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+# Installation
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+
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+We provide installation instructions for ImageNet classification experiments here.
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+
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+## Dependency Setup
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+Create an new conda virtual environment
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+```
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+conda create -n convnext python=3.8 -y
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+conda activate convnext
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+```
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+
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+Install [Pytorch](https://pytorch.org/)>=1.8.0, [torchvision](https://pytorch.org/vision/stable/index.html)>=0.9.0 following official instructions. For example:
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+```
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+pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html
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+```
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+
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+Clone this repo and install required packages:
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+```
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+git clone https://github.com/facebookresearch/ConvNeXt
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+pip install timm==0.3.2 tensorboardX six
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+```
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+
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+The results in the paper are produced with `torch==1.8.0+cu111 torchvision==0.9.0+cu111 timm==0.3.2`.
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+
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+## Dataset Preparation
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+
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+Download the [ImageNet-1K](http://image-net.org/) classification dataset and structure the data as follows:
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+```
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+/path/to/imagenet-1k/
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+ train/
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+ class1/
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+ img1.jpeg
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+ class2/
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+ img2.jpeg
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+ val/
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+ class1/
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+ img3.jpeg
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+ class2/
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+ img4.jpeg
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+```
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+
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+For pre-training on [ImageNet-22K](http://image-net.org/), download the dataset and structure the data as follows:
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+```
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+/path/to/imagenet-22k/
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+ class1/
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+ img1.jpeg
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+ class2/
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+ img2.jpeg
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+ class3/
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+ img3.jpeg
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+ class4/
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+ img4.jpeg
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+```
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