chainyo commited on
Commit
fcb528d
1 Parent(s): 56db83f

add config

Browse files
Files changed (2) hide show
  1. config.json +70 -1999
  2. finetuning.ipynb +12 -21
config.json CHANGED
@@ -28,2009 +28,80 @@
28
  256
29
  ],
30
  "id2label": {
31
- "0": "tench, Tinca tinca",
32
- "1": "goldfish, Carassius auratus",
33
- "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
34
- "3": "tiger shark, Galeocerdo cuvieri",
35
- "4": "hammerhead, hammerhead shark",
36
- "5": "electric ray, crampfish, numbfish, torpedo",
37
- "6": "stingray",
38
- "7": "cock",
39
- "8": "hen",
40
- "9": "ostrich, Struthio camelus",
41
- "10": "brambling, Fringilla montifringilla",
42
- "11": "goldfinch, Carduelis carduelis",
43
- "12": "house finch, linnet, Carpodacus mexicanus",
44
- "13": "junco, snowbird",
45
- "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea",
46
- "15": "robin, American robin, Turdus migratorius",
47
- "16": "bulbul",
48
- "17": "jay",
49
- "18": "magpie",
50
- "19": "chickadee",
51
- "20": "water ouzel, dipper",
52
- "21": "kite",
53
- "22": "bald eagle, American eagle, Haliaeetus leucocephalus",
54
- "23": "vulture",
55
- "24": "great grey owl, great gray owl, Strix nebulosa",
56
- "25": "European fire salamander, Salamandra salamandra",
57
- "26": "common newt, Triturus vulgaris",
58
- "27": "eft",
59
- "28": "spotted salamander, Ambystoma maculatum",
60
- "29": "axolotl, mud puppy, Ambystoma mexicanum",
61
- "30": "bullfrog, Rana catesbeiana",
62
- "31": "tree frog, tree-frog",
63
- "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui",
64
- "33": "loggerhead, loggerhead turtle, Caretta caretta",
65
- "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea",
66
- "35": "mud turtle",
67
- "36": "terrapin",
68
- "37": "box turtle, box tortoise",
69
- "38": "banded gecko",
70
- "39": "common iguana, iguana, Iguana iguana",
71
- "40": "American chameleon, anole, Anolis carolinensis",
72
- "41": "whiptail, whiptail lizard",
73
- "42": "agama",
74
- "43": "frilled lizard, Chlamydosaurus kingi",
75
- "44": "alligator lizard",
76
- "45": "Gila monster, Heloderma suspectum",
77
- "46": "green lizard, Lacerta viridis",
78
- "47": "African chameleon, Chamaeleo chamaeleon",
79
- "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis",
80
- "49": "African crocodile, Nile crocodile, Crocodylus niloticus",
81
- "50": "American alligator, Alligator mississipiensis",
82
- "51": "triceratops",
83
- "52": "thunder snake, worm snake, Carphophis amoenus",
84
- "53": "ringneck snake, ring-necked snake, ring snake",
85
- "54": "hognose snake, puff adder, sand viper",
86
- "55": "green snake, grass snake",
87
- "56": "king snake, kingsnake",
88
- "57": "garter snake, grass snake",
89
- "58": "water snake",
90
- "59": "vine snake",
91
- "60": "night snake, Hypsiglena torquata",
92
- "61": "boa constrictor, Constrictor constrictor",
93
- "62": "rock python, rock snake, Python sebae",
94
- "63": "Indian cobra, Naja naja",
95
- "64": "green mamba",
96
- "65": "sea snake",
97
- "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus",
98
- "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus",
99
- "68": "sidewinder, horned rattlesnake, Crotalus cerastes",
100
- "69": "trilobite",
101
- "70": "harvestman, daddy longlegs, Phalangium opilio",
102
- "71": "scorpion",
103
- "72": "black and gold garden spider, Argiope aurantia",
104
- "73": "barn spider, Araneus cavaticus",
105
- "74": "garden spider, Aranea diademata",
106
- "75": "black widow, Latrodectus mactans",
107
- "76": "tarantula",
108
- "77": "wolf spider, hunting spider",
109
- "78": "tick",
110
- "79": "centipede",
111
- "80": "black grouse",
112
- "81": "ptarmigan",
113
- "82": "ruffed grouse, partridge, Bonasa umbellus",
114
- "83": "prairie chicken, prairie grouse, prairie fowl",
115
- "84": "peacock",
116
- "85": "quail",
117
- "86": "partridge",
118
- "87": "African grey, African gray, Psittacus erithacus",
119
- "88": "macaw",
120
- "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita",
121
- "90": "lorikeet",
122
- "91": "coucal",
123
- "92": "bee eater",
124
- "93": "hornbill",
125
- "94": "hummingbird",
126
- "95": "jacamar",
127
- "96": "toucan",
128
- "97": "drake",
129
- "98": "red-breasted merganser, Mergus serrator",
130
- "99": "goose",
131
- "100": "black swan, Cygnus atratus",
132
- "101": "tusker",
133
- "102": "echidna, spiny anteater, anteater",
134
- "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus",
135
- "104": "wallaby, brush kangaroo",
136
- "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus",
137
- "106": "wombat",
138
- "107": "jellyfish",
139
- "108": "sea anemone, anemone",
140
- "109": "brain coral",
141
- "110": "flatworm, platyhelminth",
142
- "111": "nematode, nematode worm, roundworm",
143
- "112": "conch",
144
- "113": "snail",
145
- "114": "slug",
146
- "115": "sea slug, nudibranch",
147
- "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore",
148
- "117": "chambered nautilus, pearly nautilus, nautilus",
149
- "118": "Dungeness crab, Cancer magister",
150
- "119": "rock crab, Cancer irroratus",
151
- "120": "fiddler crab",
152
- "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica",
153
- "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus",
154
- "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish",
155
- "124": "crayfish, crawfish, crawdad, crawdaddy",
156
- "125": "hermit crab",
157
- "126": "isopod",
158
- "127": "white stork, Ciconia ciconia",
159
- "128": "black stork, Ciconia nigra",
160
- "129": "spoonbill",
161
- "130": "flamingo",
162
- "131": "little blue heron, Egretta caerulea",
163
- "132": "American egret, great white heron, Egretta albus",
164
- "133": "bittern",
165
- "134": "crane",
166
- "135": "limpkin, Aramus pictus",
167
- "136": "European gallinule, Porphyrio porphyrio",
168
- "137": "American coot, marsh hen, mud hen, water hen, Fulica americana",
169
- "138": "bustard",
170
- "139": "ruddy turnstone, Arenaria interpres",
171
- "140": "red-backed sandpiper, dunlin, Erolia alpina",
172
- "141": "redshank, Tringa totanus",
173
- "142": "dowitcher",
174
- "143": "oystercatcher, oyster catcher",
175
- "144": "pelican",
176
- "145": "king penguin, Aptenodytes patagonica",
177
- "146": "albatross, mollymawk",
178
- "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus",
179
- "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca",
180
- "149": "dugong, Dugong dugon",
181
- "150": "sea lion",
182
- "151": "Chihuahua",
183
- "152": "Japanese spaniel",
184
- "153": "Maltese dog, Maltese terrier, Maltese",
185
- "154": "Pekinese, Pekingese, Peke",
186
- "155": "Shih-Tzu",
187
- "156": "Blenheim spaniel",
188
- "157": "papillon",
189
- "158": "toy terrier",
190
- "159": "Rhodesian ridgeback",
191
- "160": "Afghan hound, Afghan",
192
- "161": "basset, basset hound",
193
- "162": "beagle",
194
- "163": "bloodhound, sleuthhound",
195
- "164": "bluetick",
196
- "165": "black-and-tan coonhound",
197
- "166": "Walker hound, Walker foxhound",
198
- "167": "English foxhound",
199
- "168": "redbone",
200
- "169": "borzoi, Russian wolfhound",
201
- "170": "Irish wolfhound",
202
- "171": "Italian greyhound",
203
- "172": "whippet",
204
- "173": "Ibizan hound, Ibizan Podenco",
205
- "174": "Norwegian elkhound, elkhound",
206
- "175": "otterhound, otter hound",
207
- "176": "Saluki, gazelle hound",
208
- "177": "Scottish deerhound, deerhound",
209
- "178": "Weimaraner",
210
- "179": "Staffordshire bullterrier, Staffordshire bull terrier",
211
- "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier",
212
- "181": "Bedlington terrier",
213
- "182": "Border terrier",
214
- "183": "Kerry blue terrier",
215
- "184": "Irish terrier",
216
- "185": "Norfolk terrier",
217
- "186": "Norwich terrier",
218
- "187": "Yorkshire terrier",
219
- "188": "wire-haired fox terrier",
220
- "189": "Lakeland terrier",
221
- "190": "Sealyham terrier, Sealyham",
222
- "191": "Airedale, Airedale terrier",
223
- "192": "cairn, cairn terrier",
224
- "193": "Australian terrier",
225
- "194": "Dandie Dinmont, Dandie Dinmont terrier",
226
- "195": "Boston bull, Boston terrier",
227
- "196": "miniature schnauzer",
228
- "197": "giant schnauzer",
229
- "198": "standard schnauzer",
230
- "199": "Scotch terrier, Scottish terrier, Scottie",
231
- "200": "Tibetan terrier, chrysanthemum dog",
232
- "201": "silky terrier, Sydney silky",
233
- "202": "soft-coated wheaten terrier",
234
- "203": "West Highland white terrier",
235
- "204": "Lhasa, Lhasa apso",
236
- "205": "flat-coated retriever",
237
- "206": "curly-coated retriever",
238
- "207": "golden retriever",
239
- "208": "Labrador retriever",
240
- "209": "Chesapeake Bay retriever",
241
- "210": "German short-haired pointer",
242
- "211": "vizsla, Hungarian pointer",
243
- "212": "English setter",
244
- "213": "Irish setter, red setter",
245
- "214": "Gordon setter",
246
- "215": "Brittany spaniel",
247
- "216": "clumber, clumber spaniel",
248
- "217": "English springer, English springer spaniel",
249
- "218": "Welsh springer spaniel",
250
- "219": "cocker spaniel, English cocker spaniel, cocker",
251
- "220": "Sussex spaniel",
252
- "221": "Irish water spaniel",
253
- "222": "kuvasz",
254
- "223": "schipperke",
255
- "224": "groenendael",
256
- "225": "malinois",
257
- "226": "briard",
258
- "227": "kelpie",
259
- "228": "komondor",
260
- "229": "Old English sheepdog, bobtail",
261
- "230": "Shetland sheepdog, Shetland sheep dog, Shetland",
262
- "231": "collie",
263
- "232": "Border collie",
264
- "233": "Bouvier des Flandres, Bouviers des Flandres",
265
- "234": "Rottweiler",
266
- "235": "German shepherd, German shepherd dog, German police dog, alsatian",
267
- "236": "Doberman, Doberman pinscher",
268
- "237": "miniature pinscher",
269
- "238": "Greater Swiss Mountain dog",
270
- "239": "Bernese mountain dog",
271
- "240": "Appenzeller",
272
- "241": "EntleBucher",
273
- "242": "boxer",
274
- "243": "bull mastiff",
275
- "244": "Tibetan mastiff",
276
- "245": "French bulldog",
277
- "246": "Great Dane",
278
- "247": "Saint Bernard, St Bernard",
279
- "248": "Eskimo dog, husky",
280
- "249": "malamute, malemute, Alaskan malamute",
281
- "250": "Siberian husky",
282
- "251": "dalmatian, coach dog, carriage dog",
283
- "252": "affenpinscher, monkey pinscher, monkey dog",
284
- "253": "basenji",
285
- "254": "pug, pug-dog",
286
- "255": "Leonberg",
287
- "256": "Newfoundland, Newfoundland dog",
288
- "257": "Great Pyrenees",
289
- "258": "Samoyed, Samoyede",
290
- "259": "Pomeranian",
291
- "260": "chow, chow chow",
292
- "261": "keeshond",
293
- "262": "Brabancon griffon",
294
- "263": "Pembroke, Pembroke Welsh corgi",
295
- "264": "Cardigan, Cardigan Welsh corgi",
296
- "265": "toy poodle",
297
- "266": "miniature poodle",
298
- "267": "standard poodle",
299
- "268": "Mexican hairless",
300
- "269": "timber wolf, grey wolf, gray wolf, Canis lupus",
301
- "270": "white wolf, Arctic wolf, Canis lupus tundrarum",
302
- "271": "red wolf, maned wolf, Canis rufus, Canis niger",
303
- "272": "coyote, prairie wolf, brush wolf, Canis latrans",
304
- "273": "dingo, warrigal, warragal, Canis dingo",
305
- "274": "dhole, Cuon alpinus",
306
- "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus",
307
- "276": "hyena, hyaena",
308
- "277": "red fox, Vulpes vulpes",
309
- "278": "kit fox, Vulpes macrotis",
310
- "279": "Arctic fox, white fox, Alopex lagopus",
311
- "280": "grey fox, gray fox, Urocyon cinereoargenteus",
312
- "281": "tabby, tabby cat",
313
- "282": "tiger cat",
314
- "283": "Persian cat",
315
- "284": "Siamese cat, Siamese",
316
- "285": "Egyptian cat",
317
- "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor",
318
- "287": "lynx, catamount",
319
- "288": "leopard, Panthera pardus",
320
- "289": "snow leopard, ounce, Panthera uncia",
321
- "290": "jaguar, panther, Panthera onca, Felis onca",
322
- "291": "lion, king of beasts, Panthera leo",
323
- "292": "tiger, Panthera tigris",
324
- "293": "cheetah, chetah, Acinonyx jubatus",
325
- "294": "brown bear, bruin, Ursus arctos",
326
- "295": "American black bear, black bear, Ursus americanus, Euarctos americanus",
327
- "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus",
328
- "297": "sloth bear, Melursus ursinus, Ursus ursinus",
329
- "298": "mongoose",
330
- "299": "meerkat, mierkat",
331
- "300": "tiger beetle",
332
- "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle",
333
- "302": "ground beetle, carabid beetle",
334
- "303": "long-horned beetle, longicorn, longicorn beetle",
335
- "304": "leaf beetle, chrysomelid",
336
- "305": "dung beetle",
337
- "306": "rhinoceros beetle",
338
- "307": "weevil",
339
- "308": "fly",
340
- "309": "bee",
341
- "310": "ant, emmet, pismire",
342
- "311": "grasshopper, hopper",
343
- "312": "cricket",
344
- "313": "walking stick, walkingstick, stick insect",
345
- "314": "cockroach, roach",
346
- "315": "mantis, mantid",
347
- "316": "cicada, cicala",
348
- "317": "leafhopper",
349
- "318": "lacewing, lacewing fly",
350
- "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
351
- "320": "damselfly",
352
- "321": "admiral",
353
- "322": "ringlet, ringlet butterfly",
354
- "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus",
355
- "324": "cabbage butterfly",
356
- "325": "sulphur butterfly, sulfur butterfly",
357
- "326": "lycaenid, lycaenid butterfly",
358
- "327": "starfish, sea star",
359
- "328": "sea urchin",
360
- "329": "sea cucumber, holothurian",
361
- "330": "wood rabbit, cottontail, cottontail rabbit",
362
- "331": "hare",
363
- "332": "Angora, Angora rabbit",
364
- "333": "hamster",
365
- "334": "porcupine, hedgehog",
366
- "335": "fox squirrel, eastern fox squirrel, Sciurus niger",
367
- "336": "marmot",
368
- "337": "beaver",
369
- "338": "guinea pig, Cavia cobaya",
370
- "339": "sorrel",
371
- "340": "zebra",
372
- "341": "hog, pig, grunter, squealer, Sus scrofa",
373
- "342": "wild boar, boar, Sus scrofa",
374
- "343": "warthog",
375
- "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius",
376
- "345": "ox",
377
- "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis",
378
- "347": "bison",
379
- "348": "ram, tup",
380
- "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis",
381
- "350": "ibex, Capra ibex",
382
- "351": "hartebeest",
383
- "352": "impala, Aepyceros melampus",
384
- "353": "gazelle",
385
- "354": "Arabian camel, dromedary, Camelus dromedarius",
386
- "355": "llama",
387
- "356": "weasel",
388
- "357": "mink",
389
- "358": "polecat, fitch, foulmart, foumart, Mustela putorius",
390
- "359": "black-footed ferret, ferret, Mustela nigripes",
391
- "360": "otter",
392
- "361": "skunk, polecat, wood pussy",
393
- "362": "badger",
394
- "363": "armadillo",
395
- "364": "three-toed sloth, ai, Bradypus tridactylus",
396
- "365": "orangutan, orang, orangutang, Pongo pygmaeus",
397
- "366": "gorilla, Gorilla gorilla",
398
- "367": "chimpanzee, chimp, Pan troglodytes",
399
- "368": "gibbon, Hylobates lar",
400
- "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus",
401
- "370": "guenon, guenon monkey",
402
- "371": "patas, hussar monkey, Erythrocebus patas",
403
- "372": "baboon",
404
- "373": "macaque",
405
- "374": "langur",
406
- "375": "colobus, colobus monkey",
407
- "376": "proboscis monkey, Nasalis larvatus",
408
- "377": "marmoset",
409
- "378": "capuchin, ringtail, Cebus capucinus",
410
- "379": "howler monkey, howler",
411
- "380": "titi, titi monkey",
412
- "381": "spider monkey, Ateles geoffroyi",
413
- "382": "squirrel monkey, Saimiri sciureus",
414
- "383": "Madagascar cat, ring-tailed lemur, Lemur catta",
415
- "384": "indri, indris, Indri indri, Indri brevicaudatus",
416
- "385": "Indian elephant, Elephas maximus",
417
- "386": "African elephant, Loxodonta africana",
418
- "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
419
- "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
420
- "389": "barracouta, snoek",
421
- "390": "eel",
422
- "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch",
423
- "392": "rock beauty, Holocanthus tricolor",
424
- "393": "anemone fish",
425
- "394": "sturgeon",
426
- "395": "gar, garfish, garpike, billfish, Lepisosteus osseus",
427
- "396": "lionfish",
428
- "397": "puffer, pufferfish, blowfish, globefish",
429
- "398": "abacus",
430
- "399": "abaya",
431
- "400": "academic gown, academic robe, judge's robe",
432
- "401": "accordion, piano accordion, squeeze box",
433
- "402": "acoustic guitar",
434
- "403": "aircraft carrier, carrier, flattop, attack aircraft carrier",
435
- "404": "airliner",
436
- "405": "airship, dirigible",
437
- "406": "altar",
438
- "407": "ambulance",
439
- "408": "amphibian, amphibious vehicle",
440
- "409": "analog clock",
441
- "410": "apiary, bee house",
442
- "411": "apron",
443
- "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin",
444
- "413": "assault rifle, assault gun",
445
- "414": "backpack, back pack, knapsack, packsack, rucksack, haversack",
446
- "415": "bakery, bakeshop, bakehouse",
447
- "416": "balance beam, beam",
448
- "417": "balloon",
449
- "418": "ballpoint, ballpoint pen, ballpen, Biro",
450
- "419": "Band Aid",
451
- "420": "banjo",
452
- "421": "bannister, banister, balustrade, balusters, handrail",
453
- "422": "barbell",
454
- "423": "barber chair",
455
- "424": "barbershop",
456
- "425": "barn",
457
- "426": "barometer",
458
- "427": "barrel, cask",
459
- "428": "barrow, garden cart, lawn cart, wheelbarrow",
460
- "429": "baseball",
461
- "430": "basketball",
462
- "431": "bassinet",
463
- "432": "bassoon",
464
- "433": "bathing cap, swimming cap",
465
- "434": "bath towel",
466
- "435": "bathtub, bathing tub, bath, tub",
467
- "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon",
468
- "437": "beacon, lighthouse, beacon light, pharos",
469
- "438": "beaker",
470
- "439": "bearskin, busby, shako",
471
- "440": "beer bottle",
472
- "441": "beer glass",
473
- "442": "bell cote, bell cot",
474
- "443": "bib",
475
- "444": "bicycle-built-for-two, tandem bicycle, tandem",
476
- "445": "bikini, two-piece",
477
- "446": "binder, ring-binder",
478
- "447": "binoculars, field glasses, opera glasses",
479
- "448": "birdhouse",
480
- "449": "boathouse",
481
- "450": "bobsled, bobsleigh, bob",
482
- "451": "bolo tie, bolo, bola tie, bola",
483
- "452": "bonnet, poke bonnet",
484
- "453": "bookcase",
485
- "454": "bookshop, bookstore, bookstall",
486
- "455": "bottlecap",
487
- "456": "bow",
488
- "457": "bow tie, bow-tie, bowtie",
489
- "458": "brass, memorial tablet, plaque",
490
- "459": "brassiere, bra, bandeau",
491
- "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty",
492
- "461": "breastplate, aegis, egis",
493
- "462": "broom",
494
- "463": "bucket, pail",
495
- "464": "buckle",
496
- "465": "bulletproof vest",
497
- "466": "bullet train, bullet",
498
- "467": "butcher shop, meat market",
499
- "468": "cab, hack, taxi, taxicab",
500
- "469": "caldron, cauldron",
501
- "470": "candle, taper, wax light",
502
- "471": "cannon",
503
- "472": "canoe",
504
- "473": "can opener, tin opener",
505
- "474": "cardigan",
506
- "475": "car mirror",
507
- "476": "carousel, carrousel, merry-go-round, roundabout, whirligig",
508
- "477": "carpenter's kit, tool kit",
509
- "478": "carton",
510
- "479": "car wheel",
511
- "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM",
512
- "481": "cassette",
513
- "482": "cassette player",
514
- "483": "castle",
515
- "484": "catamaran",
516
- "485": "CD player",
517
- "486": "cello, violoncello",
518
- "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone",
519
- "488": "chain",
520
- "489": "chainlink fence",
521
- "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour",
522
- "491": "chain saw, chainsaw",
523
- "492": "chest",
524
- "493": "chiffonier, commode",
525
- "494": "chime, bell, gong",
526
- "495": "china cabinet, china closet",
527
- "496": "Christmas stocking",
528
- "497": "church, church building",
529
- "498": "cinema, movie theater, movie theatre, movie house, picture palace",
530
- "499": "cleaver, meat cleaver, chopper",
531
- "500": "cliff dwelling",
532
- "501": "cloak",
533
- "502": "clog, geta, patten, sabot",
534
- "503": "cocktail shaker",
535
- "504": "coffee mug",
536
- "505": "coffeepot",
537
- "506": "coil, spiral, volute, whorl, helix",
538
- "507": "combination lock",
539
- "508": "computer keyboard, keypad",
540
- "509": "confectionery, confectionary, candy store",
541
- "510": "container ship, containership, container vessel",
542
- "511": "convertible",
543
- "512": "corkscrew, bottle screw",
544
- "513": "cornet, horn, trumpet, trump",
545
- "514": "cowboy boot",
546
- "515": "cowboy hat, ten-gallon hat",
547
- "516": "cradle",
548
- "517": "crane",
549
- "518": "crash helmet",
550
- "519": "crate",
551
- "520": "crib, cot",
552
- "521": "Crock Pot",
553
- "522": "croquet ball",
554
- "523": "crutch",
555
- "524": "cuirass",
556
- "525": "dam, dike, dyke",
557
- "526": "desk",
558
- "527": "desktop computer",
559
- "528": "dial telephone, dial phone",
560
- "529": "diaper, nappy, napkin",
561
- "530": "digital clock",
562
- "531": "digital watch",
563
- "532": "dining table, board",
564
- "533": "dishrag, dishcloth",
565
- "534": "dishwasher, dish washer, dishwashing machine",
566
- "535": "disk brake, disc brake",
567
- "536": "dock, dockage, docking facility",
568
- "537": "dogsled, dog sled, dog sleigh",
569
- "538": "dome",
570
- "539": "doormat, welcome mat",
571
- "540": "drilling platform, offshore rig",
572
- "541": "drum, membranophone, tympan",
573
- "542": "drumstick",
574
- "543": "dumbbell",
575
- "544": "Dutch oven",
576
- "545": "electric fan, blower",
577
- "546": "electric guitar",
578
- "547": "electric locomotive",
579
- "548": "entertainment center",
580
- "549": "envelope",
581
- "550": "espresso maker",
582
- "551": "face powder",
583
- "552": "feather boa, boa",
584
- "553": "file, file cabinet, filing cabinet",
585
- "554": "fireboat",
586
- "555": "fire engine, fire truck",
587
- "556": "fire screen, fireguard",
588
- "557": "flagpole, flagstaff",
589
- "558": "flute, transverse flute",
590
- "559": "folding chair",
591
- "560": "football helmet",
592
- "561": "forklift",
593
- "562": "fountain",
594
- "563": "fountain pen",
595
- "564": "four-poster",
596
- "565": "freight car",
597
- "566": "French horn, horn",
598
- "567": "frying pan, frypan, skillet",
599
- "568": "fur coat",
600
- "569": "garbage truck, dustcart",
601
- "570": "gasmask, respirator, gas helmet",
602
- "571": "gas pump, gasoline pump, petrol pump, island dispenser",
603
- "572": "goblet",
604
- "573": "go-kart",
605
- "574": "golf ball",
606
- "575": "golfcart, golf cart",
607
- "576": "gondola",
608
- "577": "gong, tam-tam",
609
- "578": "gown",
610
- "579": "grand piano, grand",
611
- "580": "greenhouse, nursery, glasshouse",
612
- "581": "grille, radiator grille",
613
- "582": "grocery store, grocery, food market, market",
614
- "583": "guillotine",
615
- "584": "hair slide",
616
- "585": "hair spray",
617
- "586": "half track",
618
- "587": "hammer",
619
- "588": "hamper",
620
- "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier",
621
- "590": "hand-held computer, hand-held microcomputer",
622
- "591": "handkerchief, hankie, hanky, hankey",
623
- "592": "hard disc, hard disk, fixed disk",
624
- "593": "harmonica, mouth organ, harp, mouth harp",
625
- "594": "harp",
626
- "595": "harvester, reaper",
627
- "596": "hatchet",
628
- "597": "holster",
629
- "598": "home theater, home theatre",
630
- "599": "honeycomb",
631
- "600": "hook, claw",
632
- "601": "hoopskirt, crinoline",
633
- "602": "horizontal bar, high bar",
634
- "603": "horse cart, horse-cart",
635
- "604": "hourglass",
636
- "605": "iPod",
637
- "606": "iron, smoothing iron",
638
- "607": "jack-o'-lantern",
639
- "608": "jean, blue jean, denim",
640
- "609": "jeep, landrover",
641
- "610": "jersey, T-shirt, tee shirt",
642
- "611": "jigsaw puzzle",
643
- "612": "jinrikisha, ricksha, rickshaw",
644
- "613": "joystick",
645
- "614": "kimono",
646
- "615": "knee pad",
647
- "616": "knot",
648
- "617": "lab coat, laboratory coat",
649
- "618": "ladle",
650
- "619": "lampshade, lamp shade",
651
- "620": "laptop, laptop computer",
652
- "621": "lawn mower, mower",
653
- "622": "lens cap, lens cover",
654
- "623": "letter opener, paper knife, paperknife",
655
- "624": "library",
656
- "625": "lifeboat",
657
- "626": "lighter, light, igniter, ignitor",
658
- "627": "limousine, limo",
659
- "628": "liner, ocean liner",
660
- "629": "lipstick, lip rouge",
661
- "630": "Loafer",
662
- "631": "lotion",
663
- "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system",
664
- "633": "loupe, jeweler's loupe",
665
- "634": "lumbermill, sawmill",
666
- "635": "magnetic compass",
667
- "636": "mailbag, postbag",
668
- "637": "mailbox, letter box",
669
- "638": "maillot",
670
- "639": "maillot, tank suit",
671
- "640": "manhole cover",
672
- "641": "maraca",
673
- "642": "marimba, xylophone",
674
- "643": "mask",
675
- "644": "matchstick",
676
- "645": "maypole",
677
- "646": "maze, labyrinth",
678
- "647": "measuring cup",
679
- "648": "medicine chest, medicine cabinet",
680
- "649": "megalith, megalithic structure",
681
- "650": "microphone, mike",
682
- "651": "microwave, microwave oven",
683
- "652": "military uniform",
684
- "653": "milk can",
685
- "654": "minibus",
686
- "655": "miniskirt, mini",
687
- "656": "minivan",
688
- "657": "missile",
689
- "658": "mitten",
690
- "659": "mixing bowl",
691
- "660": "mobile home, manufactured home",
692
- "661": "Model T",
693
- "662": "modem",
694
- "663": "monastery",
695
- "664": "monitor",
696
- "665": "moped",
697
- "666": "mortar",
698
- "667": "mortarboard",
699
- "668": "mosque",
700
- "669": "mosquito net",
701
- "670": "motor scooter, scooter",
702
- "671": "mountain bike, all-terrain bike, off-roader",
703
- "672": "mountain tent",
704
- "673": "mouse, computer mouse",
705
- "674": "mousetrap",
706
- "675": "moving van",
707
- "676": "muzzle",
708
- "677": "nail",
709
- "678": "neck brace",
710
- "679": "necklace",
711
- "680": "nipple",
712
- "681": "notebook, notebook computer",
713
- "682": "obelisk",
714
- "683": "oboe, hautboy, hautbois",
715
- "684": "ocarina, sweet potato",
716
- "685": "odometer, hodometer, mileometer, milometer",
717
- "686": "oil filter",
718
- "687": "organ, pipe organ",
719
- "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO",
720
- "689": "overskirt",
721
- "690": "oxcart",
722
- "691": "oxygen mask",
723
- "692": "packet",
724
- "693": "paddle, boat paddle",
725
- "694": "paddlewheel, paddle wheel",
726
- "695": "padlock",
727
- "696": "paintbrush",
728
- "697": "pajama, pyjama, pj's, jammies",
729
- "698": "palace",
730
- "699": "panpipe, pandean pipe, syrinx",
731
- "700": "paper towel",
732
- "701": "parachute, chute",
733
- "702": "parallel bars, bars",
734
- "703": "park bench",
735
- "704": "parking meter",
736
- "705": "passenger car, coach, carriage",
737
- "706": "patio, terrace",
738
- "707": "pay-phone, pay-station",
739
- "708": "pedestal, plinth, footstall",
740
- "709": "pencil box, pencil case",
741
- "710": "pencil sharpener",
742
- "711": "perfume, essence",
743
- "712": "Petri dish",
744
- "713": "photocopier",
745
- "714": "pick, plectrum, plectron",
746
- "715": "pickelhaube",
747
- "716": "picket fence, paling",
748
- "717": "pickup, pickup truck",
749
- "718": "pier",
750
- "719": "piggy bank, penny bank",
751
- "720": "pill bottle",
752
- "721": "pillow",
753
- "722": "ping-pong ball",
754
- "723": "pinwheel",
755
- "724": "pirate, pirate ship",
756
- "725": "pitcher, ewer",
757
- "726": "plane, carpenter's plane, woodworking plane",
758
- "727": "planetarium",
759
- "728": "plastic bag",
760
- "729": "plate rack",
761
- "730": "plow, plough",
762
- "731": "plunger, plumber's helper",
763
- "732": "Polaroid camera, Polaroid Land camera",
764
- "733": "pole",
765
- "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria",
766
- "735": "poncho",
767
- "736": "pool table, billiard table, snooker table",
768
- "737": "pop bottle, soda bottle",
769
- "738": "pot, flowerpot",
770
- "739": "potter's wheel",
771
- "740": "power drill",
772
- "741": "prayer rug, prayer mat",
773
- "742": "printer",
774
- "743": "prison, prison house",
775
- "744": "projectile, missile",
776
- "745": "projector",
777
- "746": "puck, hockey puck",
778
- "747": "punching bag, punch bag, punching ball, punchball",
779
- "748": "purse",
780
- "749": "quill, quill pen",
781
- "750": "quilt, comforter, comfort, puff",
782
- "751": "racer, race car, racing car",
783
- "752": "racket, racquet",
784
- "753": "radiator",
785
- "754": "radio, wireless",
786
- "755": "radio telescope, radio reflector",
787
- "756": "rain barrel",
788
- "757": "recreational vehicle, RV, R.V.",
789
- "758": "reel",
790
- "759": "reflex camera",
791
- "760": "refrigerator, icebox",
792
- "761": "remote control, remote",
793
- "762": "restaurant, eating house, eating place, eatery",
794
- "763": "revolver, six-gun, six-shooter",
795
- "764": "rifle",
796
- "765": "rocking chair, rocker",
797
- "766": "rotisserie",
798
- "767": "rubber eraser, rubber, pencil eraser",
799
- "768": "rugby ball",
800
- "769": "rule, ruler",
801
- "770": "running shoe",
802
- "771": "safe",
803
- "772": "safety pin",
804
- "773": "saltshaker, salt shaker",
805
- "774": "sandal",
806
- "775": "sarong",
807
- "776": "sax, saxophone",
808
- "777": "scabbard",
809
- "778": "scale, weighing machine",
810
- "779": "school bus",
811
- "780": "schooner",
812
- "781": "scoreboard",
813
- "782": "screen, CRT screen",
814
- "783": "screw",
815
- "784": "screwdriver",
816
- "785": "seat belt, seatbelt",
817
- "786": "sewing machine",
818
- "787": "shield, buckler",
819
- "788": "shoe shop, shoe-shop, shoe store",
820
- "789": "shoji",
821
- "790": "shopping basket",
822
- "791": "shopping cart",
823
- "792": "shovel",
824
- "793": "shower cap",
825
- "794": "shower curtain",
826
- "795": "ski",
827
- "796": "ski mask",
828
- "797": "sleeping bag",
829
- "798": "slide rule, slipstick",
830
- "799": "sliding door",
831
- "800": "slot, one-armed bandit",
832
- "801": "snorkel",
833
- "802": "snowmobile",
834
- "803": "snowplow, snowplough",
835
- "804": "soap dispenser",
836
- "805": "soccer ball",
837
- "806": "sock",
838
- "807": "solar dish, solar collector, solar furnace",
839
- "808": "sombrero",
840
- "809": "soup bowl",
841
- "810": "space bar",
842
- "811": "space heater",
843
- "812": "space shuttle",
844
- "813": "spatula",
845
- "814": "speedboat",
846
- "815": "spider web, spider's web",
847
- "816": "spindle",
848
- "817": "sports car, sport car",
849
- "818": "spotlight, spot",
850
- "819": "stage",
851
- "820": "steam locomotive",
852
- "821": "steel arch bridge",
853
- "822": "steel drum",
854
- "823": "stethoscope",
855
- "824": "stole",
856
- "825": "stone wall",
857
- "826": "stopwatch, stop watch",
858
- "827": "stove",
859
- "828": "strainer",
860
- "829": "streetcar, tram, tramcar, trolley, trolley car",
861
- "830": "stretcher",
862
- "831": "studio couch, day bed",
863
- "832": "stupa, tope",
864
- "833": "submarine, pigboat, sub, U-boat",
865
- "834": "suit, suit of clothes",
866
- "835": "sundial",
867
- "836": "sunglass",
868
- "837": "sunglasses, dark glasses, shades",
869
- "838": "sunscreen, sunblock, sun blocker",
870
- "839": "suspension bridge",
871
- "840": "swab, swob, mop",
872
- "841": "sweatshirt",
873
- "842": "swimming trunks, bathing trunks",
874
- "843": "swing",
875
- "844": "switch, electric switch, electrical switch",
876
- "845": "syringe",
877
- "846": "table lamp",
878
- "847": "tank, army tank, armored combat vehicle, armoured combat vehicle",
879
- "848": "tape player",
880
- "849": "teapot",
881
- "850": "teddy, teddy bear",
882
- "851": "television, television system",
883
- "852": "tennis ball",
884
- "853": "thatch, thatched roof",
885
- "854": "theater curtain, theatre curtain",
886
- "855": "thimble",
887
- "856": "thresher, thrasher, threshing machine",
888
- "857": "throne",
889
- "858": "tile roof",
890
- "859": "toaster",
891
- "860": "tobacco shop, tobacconist shop, tobacconist",
892
- "861": "toilet seat",
893
- "862": "torch",
894
- "863": "totem pole",
895
- "864": "tow truck, tow car, wrecker",
896
- "865": "toyshop",
897
- "866": "tractor",
898
- "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi",
899
- "868": "tray",
900
- "869": "trench coat",
901
- "870": "tricycle, trike, velocipede",
902
- "871": "trimaran",
903
- "872": "tripod",
904
- "873": "triumphal arch",
905
- "874": "trolleybus, trolley coach, trackless trolley",
906
- "875": "trombone",
907
- "876": "tub, vat",
908
- "877": "turnstile",
909
- "878": "typewriter keyboard",
910
- "879": "umbrella",
911
- "880": "unicycle, monocycle",
912
- "881": "upright, upright piano",
913
- "882": "vacuum, vacuum cleaner",
914
- "883": "vase",
915
- "884": "vault",
916
- "885": "velvet",
917
- "886": "vending machine",
918
- "887": "vestment",
919
- "888": "viaduct",
920
- "889": "violin, fiddle",
921
- "890": "volleyball",
922
- "891": "waffle iron",
923
- "892": "wall clock",
924
- "893": "wallet, billfold, notecase, pocketbook",
925
- "894": "wardrobe, closet, press",
926
- "895": "warplane, military plane",
927
- "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin",
928
- "897": "washer, automatic washer, washing machine",
929
- "898": "water bottle",
930
- "899": "water jug",
931
- "900": "water tower",
932
- "901": "whiskey jug",
933
- "902": "whistle",
934
- "903": "wig",
935
- "904": "window screen",
936
- "905": "window shade",
937
- "906": "Windsor tie",
938
- "907": "wine bottle",
939
- "908": "wing",
940
- "909": "wok",
941
- "910": "wooden spoon",
942
- "911": "wool, woolen, woollen",
943
- "912": "worm fence, snake fence, snake-rail fence, Virginia fence",
944
- "913": "wreck",
945
- "914": "yawl",
946
- "915": "yurt",
947
- "916": "web site, website, internet site, site",
948
- "917": "comic book",
949
- "918": "crossword puzzle, crossword",
950
- "919": "street sign",
951
- "920": "traffic light, traffic signal, stoplight",
952
- "921": "book jacket, dust cover, dust jacket, dust wrapper",
953
- "922": "menu",
954
- "923": "plate",
955
- "924": "guacamole",
956
- "925": "consomme",
957
- "926": "hot pot, hotpot",
958
- "927": "trifle",
959
- "928": "ice cream, icecream",
960
- "929": "ice lolly, lolly, lollipop, popsicle",
961
- "930": "French loaf",
962
- "931": "bagel, beigel",
963
- "932": "pretzel",
964
- "933": "cheeseburger",
965
- "934": "hotdog, hot dog, red hot",
966
- "935": "mashed potato",
967
- "936": "head cabbage",
968
- "937": "broccoli",
969
- "938": "cauliflower",
970
- "939": "zucchini, courgette",
971
- "940": "spaghetti squash",
972
- "941": "acorn squash",
973
- "942": "butternut squash",
974
- "943": "cucumber, cuke",
975
- "944": "artichoke, globe artichoke",
976
- "945": "bell pepper",
977
- "946": "cardoon",
978
- "947": "mushroom",
979
- "948": "Granny Smith",
980
- "949": "strawberry",
981
- "950": "orange",
982
- "951": "lemon",
983
- "952": "fig",
984
- "953": "pineapple, ananas",
985
- "954": "banana",
986
- "955": "jackfruit, jak, jack",
987
- "956": "custard apple",
988
- "957": "pomegranate",
989
- "958": "hay",
990
- "959": "carbonara",
991
- "960": "chocolate sauce, chocolate syrup",
992
- "961": "dough",
993
- "962": "meat loaf, meatloaf",
994
- "963": "pizza, pizza pie",
995
- "964": "potpie",
996
- "965": "burrito",
997
- "966": "red wine",
998
- "967": "espresso",
999
- "968": "cup",
1000
- "969": "eggnog",
1001
- "970": "alp",
1002
- "971": "bubble",
1003
- "972": "cliff, drop, drop-off",
1004
- "973": "coral reef",
1005
- "974": "geyser",
1006
- "975": "lakeside, lakeshore",
1007
- "976": "promontory, headland, head, foreland",
1008
- "977": "sandbar, sand bar",
1009
- "978": "seashore, coast, seacoast, sea-coast",
1010
- "979": "valley, vale",
1011
- "980": "volcano",
1012
- "981": "ballplayer, baseball player",
1013
- "982": "groom, bridegroom",
1014
- "983": "scuba diver",
1015
- "984": "rapeseed",
1016
- "985": "daisy",
1017
- "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
1018
- "987": "corn",
1019
- "988": "acorn",
1020
- "989": "hip, rose hip, rosehip",
1021
- "990": "buckeye, horse chestnut, conker",
1022
- "991": "coral fungus",
1023
- "992": "agaric",
1024
- "993": "gyromitra",
1025
- "994": "stinkhorn, carrion fungus",
1026
- "995": "earthstar",
1027
- "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa",
1028
- "997": "bolete",
1029
- "998": "ear, spike, capitulum",
1030
- "999": "toilet tissue, toilet paper, bathroom tissue"
1031
  },
1032
  "image_size": 224,
1033
  "initializer_range": 0.02,
1034
  "label2id": {
1035
- "Afghan hound, Afghan": 160,
1036
- "African chameleon, Chamaeleo chamaeleon": 47,
1037
- "African crocodile, Nile crocodile, Crocodylus niloticus": 49,
1038
- "African elephant, Loxodonta africana": 386,
1039
- "African grey, African gray, Psittacus erithacus": 87,
1040
- "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus": 275,
1041
- "Airedale, Airedale terrier": 191,
1042
- "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier": 180,
1043
- "American alligator, Alligator mississipiensis": 50,
1044
- "American black bear, black bear, Ursus americanus, Euarctos americanus": 295,
1045
- "American chameleon, anole, Anolis carolinensis": 40,
1046
- "American coot, marsh hen, mud hen, water hen, Fulica americana": 137,
1047
- "American egret, great white heron, Egretta albus": 132,
1048
- "American lobster, Northern lobster, Maine lobster, Homarus americanus": 122,
1049
- "Angora, Angora rabbit": 332,
1050
- "Appenzeller": 240,
1051
- "Arabian camel, dromedary, Camelus dromedarius": 354,
1052
- "Arctic fox, white fox, Alopex lagopus": 279,
1053
- "Australian terrier": 193,
1054
- "Band Aid": 419,
1055
- "Bedlington terrier": 181,
1056
- "Bernese mountain dog": 239,
1057
- "Blenheim spaniel": 156,
1058
- "Border collie": 232,
1059
- "Border terrier": 182,
1060
- "Boston bull, Boston terrier": 195,
1061
- "Bouvier des Flandres, Bouviers des Flandres": 233,
1062
- "Brabancon griffon": 262,
1063
- "Brittany spaniel": 215,
1064
- "CD player": 485,
1065
- "Cardigan, Cardigan Welsh corgi": 264,
1066
- "Chesapeake Bay retriever": 209,
1067
- "Chihuahua": 151,
1068
- "Christmas stocking": 496,
1069
- "Crock Pot": 521,
1070
- "Dandie Dinmont, Dandie Dinmont terrier": 194,
1071
- "Doberman, Doberman pinscher": 236,
1072
- "Dungeness crab, Cancer magister": 118,
1073
- "Dutch oven": 544,
1074
- "Egyptian cat": 285,
1075
- "English foxhound": 167,
1076
- "English setter": 212,
1077
- "English springer, English springer spaniel": 217,
1078
- "EntleBucher": 241,
1079
- "Eskimo dog, husky": 248,
1080
- "European fire salamander, Salamandra salamandra": 25,
1081
- "European gallinule, Porphyrio porphyrio": 136,
1082
- "French bulldog": 245,
1083
- "French horn, horn": 566,
1084
- "French loaf": 930,
1085
- "German shepherd, German shepherd dog, German police dog, alsatian": 235,
1086
- "German short-haired pointer": 210,
1087
- "Gila monster, Heloderma suspectum": 45,
1088
- "Gordon setter": 214,
1089
- "Granny Smith": 948,
1090
- "Great Dane": 246,
1091
- "Great Pyrenees": 257,
1092
- "Greater Swiss Mountain dog": 238,
1093
- "Ibizan hound, Ibizan Podenco": 173,
1094
- "Indian cobra, Naja naja": 63,
1095
- "Indian elephant, Elephas maximus": 385,
1096
- "Irish setter, red setter": 213,
1097
- "Irish terrier": 184,
1098
- "Irish water spaniel": 221,
1099
- "Irish wolfhound": 170,
1100
- "Italian greyhound": 171,
1101
- "Japanese spaniel": 152,
1102
- "Kerry blue terrier": 183,
1103
- "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis": 48,
1104
- "Labrador retriever": 208,
1105
- "Lakeland terrier": 189,
1106
- "Leonberg": 255,
1107
- "Lhasa, Lhasa apso": 204,
1108
- "Loafer": 630,
1109
- "Madagascar cat, ring-tailed lemur, Lemur catta": 383,
1110
- "Maltese dog, Maltese terrier, Maltese": 153,
1111
- "Mexican hairless": 268,
1112
- "Model T": 661,
1113
- "Newfoundland, Newfoundland dog": 256,
1114
- "Norfolk terrier": 185,
1115
- "Norwegian elkhound, elkhound": 174,
1116
- "Norwich terrier": 186,
1117
- "Old English sheepdog, bobtail": 229,
1118
- "Pekinese, Pekingese, Peke": 154,
1119
- "Pembroke, Pembroke Welsh corgi": 263,
1120
- "Persian cat": 283,
1121
- "Petri dish": 712,
1122
- "Polaroid camera, Polaroid Land camera": 732,
1123
- "Pomeranian": 259,
1124
- "Rhodesian ridgeback": 159,
1125
- "Rottweiler": 234,
1126
- "Saint Bernard, St Bernard": 247,
1127
- "Saluki, gazelle hound": 176,
1128
- "Samoyed, Samoyede": 258,
1129
- "Scotch terrier, Scottish terrier, Scottie": 199,
1130
- "Scottish deerhound, deerhound": 177,
1131
- "Sealyham terrier, Sealyham": 190,
1132
- "Shetland sheepdog, Shetland sheep dog, Shetland": 230,
1133
- "Shih-Tzu": 155,
1134
- "Siamese cat, Siamese": 284,
1135
- "Siberian husky": 250,
1136
- "Staffordshire bullterrier, Staffordshire bull terrier": 179,
1137
- "Sussex spaniel": 220,
1138
- "Tibetan mastiff": 244,
1139
- "Tibetan terrier, chrysanthemum dog": 200,
1140
- "Walker hound, Walker foxhound": 166,
1141
- "Weimaraner": 178,
1142
- "Welsh springer spaniel": 218,
1143
- "West Highland white terrier": 203,
1144
- "Windsor tie": 906,
1145
- "Yorkshire terrier": 187,
1146
- "abacus": 398,
1147
- "abaya": 399,
1148
- "academic gown, academic robe, judge's robe": 400,
1149
- "accordion, piano accordion, squeeze box": 401,
1150
- "acorn": 988,
1151
- "acorn squash": 941,
1152
- "acoustic guitar": 402,
1153
- "admiral": 321,
1154
- "affenpinscher, monkey pinscher, monkey dog": 252,
1155
- "agama": 42,
1156
- "agaric": 992,
1157
- "aircraft carrier, carrier, flattop, attack aircraft carrier": 403,
1158
- "airliner": 404,
1159
- "airship, dirigible": 405,
1160
- "albatross, mollymawk": 146,
1161
- "alligator lizard": 44,
1162
- "alp": 970,
1163
- "altar": 406,
1164
- "ambulance": 407,
1165
- "amphibian, amphibious vehicle": 408,
1166
- "analog clock": 409,
1167
- "anemone fish": 393,
1168
- "ant, emmet, pismire": 310,
1169
- "apiary, bee house": 410,
1170
- "apron": 411,
1171
- "armadillo": 363,
1172
- "artichoke, globe artichoke": 944,
1173
- "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin": 412,
1174
- "assault rifle, assault gun": 413,
1175
- "axolotl, mud puppy, Ambystoma mexicanum": 29,
1176
- "baboon": 372,
1177
- "backpack, back pack, knapsack, packsack, rucksack, haversack": 414,
1178
- "badger": 362,
1179
- "bagel, beigel": 931,
1180
- "bakery, bakeshop, bakehouse": 415,
1181
- "balance beam, beam": 416,
1182
- "bald eagle, American eagle, Haliaeetus leucocephalus": 22,
1183
- "balloon": 417,
1184
- "ballplayer, baseball player": 981,
1185
- "ballpoint, ballpoint pen, ballpen, Biro": 418,
1186
- "banana": 954,
1187
- "banded gecko": 38,
1188
- "banjo": 420,
1189
- "bannister, banister, balustrade, balusters, handrail": 421,
1190
- "barbell": 422,
1191
- "barber chair": 423,
1192
- "barbershop": 424,
1193
- "barn": 425,
1194
- "barn spider, Araneus cavaticus": 73,
1195
- "barometer": 426,
1196
- "barracouta, snoek": 389,
1197
- "barrel, cask": 427,
1198
- "barrow, garden cart, lawn cart, wheelbarrow": 428,
1199
- "baseball": 429,
1200
- "basenji": 253,
1201
- "basketball": 430,
1202
- "basset, basset hound": 161,
1203
- "bassinet": 431,
1204
- "bassoon": 432,
1205
- "bath towel": 434,
1206
- "bathing cap, swimming cap": 433,
1207
- "bathtub, bathing tub, bath, tub": 435,
1208
- "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon": 436,
1209
- "beacon, lighthouse, beacon light, pharos": 437,
1210
- "beagle": 162,
1211
- "beaker": 438,
1212
- "bearskin, busby, shako": 439,
1213
- "beaver": 337,
1214
- "bee": 309,
1215
- "bee eater": 92,
1216
- "beer bottle": 440,
1217
- "beer glass": 441,
1218
- "bell cote, bell cot": 442,
1219
- "bell pepper": 945,
1220
- "bib": 443,
1221
- "bicycle-built-for-two, tandem bicycle, tandem": 444,
1222
- "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis": 349,
1223
- "bikini, two-piece": 445,
1224
- "binder, ring-binder": 446,
1225
- "binoculars, field glasses, opera glasses": 447,
1226
- "birdhouse": 448,
1227
- "bison": 347,
1228
- "bittern": 133,
1229
- "black and gold garden spider, Argiope aurantia": 72,
1230
- "black grouse": 80,
1231
- "black stork, Ciconia nigra": 128,
1232
- "black swan, Cygnus atratus": 100,
1233
- "black widow, Latrodectus mactans": 75,
1234
- "black-and-tan coonhound": 165,
1235
- "black-footed ferret, ferret, Mustela nigripes": 359,
1236
- "bloodhound, sleuthhound": 163,
1237
- "bluetick": 164,
1238
- "boa constrictor, Constrictor constrictor": 61,
1239
- "boathouse": 449,
1240
- "bobsled, bobsleigh, bob": 450,
1241
- "bolete": 997,
1242
- "bolo tie, bolo, bola tie, bola": 451,
1243
- "bonnet, poke bonnet": 452,
1244
- "book jacket, dust cover, dust jacket, dust wrapper": 921,
1245
- "bookcase": 453,
1246
- "bookshop, bookstore, bookstall": 454,
1247
- "borzoi, Russian wolfhound": 169,
1248
- "bottlecap": 455,
1249
- "bow": 456,
1250
- "bow tie, bow-tie, bowtie": 457,
1251
- "box turtle, box tortoise": 37,
1252
- "boxer": 242,
1253
- "brain coral": 109,
1254
- "brambling, Fringilla montifringilla": 10,
1255
- "brass, memorial tablet, plaque": 458,
1256
- "brassiere, bra, bandeau": 459,
1257
- "breakwater, groin, groyne, mole, bulwark, seawall, jetty": 460,
1258
- "breastplate, aegis, egis": 461,
1259
- "briard": 226,
1260
- "broccoli": 937,
1261
- "broom": 462,
1262
- "brown bear, bruin, Ursus arctos": 294,
1263
- "bubble": 971,
1264
- "bucket, pail": 463,
1265
- "buckeye, horse chestnut, conker": 990,
1266
- "buckle": 464,
1267
- "bulbul": 16,
1268
- "bull mastiff": 243,
1269
- "bullet train, bullet": 466,
1270
- "bulletproof vest": 465,
1271
- "bullfrog, Rana catesbeiana": 30,
1272
- "burrito": 965,
1273
- "bustard": 138,
1274
- "butcher shop, meat market": 467,
1275
- "butternut squash": 942,
1276
- "cab, hack, taxi, taxicab": 468,
1277
- "cabbage butterfly": 324,
1278
- "cairn, cairn terrier": 192,
1279
- "caldron, cauldron": 469,
1280
- "can opener, tin opener": 473,
1281
- "candle, taper, wax light": 470,
1282
- "cannon": 471,
1283
- "canoe": 472,
1284
- "capuchin, ringtail, Cebus capucinus": 378,
1285
- "car mirror": 475,
1286
- "car wheel": 479,
1287
- "carbonara": 959,
1288
- "cardigan": 474,
1289
- "cardoon": 946,
1290
- "carousel, carrousel, merry-go-round, roundabout, whirligig": 476,
1291
- "carpenter's kit, tool kit": 477,
1292
- "carton": 478,
1293
- "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM": 480,
1294
- "cassette": 481,
1295
- "cassette player": 482,
1296
- "castle": 483,
1297
- "catamaran": 484,
1298
- "cauliflower": 938,
1299
- "cello, violoncello": 486,
1300
- "cellular telephone, cellular phone, cellphone, cell, mobile phone": 487,
1301
- "centipede": 79,
1302
- "chain": 488,
1303
- "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour": 490,
1304
- "chain saw, chainsaw": 491,
1305
- "chainlink fence": 489,
1306
- "chambered nautilus, pearly nautilus, nautilus": 117,
1307
- "cheeseburger": 933,
1308
- "cheetah, chetah, Acinonyx jubatus": 293,
1309
- "chest": 492,
1310
- "chickadee": 19,
1311
- "chiffonier, commode": 493,
1312
- "chime, bell, gong": 494,
1313
- "chimpanzee, chimp, Pan troglodytes": 367,
1314
- "china cabinet, china closet": 495,
1315
- "chiton, coat-of-mail shell, sea cradle, polyplacophore": 116,
1316
- "chocolate sauce, chocolate syrup": 960,
1317
- "chow, chow chow": 260,
1318
- "church, church building": 497,
1319
- "cicada, cicala": 316,
1320
- "cinema, movie theater, movie theatre, movie house, picture palace": 498,
1321
- "cleaver, meat cleaver, chopper": 499,
1322
- "cliff dwelling": 500,
1323
- "cliff, drop, drop-off": 972,
1324
- "cloak": 501,
1325
- "clog, geta, patten, sabot": 502,
1326
- "clumber, clumber spaniel": 216,
1327
- "cock": 7,
1328
- "cocker spaniel, English cocker spaniel, cocker": 219,
1329
- "cockroach, roach": 314,
1330
- "cocktail shaker": 503,
1331
- "coffee mug": 504,
1332
- "coffeepot": 505,
1333
- "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch": 391,
1334
- "coil, spiral, volute, whorl, helix": 506,
1335
- "collie": 231,
1336
- "colobus, colobus monkey": 375,
1337
- "combination lock": 507,
1338
- "comic book": 917,
1339
- "common iguana, iguana, Iguana iguana": 39,
1340
- "common newt, Triturus vulgaris": 26,
1341
- "computer keyboard, keypad": 508,
1342
- "conch": 112,
1343
- "confectionery, confectionary, candy store": 509,
1344
- "consomme": 925,
1345
- "container ship, containership, container vessel": 510,
1346
- "convertible": 511,
1347
- "coral fungus": 991,
1348
- "coral reef": 973,
1349
- "corkscrew, bottle screw": 512,
1350
- "corn": 987,
1351
- "cornet, horn, trumpet, trump": 513,
1352
- "coucal": 91,
1353
- "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor": 286,
1354
- "cowboy boot": 514,
1355
- "cowboy hat, ten-gallon hat": 515,
1356
- "coyote, prairie wolf, brush wolf, Canis latrans": 272,
1357
- "cradle": 516,
1358
- "crane": 517,
1359
- "crash helmet": 518,
1360
- "crate": 519,
1361
- "crayfish, crawfish, crawdad, crawdaddy": 124,
1362
- "crib, cot": 520,
1363
- "cricket": 312,
1364
- "croquet ball": 522,
1365
- "crossword puzzle, crossword": 918,
1366
- "crutch": 523,
1367
- "cucumber, cuke": 943,
1368
- "cuirass": 524,
1369
- "cup": 968,
1370
- "curly-coated retriever": 206,
1371
- "custard apple": 956,
1372
- "daisy": 985,
1373
- "dalmatian, coach dog, carriage dog": 251,
1374
- "dam, dike, dyke": 525,
1375
- "damselfly": 320,
1376
- "desk": 526,
1377
- "desktop computer": 527,
1378
- "dhole, Cuon alpinus": 274,
1379
- "dial telephone, dial phone": 528,
1380
- "diamondback, diamondback rattlesnake, Crotalus adamanteus": 67,
1381
- "diaper, nappy, napkin": 529,
1382
- "digital clock": 530,
1383
- "digital watch": 531,
1384
- "dingo, warrigal, warragal, Canis dingo": 273,
1385
- "dining table, board": 532,
1386
- "dishrag, dishcloth": 533,
1387
- "dishwasher, dish washer, dishwashing machine": 534,
1388
- "disk brake, disc brake": 535,
1389
- "dock, dockage, docking facility": 536,
1390
- "dogsled, dog sled, dog sleigh": 537,
1391
- "dome": 538,
1392
- "doormat, welcome mat": 539,
1393
- "dough": 961,
1394
- "dowitcher": 142,
1395
- "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk": 319,
1396
- "drake": 97,
1397
- "drilling platform, offshore rig": 540,
1398
- "drum, membranophone, tympan": 541,
1399
- "drumstick": 542,
1400
- "dugong, Dugong dugon": 149,
1401
- "dumbbell": 543,
1402
- "dung beetle": 305,
1403
- "ear, spike, capitulum": 998,
1404
- "earthstar": 995,
1405
- "echidna, spiny anteater, anteater": 102,
1406
- "eel": 390,
1407
- "eft": 27,
1408
- "eggnog": 969,
1409
- "electric fan, blower": 545,
1410
- "electric guitar": 546,
1411
- "electric locomotive": 547,
1412
- "electric ray, crampfish, numbfish, torpedo": 5,
1413
- "entertainment center": 548,
1414
- "envelope": 549,
1415
- "espresso": 967,
1416
- "espresso maker": 550,
1417
- "face powder": 551,
1418
- "feather boa, boa": 552,
1419
- "fiddler crab": 120,
1420
- "fig": 952,
1421
- "file, file cabinet, filing cabinet": 553,
1422
- "fire engine, fire truck": 555,
1423
- "fire screen, fireguard": 556,
1424
- "fireboat": 554,
1425
- "flagpole, flagstaff": 557,
1426
- "flamingo": 130,
1427
- "flat-coated retriever": 205,
1428
- "flatworm, platyhelminth": 110,
1429
- "flute, transverse flute": 558,
1430
- "fly": 308,
1431
- "folding chair": 559,
1432
- "football helmet": 560,
1433
- "forklift": 561,
1434
- "fountain": 562,
1435
- "fountain pen": 563,
1436
- "four-poster": 564,
1437
- "fox squirrel, eastern fox squirrel, Sciurus niger": 335,
1438
- "freight car": 565,
1439
- "frilled lizard, Chlamydosaurus kingi": 43,
1440
- "frying pan, frypan, skillet": 567,
1441
- "fur coat": 568,
1442
- "gar, garfish, garpike, billfish, Lepisosteus osseus": 395,
1443
- "garbage truck, dustcart": 569,
1444
- "garden spider, Aranea diademata": 74,
1445
- "garter snake, grass snake": 57,
1446
- "gas pump, gasoline pump, petrol pump, island dispenser": 571,
1447
- "gasmask, respirator, gas helmet": 570,
1448
- "gazelle": 353,
1449
- "geyser": 974,
1450
- "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca": 388,
1451
- "giant schnauzer": 197,
1452
- "gibbon, Hylobates lar": 368,
1453
- "go-kart": 573,
1454
- "goblet": 572,
1455
- "golden retriever": 207,
1456
- "goldfinch, Carduelis carduelis": 11,
1457
- "goldfish, Carassius auratus": 1,
1458
- "golf ball": 574,
1459
- "golfcart, golf cart": 575,
1460
- "gondola": 576,
1461
- "gong, tam-tam": 577,
1462
- "goose": 99,
1463
- "gorilla, Gorilla gorilla": 366,
1464
- "gown": 578,
1465
- "grand piano, grand": 579,
1466
- "grasshopper, hopper": 311,
1467
- "great grey owl, great gray owl, Strix nebulosa": 24,
1468
- "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias": 2,
1469
- "green lizard, Lacerta viridis": 46,
1470
- "green mamba": 64,
1471
- "green snake, grass snake": 55,
1472
- "greenhouse, nursery, glasshouse": 580,
1473
- "grey fox, gray fox, Urocyon cinereoargenteus": 280,
1474
- "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus": 147,
1475
- "grille, radiator grille": 581,
1476
- "grocery store, grocery, food market, market": 582,
1477
- "groenendael": 224,
1478
- "groom, bridegroom": 982,
1479
- "ground beetle, carabid beetle": 302,
1480
- "guacamole": 924,
1481
- "guenon, guenon monkey": 370,
1482
- "guillotine": 583,
1483
- "guinea pig, Cavia cobaya": 338,
1484
- "gyromitra": 993,
1485
- "hair slide": 584,
1486
- "hair spray": 585,
1487
- "half track": 586,
1488
- "hammer": 587,
1489
- "hammerhead, hammerhead shark": 4,
1490
- "hamper": 588,
1491
- "hamster": 333,
1492
- "hand blower, blow dryer, blow drier, hair dryer, hair drier": 589,
1493
- "hand-held computer, hand-held microcomputer": 590,
1494
- "handkerchief, hankie, hanky, hankey": 591,
1495
- "hard disc, hard disk, fixed disk": 592,
1496
- "hare": 331,
1497
- "harmonica, mouth organ, harp, mouth harp": 593,
1498
- "harp": 594,
1499
- "hartebeest": 351,
1500
- "harvester, reaper": 595,
1501
- "harvestman, daddy longlegs, Phalangium opilio": 70,
1502
- "hatchet": 596,
1503
- "hay": 958,
1504
- "head cabbage": 936,
1505
- "hen": 8,
1506
- "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa": 996,
1507
- "hermit crab": 125,
1508
- "hip, rose hip, rosehip": 989,
1509
- "hippopotamus, hippo, river horse, Hippopotamus amphibius": 344,
1510
- "hog, pig, grunter, squealer, Sus scrofa": 341,
1511
- "hognose snake, puff adder, sand viper": 54,
1512
- "holster": 597,
1513
- "home theater, home theatre": 598,
1514
- "honeycomb": 599,
1515
- "hook, claw": 600,
1516
- "hoopskirt, crinoline": 601,
1517
- "horizontal bar, high bar": 602,
1518
- "hornbill": 93,
1519
- "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus": 66,
1520
- "horse cart, horse-cart": 603,
1521
- "hot pot, hotpot": 926,
1522
- "hotdog, hot dog, red hot": 934,
1523
- "hourglass": 604,
1524
- "house finch, linnet, Carpodacus mexicanus": 12,
1525
- "howler monkey, howler": 379,
1526
- "hummingbird": 94,
1527
- "hyena, hyaena": 276,
1528
- "iPod": 605,
1529
- "ibex, Capra ibex": 350,
1530
- "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus": 296,
1531
- "ice cream, icecream": 928,
1532
- "ice lolly, lolly, lollipop, popsicle": 929,
1533
- "impala, Aepyceros melampus": 352,
1534
- "indigo bunting, indigo finch, indigo bird, Passerina cyanea": 14,
1535
- "indri, indris, Indri indri, Indri brevicaudatus": 384,
1536
- "iron, smoothing iron": 606,
1537
- "isopod": 126,
1538
- "jacamar": 95,
1539
- "jack-o'-lantern": 607,
1540
- "jackfruit, jak, jack": 955,
1541
- "jaguar, panther, Panthera onca, Felis onca": 290,
1542
- "jay": 17,
1543
- "jean, blue jean, denim": 608,
1544
- "jeep, landrover": 609,
1545
- "jellyfish": 107,
1546
- "jersey, T-shirt, tee shirt": 610,
1547
- "jigsaw puzzle": 611,
1548
- "jinrikisha, ricksha, rickshaw": 612,
1549
- "joystick": 613,
1550
- "junco, snowbird": 13,
1551
- "keeshond": 261,
1552
- "kelpie": 227,
1553
- "killer whale, killer, orca, grampus, sea wolf, Orcinus orca": 148,
1554
- "kimono": 614,
1555
- "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica": 121,
1556
- "king penguin, Aptenodytes patagonica": 145,
1557
- "king snake, kingsnake": 56,
1558
- "kit fox, Vulpes macrotis": 278,
1559
- "kite": 21,
1560
- "knee pad": 615,
1561
- "knot": 616,
1562
- "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus": 105,
1563
- "komondor": 228,
1564
- "kuvasz": 222,
1565
- "lab coat, laboratory coat": 617,
1566
- "lacewing, lacewing fly": 318,
1567
- "ladle": 618,
1568
- "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle": 301,
1569
- "lakeside, lakeshore": 975,
1570
- "lampshade, lamp shade": 619,
1571
- "langur": 374,
1572
- "laptop, laptop computer": 620,
1573
- "lawn mower, mower": 621,
1574
- "leaf beetle, chrysomelid": 304,
1575
- "leafhopper": 317,
1576
- "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea": 34,
1577
- "lemon": 951,
1578
- "lens cap, lens cover": 622,
1579
- "leopard, Panthera pardus": 288,
1580
- "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens": 387,
1581
- "letter opener, paper knife, paperknife": 623,
1582
- "library": 624,
1583
- "lifeboat": 625,
1584
- "lighter, light, igniter, ignitor": 626,
1585
- "limousine, limo": 627,
1586
- "limpkin, Aramus pictus": 135,
1587
- "liner, ocean liner": 628,
1588
- "lion, king of beasts, Panthera leo": 291,
1589
- "lionfish": 396,
1590
- "lipstick, lip rouge": 629,
1591
- "little blue heron, Egretta caerulea": 131,
1592
- "llama": 355,
1593
- "loggerhead, loggerhead turtle, Caretta caretta": 33,
1594
- "long-horned beetle, longicorn, longicorn beetle": 303,
1595
- "lorikeet": 90,
1596
- "lotion": 631,
1597
- "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system": 632,
1598
- "loupe, jeweler's loupe": 633,
1599
- "lumbermill, sawmill": 634,
1600
- "lycaenid, lycaenid butterfly": 326,
1601
- "lynx, catamount": 287,
1602
- "macaque": 373,
1603
- "macaw": 88,
1604
- "magnetic compass": 635,
1605
- "magpie": 18,
1606
- "mailbag, postbag": 636,
1607
- "mailbox, letter box": 637,
1608
- "maillot": 638,
1609
- "maillot, tank suit": 639,
1610
- "malamute, malemute, Alaskan malamute": 249,
1611
- "malinois": 225,
1612
- "manhole cover": 640,
1613
- "mantis, mantid": 315,
1614
- "maraca": 641,
1615
- "marimba, xylophone": 642,
1616
- "marmoset": 377,
1617
- "marmot": 336,
1618
- "mashed potato": 935,
1619
- "mask": 643,
1620
- "matchstick": 644,
1621
- "maypole": 645,
1622
- "maze, labyrinth": 646,
1623
- "measuring cup": 647,
1624
- "meat loaf, meatloaf": 962,
1625
- "medicine chest, medicine cabinet": 648,
1626
- "meerkat, mierkat": 299,
1627
- "megalith, megalithic structure": 649,
1628
- "menu": 922,
1629
- "microphone, mike": 650,
1630
- "microwave, microwave oven": 651,
1631
- "military uniform": 652,
1632
- "milk can": 653,
1633
- "miniature pinscher": 237,
1634
- "miniature poodle": 266,
1635
- "miniature schnauzer": 196,
1636
- "minibus": 654,
1637
- "miniskirt, mini": 655,
1638
- "minivan": 656,
1639
- "mink": 357,
1640
- "missile": 657,
1641
- "mitten": 658,
1642
- "mixing bowl": 659,
1643
- "mobile home, manufactured home": 660,
1644
- "modem": 662,
1645
- "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus": 323,
1646
- "monastery": 663,
1647
- "mongoose": 298,
1648
- "monitor": 664,
1649
- "moped": 665,
1650
- "mortar": 666,
1651
- "mortarboard": 667,
1652
- "mosque": 668,
1653
- "mosquito net": 669,
1654
- "motor scooter, scooter": 670,
1655
- "mountain bike, all-terrain bike, off-roader": 671,
1656
- "mountain tent": 672,
1657
- "mouse, computer mouse": 673,
1658
- "mousetrap": 674,
1659
- "moving van": 675,
1660
- "mud turtle": 35,
1661
- "mushroom": 947,
1662
- "muzzle": 676,
1663
- "nail": 677,
1664
- "neck brace": 678,
1665
- "necklace": 679,
1666
- "nematode, nematode worm, roundworm": 111,
1667
- "night snake, Hypsiglena torquata": 60,
1668
- "nipple": 680,
1669
- "notebook, notebook computer": 681,
1670
- "obelisk": 682,
1671
- "oboe, hautboy, hautbois": 683,
1672
- "ocarina, sweet potato": 684,
1673
- "odometer, hodometer, mileometer, milometer": 685,
1674
- "oil filter": 686,
1675
- "orange": 950,
1676
- "orangutan, orang, orangutang, Pongo pygmaeus": 365,
1677
- "organ, pipe organ": 687,
1678
- "oscilloscope, scope, cathode-ray oscilloscope, CRO": 688,
1679
- "ostrich, Struthio camelus": 9,
1680
- "otter": 360,
1681
- "otterhound, otter hound": 175,
1682
- "overskirt": 689,
1683
- "ox": 345,
1684
- "oxcart": 690,
1685
- "oxygen mask": 691,
1686
- "oystercatcher, oyster catcher": 143,
1687
- "packet": 692,
1688
- "paddle, boat paddle": 693,
1689
- "paddlewheel, paddle wheel": 694,
1690
- "padlock": 695,
1691
- "paintbrush": 696,
1692
- "pajama, pyjama, pj's, jammies": 697,
1693
- "palace": 698,
1694
- "panpipe, pandean pipe, syrinx": 699,
1695
- "paper towel": 700,
1696
- "papillon": 157,
1697
- "parachute, chute": 701,
1698
- "parallel bars, bars": 702,
1699
- "park bench": 703,
1700
- "parking meter": 704,
1701
- "partridge": 86,
1702
- "passenger car, coach, carriage": 705,
1703
- "patas, hussar monkey, Erythrocebus patas": 371,
1704
- "patio, terrace": 706,
1705
- "pay-phone, pay-station": 707,
1706
- "peacock": 84,
1707
- "pedestal, plinth, footstall": 708,
1708
- "pelican": 144,
1709
- "pencil box, pencil case": 709,
1710
- "pencil sharpener": 710,
1711
- "perfume, essence": 711,
1712
- "photocopier": 713,
1713
- "pick, plectrum, plectron": 714,
1714
- "pickelhaube": 715,
1715
- "picket fence, paling": 716,
1716
- "pickup, pickup truck": 717,
1717
- "pier": 718,
1718
- "piggy bank, penny bank": 719,
1719
- "pill bottle": 720,
1720
- "pillow": 721,
1721
- "pineapple, ananas": 953,
1722
- "ping-pong ball": 722,
1723
- "pinwheel": 723,
1724
- "pirate, pirate ship": 724,
1725
- "pitcher, ewer": 725,
1726
- "pizza, pizza pie": 963,
1727
- "plane, carpenter's plane, woodworking plane": 726,
1728
- "planetarium": 727,
1729
- "plastic bag": 728,
1730
- "plate": 923,
1731
- "plate rack": 729,
1732
- "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus": 103,
1733
- "plow, plough": 730,
1734
- "plunger, plumber's helper": 731,
1735
- "pole": 733,
1736
- "polecat, fitch, foulmart, foumart, Mustela putorius": 358,
1737
- "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria": 734,
1738
- "pomegranate": 957,
1739
- "poncho": 735,
1740
- "pool table, billiard table, snooker table": 736,
1741
- "pop bottle, soda bottle": 737,
1742
- "porcupine, hedgehog": 334,
1743
- "pot, flowerpot": 738,
1744
- "potpie": 964,
1745
- "potter's wheel": 739,
1746
- "power drill": 740,
1747
- "prairie chicken, prairie grouse, prairie fowl": 83,
1748
- "prayer rug, prayer mat": 741,
1749
- "pretzel": 932,
1750
- "printer": 742,
1751
- "prison, prison house": 743,
1752
- "proboscis monkey, Nasalis larvatus": 376,
1753
- "projectile, missile": 744,
1754
- "projector": 745,
1755
- "promontory, headland, head, foreland": 976,
1756
- "ptarmigan": 81,
1757
- "puck, hockey puck": 746,
1758
- "puffer, pufferfish, blowfish, globefish": 397,
1759
- "pug, pug-dog": 254,
1760
- "punching bag, punch bag, punching ball, punchball": 747,
1761
- "purse": 748,
1762
- "quail": 85,
1763
- "quill, quill pen": 749,
1764
- "quilt, comforter, comfort, puff": 750,
1765
- "racer, race car, racing car": 751,
1766
- "racket, racquet": 752,
1767
- "radiator": 753,
1768
- "radio telescope, radio reflector": 755,
1769
- "radio, wireless": 754,
1770
- "rain barrel": 756,
1771
- "ram, tup": 348,
1772
- "rapeseed": 984,
1773
- "recreational vehicle, RV, R.V.": 757,
1774
- "red fox, Vulpes vulpes": 277,
1775
- "red wine": 966,
1776
- "red wolf, maned wolf, Canis rufus, Canis niger": 271,
1777
- "red-backed sandpiper, dunlin, Erolia alpina": 140,
1778
- "red-breasted merganser, Mergus serrator": 98,
1779
- "redbone": 168,
1780
- "redshank, Tringa totanus": 141,
1781
- "reel": 758,
1782
- "reflex camera": 759,
1783
- "refrigerator, icebox": 760,
1784
- "remote control, remote": 761,
1785
- "restaurant, eating house, eating place, eatery": 762,
1786
- "revolver, six-gun, six-shooter": 763,
1787
- "rhinoceros beetle": 306,
1788
- "rifle": 764,
1789
- "ringlet, ringlet butterfly": 322,
1790
- "ringneck snake, ring-necked snake, ring snake": 53,
1791
- "robin, American robin, Turdus migratorius": 15,
1792
- "rock beauty, Holocanthus tricolor": 392,
1793
- "rock crab, Cancer irroratus": 119,
1794
- "rock python, rock snake, Python sebae": 62,
1795
- "rocking chair, rocker": 765,
1796
- "rotisserie": 766,
1797
- "rubber eraser, rubber, pencil eraser": 767,
1798
- "ruddy turnstone, Arenaria interpres": 139,
1799
- "ruffed grouse, partridge, Bonasa umbellus": 82,
1800
- "rugby ball": 768,
1801
- "rule, ruler": 769,
1802
- "running shoe": 770,
1803
- "safe": 771,
1804
- "safety pin": 772,
1805
- "saltshaker, salt shaker": 773,
1806
- "sandal": 774,
1807
- "sandbar, sand bar": 977,
1808
- "sarong": 775,
1809
- "sax, saxophone": 776,
1810
- "scabbard": 777,
1811
- "scale, weighing machine": 778,
1812
- "schipperke": 223,
1813
- "school bus": 779,
1814
- "schooner": 780,
1815
- "scoreboard": 781,
1816
- "scorpion": 71,
1817
- "screen, CRT screen": 782,
1818
- "screw": 783,
1819
- "screwdriver": 784,
1820
- "scuba diver": 983,
1821
- "sea anemone, anemone": 108,
1822
- "sea cucumber, holothurian": 329,
1823
- "sea lion": 150,
1824
- "sea slug, nudibranch": 115,
1825
- "sea snake": 65,
1826
- "sea urchin": 328,
1827
- "seashore, coast, seacoast, sea-coast": 978,
1828
- "seat belt, seatbelt": 785,
1829
- "sewing machine": 786,
1830
- "shield, buckler": 787,
1831
- "shoe shop, shoe-shop, shoe store": 788,
1832
- "shoji": 789,
1833
- "shopping basket": 790,
1834
- "shopping cart": 791,
1835
- "shovel": 792,
1836
- "shower cap": 793,
1837
- "shower curtain": 794,
1838
- "siamang, Hylobates syndactylus, Symphalangus syndactylus": 369,
1839
- "sidewinder, horned rattlesnake, Crotalus cerastes": 68,
1840
- "silky terrier, Sydney silky": 201,
1841
- "ski": 795,
1842
- "ski mask": 796,
1843
- "skunk, polecat, wood pussy": 361,
1844
- "sleeping bag": 797,
1845
- "slide rule, slipstick": 798,
1846
- "sliding door": 799,
1847
- "slot, one-armed bandit": 800,
1848
- "sloth bear, Melursus ursinus, Ursus ursinus": 297,
1849
- "slug": 114,
1850
- "snail": 113,
1851
- "snorkel": 801,
1852
- "snow leopard, ounce, Panthera uncia": 289,
1853
- "snowmobile": 802,
1854
- "snowplow, snowplough": 803,
1855
- "soap dispenser": 804,
1856
- "soccer ball": 805,
1857
- "sock": 806,
1858
- "soft-coated wheaten terrier": 202,
1859
- "solar dish, solar collector, solar furnace": 807,
1860
- "sombrero": 808,
1861
- "sorrel": 339,
1862
- "soup bowl": 809,
1863
- "space bar": 810,
1864
- "space heater": 811,
1865
- "space shuttle": 812,
1866
- "spaghetti squash": 940,
1867
- "spatula": 813,
1868
- "speedboat": 814,
1869
- "spider monkey, Ateles geoffroyi": 381,
1870
- "spider web, spider's web": 815,
1871
- "spindle": 816,
1872
- "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish": 123,
1873
- "spoonbill": 129,
1874
- "sports car, sport car": 817,
1875
- "spotlight, spot": 818,
1876
- "spotted salamander, Ambystoma maculatum": 28,
1877
- "squirrel monkey, Saimiri sciureus": 382,
1878
- "stage": 819,
1879
- "standard poodle": 267,
1880
- "standard schnauzer": 198,
1881
- "starfish, sea star": 327,
1882
- "steam locomotive": 820,
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- "steel arch bridge": 821,
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- "steel drum": 822,
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- "stethoscope": 823,
1886
- "stingray": 6,
1887
- "stinkhorn, carrion fungus": 994,
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- "stole": 824,
1889
- "stone wall": 825,
1890
- "stopwatch, stop watch": 826,
1891
- "stove": 827,
1892
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1893
- "strawberry": 949,
1894
- "street sign": 919,
1895
- "streetcar, tram, tramcar, trolley, trolley car": 829,
1896
- "stretcher": 830,
1897
- "studio couch, day bed": 831,
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- "stupa, tope": 832,
1899
- "sturgeon": 394,
1900
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- "suit, suit of clothes": 834,
1902
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1903
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- "sunglasses, dark glasses, shades": 837,
1907
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1908
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1909
- "swab, swob, mop": 840,
1910
- "sweatshirt": 841,
1911
- "swimming trunks, bathing trunks": 842,
1912
- "swing": 843,
1913
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1914
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1915
- "tabby, tabby cat": 281,
1916
- "table lamp": 846,
1917
- "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui": 32,
1918
- "tank, army tank, armored combat vehicle, armoured combat vehicle": 847,
1919
- "tape player": 848,
1920
- "tarantula": 76,
1921
- "teapot": 849,
1922
- "teddy, teddy bear": 850,
1923
- "television, television system": 851,
1924
- "tench, Tinca tinca": 0,
1925
- "tennis ball": 852,
1926
- "terrapin": 36,
1927
- "thatch, thatched roof": 853,
1928
- "theater curtain, theatre curtain": 854,
1929
- "thimble": 855,
1930
- "three-toed sloth, ai, Bradypus tridactylus": 364,
1931
- "thresher, thrasher, threshing machine": 856,
1932
- "throne": 857,
1933
- "thunder snake, worm snake, Carphophis amoenus": 52,
1934
- "tick": 78,
1935
- "tiger beetle": 300,
1936
- "tiger cat": 282,
1937
- "tiger shark, Galeocerdo cuvieri": 3,
1938
- "tiger, Panthera tigris": 292,
1939
- "tile roof": 858,
1940
- "timber wolf, grey wolf, gray wolf, Canis lupus": 269,
1941
- "titi, titi monkey": 380,
1942
- "toaster": 859,
1943
- "tobacco shop, tobacconist shop, tobacconist": 860,
1944
- "toilet seat": 861,
1945
- "toilet tissue, toilet paper, bathroom tissue": 999,
1946
- "torch": 862,
1947
- "totem pole": 863,
1948
- "toucan": 96,
1949
- "tow truck, tow car, wrecker": 864,
1950
- "toy poodle": 265,
1951
- "toy terrier": 158,
1952
- "toyshop": 865,
1953
- "tractor": 866,
1954
- "traffic light, traffic signal, stoplight": 920,
1955
- "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi": 867,
1956
- "tray": 868,
1957
- "tree frog, tree-frog": 31,
1958
- "trench coat": 869,
1959
- "triceratops": 51,
1960
- "tricycle, trike, velocipede": 870,
1961
- "trifle": 927,
1962
- "trilobite": 69,
1963
- "trimaran": 871,
1964
- "tripod": 872,
1965
- "triumphal arch": 873,
1966
- "trolleybus, trolley coach, trackless trolley": 874,
1967
- "trombone": 875,
1968
- "tub, vat": 876,
1969
- "turnstile": 877,
1970
- "tusker": 101,
1971
- "typewriter keyboard": 878,
1972
- "umbrella": 879,
1973
- "unicycle, monocycle": 880,
1974
- "upright, upright piano": 881,
1975
- "vacuum, vacuum cleaner": 882,
1976
- "valley, vale": 979,
1977
- "vase": 883,
1978
- "vault": 884,
1979
- "velvet": 885,
1980
- "vending machine": 886,
1981
- "vestment": 887,
1982
- "viaduct": 888,
1983
- "vine snake": 59,
1984
- "violin, fiddle": 889,
1985
- "vizsla, Hungarian pointer": 211,
1986
- "volcano": 980,
1987
- "volleyball": 890,
1988
- "vulture": 23,
1989
- "waffle iron": 891,
1990
- "walking stick, walkingstick, stick insect": 313,
1991
- "wall clock": 892,
1992
- "wallaby, brush kangaroo": 104,
1993
- "wallet, billfold, notecase, pocketbook": 893,
1994
- "wardrobe, closet, press": 894,
1995
- "warplane, military plane": 895,
1996
- "warthog": 343,
1997
- "washbasin, handbasin, washbowl, lavabo, wash-hand basin": 896,
1998
- "washer, automatic washer, washing machine": 897,
1999
- "water bottle": 898,
2000
- "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis": 346,
2001
- "water jug": 899,
2002
- "water ouzel, dipper": 20,
2003
- "water snake": 58,
2004
- "water tower": 900,
2005
- "weasel": 356,
2006
- "web site, website, internet site, site": 916,
2007
- "weevil": 307,
2008
- "whippet": 172,
2009
- "whiptail, whiptail lizard": 41,
2010
- "whiskey jug": 901,
2011
- "whistle": 902,
2012
- "white stork, Ciconia ciconia": 127,
2013
- "white wolf, Arctic wolf, Canis lupus tundrarum": 270,
2014
- "wig": 903,
2015
- "wild boar, boar, Sus scrofa": 342,
2016
- "window screen": 904,
2017
- "window shade": 905,
2018
- "wine bottle": 907,
2019
- "wing": 908,
2020
- "wire-haired fox terrier": 188,
2021
- "wok": 909,
2022
- "wolf spider, hunting spider": 77,
2023
- "wombat": 106,
2024
- "wood rabbit, cottontail, cottontail rabbit": 330,
2025
- "wooden spoon": 910,
2026
- "wool, woolen, woollen": 911,
2027
- "worm fence, snake fence, snake-rail fence, Virginia fence": 912,
2028
- "wreck": 913,
2029
- "yawl": 914,
2030
- "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum": 986,
2031
- "yurt": 915,
2032
- "zebra": 340,
2033
- "zucchini, courgette": 939
2034
  },
2035
  "layer_norm_eps": 1e-06,
2036
  "mlp_ratios": [
 
28
  256
29
  ],
30
  "id2label": {
31
+ "0": "unlabeled",
32
+ "1": "flat-road",
33
+ "2": "flat-sidewalk",
34
+ "3": "flat-crosswalk",
35
+ "4": "flat-cyclinglane",
36
+ "5": "flat-parkingdriveway",
37
+ "6": "flat-railtrack",
38
+ "7": "flat-curb",
39
+ "8": "human-person",
40
+ "9": "human-rider",
41
+ "10": "vehicle-car",
42
+ "11": "vehicle-truck",
43
+ "12": "vehicle-bus",
44
+ "13": "vehicle-tramtrain",
45
+ "14": "vehicle-motorcycle",
46
+ "15": "vehicle-bicycle",
47
+ "16": "vehicle-caravan",
48
+ "17": "vehicle-cartrailer",
49
+ "18": "construction-building",
50
+ "19": "construction-door",
51
+ "20": "construction-wall",
52
+ "21": "construction-fenceguardrail",
53
+ "22": "construction-bridge",
54
+ "23": "construction-tunnel",
55
+ "24": "construction-stairs",
56
+ "25": "object-pole",
57
+ "26": "object-trafficsign",
58
+ "27": "object-trafficlight",
59
+ "28": "nature-vegetation",
60
+ "29": "nature-terrain",
61
+ "30": "sky",
62
+ "31": "void-ground",
63
+ "32": "void-dynamic",
64
+ "33": "void-static",
65
+ "34": "void-unclear"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
  },
67
  "image_size": 224,
68
  "initializer_range": 0.02,
69
  "label2id": {
70
+ "construction-bridge": "22",
71
+ "construction-building": "18",
72
+ "construction-door": "19",
73
+ "construction-fenceguardrail": "21",
74
+ "construction-stairs": "24",
75
+ "construction-tunnel": "23",
76
+ "construction-wall": "20",
77
+ "flat-crosswalk": "3",
78
+ "flat-curb": "7",
79
+ "flat-cyclinglane": "4",
80
+ "flat-parkingdriveway": "5",
81
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82
+ "flat-road": "1",
83
+ "flat-sidewalk": "2",
84
+ "human-person": "8",
85
+ "human-rider": "9",
86
+ "nature-terrain": "29",
87
+ "nature-vegetation": "28",
88
+ "object-pole": "25",
89
+ "object-trafficlight": "27",
90
+ "object-trafficsign": "26",
91
+ "sky": "30",
92
+ "unlabeled": "0",
93
+ "vehicle-bicycle": "15",
94
+ "vehicle-bus": "12",
95
+ "vehicle-car": "10",
96
+ "vehicle-caravan": "16",
97
+ "vehicle-cartrailer": "17",
98
+ "vehicle-motorcycle": "14",
99
+ "vehicle-tramtrain": "13",
100
+ "vehicle-truck": "11",
101
+ "void-dynamic": "32",
102
+ "void-ground": "31",
103
+ "void-static": "33",
104
+ "void-unclear": "34"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
105
  },
106
  "layer_norm_eps": 1e-06,
107
  "mlp_ratios": [
finetuning.ipynb CHANGED
@@ -940,40 +940,31 @@
940
  },
941
  {
942
  "cell_type": "code",
943
- "execution_count": 31,
944
  "metadata": {},
945
  "outputs": [
946
  {
947
  "name": "stderr",
948
  "output_type": "stream",
949
  "text": [
950
- "Cloning https://huggingface.co/ChainYo/segformer-sidewalk into local empty directory.\n",
951
  "remote: Enforcing permissions... \n",
952
  "remote: Allowed refs: all \n",
953
  "To https://huggingface.co/ChainYo/segformer-sidewalk\n",
954
- " c75c928..5d5f276 main -> main\n",
955
  "\n"
956
  ]
957
  },
958
  {
959
- "ename": "OSError",
960
- "evalue": "It looks like the config file at '/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt' is not a valid JSON file.",
961
  "output_type": "error",
962
  "traceback": [
963
  "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
964
- "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
965
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py:650\u001b[0m, in \u001b[0;36mPretrainedConfig._get_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=647'>648</a>\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=648'>649</a>\u001b[0m \u001b[39m# Load config dict\u001b[39;00m\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=649'>650</a>\u001b[0m config_dict \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49m_dict_from_json_file(resolved_config_file)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=650'>651</a>\u001b[0m \u001b[39mexcept\u001b[39;00m (json\u001b[39m.\u001b[39mJSONDecodeError, \u001b[39mUnicodeDecodeError\u001b[39;00m):\n",
966
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py:733\u001b[0m, in \u001b[0;36mPretrainedConfig._dict_from_json_file\u001b[0;34m(cls, json_file)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=731'>732</a>\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mopen\u001b[39m(json_file, \u001b[39m\"\u001b[39m\u001b[39mr\u001b[39m\u001b[39m\"\u001b[39m, encoding\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mutf-8\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mas\u001b[39;00m reader:\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=732'>733</a>\u001b[0m text \u001b[39m=\u001b[39m reader\u001b[39m.\u001b[39;49mread()\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=733'>734</a>\u001b[0m \u001b[39mreturn\u001b[39;00m json\u001b[39m.\u001b[39mloads(text)\n",
967
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/codecs.py:322\u001b[0m, in \u001b[0;36mBufferedIncrementalDecoder.decode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/codecs.py?line=320'>321</a>\u001b[0m data \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbuffer \u001b[39m+\u001b[39m \u001b[39minput\u001b[39m\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/codecs.py?line=321'>322</a>\u001b[0m (result, consumed) \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_buffer_decode(data, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49merrors, final)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/codecs.py?line=322'>323</a>\u001b[0m \u001b[39m# keep undecoded input until the next call\u001b[39;00m\n",
968
- "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x80 in position 64: invalid start byte",
969
- "\nDuring handling of the above exception, another exception occurred:\n",
970
- "\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
971
- "\u001b[1;32m/home/chainyo/code/segformer-sidewalk/finetuning.ipynb Cell 23'\u001b[0m in \u001b[0;36m<cell line: 11>\u001b[0;34m()\u001b[0m\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=7'>8</a>\u001b[0m config \u001b[39m=\u001b[39m AutoConfig\u001b[39m.\u001b[39mfrom_pretrained(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mnvidia/mit-b0\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=8'>9</a>\u001b[0m config\u001b[39m.\u001b[39mpush_to_hub(\u001b[39m\"\u001b[39m\u001b[39msegformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m, repo_url\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhttps://huggingface.co/ChainYo/segformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m---> <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=10'>11</a>\u001b[0m model \u001b[39m=\u001b[39m SegformerForSemanticSegmentation\u001b[39m.\u001b[39;49mfrom_pretrained(\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=11'>12</a>\u001b[0m \u001b[39m\"\u001b[39;49m\u001b[39m/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=12'>13</a>\u001b[0m num_labels\u001b[39m=\u001b[39;49mnum_labels, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=13'>14</a>\u001b[0m id2label\u001b[39m=\u001b[39;49mid2label, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=14'>15</a>\u001b[0m label2id\u001b[39m=\u001b[39;49mid2label,\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=15'>16</a>\u001b[0m )\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=16'>17</a>\u001b[0m model\u001b[39m.\u001b[39mpush_to_hub(\u001b[39m\"\u001b[39m\u001b[39msegformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m, repo_url\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhttps://huggingface.co/ChainYo/segformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m)\n",
972
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py:1764\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1761'>1762</a>\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39misinstance\u001b[39m(config, PretrainedConfig):\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1762'>1763</a>\u001b[0m config_path \u001b[39m=\u001b[39m config \u001b[39mif\u001b[39;00m config \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m pretrained_model_name_or_path\n\u001b[0;32m-> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1763'>1764</a>\u001b[0m config, model_kwargs \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49mconfig_class\u001b[39m.\u001b[39;49mfrom_pretrained(\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1764'>1765</a>\u001b[0m config_path,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1765'>1766</a>\u001b[0m cache_dir\u001b[39m=\u001b[39;49mcache_dir,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1766'>1767</a>\u001b[0m return_unused_kwargs\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1767'>1768</a>\u001b[0m force_download\u001b[39m=\u001b[39;49mforce_download,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1768'>1769</a>\u001b[0m resume_download\u001b[39m=\u001b[39;49mresume_download,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1769'>1770</a>\u001b[0m proxies\u001b[39m=\u001b[39;49mproxies,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1770'>1771</a>\u001b[0m local_files_only\u001b[39m=\u001b[39;49mlocal_files_only,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1771'>1772</a>\u001b[0m use_auth_token\u001b[39m=\u001b[39;49muse_auth_token,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1772'>1773</a>\u001b[0m revision\u001b[39m=\u001b[39;49mrevision,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1773'>1774</a>\u001b[0m _from_auto\u001b[39m=\u001b[39;49mfrom_auto_class,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1774'>1775</a>\u001b[0m _from_pipeline\u001b[39m=\u001b[39;49mfrom_pipeline,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1775'>1776</a>\u001b[0m \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs,\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1776'>1777</a>\u001b[0m )\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1777'>1778</a>\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=1778'>1779</a>\u001b[0m model_kwargs \u001b[39m=\u001b[39m kwargs\n",
973
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py:526\u001b[0m, in \u001b[0;36mPretrainedConfig.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=451'>452</a>\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=452'>453</a>\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mfrom_pretrained\u001b[39m(\u001b[39mcls\u001b[39m, pretrained_model_name_or_path: Union[\u001b[39mstr\u001b[39m, os\u001b[39m.\u001b[39mPathLike], \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mPretrainedConfig\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=453'>454</a>\u001b[0m \u001b[39mr\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=454'>455</a>\u001b[0m \u001b[39m Instantiate a [`PretrainedConfig`] (or a derived class) from a pretrained model configuration.\u001b[39;00m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=455'>456</a>\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=523'>524</a>\u001b[0m \u001b[39m assert unused_kwargs == {\"foo\": False}\u001b[39;00m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=524'>525</a>\u001b[0m \u001b[39m ```\"\"\"\u001b[39;00m\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=525'>526</a>\u001b[0m config_dict, kwargs \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49mget_config_dict(pretrained_model_name_or_path, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=526'>527</a>\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mmodel_type\u001b[39m\u001b[39m\"\u001b[39m \u001b[39min\u001b[39;00m config_dict \u001b[39mand\u001b[39;00m \u001b[39mhasattr\u001b[39m(\u001b[39mcls\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39mmodel_type\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mand\u001b[39;00m config_dict[\u001b[39m\"\u001b[39m\u001b[39mmodel_type\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m!=\u001b[39m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mmodel_type:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=527'>528</a>\u001b[0m logger\u001b[39m.\u001b[39mwarning(\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=528'>529</a>\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mYou are using a model of type \u001b[39m\u001b[39m{\u001b[39;00mconfig_dict[\u001b[39m'\u001b[39m\u001b[39mmodel_type\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m to instantiate a model of type \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=529'>530</a>\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mmodel_type\u001b[39m}\u001b[39;00m\u001b[39m. This is not supported for all configurations of models and can yield errors.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=530'>531</a>\u001b[0m )\n",
974
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py:553\u001b[0m, in \u001b[0;36mPretrainedConfig.get_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=550'>551</a>\u001b[0m original_kwargs \u001b[39m=\u001b[39m copy\u001b[39m.\u001b[39mdeepcopy(kwargs)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=551'>552</a>\u001b[0m \u001b[39m# Get config dict associated with the base config file\u001b[39;00m\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=552'>553</a>\u001b[0m config_dict, kwargs \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49m_get_config_dict(pretrained_model_name_or_path, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=554'>555</a>\u001b[0m \u001b[39m# That config file may point us toward another config file to use.\u001b[39;00m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=555'>556</a>\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mconfiguration_files\u001b[39m\u001b[39m\"\u001b[39m \u001b[39min\u001b[39;00m config_dict:\n",
975
- "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py:652\u001b[0m, in \u001b[0;36mPretrainedConfig._get_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=649'>650</a>\u001b[0m config_dict \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m_dict_from_json_file(resolved_config_file)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=650'>651</a>\u001b[0m \u001b[39mexcept\u001b[39;00m (json\u001b[39m.\u001b[39mJSONDecodeError, \u001b[39mUnicodeDecodeError\u001b[39;00m):\n\u001b[0;32m--> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=651'>652</a>\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mEnvironmentError\u001b[39;00m(\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=652'>653</a>\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mIt looks like the config file at \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mresolved_config_file\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m is not a valid JSON file.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=653'>654</a>\u001b[0m )\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=655'>656</a>\u001b[0m \u001b[39mif\u001b[39;00m resolved_config_file \u001b[39m==\u001b[39m config_file:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/configuration_utils.py?line=656'>657</a>\u001b[0m logger\u001b[39m.\u001b[39minfo(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mloading configuration file \u001b[39m\u001b[39m{\u001b[39;00mconfig_file\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n",
976
- "\u001b[0;31mOSError\u001b[0m: It looks like the config file at '/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt' is not a valid JSON file."
977
  ]
978
  }
979
  ],
@@ -986,13 +977,13 @@
986
  "num_labels = len(id2label)\n",
987
  "\n",
988
  "config = AutoConfig.from_pretrained(f\"nvidia/mit-b0\")\n",
 
 
 
989
  "config.push_to_hub(\".\", repo_url=\"https://huggingface.co/ChainYo/segformer-sidewalk\")\n",
990
  "\n",
991
  "model = SegformerForSemanticSegmentation.from_pretrained(\n",
992
  " \"/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt\", \n",
993
- " num_labels=num_labels, \n",
994
- " id2label=id2label, \n",
995
- " label2id=id2label,\n",
996
  " config=config,\n",
997
  ")\n",
998
  "model.push_to_hub(\".\", repo_url=\"https://huggingface.co/ChainYo/segformer-sidewalk\")"
 
940
  },
941
  {
942
  "cell_type": "code",
943
+ "execution_count": 32,
944
  "metadata": {},
945
  "outputs": [
946
  {
947
  "name": "stderr",
948
  "output_type": "stream",
949
  "text": [
950
+ "/home/chainyo/code/segformer-sidewalk/. is already a clone of https://huggingface.co/ChainYo/segformer-sidewalk. Make sure you pull the latest changes with `repo.git_pull()`.\n",
951
  "remote: Enforcing permissions... \n",
952
  "remote: Allowed refs: all \n",
953
  "To https://huggingface.co/ChainYo/segformer-sidewalk\n",
954
+ " 5d5f276..56db83f main -> main\n",
955
  "\n"
956
  ]
957
  },
958
  {
959
+ "ename": "TypeError",
960
+ "evalue": "__init__() got an unexpected keyword argument 'num_labels'",
961
  "output_type": "error",
962
  "traceback": [
963
  "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
964
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
965
+ "\u001b[1;32m/home/chainyo/code/segformer-sidewalk/finetuning.ipynb Cell 23'\u001b[0m in \u001b[0;36m<cell line: 11>\u001b[0;34m()\u001b[0m\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=7'>8</a>\u001b[0m config \u001b[39m=\u001b[39m AutoConfig\u001b[39m.\u001b[39mfrom_pretrained(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mnvidia/mit-b0\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=8'>9</a>\u001b[0m config\u001b[39m.\u001b[39mpush_to_hub(\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, repo_url\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhttps://huggingface.co/ChainYo/segformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m---> <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=10'>11</a>\u001b[0m model \u001b[39m=\u001b[39m SegformerForSemanticSegmentation\u001b[39m.\u001b[39;49mfrom_pretrained(\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=11'>12</a>\u001b[0m \u001b[39m\"\u001b[39;49m\u001b[39m/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=12'>13</a>\u001b[0m num_labels\u001b[39m=\u001b[39;49mnum_labels, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=13'>14</a>\u001b[0m id2label\u001b[39m=\u001b[39;49mid2label, \n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=14'>15</a>\u001b[0m label2id\u001b[39m=\u001b[39;49mid2label,\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=15'>16</a>\u001b[0m config\u001b[39m=\u001b[39;49mconfig,\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=16'>17</a>\u001b[0m )\n\u001b[1;32m <a href='vscode-notebook-cell:/home/chainyo/code/segformer-sidewalk/finetuning.ipynb#ch0000016?line=17'>18</a>\u001b[0m model\u001b[39m.\u001b[39mpush_to_hub(\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m, repo_url\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mhttps://huggingface.co/ChainYo/segformer-sidewalk\u001b[39m\u001b[39m\"\u001b[39m)\n",
966
+ "File \u001b[0;32m~/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py:2024\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2021'>2022</a>\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2022'>2023</a>\u001b[0m \u001b[39mwith\u001b[39;00m no_init_weights(_enable\u001b[39m=\u001b[39m_fast_init):\n\u001b[0;32m-> <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2023'>2024</a>\u001b[0m model \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39;49m(config, \u001b[39m*\u001b[39;49mmodel_args, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mmodel_kwargs)\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2025'>2026</a>\u001b[0m \u001b[39mif\u001b[39;00m from_tf:\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2026'>2027</a>\u001b[0m \u001b[39mif\u001b[39;00m resolved_archive_file\u001b[39m.\u001b[39mendswith(\u001b[39m\"\u001b[39m\u001b[39m.index\u001b[39m\u001b[39m\"\u001b[39m):\n\u001b[1;32m <a href='file:///home/chainyo/miniconda3/envs/segformer/lib/python3.8/site-packages/transformers/modeling_utils.py?line=2027'>2028</a>\u001b[0m \u001b[39m# Load from a TensorFlow 1.X checkpoint - provided by original authors\u001b[39;00m\n",
967
+ "\u001b[0;31mTypeError\u001b[0m: __init__() got an unexpected keyword argument 'num_labels'"
 
 
 
 
 
 
 
 
 
968
  ]
969
  }
970
  ],
 
977
  "num_labels = len(id2label)\n",
978
  "\n",
979
  "config = AutoConfig.from_pretrained(f\"nvidia/mit-b0\")\n",
980
+ "config.num_labels = num_labels\n",
981
+ "config.id2label = id2label\n",
982
+ "config.label2id = {v: k for k, v in id2label_file.items()}\n",
983
  "config.push_to_hub(\".\", repo_url=\"https://huggingface.co/ChainYo/segformer-sidewalk\")\n",
984
  "\n",
985
  "model = SegformerForSemanticSegmentation.from_pretrained(\n",
986
  " \"/home/chainyo/code/segformer-sidewalk/checkpoints/epoch=44-step=1125.ckpt\", \n",
 
 
 
987
  " config=config,\n",
988
  ")\n",
989
  "model.push_to_hub(\".\", repo_url=\"https://huggingface.co/ChainYo/segformer-sidewalk\")"