We provide installation instructions for ImageNet classification experiments here.
Create a new conda virtual environment
conda create -n rest python=3.9 -y
conda activate rest
Install PyTorch >= 1.8.0, torchvision >=0.9.0 following official instructions. For example:
pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html
Clone this repo and install required packages:
pip install timm==0.5.4 tensorboardX six
The results in the paper are generated with torch==1.8.0+cu111 torchvision==0.9.0+cu111 timm==0.5.4.
Download the ImageNet-1K classification dataset and structure the data as follows:
/path/to/imagenet-1k/
train/
class1/
img1.jpeg
class2/
img2.jpeg
val/
class1/
img3.jpeg
class2/
img4.jpeg