which section of imagenet data should be used?

[oym1994]

Hi , I am a new research student in DL, could u tell us which section of imagenet should I download to use? Thank you!
Download
Download ImageNet Data
March 11, 2021. Face-blurred ILSVRC 2012–2017 classification data is released. We strongly urge researchers to use this new privacy-aware version.

October 10, 2019: The ILSVRC 2012 classification and localization test set has been updated.

You have been granted access to the the whole ImageNet database through our site. By doing so you agree to the terms of access.

Winter 2021 release
ImageNet21K MD5: ab313ce03179fd803a401b02c651c0a2
Processed version of ImageNet21K using the script of "ImageNet-21K pretraining for the masses"
ImageNet10K from Deng et al. ECCV2010

People subtree annotations (FAT 2020).*
Description and details
Unsafe synsets
Imageability annotations
Due to sensitivity of the data, the demographic annotations are not available here. Please contact us at [e-mail] to request access.

ImageNet Large-scale Visual Recognition Challenge (ILSVRC)
2017
2016
2015
2014
2013
2012
2011
2010
ILSVRC 2012–2017 evaluation server

Face-blurred ILSVRC2012–2017 classification data is now available (below). We strongly encourage researchers to use this new privacy-aware version for all purposes.

Face obfuscation in ILSVRC
Description and details
Face annotations
Blurred training images
Blurred validation images

Object bounding boxes (AAAI 2010).
Description and details
Download all available

Object attributes (ECCV workshop 2010).
Description, details, and download

Download image data for Visual Domain Decathlon(PASCAL in Detail Workshop Challenge)
Description and details
Decathlon data, 6.1 GB

Download downsampled image data (32x32, 64x64)
Description and details
Train(8x8), npz format, 227 MB
Val(8x8), npz format 9 MB
Train(16x16), npz format, 888 MB
Val(16x16), npz format, 34 MB
Train(32x32), npz format, 3 GB
Val(32x32), npz format, 134 MB
Train(64x64) part1, npz format, 6 GB
Train(64x64) part2, npz format, 6 GB
Val(64x64), npz format, 509 MB

Tiny Imagenet(Stanford CS231N)
Description and details
Tiny, 236 MB

[Andrei Bursuc]

Hi @oym1994 !

Thank you for the interest in our work.
I think your question is not particularly related to this repo.
For OBoW we used the original ImageNet dataset for pre-training (we submitted it to CVPR one year ago).

The updated dataset is more privacy-aware, but I would not expect major differences in the final performance of the self-supervised trained models. You can use that one for your experiments.

Best,
Andrei