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Deep Residual Learning for Image Recognition

This repository is the first assignment of my AI security course, which is a simple PyTorch implementation of 34 - layer ResNet on CIFAR10.

Requirements

conda create -n resnet python=3.7
conda activate resnet
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch

Please go to the official website and download torch which matches your CUDA version.

Train and Test

CUDA_VISIBLE_DEVICES=0 python run.py

Run the above command. The loss and accuracy of training and testing can be found in result.png.

Citation

@inproceedings{he2016deep,
title={Deep residual learning for image recognition},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={770--778},
year={2016}
}