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ConvNet for the 2020s (installation guide )

Installation

We provide installation instructions for ImageNet classification experiments here.

Dependency Setup

Create an new conda virtual environment

conda create -n convnext python=3.8 -y
conda activate convnext

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:

git clone https://github.com/facebookresearch/ConvneXt
pip install timm==0.3.2 tensorboardX six

The results in the paper are generated with torch==1.8.0+cu111 torchvision==0.9.0+cu111 timm==0.3.2.

Dataset Preparation

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

For pre-training on ImageNet-22K, download the dataset and structure the data as follows:

/path/to/imagenet-22k/
  class1/
    img1.jpeg
  class2/
    img2.jpeg
  class1/
    img3.jpeg
  class2/
    img4.jpeg