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Automatic Deblurring and Rating Classification for Metal Corrosion Images

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Installation

create conda environment

conda create -n ccnet python=3.9
conda activate ccnet

Install dependencies

pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu116
pip install -r requirements.txt
python setup.py develop --no_cuda_ext

Quick Start

1. Deblurring

Train
python -m torch.distributed.launch --nproc_per_node=1 --master_port=2233 basicsr/train.py -opt options/train/NAFNet-width32.yml --launcher pytorch
Test
python -m torch.distributed.launch --nproc_per_node=1 --master_port=2233 basicsr/test.py -opt options/test/NAFNet-width32.yml --launcher pytorch

2. Corrosion Classification

Train
python main.py
visualize
python visualize.py

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Automatic Deblurring and Rating Classification for Metal Corrosion Images

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