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Download ImageNet Data
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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.
Citing ImageNet
Please cite the main ImageNet paper (Deng et al. CVPR 2009) if you use ImageNet data, in addition to specific follow-up papers:
@inproceedings{deng2009imagenet,
title={Imagenet: A large-scale hierarchical image database},
author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
booktitle={2009 IEEE conference on computer vision and pattern recognition},
pages={248--255},
year={2009},
organization={IEEE}
}
Winter 2021 release
- ImageNet21K MD5: ab313ce03179fd803a401b02c651c0a2
- Download a single Synset: https://image-net.org/data/winter21_whole/SYNSET_ID.tar, e.g., https://image-net.org/data/winter21_whole/n02352591.tar
- Processed version of ImageNet21K (MD5: c314e95f17e357b3e9cbf0a18ef7ecd6) 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 imagenet.help.desk@gmail.com to request access.
ImageNet Large-scale Visual Recognition Challenge (ILSVRC)
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
ReImageNet: The ImageNet‑1k Validation Set re-annotated
- Project page, courtesy of Czech Technical University in Prague.
Object bounding boxes (AAAI 2010).
Object attributes (ECCV workshop 2010).
Download image data for Visual Domain Decathlon(PASCAL in Detail Workshop Challenge)
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
ImageNet-OOD (ICLR 2024)
- Description and details
- Download, 608 MB (MD5: f223759a476610dd59ee1010c97e29e9)