High-Performance Large-Scale Image Recognition Without Normalization
NFNet Pytorch Implementation
This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale Image Recognition Without Normalization. The small models are as accurate as an EfficientNet-B7, but train 8.7 times faster. The large models set a new SOTA top-1 accuracy on ImageNet.
| NFNet | F0 | F1 | F2 | F3 | F4 | F5 | F6+SAM |
|---|---|---|---|---|---|---|---|
| Top-1 accuracy Brock et al. | 83.6 | 84.7 | 85.1 | 85.7 | 85.9 | 86.0 | 86.5 |
| Top-1 accuracy this implementation | 82.82 | 84.63 | 84.90 | 85.46 | 85.66 | 85.62 | TBD |
All credits go to the authors of the original paper. This repo is heavily inspired by their nice JAX implementation in the official repository. Visit their repo for citing.
Get started
git clone https://github.com/benjs/nfnets_pytorch.git
pip3 install -r requirements.txt
or if you don’t need