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Dataset Card for "imagenet_1k_resized_256"

Dataset summary

The same ImageNet dataset but all the smaller side resized to 256. A lot of pretraining workflows contain resizing images to 256 and random cropping to 224x224, this is why 256 is chosen. The resized dataset can also be downloaded much faster and consume less space than the original one. See here for detailed readme.

Dataset Structure

Below is the example of one row of data. Note that the labels in the test split are all -1.

{
  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=256x384 at 0x276021C5EB8>,
  'label': 23
}

The number of rows per split is the same as the original ImageNet.

train validation test
# of examples 1281167 50000 100000

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}
}
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