PyTorch v0.1.10",
  5154. "link": "https://github.com/MagicLeapResearch/SuperPointPretrainedNetwork"
  5155. },
  5156. {
  5157. "type": "pytorch",
  5158. "target": "superpoint.pt",
  5159. "source": "https://raw.githubusercontent.com/KinglittleQ/SuperPoint_SLAM/master/superpoint.pt",
  5160. "format": "TorchScript v1.0",
  5161. "link": "https://github.com/KinglittleQ/SuperPoint_SLAM"
  5162. },
  5163. {
  5164. "type": "pytorch",
  5165. "target": "traced_fft.pt",
  5166. "source": "https://github.com/lutzroeder/netron/files/5172197/traced_fft.zip[traced_fft.pt]",
  5167. "format": "TorchScript v1.3",
  5168. "link": "https://github.com/lutzroeder/netron/issues/546"
  5169. },
  5170. {
  5171. "type": "pytorch",
  5172. "target": "traced_online_lane_enc.pt",
  5173. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_lane_enc.pt",
  5174. "format": "TorchScript v1.0",
  5175. "link": "https://github.com/ApolloAuto/apollo"
  5176. },
  5177. {
  5178. "type": "pytorch",
  5179. "target": "traced_online_obs_enc.pt",
  5180. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_obs_enc.pt",
  5181. "format": "TorchScript v1.0",
  5182. "link": "https://github.com/ApolloAuto/apollo"
  5183. },
  5184. {
  5185. "type": "pytorch",
  5186. "target": "traced_online_pred_layer.pt",
  5187. "source": "https://raw.githubusercontent.com/ApolloAuto/apollo/master/modules/prediction/data/traced_online_pred_layer.pt",
  5188. "format": "TorchScript v1.0",
  5189. "link": "https://github.com/ApolloAuto/apollo"
  5190. },
  5191. {
  5192. "type": "pytorch",
  5193. "target": "test.8bit.pth",
  5194. "source": "https://github.com/lutzroeder/netron/files/5238524/test.8bit.pth.zip[test.8bit.pth]",
  5195. "format": "TorchScript v1.6",
  5196. "link": "https://github.com/lutzroeder/netron/issues/546"
  5197. },
  5198. {
  5199. "type": "pytorch",
  5200. "target": "torch_script_model_dot15.pt",
  5201. "source": "https://github.com/lutzroeder/netron/files/6308295/torch_script_model_dot15.pt.zip[torch_script_model_dot15.pt]",
  5202. "format": "TorchScript v1.5",
  5203. "link": "https://github.com/lutzroeder/netron/issues/546"
  5204. },
  5205. {
  5206. "type": "pytorch",
  5207. "target": "torchscript_resnet50_fp32.pth",
  5208. "source": "https://github.com/lutzroeder/netron/files/7688572/torchscript_resnet50_fp32.pth.zip[torchscript_resnet50_fp32.pth]",
  5209. "format": "TorchScript v1.6",
  5210. "link": "https://github.com/lutzroeder/netron/issues/842"
  5211. },
  5212. {
  5213. "type": "pytorch",
  5214. "target": "tutorial_bidirectional_recurrent_neural_network.pth",
  5215. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_bidirectional_recurrent_neural_network.pth]",
  5216. "format": "PyTorch v0.1.10",
  5217. "link": "https://github.com/lutzroeder/netron/issues/133"
  5218. },
  5219. {
  5220. "type": "pytorch",
  5221. "target": "tutorial_convolutional_neural_network.pth",
  5222. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_convolutional_neural_network.pth]",
  5223. "format": "PyTorch v0.1.10",
  5224. "link": "https://github.com/lutzroeder/netron/issues/133"
  5225. },
  5226. {
  5227. "type": "pytorch",
  5228. "target": "tutorial_deep_residual_network.pth",
  5229. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_deep_residual_network.pth]",
  5230. "format": "PyTorch v0.1.10",
  5231. "link": "https://github.com/lutzroeder/netron/issues/133"
  5232. },
  5233. {
  5234. "type": "pytorch",
  5235. "target": "tutorial_logistic_regression.pth",
  5236. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_logistic_regression.pth]",
  5237. "format": "PyTorch v0.1.10",
  5238. "link": "https://github.com/lutzroeder/netron/issues/133"
  5239. },
  5240. {
  5241. "type": "pytorch",
  5242. "target": "tutorial_mnist.pth",
  5243. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_mnist.pth]",
  5244. "format": "PyTorch v0.1.10",
  5245. "link": "https://github.com/lutzroeder/netron/issues/133"
  5246. },
  5247. {
  5248. "type": "pytorch",
  5249. "target": "tutorial_recurrent_neural_network.pth",
  5250. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_recurrent_neural_network.pth]",
  5251. "format": "PyTorch v0.1.10",
  5252. "link": "https://github.com/lutzroeder/netron/issues/133"
  5253. },
  5254. {
  5255. "type": "pytorch",
  5256. "target": "tutorial_variational_autoencoder.pth.tar",
  5257. "source": "https://github.com/lutzroeder/netron/files/2587823/tutorial_models.zip[tutorial_variational_autoencoder.pth]",
  5258. "format": "PyTorch v0.1.10",
  5259. "link": "https://github.com/lutzroeder/netron/issues/133"
  5260. },
  5261. {
  5262. "type": "pytorch",
  5263. "target": "valid-bert-base-uncased.pt",
  5264. "source": "https://github.com/lutzroeder/netron/files/4977150/valid-bert-base-uncased.zip[valid-bert-base-uncased.pt]",
  5265. "format": "PyTorch v0.1.10",
  5266. "link": "https://github.com/lutzroeder/netron/issues/133"
  5267. },
  5268. {
  5269. "type": "pytorch",
  5270. "target": "ViT-B-32.pt",
  5271. "source": "https://github.com/lutzroeder/netron/files/5790183/ViT-B-32.pt.zip[ViT-B-32.pt]",
  5272. "format": "TorchScript v1.6",
  5273. "link": "https://github.com/lutzroeder/netron/issues/546"
  5274. },
  5275. {
  5276. "type": "pytorch",
  5277. "target": "vgg-cifar10.pth.tar",
  5278. "source": "http://www.cs.unc.edu/~cyfu/cifar10/model_best.pth.tar",
  5279. "format": "PyTorch v0.1.10",
  5280. "link": "https://github.com/chengyangfu/pytorch-vgg-cifar10"
  5281. },
  5282. {
  5283. "type": "pytorch",
  5284. "target": "video_classification.pt",
  5285. "source": "https://github.com/lutzroeder/netron/files/6341327/video_classification.pt.zip[video_classification.pt]",
  5286. "format": "TorchScript v1.6",
  5287. "link": "https://github.com/lutzroeder/netron/issues/728"
  5288. },
  5289. {
  5290. "type": "pytorch",
  5291. "target": "wav2mel.pt",
  5292. "source": "https://github.com/lutzroeder/netron/files/7534717/wav2mel.pt.zip[wav2mel.pt]",
  5293. "format": "TorchScript v1.6",
  5294. "link": "https://github.com/lutzroeder/netron/issues/842"
  5295. },
  5296. {
  5297. "type": "pytorch",
  5298. "target": "wav2vec2.ptl",
  5299. "source": "https://github.com/lutzroeder/netron/files/7447547/wav2vec2.ptl.zip[wav2vec2.ptl]",
  5300. "format": "TorchScript v1.6",
  5301. "link": "https://github.com/lutzroeder/netron/issues/827"
  5302. },
  5303. {
  5304. "type": "pytorch",
  5305. "target": "yolov5n.torchscript",
  5306. "source": "https://github.com/lutzroeder/netron/files/8457287/yolov5n.torchscript.zip[yolov5n.torchscript]",
  5307. "format": "TorchScript v1.6",
  5308. "error": "Offset is outside the bounds of the DataView",
  5309. "link": "https://github.com/lutzroeder/netron/issues/882"
  5310. },
  5311. {
  5312. "type": "pytorch",
  5313. "target": "yolo4_tiny.pt",
  5314. "source": "https://github.com/lutzroeder/netron/files/7995416/yolo4_tiny.pt.zip[yolo4_tiny.pt]",
  5315. "format": "TorchScript v1.5",
  5316. "link": "https://github.com/lutzroeder/netron/issues/842"
  5317. },
  5318. {
  5319. "type": "rknn",
  5320. "target": "autopilot.rknn",
  5321. "source": "https://github.com/lutzroeder/netron/files/5621074/autopilot.rknn.zip[autopilot.rknn]",
  5322. "format": "RKNN v1.3.0",
  5323. "link": "https://github.com/lutzroeder/netron/issues/639"
  5324. },
  5325. {
  5326. "type": "rknn",
  5327. "target": "deepfusion.rknn",
  5328. "source": "https://github.com/lutzroeder/netron/files/5621075/deepfusion.rknn.zip[deepfusion.rknn]",
  5329. "format": "RKNN v1.2.1",
  5330. "link": "https://github.com/lutzroeder/netron/issues/639"
  5331. },
  5332. {
  5333. "type": "rknn",
  5334. "target": "kindnet.rknn",
  5335. "source": "https://github.com/lutzroeder/netron/files/5621076/kindnet.rknn.zip[kindnet.rknn]",
  5336. "format": "RKNN v1.3.2",
  5337. "link": "https://github.com/lutzroeder/netron/issues/639"
  5338. },
  5339. {
  5340. "type": "rknn",
  5341. "target": "resnet_18.rknn",
  5342. "source": "https://github.com/lutzroeder/netron/files/5621078/resnet_18.rknn.zip[resnet_18.rknn]",
  5343. "format": "RKNN v1.3.2",
  5344. "link": "https://github.com/lutzroeder/netron/issues/639"
  5345. },
  5346. {
  5347. "type": "sklearn",
  5348. "target": "best_boston.pb",
  5349. "source": "https://github.com/lutzroeder/netron/files/3335715/xgboost_best_boston.zip[best_boston.pkl]",
  5350. "format": "scikit-learn v0.20.2",
  5351. "link": "https://github.com/lutzroeder/netron/issues/182"
  5352. },
  5353. {
  5354. "type": "sklearn",
  5355. "target": "binarizer.pkl",
  5356. "source": "https://github.com/lutzroeder/netron/files/2587902/binarizer.zip[binarizer.pkl]",
  5357. "format": "scikit-learn v0.19.1",
  5358. "link": "https://github.com/lutzroeder/netron/issues/182"
  5359. },
  5360. {
  5361. "type": "sklearn",
  5362. "target": "binarizer.joblib",
  5363. "source": "https://github.com/lutzroeder/netron/files/2587902/binarizer.zip[binarizer.joblib]",
  5364. "format": "scikit-learn v0.19.1",
  5365. "link": "https://github.com/lutzroeder/netron/issues/182"
  5366. },
  5367. {
  5368. "type": "sklearn",
  5369. "target": "celeb-classifier.nn4.small2.v1.pkl.zip",
  5370. "source": "https://github.com/lutzroeder/netron/files/6176216/celeb-classifier.nn4.small2.v1.pkl.zip",
  5371. "format": "scikit-learn",
  5372. "link": "https://github.com/lutzroeder/netron/issues/182"
  5373. },
  5374. {
  5375. "type": "sklearn",
  5376. "target": "column_pipeline.pkl",
  5377. "source": "https://github.com/lutzroeder/netron/files/4672437/column_pipeline.zip[column_pipeline.pkl]",
  5378. "format": "scikit-learn v0.22.1",
  5379. "link": "https://github.com/lutzroeder/netron/issues/498"
  5380. },
  5381. {
  5382. "type": "sklearn",
  5383. "target": "column_transformer_pipeline.pkl",
  5384. "source": "https://github.com/lutzroeder/netron/files/4672438/column_transformer_pipeline.zip[column_transformer_pipeline.pkl]",
  5385. "format": "scikit-learn v0.22.1",
  5386. "link": "https://github.com/lutzroeder/netron/issues/498"
  5387. },
  5388. {
  5389. "type": "sklearn",
  5390. "target": "encoder.pkl",
  5391. "source": "https://github.com/lutzroeder/netron/files/8506805/encoder.pkl.zip[encoder.pkl]",
  5392. "format": "scikit-learn v0.22.2.post1",
  5393. "link": "https://github.com/lutzroeder/netron/issues/182"
  5394. },
  5395. {
  5396. "type": "sklearn",
  5397. "target": "forest_iris_ExtraTreesClassifier.pkl",
  5398. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_ExtraTreesClassifier.pkl]",
  5399. "format": "scikit-learn v0.19.2",
  5400. "link": "https://github.com/lutzroeder/netron/issues/182"
  5401. },
  5402. {
  5403. "type": "sklearn",
  5404. "target": "forest_iris_RandomForestClassifier.pkl",
  5405. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_RandomForestClassifier.pkl]",
  5406. "format": "scikit-learn v0.19.2",
  5407. "link": "https://github.com/lutzroeder/netron/issues/182"
  5408. },
  5409. {
  5410. "type": "sklearn",
  5411. "target": "forest_iris_AdaBoostClassifier.pkl",
  5412. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_AdaBoostClassifier.pkl]",
  5413. "format": "scikit-learn v0.19.2",
  5414. "link": "https://github.com/lutzroeder/netron/issues/182"
  5415. },
  5416. {
  5417. "type": "sklearn",
  5418. "target": "forest_iris_DecisionTreeClassifier.pkl",
  5419. "source": "https://github.com/lutzroeder/netron/files/2592356/forest_iris_models.zip[forest_iris_DecisionTreeClassifier.pkl]",
  5420. "format": "scikit-learn v0.19.2",
  5421. "link": "https://github.com/lutzroeder/netron/issues/182"
  5422. },
  5423. {
  5424. "type": "sklearn",
  5425. "target": "iris_svc.joblib.z",
  5426. "source": "https://github.com/lutzroeder/netron/files/5728549/iris_svc.joblib.z.zip[iris_svc.joblib.z]",
  5427. "format": "scikit-learn v0.24.0rc1",
  5428. "link": "https://github.com/lutzroeder/netron/issues/182"
  5429. },
  5430. {
  5431. "type": "sklearn",
  5432. "target": "LDA_model.pkl",
  5433. "source": "https://raw.githubusercontent.com/rainer85ah/DCS/master/Output/LDA_model.pkl",
  5434. "format": "scikit-learn",
  5435. "link": "https://github.com/rainer85ah/DCS"
  5436. },
  5437. {
  5438. "type": "sklearn",
  5439. "target": "phoenix_ml_classifier.pkl",
  5440. "source": "https://raw.githubusercontent.com/imeraj/Phoenix_Playground/master/1.4/phoenix_ml/lib/phoenix_ml/model/classifier.pkl",
  5441. "format": "scikit-learn v0.19.1",
  5442. "link": "https://github.com/imeraj/Phoenix_Playground/tree/master/1.4/phoenix_ml/lib/phoenix_ml/model"
  5443. },
  5444. {
  5445. "type": "sklearn",
  5446. "target": "pima.xgboost.joblib.pkl",
  5447. "source": "https://github.com/lutzroeder/netron/files/2656501/pima.xgboost.joblib.pkl.zip[pima.xgboost.joblib.pkl]",
  5448. "format": "scikit-learn",
  5449. "link": "https://github.com/lutzroeder/netron/issues/182"
  5450. },
  5451. {
  5452. "type": "sklearn",
  5453. "target": "svc.joblib.pkl",
  5454. "source": "https://github.com/lutzroeder/netron/files/2592359/svc.zip[svc.joblib.pkl]",
  5455. "format": "scikit-learn v0.19.1",
  5456. "link": "https://github.com/lutzroeder/netron/issues/182"
  5457. },
  5458. {
  5459. "type": "sklearn",
  5460. "target": "svc.pkl",
  5461. "source": "https://github.com/lutzroeder/netron/files/2592359/svc.zip[svc.pkl]",
  5462. "format": "scikit-learn v0.19.1",
  5463. "link": "https://github.com/lutzroeder/netron/issues/182"
  5464. },
  5465. {
  5466. "type": "sklearn",
  5467. "target": "svm.pkl",
  5468. "source": "https://raw.githubusercontent.com/dfridovi/imagelib/master/svm.pkl",
  5469. "format": "scikit-learn",
  5470. "link": "https://github.com/dfridovi/imagelib/blob/master/svm.pkl"
  5471. },
  5472. {
  5473. "type": "sklearn",
  5474. "target": "tree.pkl",
  5475. "source": "https://github.com/wjqkkky/TTS-front-end/raw/56e09ef79bb6679e51a7c8ff3d302ccd917c0992/ChineseRhythmPredictor/tree.pkl",
  5476. "error": "Invalid string length",
  5477. "format": "scikit-learn v0.21.3",
  5478. "link": "https://github.com/wjqkkky/TTS-front-end"
  5479. },
  5480. {
  5481. "type": "sklearn",
  5482. "target": "wiki-aa-mlp.pkl",
  5483. "source": "https://github.com/lutzroeder/netron/files/2674319/wiki-aa-mlp.pkl.zip[wiki-aa-mlp.pkl]",
  5484. "format": "scikit-learn v0.19.0",
  5485. "link": "https://github.com/lutzroeder/netron/issues/182"
  5486. },
  5487. {
  5488. "type": "tengine",
  5489. "target": "detect_tflite.tmfile",
  5490. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/detect_tflite.tmfile",
  5491. "format": "Tengine v2.0",
  5492. "link": "https://github.com/pierricklee/tmfile-sample"
  5493. },
  5494. {
  5495. "type": "tengine",
  5496. "target": "detect_tflite_issue_466.tmfile",
  5497. "source": "https://github.com/lutzroeder/netron/files/4479142/detect_tflite_issue_466.zip[detect_tflite_issue_466.tmfile]",
  5498. "format": "Tengine v2.0",
  5499. "link": "https://github.com/lutzroeder/netron/issues/466"
  5500. },
  5501. {
  5502. "type": "tengine",
  5503. "target": "lighten_cnn.tmfile",
  5504. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/lighten_cnn.tmfile",
  5505. "format": "Tengine v2.0",
  5506. "link": "https://github.com/pierricklee/tmfile-sample"
  5507. },
  5508. {
  5509. "type": "tengine",
  5510. "target": "mobilenet.tmfile",
  5511. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet.tmfile",
  5512. "format": "Tengine v2.0",
  5513. "link": "https://github.com/pierricklee/tmfile-sample"
  5514. },
  5515. {
  5516. "type": "tengine",
  5517. "target": "mobilenet_quant_tflite.tmfile",
  5518. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_quant_tflite.tmfile",
  5519. "format": "Tengine v2.0",
  5520. "link": "https://github.com/pierricklee/tmfile-sample"
  5521. },
  5522. {
  5523. "type": "tengine",
  5524. "target": "mobolenet_ssd_v1_quant_tflite.tmfile",
  5525. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobolenet_ssd_v1_quant_tflite.tmfile",
  5526. "format": "Tengine v2.0",
  5527. "link": "https://github.com/pierricklee/tmfile-sample"
  5528. },
  5529. {
  5530. "type": "tengine",
  5531. "target": "mobilenet_v1_tf.tmfile",
  5532. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v1_tf.tmfile",
  5533. "format": "Tengine v2.0",
  5534. "link": "https://github.com/pierricklee/tmfile-sample"
  5535. },
  5536. {
  5537. "type": "tengine",
  5538. "target": "mobilenet_v2.tmfile",
  5539. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v2.tmfile",
  5540. "format": "Tengine v2.0",
  5541. "link": "https://github.com/pierricklee/tmfile-sample"
  5542. },
  5543. {
  5544. "type": "tengine",
  5545. "target": "mobilenet_v2_tf.tmfile",
  5546. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/mobilenet_v2_tf.tmfile",
  5547. "format": "Tengine v2.0",
  5548. "link": "https://github.com/pierricklee/tmfile-sample"
  5549. },
  5550. {
  5551. "type": "tengine",
  5552. "target": "nasnet_tf.tmfile",
  5553. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/nasnet_tf.tmfile",
  5554. "format": "Tengine v2.0",
  5555. "link": "https://github.com/pierricklee/tmfile-sample"
  5556. },
  5557. {
  5558. "type": "tengine",
  5559. "target": "retinaface_benchmark.tmfile",
  5560. "source": "https://raw.githubusercontent.com/OAID/Tengine/master/models/retinaface_benchmark.tmfile",
  5561. "format": "Tengine v2.0",
  5562. "link": "https://github.com/OAID/Tengine"
  5563. },
  5564. {
  5565. "type": "tengine",
  5566. "target": "squeezenet.tmfile",
  5567. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/squeezenet.tmfile",
  5568. "format": "Tengine v2.0",
  5569. "link": "https://github.com/pierricklee/tmfile-sample"
  5570. },
  5571. {
  5572. "type": "tengine",
  5573. "target": "squeezenet_on.tmfile",
  5574. "source": "https://raw.githubusercontent.com/pierricklee/tmfile-sample/master/squeezenet_on.tmfile",
  5575. "format": "Tengine v2.0",
  5576. "link": "https://github.com/pierricklee/tmfile-sample"
  5577. },
  5578. {
  5579. "type": "tengine",
  5580. "target": "test_multi_input_output.tmfile",
  5581. "source": "https://github.com/lutzroeder/netron/files/5248932/test_multi_input_output.zip[test_multi_input_output.tmfile]",
  5582. "format": "Tengine v2.0",
  5583. "link": "https://github.com/lutzroeder/netron/issues/440"
  5584. },
  5585. {
  5586. "type": "tf",
  5587. "target": "bert_uncased_L-12_H-768_A-12.meta",
  5588. "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]",
  5589. "format": "TensorFlow MetaGraph",
  5590. "producer": "TensorFlow v1.11.0-rc1",
  5591. "action": "skip-render",
  5592. "link": "https://github.com/google-research/bert#pre-trained-models"
  5593. },
  5594. {
  5595. "type": "tf",
  5596. "target": "bert_cased_L-24_H-1024_A-16.meta",
  5597. "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]",
  5598. "format": "TensorFlow MetaGraph",
  5599. "action": "skip-render",
  5600. "link": "https://github.com/google-research/bert#pre-trained-models"
  5601. },
  5602. {
  5603. "type": "tf",
  5604. "target": "char-rnn-tensorflow.pb",
  5605. "source": "https://github.com/lutzroeder/netron/files/2592462/char-rnn-tensorflow.pb.zip[char-rnn-tensorflow.pb]",
  5606. "format": "TensorFlow Graph",
  5607. "action": "skip-render",
  5608. "link": "https://github.com/lutzroeder/netron/issues/187"
  5609. },
  5610. {
  5611. "type": "tf",
  5612. "target": "chessbot.pb",
  5613. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/chessbot.pb",
  5614. "format": "TensorFlow Graph",
  5615. "link": "https://github.com/srom/chessbot"
  5616. },
  5617. {
  5618. "type": "tf",
  5619. "target": "chessbot_estimator.pb",
  5620. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/estimator.pb",
  5621. "format": "TensorFlow Graph",
  5622. "link": "https://github.com/srom/chessbot"
  5623. },
  5624. {
  5625. "type": "tf",
  5626. "target": "chessbot_classifier.pb",
  5627. "source": "https://raw.githubusercontent.com/srom/chessbot/master/model/classifier.pb",
  5628. "format": "TensorFlow Graph",
  5629. "link": "https://github.com/srom/chessbot"
  5630. },
  5631. {
  5632. "type": "tf",
  5633. "target": "classify_image_graph_def.pb",
  5634. "source": "https://raw.githubusercontent.com/taey16/tf/master/imagenet/classify_image_graph_def.pb",
  5635. "format": "TensorFlow Graph",
  5636. "link": "https://github.com/taey16/tf"
  5637. },
  5638. {
  5639. "type": "tf",
  5640. "target": "conv-layers.pb.zip",
  5641. "source": "https://github.com/lutzroeder/netron/files/2592468/conv-layers.pb.zip",
  5642. "format": "TensorFlow Graph",
  5643. "link": "https://github.com/lutzroeder/netron/issues/187"
  5644. },
  5645. {
  5646. "type": "tf",
  5647. "target": "densenet.pb",
  5648. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/densenet_2018_04_27.tgz[densenet/densenet.pb]",
  5649. "format": "TensorFlow Graph",
  5650. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/guide/hosted_models.md"
  5651. },
  5652. {
  5653. "type": "tf",
  5654. "target": "drawmodel_attn.ckpt",
  5655. "source": "https://github.com/lutzroeder/netron/files/8647412/drawmodel_attn.ckpt.zip[drawmodel_attn.ckpt]",
  5656. "format": "TensorFlow Tensor Bundle v1",
  5657. "link": "https://github.com/lutzroeder/netron/issues/405"
  5658. },
  5659. {
  5660. "type": "tf",
  5661. "target": "events.out.tfevents.1606692323.b5c8f88cc7ee.58.2",
  5662. "source": "https://github.com/lutzroeder/netron/files/5613448/events.out.tfevents.1606692323.b5c8f88cc7ee.58.2.zip[events.out.tfevents.1606692323.b5c8f88cc7ee.58.2]",
  5663. "format": "TensorFlow Event File v2",
  5664. "assert": [ "model.graphs[0].nodes[0].type.name=aten::_convolution" ],
  5665. "producer": "PyTorch",
  5666. "link": "https://github.com/lutzroeder/netron/issues/638"
  5667. },
  5668. {
  5669. "type": "tf",
  5670. "target": "events.out.tfevents.1606696207.eba7c8084653.55.0",
  5671. "source": "https://github.com/lutzroeder/netron/files/5613451/events.out.tfevents.1606696207.eba7c8084653.55.0.zip[events.out.tfevents.1606696207.eba7c8084653.55.0]",
  5672. "format": "TensorFlow Event File v2",
  5673. "producer": "PyTorch",
  5674. "link": "https://github.com/lutzroeder/netron/issues/638"
  5675. },
  5676. {
  5677. "type": "tf",
  5678. "target": "events.out.tfevents.1606704213.784cbcc2d49a.55.162.v2",
  5679. "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]",
  5680. "format": "TensorFlow Event File v2",
  5681. "link": "https://github.com/lutzroeder/netron/issues/638"
  5682. },
  5683. {
  5684. "type": "tf",
  5685. "target": "events.out.tfevents.1617485839.39aaee5846c1.58.0",
  5686. "source": "https://github.com/lutzroeder/netron/files/6261502/events.out.tfevents.1617485839.39aaee5846c1.58.0.zip[events.out.tfevents.1617485839.39aaee5846c1.58.0]",
  5687. "format": "TensorFlow Event File v2",
  5688. "producer": "PyTorch",
  5689. "link": "https://github.com/lutzroeder/netron/issues/638"
  5690. },
  5691. {
  5692. "type": "tf",
  5693. "target": "exDeepFM-criteo.meta",
  5694. "source": "https://raw.githubusercontent.com/Leavingseason/xDeepFM/master/exdeepfm/checkpoint/epoch_0.meta",
  5695. "format": "TensorFlow MetaGraph",
  5696. "action": "skip-render",
  5697. "link": "https://github.com/Leavingseason/xDeepFM"
  5698. },
  5699. {
  5700. "type": "tf",
  5701. "target": "faster_rcnn_inception_resnet_v2_atrous_oid_2018_01_28.ckpt.meta",
  5702. "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]",
  5703. "format": "TensorFlow MetaGraph",
  5704. "action": "skip-render",
  5705. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  5706. },
  5707. {
  5708. "type": "tf",
  5709. "target": "faster_rcnn_resnet50_lowproposals_coco_2017_11_08.ckpt.meta",
  5710. "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]",
  5711. "action": "skip-render",
  5712. "format": "TensorFlow MetaGraph"
  5713. },
  5714. {
  5715. "type": "tf",
  5716. "target": "float16.txt",
  5717. "source": "https://github.com/lutzroeder/netron/files/8547644/float16.txt.zip[float16.txt]",
  5718. "format": "TensorFlow Graph",
  5719. "link": "https://github.com/lutzroeder/netron/issues/187"
  5720. },
  5721. {
  5722. "type": "tf",
  5723. "target": "graph_missing_function.pbtxt",
  5724. "source": "https://github.com/lutzroeder/netron/files/7464813/graph_missing_function.pbtxt.zip[graph_missing_function.pbtxt]",
  5725. "format": "TensorFlow Graph",
  5726. "link": "https://github.com/lutzroeder/netron/issues/838"
  5727. },
  5728. {
  5729. "type": "tf",
  5730. "target": "graphdef_saved_model.pb",
  5731. "source": "https://github.com/lutzroeder/netron/files/2528688/saved_model.zip[saved_model.pb]",
  5732. "format": "TensorFlow Graph",
  5733. "link": "https://github.com/lutzroeder/netron/issues/171"
  5734. },
  5735. {
  5736. "type": "tf",
  5737. "target": "gpt-2-124M.ckpt.meta",
  5738. "source": "https://github.com/lutzroeder/netron/files/7775216/gpt-2-124M.ckpt.meta.zip[gpt-2-124M.ckpt.meta]",
  5739. "format": "TensorFlow MetaGraph",
  5740. "link": "https://github.com/lutzroeder/netron/issues/187"
  5741. },
  5742. {
  5743. "type": "tf",
  5744. "target": "half_plus_two_saved_model.pb",
  5745. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two/00000123/saved_model.pb",
  5746. "format": "TensorFlow Saved Model v1",
  5747. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5748. },
  5749. {
  5750. "type": "tf",
  5751. "target": "half_plus_two_main_op_saved_model.pb",
  5752. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two_main_op/00000123/saved_model.pb",
  5753. "format": "TensorFlow Saved Model v1",
  5754. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5755. },
  5756. {
  5757. "type": "tf",
  5758. "target": "half_plus_two_pbtxt_saved_model.pbtxt",
  5759. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/cc/saved_model/testdata/half_plus_two_pbtxt/00000123/saved_model.pbtxt",
  5760. "format": "TensorFlow Saved Model v1",
  5761. "link": "https://github.com/tensorflow/tensorflow/tree/master/tensorflow/cc/saved_model/testdata"
  5762. },
  5763. {
  5764. "type": "tf",
  5765. "target": "inception_v2_2016_08_28_frozen.pb",
  5766. "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]",
  5767. "format": "TensorFlow Graph",
  5768. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5769. },
  5770. {
  5771. "type": "tf",
  5772. "target": "inception5h.pb",
  5773. "source": "https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip[tensorflow_inception_graph.pb]"
  5774. },
  5775. {
  5776. "type": "tf",
  5777. "target": "invalid_graph.pbtxt",
  5778. "source": "https://github.com/lutzroeder/netron/files/6859459/invalid_graph.pbtxt.zip[invalid_graph.pbtxt]",
  5779. "error": "File text format is not tensorflow.GraphDef (Unexpected end of input at 8:1) in 'invalid_graph.pbtxt'."
  5780. },
  5781. {
  5782. "type": "tf",
  5783. "target": "mask_rcnn_resnet50_atrous_coco_2018_01_28.ckpt.meta",
  5784. "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]",
  5785. "format": "TensorFlow MetaGraph",
  5786. "action": "skip-render"
  5787. },
  5788. {
  5789. "type": "tf",
  5790. "target": "mnist_model.pbtxt",
  5791. "source": "https://raw.githubusercontent.com/ShauralP/MobileML/master/SimpleMNIST/mnist_model.pbtxt",
  5792. "format": "TensorFlow Graph",
  5793. "link": "https://github.com/ShauralP/MobileML"
  5794. },
  5795. {
  5796. "type": "tf",
  5797. "target": "mobilenet_v1_1.0_224_frozen.pb",
  5798. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224_frozen.pb]",
  5799. "format": "TensorFlow Graph"
  5800. },
  5801. {
  5802. "type": "tf",
  5803. "target": "mobilenet_v1_1.0_224_eval.pbtxt",
  5804. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224_eval.pbtxt]",
  5805. "format": "TensorFlow Graph"
  5806. },
  5807. {
  5808. "type": "tf",
  5809. "target": "mobilenet_v1_1.0_224_quant_eval.pbtxt",
  5810. "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]",
  5811. "format": "TensorFlow Graph",
  5812. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5813. },
  5814. {
  5815. "type": "tf",
  5816. "target": "mobilenet_v1_1.0_224_quant_frozen.pb",
  5817. "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]",
  5818. "format": "TensorFlow Graph",
  5819. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5820. },
  5821. {
  5822. "type": "tf",
  5823. "target": "mobilenet_v1_1.0_224_quant.ckpt.meta",
  5824. "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]",
  5825. "format": "TensorFlow MetaGraph",
  5826. "action": "skip-render",
  5827. "link": "https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md"
  5828. },
  5829. {
  5830. "type": "tf",
  5831. "target": "mobilenet_v2_1.4_224_frozen.pb",
  5832. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224_frozen.pb]",
  5833. "format": "TensorFlow Graph",
  5834. "link": "https://www.tensorflow.org/lite/models"
  5835. },
  5836. {
  5837. "type": "tf",
  5838. "target": "mobilenet_v2_1.4_224.ckpt.meta",
  5839. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224.ckpt.meta]",
  5840. "format": "TensorFlow MetaGraph",
  5841. "action": "skip-render",
  5842. "link": "https://www.tensorflow.org/lite/models"
  5843. },
  5844. {
  5845. "type": "tf",
  5846. "target": "mobilenet_v2_1.4_224_eval.pbtxt",
  5847. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224_eval.pbtxt]",
  5848. "format": "TensorFlow Graph",
  5849. "link": "https://www.tensorflow.org/lite/models"
  5850. },
  5851. {
  5852. "type": "tf",
  5853. "target": "mnasnet_0.5_224.pb",
  5854. "source": "http://download.tensorflow.org/models/tflite/mnasnet_0.5_224_09_07_2018.tgz[mnasnet_0.5_224/mnasnet_0.5_224.pb]",
  5855. "format": "TensorFlow Graph",
  5856. "link": "https://www.tensorflow.org/lite/models"
  5857. },
  5858. {
  5859. "type": "tf",
  5860. "target": "mnasnet_1.3_224.pb",
  5861. "source": "http://download.tensorflow.org/models/tflite/mnasnet_1.3_224_09_07_2018.tgz[mnasnet_1.3_224/mnasnet_1.3_224.pb]",
  5862. "format": "TensorFlow Graph",
  5863. "link": "https://www.tensorflow.org/lite/models"
  5864. },
  5865. {
  5866. "type": "tf",
  5867. "target": "nasnet_mobile.pb",
  5868. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_mobile_2018_04_27.tgz[./nasnet_mobile.pb]",
  5869. "format": "TensorFlow Graph",
  5870. "link": "https://www.tensorflow.org/lite/models"
  5871. },
  5872. {
  5873. "type": "tf",
  5874. "target": "netron_issue_110.pb",
  5875. "source": "https://github.com/lutzroeder/netron/files/2592457/netron_issue_110.pb.zip[netron_issue_110.pb]",
  5876. "format": "TensorFlow Graph",
  5877. "link": "https://github.com/lutzroeder/netron/issues/110"
  5878. },
  5879. {
  5880. "type": "tf",
  5881. "target": "netron_issue_224.pbtxt",
  5882. "source": "https://github.com/lutzroeder/netron/files/2823959/netron_issue_224.zip[netron_issue_224.pbtxt]",
  5883. "format": "TensorFlow Graph",
  5884. "link": "https://github.com/lutzroeder/netron/issues/224"
  5885. },
  5886. {
  5887. "type": "tf",
  5888. "target": "netron_issue_291.pbtxt",
  5889. "source": "https://github.com/lutzroeder/netron/files/3336368/netron_issue_291.zip[netron_issue_291.pbtxt]",
  5890. "format": "TensorFlow Graph",
  5891. "link": "https://github.com/lutzroeder/netron/issues/291"
  5892. },
  5893. {
  5894. "type": "tf",
  5895. "target": "netron_issue_320.pb",
  5896. "source": "https://github.com/lutzroeder/netron/files/3499707/netron_issue_320.zip[netron_issue_320.pb]",
  5897. "format": "TensorFlow Graph",
  5898. "link": "https://github.com/lutzroeder/netron/issues/320"
  5899. },
  5900. {
  5901. "type": "tf",
  5902. "target": "netron_issue_320.pbtxt",
  5903. "source": "https://github.com/lutzroeder/netron/files/3499707/netron_issue_320.zip[netron_issue_320.pbtxt]",
  5904. "format": "TensorFlow Graph",
  5905. "link": "https://github.com/lutzroeder/netron/issues/320"
  5906. },
  5907. {
  5908. "type": "tf",
  5909. "target": "netron_issue_323.pbtxt",
  5910. "source": "https://github.com/lutzroeder/netron/files/3539403/graph.zip[graph.pbtxt]",
  5911. "action": "skip-render",
  5912. "format": "TensorFlow Graph",
  5913. "link": "https://github.com/lutzroeder/netron/issues/323"
  5914. },
  5915. {
  5916. "type": "tf",
  5917. "target": "netron_issue_342.zip",
  5918. "source": "https://github.com/lutzroeder/netron/files/3918584/netron_issue_342.zip",
  5919. "format": "TensorFlow Saved Model v1",
  5920. "link": "https://github.com/lutzroeder/netron/issues/342"
  5921. },
  5922. {
  5923. "type": "tf",
  5924. "target": "netron_issue_405.zip",
  5925. "source": "https://github.com/lutzroeder/netron/files/4017943/netron_issue_405.zip",
  5926. "format": "TensorFlow Tensor Bundle v2",
  5927. "link": "https://github.com/lutzroeder/netron/issues/405"
  5928. },
  5929. {
  5930. "type": "tf",
  5931. "target": "netron_issue_847.pbtxt",
  5932. "source": "https://github.com/lutzroeder/netron/files/7642864/netron_issue_847.pbtxt.zip[netron_issue_847.pbtxt]",
  5933. "format": "TensorFlow Graph",
  5934. "link": "https://github.com/lutzroeder/netron/issues/847"
  5935. },
  5936. {
  5937. "type": "tf",
  5938. "target": "netron_issue_895.pbtxt",
  5939. "source": "https://github.com/lutzroeder/netron/files/8459475/netron_issue_895.pbtxt.zip[netron_issue_895.pbtxt]",
  5940. "format": "TensorFlow Graph",
  5941. "link": "https://github.com/lutzroeder/netron/issues/895"
  5942. },
  5943. {
  5944. "type": "tf",
  5945. "target": "output_graph.pbmm",
  5946. "source": "https://github.com/lutzroeder/netron/files/8645971/output_graph.pbmm.zip[output_graph.pbmm]",
  5947. "format": "TensorFlow GraphDef Memmapped",
  5948. "link": "https://github.com/lutzroeder/netron/issues/836"
  5949. },
  5950. {
  5951. "type": "tf",
  5952. "target": "pose_estimation_for_mobile.pb",
  5953. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.pb",
  5954. "format": "TensorFlow Graph",
  5955. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  5956. },
  5957. {
  5958. "type": "tf",
  5959. "target": "readable_graph.meta",
  5960. "source": "https://github.com/lutzroeder/netron/files/2592463/readable_graph.meta.zip[readable_graph.meta]",
  5961. "format": "TensorFlow MetaGraph",
  5962. "link": "https://github.com/lutzroeder/netron/issues/187"
  5963. },
  5964. {
  5965. "type": "tf",
  5966. "target": "resnet_v2_fp16_savedmodel_NHWC_saved_model.pb",
  5967. "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]",
  5968. "format": "TensorFlow Saved Model v1",
  5969. "action": "skip-render",
  5970. "link": "https://github.com/onnx/tensorflow-onnx/blob/master/tests/run_pretrained_models.yaml"
  5971. },
  5972. {
  5973. "type": "tf",
  5974. "target": "resnet18_model_baseline.pbtxt",
  5975. "source": "https://github.com/lutzroeder/netron/files/2913372/resnet18_model_baseline.pbtxt.zip[resnet18_model_baseline.pbtxt]",
  5976. "format": "TensorFlow Graph",
  5977. "action": "skip-render",
  5978. "link": "https://github.com/lutzroeder/netron/issues/235"
  5979. },
  5980. {
  5981. "type": "tf",
  5982. "target": "saved_model_xxx.pb",
  5983. "source": "https://github.com/lutzroeder/netron/files/6965264/saved_model_xxx.pb.zip[saved_model_xxx.pb]",
  5984. "format": "TensorFlow Saved Model v1",
  5985. "link": "https://github.com/lutzroeder/netron/issues/782"
  5986. },
  5987. {
  5988. "type": "tf",
  5989. "target": "speech_commands_v0.pb",
  5990. "source": "http://storage.googleapis.com/download.tensorflow.org/models/speech_commands_v0.01.zip[conv_actions_frozen.pb]",
  5991. "format": "TensorFlow Graph"
  5992. },
  5993. {
  5994. "type": "tf",
  5995. "target": "squeezenet.pb",
  5996. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/squeezenet_2018_04_27.tgz[./squeezenet.pb]"
  5997. },
  5998. {
  5999. "type": "tf",
  6000. "target": "ssd_mobilenet_v1_android_export.pb",
  6001. "source": "https://storage.googleapis.com/download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_android_export.zip[ssd_mobilenet_v1_android_export.pb]",
  6002. "format": "TensorFlow Graph",
  6003. "action": "skip-render",
  6004. "link": "https://www.tensorflow.org/lite/models"
  6005. },
  6006. {
  6007. "type": "tf",
  6008. "target": "ssd_mobilenet_v1_coco_11_06_2017_graph.pbtxt",
  6009. "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]",
  6010. "format": "TensorFlow Graph",
  6011. "action": "skip-render",
  6012. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  6013. },
  6014. {
  6015. "type": "tf",
  6016. "target": "ssd_mobilenet_v1_coco_11_06_2017_frozen_inference.pb",
  6017. "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]",
  6018. "format": "TensorFlow Graph",
  6019. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  6020. },
  6021. {
  6022. "type": "tf",
  6023. "target": "ssd_mobilenet_v1_coco_11_06_2017.ckpt.meta",
  6024. "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]",
  6025. "format": "TensorFlow MetaGraph",
  6026. "action": "skip-render",
  6027. "link": "https://github.com/GoogleCloudPlatform/tensorflow-object-detection-example"
  6028. },
  6029. {
  6030. "type": "tf",
  6031. "target": "tensorflow_issue_9169_saved_model.pbtxt",
  6032. "source": "https://github.com/tensorflow/tensorflow/files/917065/sample.zip[sample/load/saved_model.pbtxt]",
  6033. "format": "TensorFlow Saved Model v1",
  6034. "link": "https://github.com/tensorflow/tensorflow/issues/9169"
  6035. },
  6036. {
  6037. "type": "tfjs",
  6038. "target": "air-time-model/air-time-model.json",
  6039. "source": "https://github.com/lutzroeder/netron/files/3170424/air-time-model.json.zip[air-time-model.json]",
  6040. "format": "TensorFlow.js layers-model",
  6041. "producer": "TensorFlow.js tfjs-layers v1.0.4",
  6042. "link": "https://github.com/lutzroeder/netron/issues/270"
  6043. },
  6044. {
  6045. "type": "tfjs",
  6046. "target": "age_gender_model/age_gender_model-weights_manifest.json,age_gender_model/age_gender_model-shard1",
  6047. "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",
  6048. "format": "TensorFlow.js Weights"
  6049. },
  6050. {
  6051. "type": "tfjs",
  6052. "target": "deeplab_ade20k_1_quantized_2_1.zip",
  6053. "source": "https://github.com/lutzroeder/netron/files/6766475/deeplab_ade20k_1_quantized_2_1.zip",
  6054. "format": "TensorFlow.js graph-model",
  6055. "link": "https://github.com/lutzroeder/netron/issues/294"
  6056. },
  6057. {
  6058. "type": "tfjs",
  6059. "target": "iamgeai2/metadata.json,iamgeai2/model.json,iamgeai2/weights.bin",
  6060. "source": "https://github.com/lutzroeder/netron/files/7800435/iamgeai2.zip[metadata.json,model.json,weights.bin] ",
  6061. "format": "TensorFlow.js Keras vtfjs-layers 1.3.1",
  6062. "link": "https://github.com/lutzroeder/netron/issues/294"
  6063. },
  6064. {
  6065. "type": "tfjs",
  6066. "target": "mnist_transfer_cnn_v1.zip",
  6067. "source": "https://github.com/lutzroeder/netron/files/3361048/mnist_transfer_cnn_v1.zip",
  6068. "format": "TensorFlow.js Keras v2.1.4",
  6069. "link": "https://github.com/tensorflow/tfjs-examples"
  6070. },
  6071. {
  6072. "type": "tfjs",
  6073. "target": "mobilenet_v1_0.25_224/model.json",
  6074. "source": "https://storage.googleapis.com/tfjs-models/tfjs/mobilenet_v1_0.25_224/model.json",
  6075. "format": "TensorFlow.js Keras v2.1.4",
  6076. "link": "https://github.com/tensorflow/tfjs-examples"
  6077. },
  6078. {
  6079. "type": "tfjs",
  6080. "target": "posenet_mobilenet_float_075.zip",
  6081. "source": "https://github.com/lutzroeder/netron/files/3357629/posenet_mobilenet_float_075.zip",
  6082. "format": "TensorFlow.js graph-model",
  6083. "link": "https://github.com/intel/webml-polyfill/issues/880"
  6084. },
  6085. {
  6086. "type": "tfjs",
  6087. "target": "posenet_mobilenet_float_075_1_default_1.zip",
  6088. "source": "https://github.com/lutzroeder/netron/files/7204409/posenet_mobilenet_float_075_1_default_1.zip",
  6089. "format": "TensorFlow.js graph-model",
  6090. "link": "https://github.com/lutzroeder/netron/issues/294"
  6091. },
  6092. {
  6093. "type": "tfjs",
  6094. "target": "sentiment_cnn_v1/model.json",
  6095. "source": "https://github.com/lutzroeder/netron/files/3361046/sentiment_cnn_v1.zip[model.json]",
  6096. "format": "TensorFlow.js Keras v2.1.4",
  6097. "link": "https://github.com/tensorflow/tfjs-examples"
  6098. },
  6099. {
  6100. "type": "tfjs",
  6101. "target": "ssd_mobilenet_v2_1_default_1.zip",
  6102. "source": "https://github.com/lutzroeder/netron/files/6605132/ssd_mobilenet_v2_1_default_1.zip",
  6103. "format": "TensorFlow.js graph-model",
  6104. "link": "https://github.com/lutzroeder/netron/issues/294"
  6105. },
  6106. {
  6107. "type": "tfjs",
  6108. "target": "translation_en_fr_v1/model.json",
  6109. "source": "https://storage.googleapis.com/tfjs-models/tfjs/translation_en_fr_v1/model.json",
  6110. "format": "TensorFlow.js Keras v2.1.4",
  6111. "link": "https://github.com/tensorflow/tfjs-examples"
  6112. },
  6113. {
  6114. "type": "tfjs",
  6115. "target": "test_concat_const_string_tfjs.zip",
  6116. "source": "https://github.com/lutzroeder/netron/files/7207228/test_concat_const_string_tfjs.zip",
  6117. "format": "TensorFlow.js graph-model",
  6118. "link": "https://github.com/lutzroeder/netron/issues/294"
  6119. },
  6120. {
  6121. "type": "tfjs",
  6122. "target": "yamnet.tar",
  6123. "source": "https://tfhub.dev/google/tfjs-model/yamnet/tfjs/1?tfjs-format=compressed",
  6124. "format": "TensorFlow.js graph-model",
  6125. "link": "https://tfhub.dev/google/tfjs-model/yamnet/tfjs/1"
  6126. },
  6127. {
  6128. "type": "tfjs",
  6129. "target": "yolo3_tiny_darknet.zip",
  6130. "source": "https://github.com/lutzroeder/netron/files/7150178/yolo3_tiny_darknet.zip",
  6131. "format": "TensorFlow.js graph-model",
  6132. "link": "https://github.com/lutzroeder/netron/issues/764"
  6133. },
  6134. {
  6135. "type": "tflite",
  6136. "target": "deeplab_mobilenetv2_513.tflite",
  6137. "source": "https://raw.githubusercontent.com/pinzhenx/webml-demo/master/examples/deeplab/model/deeplab_mobilenetv2_513.tflite",
  6138. "format": "TensorFlow Lite v3",
  6139. "link": "https://github.com/pinzhenx/webml-demo"
  6140. },
  6141. {
  6142. "type": "tflite",
  6143. "target": "deeplab_mobilenetv2_513_dilated.tflite",
  6144. "source": "https://raw.githubusercontent.com/pinzhenx/webml-demo/master/examples/deeplab/model/deeplab_mobilenetv2_513_dilated.tflite",
  6145. "format": "TensorFlow Lite v3",
  6146. "link": "https://github.com/pinzhenx/webml-demo"
  6147. },
  6148. {
  6149. "type": "tflite",
  6150. "target": "densenet.tflite",
  6151. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/densenet_2018_04_27.tgz[densenet/densenet.tflite]",
  6152. "format": "TensorFlow Lite v3",
  6153. "assert": [ "model.graphs[0].nodes[0].type.name=Conv2D" ],
  6154. "link": "https://www.tensorflow.org/lite/guide/hosted_models"
  6155. },
  6156. {
  6157. "type": "tflite",
  6158. "target": "efficientnet-edgetpu-S_quant_edgetpu.tflite",
  6159. "source": "https://github.com/google-coral/edgetpu/raw/master/test_data/efficientnet-edgetpu-S_quant_edgetpu.tflite",
  6160. "format": "TensorFlow Lite v3",
  6161. "link": "https://github.com/lutzroeder/netron/issues/499"
  6162. },
  6163. {
  6164. "type": "tflite",
  6165. "target": "efficientnet_lite1_int8_2.tflite",
  6166. "source": "https://github.com/lutzroeder/netron/files/8309257/efficientnet_lite1_int8_2.tflite.zip[efficientnet_lite1_int8_2.tflite]",
  6167. "format": "TensorFlow Lite v3",
  6168. "link": "https://github.com/lutzroeder/netron/issues/34"
  6169. },
  6170. {
  6171. "type": "tflite",
  6172. "target": "face_detection_front.json",
  6173. "source": "https://github.com/lutzroeder/netron/files/4606685/face_detection_front.zip[face_detection_front.json]",
  6174. "format": "TensorFlow Lite v3"
  6175. },
  6176. {
  6177. "type": "tflite",
  6178. "target": "face_detection_front.tflite",
  6179. "source": "https://github.com/lutzroeder/netron/files/4606685/face_detection_front.zip[face_detection_front.tflite]",
  6180. "format": "TensorFlow Lite v3",
  6181. "link": "https://github.com/lutzroeder/netron/issues/487"
  6182. },
  6183. {
  6184. "type": "tflite",
  6185. "target": "hair_segmentation.json",
  6186. "source": "https://github.com/lutzroeder/netron/files/4606715/hair_segmentation.zip[hair_segmentation.json]",
  6187. "format": "TensorFlow Lite v3",
  6188. "link": "https://github.com/lutzroeder/netron/issues/487"
  6189. },
  6190. {
  6191. "type": "tflite",
  6192. "target": "hair_segmentation.tflite",
  6193. "source": "https://raw.githubusercontent.com/google/mediapipe/master/mediapipe/models/hair_segmentation.tflite",
  6194. "format": "TensorFlow Lite v3",
  6195. "link": "https://github.com/google/mediapipe"
  6196. },
  6197. {
  6198. "type": "tflite",
  6199. "target": "hed_lite_model_quantize.tflite",
  6200. "source": "https://raw.githubusercontent.com/pqpo/SmartCropper/master/smartcropperlib/src/main/assets/models/hed_lite_model_quantize.tflite",
  6201. "format": "TensorFlow Lite v3",
  6202. "link": "https://github.com/pqpo/SmartCropper"
  6203. },
  6204. {
  6205. "type": "tflite",
  6206. "target": "inception_v3.tflite",
  6207. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v3_2018_04_27.tgz[./inception_v3.tflite]"
  6208. },
  6209. {
  6210. "type": "tflite",
  6211. "target": "inception_v3_quant.tflite",
  6212. "source": "http://download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz[inception_v3_quant.tflite]",
  6213. "format": "TensorFlow Lite v3",
  6214. "link": "https://www.tensorflow.org/lite/models"
  6215. },
  6216. {
  6217. "type": "tflite",
  6218. "target": "keyword_scrambled_8bit.tflite",
  6219. "source": "https://raw.githubusercontent.com/tensorflow/tflite-micro/master/tensorflow/lite/micro/models/keyword_scrambled_8bit.tflite",
  6220. "format": "TensorFlow Lite v3",
  6221. "link": "https://github.com/tensorflow/tflite-micro"
  6222. },
  6223. {
  6224. "type": "tflite",
  6225. "target": "mobilenet_v1_0.75_160_quantized.tflite",
  6226. "source": "https://github.com/lutzroeder/netron/files/4569400/mobilenet_v1_0.75_160_quantized.zip[mobilenet_v1_0.75_160_quantized.tflite]",
  6227. "format": "TensorFlow Lite v3",
  6228. "link": "https://github.com/lutzroeder/netron/issues/481"
  6229. },
  6230. {
  6231. "type": "tflite",
  6232. "target": "mobilenet_v1_1.0_224.tflite",
  6233. "source": "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz[./mobilenet_v1_1.0_224.tflite]",
  6234. "format": "TensorFlow Lite v3",
  6235. "link": "https://www.tensorflow.org/lite/models"
  6236. },
  6237. {
  6238. "type": "tflite",
  6239. "target": "mobilenet_v1_1.0_224_quant.tflite",
  6240. "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]",
  6241. "format": "TensorFlow Lite v3",
  6242. "link": "https://www.tensorflow.org/lite/models"
  6243. },
  6244. {
  6245. "type": "tflite",
  6246. "target": "mobilenet_v2_0.4_224.tflite",
  6247. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.0_224.tgz[./mobilenet_v2_1.0_224.tflite]",
  6248. "format": "TensorFlow Lite v3"
  6249. },
  6250. {
  6251. "type": "tflite",
  6252. "target": "mobilenet_v2_1.4_224.tflite",
  6253. "source": "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz[./mobilenet_v2_1.4_224.tflite]",
  6254. "format": "TensorFlow Lite v3"
  6255. },
  6256. {
  6257. "type": "tflite",
  6258. "target": "model_pyramid_0_0_63_31.tflite",
  6259. "source": "https://github.com/lutzroeder/netron/files/6209444/model_pyramid_0_0_63_31.tflite.zip[model_pyramid_0_0_63_31.tflite]",
  6260. "format": "TensorFlow Lite v3",
  6261. "link": "https://github.com/lutzroeder/netron/issues/710"
  6262. },
  6263. {
  6264. "type": "tflite",
  6265. "target": "mnasnet_0.5_224.tflite",
  6266. "source": "http://download.tensorflow.org/models/tflite/mnasnet_0.5_224_09_07_2018.tgz[mnasnet_0.5_224/mnasnet_0.5_224.tflite]",
  6267. "format": "TensorFlow Lite v3",
  6268. "link": "https://www.tensorflow.org/lite/models"
  6269. },
  6270. {
  6271. "type": "tflite",
  6272. "target": "mnasnet_1.3_224.tflite",
  6273. "source": "http://download.tensorflow.org/models/tflite/mnasnet_1.3_224_09_07_2018.tgz[mnasnet_1.3_224/mnasnet_1.3_224.tflite]",
  6274. "format": "TensorFlow Lite v3",
  6275. "link": "https://www.tensorflow.org/lite/models"
  6276. },
  6277. {
  6278. "type": "tflite",
  6279. "target": "nasnet_mobile.tflite",
  6280. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/nasnet_mobile_2018_04_27.tgz[./nasnet_mobile.tflite]",
  6281. "format": "TensorFlow Lite v3",
  6282. "link": "https://www.tensorflow.org/lite/models"
  6283. },
  6284. {
  6285. "type": "tflite",
  6286. "target": "netron_issue_256.tflite",
  6287. "source": "https://github.com/lutzroeder/netron/files/3101992/test.zip[test.tflite]",
  6288. "format": "TensorFlow Lite v3",
  6289. "link": "https://github.com/lutzroeder/netron/issues/256"
  6290. },
  6291. {
  6292. "type": "tflite",
  6293. "target": "netron_issue_386.tflite",
  6294. "source": "https://github.com/lutzroeder/netron/files/3963415/netron_issue_386.zip[netron_issue_386.tflite]",
  6295. "format": "TensorFlow Lite v3",
  6296. "link": "https://github.com/lutzroeder/netron/issues/386"
  6297. },
  6298. {
  6299. "type": "tflite",
  6300. "target": "netron_issue_416.tflite",
  6301. "source": "https://github.com/lutzroeder/netron/files/4089319/netron_issue_416.zip[netron_issue_416.tflite]",
  6302. "format": "TensorFlow Lite v3",
  6303. "link": "https://github.com/lutzroeder/netron/issues/416"
  6304. },
  6305. {
  6306. "type": "tflite",
  6307. "target": "netron_issue_479.tflite",
  6308. "source": "https://github.com/lutzroeder/netron/files/4565988/netron_issue_479.zip[netron_issue_479.tflite]",
  6309. "format": "TensorFlow Lite v3",
  6310. "link": "https://github.com/lutzroeder/netron/issues/479"
  6311. },
  6312. {
  6313. "type": "tflite",
  6314. "target": "pose_estimation_for_mobile.tflite",
  6315. "source": "https://raw.githubusercontent.com/edvardHua/PoseEstimationForMobile/master/release/cpm_model/model.tflite",
  6316. "format": "TensorFlow Lite v3",
  6317. "link": "https://github.com/edvardHua/PoseEstimationForMobile"
  6318. },
  6319. {
  6320. "type": "tflite",
  6321. "target": "quicknet.tflite",
  6322. "source": "https://github.com/lutzroeder/netron/files/5184953/quicknet.zip[quicknet.tflite]",
  6323. "format": "TensorFlow Lite v3",
  6324. "link": "https://github.com/lutzroeder/netron/issues/499"
  6325. },
  6326. {
  6327. "type": "tflite",
  6328. "target": "smartreply.tflite",
  6329. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip[smartreply.tflite]",
  6330. "format": "TensorFlow Lite v3"
  6331. },
  6332. {
  6333. "type": "tflite",
  6334. "target": "smartreply_1.0_2017_11_01.zip",
  6335. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip",
  6336. "format": "TensorFlow Lite v3"
  6337. },
  6338. {
  6339. "type": "tflite",
  6340. "target": "squeezenet.tflite",
  6341. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/squeezenet_2018_04_27.tgz[./squeezenet.tflite]",
  6342. "format": "TensorFlow Lite v3"
  6343. },
  6344. {
  6345. "type": "tflite",
  6346. "target": "speech_hotword_model_rank1_2017_11_14.tflite",
  6347. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank1_2017_11_14.tflite",
  6348. "format": "TensorFlow Lite v3"
  6349. },
  6350. {
  6351. "type": "tflite",
  6352. "target": "speech_hotword_model_rank2_2017_11_14.tflite",
  6353. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank2_2017_11_14.tflite",
  6354. "format": "TensorFlow Lite v3"
  6355. },
  6356. {
  6357. "type": "tflite",
  6358. "target": "speech_speakerid_model_2017_11_14.tflite",
  6359. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_speakerid_model_2017_11_14.tflite",
  6360. "format": "TensorFlow Lite v3"
  6361. },
  6362. {
  6363. "type": "tflite",
  6364. "target": "speech_tts_model_2017_11_14.tflite",
  6365. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_tts_model_2017_11_14.tflite",
  6366. "format": "TensorFlow Lite v3"
  6367. },
  6368. {
  6369. "type": "tflite",
  6370. "target": "speech_tts_model_2017_11_14.json",
  6371. "source": "https://github.com/lutzroeder/netron/files/4606719/speech_tts_model_2017_11_14.zip[speech_tts_model_2017_11_14.json]",
  6372. "format": "TensorFlow Lite v3",
  6373. "link": "https://github.com/lutzroeder/netron/issues/487"
  6374. },
  6375. {
  6376. "type": "tflite",
  6377. "target": "subword-conformer.latest.tflite",
  6378. "source": "https://github.com/lutzroeder/netron/files/6032934/subword-conformer.zip[subword-conformer.latest.tflite]",
  6379. "format": "TensorFlow Lite v3",
  6380. "action": "skip-render",
  6381. "link": "https://github.com/lutzroeder/netron/issues/589"
  6382. },
  6383. {
  6384. "type": "tflite",
  6385. "target": "text_classification.tflite",
  6386. "source": "https://storage.googleapis.com/download.tensorflow.org/models/tflite/text_classification/text_classification.tflite",
  6387. "format": "TensorFlow Lite v3",
  6388. "link": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/models/text_classification/overview.md"
  6389. },
  6390. {
  6391. "type": "tflite",
  6392. "target": "two_subgraphs.bin",
  6393. "source": "https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/lite/testdata/two_subgraphs.bin",
  6394. "format": "TensorFlow Lite v3",
  6395. "link": "https://github.com/tensorflow/tensorflow"
  6396. },
  6397. {
  6398. "type": "tflite",
  6399. "target": "xorGate.lite",
  6400. "source": "https://raw.githubusercontent.com/kosslab-kr/Tizen-NN-Runtime/master/Xor/xorGate.lite",
  6401. "format": "TensorFlow Lite v3",
  6402. "link": "https://github.com/kosslab-kr/Tizen-NN-Runtime"
  6403. },
  6404. {
  6405. "type": "tnn",
  6406. "target": "instance_normalization.tnnproto,instance_normalization.tnnmodel",
  6407. "source": "https://github.com/lutzroeder/netron/files/5124180/instance_normalization.zip[instance_normalization.tnnproto,instance_normalization.tnnmodel]",
  6408. "format": "TNN",
  6409. "link": "https://github.com/lutzroeder/netron/pull/583"
  6410. },
  6411. {
  6412. "type": "tnn",
  6413. "target": "squeezenet_v1.1.tnnmodel,squeezenet_v1.1.tnnproto",
  6414. "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",
  6415. "format": "TNN",
  6416. "link": "https://github.com/Tencent/TNN"
  6417. },
  6418. {
  6419. "type": "tnn",
  6420. "target": "tnn_v2_model.tnnmodel,tnn_v2_model.tnnproto",
  6421. "source": "https://github.com/lutzroeder/netron/files/5753725/tnn_v2_model.zip[tnn_v2_model.tnnmodel,tnn_v2_model.tnnproto]",
  6422. "format": "TNN",
  6423. "link": "https://github.com/lutzroeder/netron/issues/521"
  6424. },
  6425. {
  6426. "type": "tnn",
  6427. "target": "squeezenet_v1.1.tnnproto,squeezenet_v1.1.tnnmodel",
  6428. "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",
  6429. "format": "TNN",
  6430. "link": "https://github.com/Tencent/TNN"
  6431. },
  6432. {
  6433. "type": "torch",
  6434. "target": "2ch_notredame.t7",
  6435. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2ch/2ch_notredame.t7]",
  6436. "format": "Torch v7",
  6437. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  6438. },
  6439. {
  6440. "type": "torch",
  6441. "target": "2ch2stream_liberty.t7",
  6442. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2ch2stream/2ch2stream_liberty.t7]",
  6443. "format": "Torch v7",
  6444. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  6445. },
  6446. {
  6447. "type": "torch",
  6448. "target": "2chdeep_yosemite.t7",
  6449. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[2chdeep/2chdeep_yosemite.t7]",
  6450. "format": "Torch v7",
  6451. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  6452. },
  6453. {
  6454. "type": "torch",
  6455. "target": "apple2orange.t7",
  6456. "source": "https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/models/apple2orange.t7",
  6457. "format": "Torch v7",
  6458. "link": "https://github.com/junyanz/CycleGAN"
  6459. },
  6460. {
  6461. "type": "torch",
  6462. "target": "bedrooms_4_net_G.t7",
  6463. "source": "https://github.com/soumith/lfs/raw/master/dcgan.torch/bedrooms_4_net_G.t7",
  6464. "format": "Torch v7",
  6465. "link": "https://github.com/soumith/dcgan.torch"
  6466. },
  6467. {
  6468. "type": "torch",
  6469. "target": "celebA_25_net_G.t7",
  6470. "source": "https://github.com/soumith/lfs/raw/master/dcgan.torch/celebA_25_net_G.t7",
  6471. "format": "Torch v7",
  6472. "link": "https://github.com/soumith/dcgan.torch"
  6473. },
  6474. {
  6475. "type": "torch",
  6476. "target": "composition_vii.t7",
  6477. "source": "https://cs.stanford.edu/people/jcjohns/fast-neural-style/models/eccv16/composition_vii.t7",
  6478. "format": "Torch v7",
  6479. "link": "https://github.com/jcjohnson/fast-neural-style"
  6480. },
  6481. {
  6482. "type": "torch",
  6483. "target": "cunet_art_14l_scale2.0x_model.t7",
  6484. "source": "https://raw.githubusercontent.com/nagadomi/waifu2x/master/models/cunet/art/noise0_model.t7",
  6485. "format": "Torch v7",
  6486. "link": "https://github.com/nagadomi/waifu2x"
  6487. },
  6488. {
  6489. "type": "torch",
  6490. "target": "facades_photo2label.t7",
  6491. "source": "https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/models/facades_photo2label.t7",
  6492. "format": "Torch v7",
  6493. "link": "https://github.com/junyanz/CycleGAN"
  6494. },
  6495. {
  6496. "type": "torch",
  6497. "target": "Helen_8x.t7",
  6498. "source": "https://raw.githubusercontent.com/tyshiwo/FSRNet/master/models/Helen_8x.t7",
  6499. "format": "Torch v7",
  6500. "link": "https://github.com/tyshiwo/FSRNet"
  6501. },
  6502. {
  6503. "type": "torch",
  6504. "target": "inception.t7",
  6505. "source": "https://raw.githubusercontent.com/cpra/fer-cnn-sota/master/models/inception.t7",
  6506. "format": "Torch v7",
  6507. "link": "https://github.com/cpra/fer-cnn-sota"
  6508. },
  6509. {
  6510. "type": "torch",
  6511. "target": "net_kitti2015_fast_-a_train_all.t7",
  6512. "source": "https://github.com/lutzroeder/netron/files/3165404/net_kitti2015_fast_-a_train_all.t7.zip[net_kitti2015_fast_-a_train_all.t7]",
  6513. "format": "Torch v7",
  6514. "link": "https://github.com/lutzroeder/netron/issues/269"
  6515. },
  6516. {
  6517. "type": "torch",
  6518. "target": "openface.nn4.small2.v1.t7",
  6519. "source": "https://raw.githubusercontent.com/pyannote/pyannote-data/master/openface.nn4.small2.v1.t7",
  6520. "format": "Torch v7",
  6521. "link": "https://github.com/pyannote/pyannote-data"
  6522. },
  6523. {
  6524. "type": "torch",
  6525. "target": "resnet-18.t7",
  6526. "source": "https://d2j0dndfm35trm.cloudfront.net/resnet-18.t7",
  6527. "format": "Torch v7",
  6528. "link": "https://github.com/facebook/fb.resnet.torch"
  6529. },
  6530. {
  6531. "type": "torch",
  6532. "target": "resnet_photo_14l_scale2.0x_model.t7",
  6533. "source": "https://raw.githubusercontent.com/nagadomi/waifu2x/master/models/resnet_14l/photo/scale2.0x_model.t7",
  6534. "format": "Torch v7",
  6535. "link": "https://github.com/nagadomi/waifu2x"
  6536. },
  6537. {
  6538. "type": "torch",
  6539. "target": "rnnTracker_r300_l1_n1_m1_d4.t7",
  6540. "source": "https://raw.githubusercontent.com/aghagol/minimal_rnntracking_deploy/master/bin/rnnTracker_r300_l1_n1_m1_d4.t7",
  6541. "format": "Torch v7",
  6542. "link": "https://github.com/aghagol"
  6543. },
  6544. {
  6545. "type": "torch",
  6546. "target": "siam_liberty.t7",
  6547. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[siam/siam_liberty.t7]",
  6548. "format": "Torch v7",
  6549. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  6550. },
  6551. {
  6552. "type": "torch",
  6553. "target": "siam2stream_notredame.t7",
  6554. "source": "https://s3.amazonaws.com/modelzoo-networks/cvpr2015matching_networks.tar.gz[siam2stream/siam2stream_notredame.t7]",
  6555. "format": "Torch v7",
  6556. "link": "https://github.com/szagoruyko/cvpr15deepcompare"
  6557. },
  6558. {
  6559. "type": "torch",
  6560. "target": "soundnet5_final.t7",
  6561. "source": "http://data.csail.mit.edu/soundnet/soundnet_models_public.zip[soundnet_models_public/soundnet5_final.t7]",
  6562. "format": "Torch v7",
  6563. "link": "https://github.com/afperezm/acoustic-images-distillation"
  6564. },
  6565. {
  6566. "type": "torch",
  6567. "target": "vgg.t7",
  6568. "source": "https://raw.githubusercontent.com/cpra/fer-cnn-sota/master/models/vgg.t7",
  6569. "format": "Torch v7",
  6570. "link": "https://github.com/cpra/fer-cnn-sota"
  6571. },
  6572. {
  6573. "type": "uff",
  6574. "target": "tmp_v2_coco.pbtxt",
  6575. "source": "https://github.com/lutzroeder/netron/files/4741218/tmp_v2_coco.zip[tmp_v2_coco.pbtxt]",
  6576. "format": "UFF v1",
  6577. "link": "https://github.com/lutzroeder/netron/issues/511"
  6578. },
  6579. {
  6580. "type": "uff",
  6581. "target": "resnet50_tensorflow_1.6.uff",
  6582. "source": "https://github.com/lutzroeder/netron/files/7402208/resnet50_tensorflow_1.6.uff.zip[resnet50_tensorflow_1.6.uff]",
  6583. "format": "UFF v1",
  6584. "link": "https://github.com/lutzroeder/netron/issues/593"
  6585. },
  6586. {
  6587. "type": "uff",
  6588. "target": "sample_unpruned_mobilenet_v2.tar.gz",
  6589. "source": "https://nvidia.box.com/shared/static/8oqvmd79llr6lq1fr43s4fu1ph37v8nt.gz",
  6590. "format": "UFF v1",
  6591. "link": "https://github.com/lutzroeder/netron/issues/511"
  6592. },
  6593. {
  6594. "type": "weka",
  6595. "target": "j48model.model",
  6596. "source": "https://raw.githubusercontent.com/PTaati/wekaTree2python/master/j48model.model",
  6597. "error": "Unsupported type 'weka.classifiers.trees.J48' in 'j48model.model'."
  6598. },
  6599. {
  6600. "type": "xmodel",
  6601. "target": "face-quality_pt.xmodel",
  6602. "source": "https://github.com/lutzroeder/netron/files/7083632/face-quality_pt-vck190-r1.4.0.tar.gz[face-quality_pt/face-quality_pt.xmodel]",
  6603. "format": "xmodel",
  6604. "link": "https://github.com/lutzroeder/netron/issues/718"
  6605. },
  6606. {
  6607. "type": "xmodel",
  6608. "target": "mobilenet_1_0_224_tf2-zcu102_zcu104-r1.3.1.xmodel",
  6609. "source": "https://www.xilinx.com/bin/public/openDownload?filename=mobilenet_1_0_224_tf2-zcu102_zcu104-r1.3.1.tar.gz[mobilenet_1_0_224_tf2/mobilenet_1_0_224_tf2.xmodel]",
  6610. "format": "xmodel",
  6611. "link": "https://github.com/Xilinx/Vitis-AI/blob/master/models/AI-Model-Zoo/model-list/tf2_mobilenetv1_imagenet_224_224_1.15G_1.3/model.yaml"
  6612. },
  6613. {
  6614. "type": "xmodel",
  6615. "target": "mobilenet_1_0_224_tf2-u50-u50lv-u280-v3me-r1.3.1.xmodel",
  6616. "source": "https://www.xilinx.com/bin/public/openDownload?filename=mobilenet_1_0_224_tf2-u50-u50lv-u280-v3me-r1.3.1.tar.gz[mobilenet_1_0_224_tf2/mobilenet_1_0_224_tf2.xmodel]",
  6617. "format": "xmodel",
  6618. "link": "https://github.com/Xilinx/Vitis-AI/blob/master/models/AI-Model-Zoo/model-list/tf2_mobilenetv1_imagenet_224_224_1.15G_1.3/model.yaml"
  6619. },
  6620. {
  6621. "type": "xmodel",
  6622. "target": "PointsQuality_int.xmodel",
  6623. "source": "https://github.com/lutzroeder/netron/files/7083633/pt_face-quality_80_60_61.68M_1.4.zip[pt_face-quality_80_60_61.68M_1.4/quantized/PointsQuality_int.xmodel]",
  6624. "format": "xmodel",
  6625. "link": "https://github.com/lutzroeder/netron/issues/718"
  6626. }
  6627. ]