n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
n01491361 tiger shark, Galeocerdo cuvieri
n01494475 hammerhead, hammerhead shark
n01496331 electric ray, crampfish, numbfish, torpedo
n01498041 stingray
n01514668 cock
n01514859 hen
n01518878 ostrich, Struthio camelus
n01530575 brambling, Fringilla montifringilla
n01531178 goldfinch, Carduelis carduelis
n01532829 house finch, linnet, Carpodacus mexicanus
n01534433 junco, snowbird
n01537544 indigo bunting, indigo finch, indigo bird, Passerina cyanea
n01558993 robin, American robin, Turdus migratorius
n01560419 bulbul
n01580077 jay
n01582220 magpie
n01592084 chickadee
n01601694 water ouzel, dipper
n01608432 kite
n01614925 bald eagle, American eagle, Haliaeetus leucocephalus
n01616318 vulture
n01622779 great grey owl, great gray owl, Strix nebulosa
n01629819 European fire salamander, Salamandra salamandra
n01630670 common newt, Triturus vulgaris
n01631663 eft
n01632458 spotted salamander, Ambystoma maculatum
n01632777 axolotl, mud puppy, Ambystoma mexicanum
n01641577 bullfrog, Rana catesbeiana
n01644373 tree frog, tree-frog
n01644900 tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui
n01664065 loggerhead, loggerhead turtle, Caretta caretta
n01665541 leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea
n01667114 mud turtle
n01667778 terrapin
n01669191 box turtle, box tortoise
n01675722 banded gecko
n01677366 common iguana, iguana, Iguana iguana
n01682714 American chameleon, anole, Anolis carolinensis
n01685808 whiptail, whiptail lizard
n01687978 agama
n01688243 frilled lizard, Chlamydosaurus kingi
n01689811 alligator lizard
n01692333 Gila monster, Heloderma suspectum
n01693334 green lizard, Lacerta viridis
n01694178 African chameleon, Chamaeleo chamaeleon
n01695060 Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis
n01697457 African crocodile, Nile crocodile, Crocodylus niloticus
n01698640 American alligator, Alligator mississipiensis
n01704323 triceratops
n01728572 thunder snake, worm snake, Carphophis amoenus
n01728920 ringneck snake, ring-necked snake, ring snake
n01729322 hognose snake, puff adder, sand viper
n01729977 green snake, grass snake
n01734418 king snake, kingsnake
n01735189 garter snake, grass snake
n01737021 water snake
n01739381 vine snake
n01740131 night snake, Hypsiglena torquata
n01742172 boa constrictor, Constrictor constrictor
n01744401 rock python, rock snake, Python sebae
n01748264 Indian cobra, Naja naja
n01749939 green mamba
n01751748 sea snake
n01753488 horned viper, cerastes, sand viper, horned asp, Cerastes cornutus
n01755581 diamondback, diamondback rattlesnake, Crotalus adamanteus
n01756291 sidewinder, horned rattlesnake, Crotalus cerastes
n01768244 trilobite
n01770081 harvestman, daddy longlegs, Phalangium opilio
n01770393 scorpion
n01773157 black and gold garden spider, Argiope aurantia
n01773549 barn spider, Araneus cavaticus
n01773797 garden spider, Aranea diademata
n01774384 black widow, Latrodectus mactans
n01774750 tarantula
n01775062 wolf spider, hunting spider
n01776313 tick
n01784675 centipede
n01795545 black grouse
n01796340 ptarmigan
n01797886 ruffed grouse, partridge, Bonasa umbellus
n01798484 prairie chicken, prairie grouse, prairie fowl
n01806143 peacock
n01806567 quail
n01807496 partridge
n01817953 African grey, African gray, Psittacus erithacus
n01818515 macaw
n01819313 sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita
n01820546 lorikeet
n01824575 coucal
n01828970 bee eater
n01829413 hornbill
n01833805 hummingbird
n01843065 jacamar
n01843383 toucan
n01847000 drake
n01855032 red-breasted merganser, Mergus serrator
n01855672 goose
n01860187 black swan, Cygnus atratus
n01871265 tusker
n01872401 echidna, spiny anteater, anteater
n01873310 platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus
n01877812 wallaby, brush kangaroo
n01882714 koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus
n01883070 wombat
n01910747 jellyfish
n01914609 sea anemone, anemone
n01917289 brain coral
n01924916 flatworm, platyhelminth
n01930112 nematode, nematode worm, roundworm
n01943899 conch
n01944390 snail
n01945685 slug
n01950731 sea slug, nudibranch
n01955084 chiton, coat-of-mail shell, sea cradle, polyplacophore
n01968897 chambered nautilus, pearly nautilus, nautilus
n01978287 Dungeness crab, Cancer magister
n01978455 rock crab, Cancer irroratus
n01980166 fiddler crab
n01981276 king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica
n01983481 American lobster, Northern lobster, Maine lobster, Homarus americanus
n01984695 spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish
n01985128 crayfish, crawfish, crawdad, crawdaddy
n01986214 hermit crab
n01990800 isopod
n02002556 white stork, Ciconia ciconia
n02002724 black stork, Ciconia nigra
n02006656 spoonbill
n02007558 flamingo
n02009229 little blue heron, Egretta caerulea
n02009912 American egret, great white heron, Egretta albus
n02011460 bittern
n02012849 crane
n02013706 limpkin, Aramus pictus
n02017213 European gallinule, Porphyrio porphyrio
n02018207 American coot, marsh hen, mud hen, water hen, Fulica americana
n02018795 bustard
n02025239 ruddy turnstone, Arenaria interpres
n02027492 red-backed sandpiper, dunlin, Erolia alpina
n02028035 redshank, Tringa totanus
n02033041 dowitcher
n02037110 oystercatcher, oyster catcher
n02051845 pelican
n02056570 king penguin, Aptenodytes patagonica
n02058221 albatross, mollymawk
n02066245 grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus
n02071294 killer whale, killer, orca, grampus, sea wolf, Orcinus orca
n02074367 dugong, Dugong dugon
n02077923 sea lion
n02085620 Chihuahua
n02085782 Japanese spaniel
n02085936 Maltese dog, Maltese terrier, Maltese
n02086079 Pekinese, Pekingese, Peke
n02086240 Shih-Tzu
n02086646 Blenheim spaniel
n02086910 papillon
n02087046 toy terrier
n02087394 Rhodesian ridgeback
n02088094 Afghan hound, Afghan
n02088238 basset, basset hound
n02088364 beagle
n02088466 bloodhound, sleuthhound
n02088632 bluetick
n02089078 black-and-tan coonhound
n02089867 Walker hound, Walker foxhound
n02089973 English foxhound
n02090379 redbone
n02090622 borzoi, Russian wolfhound
n02090721 Irish wolfhound
n02091032 Italian greyhound
n02091134 whippet
n02091244 Ibizan hound, Ibizan Podenco
n02091467 Norwegian elkhound, elkhound
n02091635 otterhound, otter hound
n02091831 Saluki, gazelle hound
n02092002 Scottish deerhound, deerhound
n02092339 Weimaraner
n02093256 Staffordshire bullterrier, Staffordshire bull terrier
n02093428 American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier
n02093647 Bedlington terrier
n02093754 Border terrier
n02093859 Kerry blue terrier
n02093991 Irish terrier
n02094114 Norfolk terrier
n02094258 Norwich terrier
n02094433 Yorkshire terrier
n02095314 wire-haired fox terrier
n02095570 Lakeland terrier
n02095889 Sealyham terrier, Sealyham
n02096051 Airedale, Airedale terrier
n02096177 cairn, cairn terrier
n02096294 Australian terrier
n02096437 Dandie Dinmont, Dandie Dinmont terrier
n02096585 Boston bull, Boston terrier
n02097047 miniature schnauzer
n02097130 giant schnauzer
n02097209 standard schnauzer
n02097298 Scotch terrier, Scottish terrier, Scottie
n02097474 Tibetan terrier, chrysanthemum dog
n02097658 silky terrier, Sydney silky
n02098105 soft-coated wheaten terrier
n02098286 West Highland white terrier
n02098413 Lhasa, Lhasa apso
n02099267 flat-coated retriever
n02099429 curly-coated retriever
n02099601 golden retriever
n02099712 Labrador retriever
n02099849 Chesapeake Bay retriever
n02100236 German short-haired pointer
n02100583 vizsla, Hungarian pointer
n02100735 English setter
n02100877 Irish setter, red setter
n02101006 Gordon setter
n02101388 Brittany spaniel
n02101556 clumber, clumber spaniel
n02102040 English spr
没有合适的资源?快使用搜索试试~ 我知道了~
部分imagenet数据(10class*100picture)
共1003个文件
jpg:1000个
csv:2个
txt:1个
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源数据:ImageNet LSVRC-2010,1000类,120万张训练图片、5万测试、15万验证 mini-imagenet数据:来自:https://blog.csdn.net/weixin_41803874/article/details/92068250 该数据:从mini-imagenet随机选取10类,每类随机选取100张图片,共1000张图片作为数据集 AlexNet结构 及 pytorch、tensorflow、keras、paddle实现ImageNet识别: https://blog.csdn.net/nominior/article/details/104047718
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部分imagenet数据(10class*100picture) (1003个子文件)
my_imagenet.csv 42KB
my_imagenet_copy.csv 36KB
n0925647900000961.jpg 816KB
n0398087400000199.jpg 789KB
n0209124400000543.jpg 753KB
n0217400100001055.jpg 644KB
n0377350400001215.jpg 607KB
n0398087400000073.jpg 528KB
n0925647900000986.jpg 520KB
n0213844100001054.jpg 430KB
n0925647900000129.jpg 380KB
n0217400100000300.jpg 326KB
n0217400100000243.jpg 312KB
n0398087400000541.jpg 309KB
n0217400100000840.jpg 282KB
n0925647900000036.jpg 239KB
n0213844100000757.jpg 226KB
n0925647900001213.jpg 214KB
n0925647900000810.jpg 206KB
n0213844100000443.jpg 205KB
n0213844100000304.jpg 188KB
n0925647900000355.jpg 169KB
n0211454800000380.jpg 164KB
n0925647900000284.jpg 147KB
n0213844100000043.jpg 144KB
n0398087400000304.jpg 134KB
n0377350400000308.jpg 134KB
n0213844100000490.jpg 130KB
n0213844100000833.jpg 125KB
n0307537000000926.jpg 125KB
n0213844100000653.jpg 123KB
n0398087400000611.jpg 120KB
n0213844100000102.jpg 116KB
n0398087400000506.jpg 113KB
n0925647900000874.jpg 113KB
n0211454800000298.jpg 111KB
n0213844100001288.jpg 109KB
n0213844100000792.jpg 109KB
n0211454800000197.jpg 108KB
n0213844100000312.jpg 107KB
n0925647900000293.jpg 106KB
n0925647900000068.jpg 105KB
n0358425400000620.jpg 105KB
n0925647900000193.jpg 105KB
n0377350400000532.jpg 103KB
n0925647900001263.jpg 102KB
n0213844100000945.jpg 101KB
n0398087400000741.jpg 100KB
n0211454800000950.jpg 100KB
n0213844100000900.jpg 98KB
n0213844100000337.jpg 97KB
n0213844100000512.jpg 97KB
n0213844100000838.jpg 95KB
n0925647900000523.jpg 94KB
n0398087400000986.jpg 94KB
n0213844100001097.jpg 94KB
n0209124400000057.jpg 94KB
n0398087400000105.jpg 94KB
n0213844100000167.jpg 93KB
n0211454800000709.jpg 93KB
n0925647900000792.jpg 93KB
n0217400100000047.jpg 91KB
n0398087400001231.jpg 91KB
n0209124400000015.jpg 90KB
n0209124400000930.jpg 90KB
n0925647900000678.jpg 90KB
n0925647900001224.jpg 90KB
n0211454800000641.jpg 90KB
n0377043900001031.jpg 89KB
n0925647900000739.jpg 89KB
n0213844100000105.jpg 89KB
n0213844100000584.jpg 88KB
n0925647900001285.jpg 88KB
n0925647900000111.jpg 88KB
n0209124400000456.jpg 87KB
n0211454800001157.jpg 87KB
n0925647900001070.jpg 87KB
n0398087400000564.jpg 87KB
n0377043900000690.jpg 87KB
n0398087400000071.jpg 86KB
n0213844100000065.jpg 86KB
n0213844100000783.jpg 86KB
n0925647900000862.jpg 86KB
n0217400100000210.jpg 86KB
n0213844100000180.jpg 85KB
n0209124400000552.jpg 85KB
n0209124400000032.jpg 85KB
n0925647900000628.jpg 85KB
n0213844100000103.jpg 84KB
n0213844100000634.jpg 84KB
n0307537000000178.jpg 84KB
n0211454800000463.jpg 84KB
n0925647900000049.jpg 84KB
n0213844100001260.jpg 83KB
n0398087400000220.jpg 83KB
n0925647900001229.jpg 83KB
n0213844100000681.jpg 82KB
n0398087400000257.jpg 82KB
n0213844100000612.jpg 82KB
n0211454800000676.jpg 82KB
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资源评论
- 本本纲目2023-07-27部分imagenet数据(10class*100picture)这个文件帮助我更好地了解了不同类别的图像样本,非常有帮助。
- 嗨了伐得了2023-07-27这个文件里的10个类别的100张照片可以作为学习和研究imagenet数据的入门素材。
- 金山文档2023-07-27这个文件提供了包含10个类别、100张照片的部分imagenet数据,非常实用!
- 我就是月下2023-07-27这个文件包含了10个类别的样本照片,数量虽然不多,但足以满足一般需求。
- 陈莽昆2023-07-27这个文件提供了一些基础的imagenet数据,方便了我对这些类别的图像进行训练和分析。
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