---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': BACKGROUND_Google
          '1': Faces
          '2': Faces_easy
          '3': Leopards
          '4': Motorbikes
          '5': accordion
          '6': airplanes
          '7': anchor
          '8': ant
          '9': barrel
          '10': bass
          '11': beaver
          '12': binocular
          '13': bonsai
          '14': brain
          '15': brontosaurus
          '16': buddha
          '17': butterfly
          '18': camera
          '19': cannon
          '20': car_side
          '21': ceiling_fan
          '22': cellphone
          '23': chair
          '24': chandelier
          '25': cougar_body
          '26': cougar_face
          '27': crab
          '28': crayfish
          '29': crocodile
          '30': crocodile_head
          '31': cup
          '32': dalmatian
          '33': dollar_bill
          '34': dolphin
          '35': dragonfly
          '36': electric_guitar
          '37': elephant
          '38': emu
          '39': euphonium
          '40': ewer
          '41': ferry
          '42': flamingo
          '43': flamingo_head
          '44': garfield
          '45': gerenuk
          '46': gramophone
          '47': grand_piano
          '48': hawksbill
          '49': headphone
          '50': hedgehog
          '51': helicopter
          '52': ibis
          '53': inline_skate
          '54': joshua_tree
          '55': kangaroo
          '56': ketch
          '57': lamp
          '58': laptop
          '59': llama
          '60': lobster
          '61': lotus
          '62': mandolin
          '63': mayfly
          '64': menorah
          '65': metronome
          '66': minaret
          '67': nautilus
          '68': octopus
          '69': okapi
          '70': pagoda
          '71': panda
          '72': pigeon
          '73': pizza
          '74': platypus
          '75': pyramid
          '76': revolver
          '77': rhino
          '78': rooster
          '79': saxophone
          '80': schooner
          '81': scissors
          '82': scorpion
          '83': sea_horse
          '84': snoopy
          '85': soccer_ball
          '86': stapler
          '87': starfish
          '88': stegosaurus
          '89': stop_sign
          '90': strawberry
          '91': sunflower
          '92': tick
          '93': trilobite
          '94': umbrella
          '95': watch
          '96': water_lilly
          '97': wheelchair
          '98': wild_cat
          '99': windsor_chair
          '100': wrench
          '101': yin_yang
  splits:
  - name: test
    num_bytes: 87143920.1032546
    num_examples: 6060
  - name: train
    num_bytes: 44935085.33674541
    num_examples: 3084
  download_size: 137936915
  dataset_size: 132079005.44000001
task_categories:
- image-classification
language:
- en
pretty_name: d
---
# Dataset Card for "Caltech-101"

This is a non-official ```Caltech-101``` dataset for **fine-grained** ```Image Classification.```

Since there is no official method for separating training and test data, we arbitrarily split the data similar to TensorFlow.  
If you want to download the official dataset, please refer to the [here](https://data.caltech.edu/records/mzrjq-6wc02).