image
imagewidth (px)
160
879
label
class label
65 classes
0bonnet, poke bonnet
0bonnet, poke bonnet
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0bonnet, poke bonnet
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0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
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0bonnet, poke bonnet
0bonnet, poke bonnet
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0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
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0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet
0bonnet, poke bonnet

Dataset Card for ImageNet-100

ImageNet-100 is a subset of the original ImageNet-1k dataset containing 100 randomly selected classes. In addition, the images have been resized to 160 pixels on the shorter side.

Dataset Structure

Data Instances

An example looks like below:

{
  'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=160x213>,
  'label': 0
}

Data Fields

The data instances have the following fields:

  • image: A PIL.Image.Image object containing the image.
  • label: an int classification label.

The labels are indexed based on the sorted list of synset ids in imagenet100.txt which we automatically map to original class names.

Data Splits

train validation
# of examples 126689 5000

Additional Information

Licensing Information

In exchange for permission to use the ImageNet database (the "Database") at Princeton University and Stanford University, Researcher hereby agrees to the following terms and conditions:

  1. Researcher shall use the Database only for non-commercial research and educational purposes.
  2. Princeton University and Stanford University make no representations or warranties regarding the Database, including but not limited to warranties of non-infringement or fitness for a particular purpose.
  3. Researcher accepts full responsibility for his or her use of the Database and shall defend and indemnify the ImageNet team, Princeton University, and Stanford University, including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Database, including but not limited to Researcher's use of any copies of copyrighted images that he or she may create from the Database.
  4. Researcher may provide research associates and colleagues with access to the Database provided that they first agree to be bound by these terms and conditions.
  5. Princeton University and Stanford University reserve the right to terminate Researcher's access to the Database at any time.
  6. If Researcher is employed by a for-profit, commercial entity, Researcher's employer shall also be bound by these terms and conditions, and Researcher hereby represents that he or she is fully authorized to enter into this agreement on behalf of such employer.
  7. The law of the State of New Jersey shall apply to all disputes under this agreement.

Citation Information

@article{imagenet15russakovsky,
    Author = {Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
    Title = { {ImageNet Large Scale Visual Recognition Challenge} },
    Year = {2015},
    journal   = {International Journal of Computer Vision (IJCV)},
    doi = {10.1007/s11263-015-0816-y},
    volume={115},
    number={3},
    pages={211-252}
}

@inproceedings{tian2020contrastive,
  title={Contrastive multiview coding},
  author={Tian, Yonglong and Krishnan, Dilip and Isola, Phillip},
  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XI 16},
  pages={776--794},
  year={2020},
  organization={Springer}
}

Contributions

Thanks to the 🤗 authors for the imagenet-1k dataset which was used as a reference.

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