wuji3 / visiondk Goto Github PK

# It is recommanded to create a separate virtual environment
conda create -n vision python=3.10 
conda activate vision

# torch==2.0.1(lower is also ok) -> https://pytorch.org/get-started/locally/
conda install pytorch torchvision torchaudio cpuonly -c pytorch # cpu-version
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia  # cuda-version

pip install -r requirements.txt

# Without Arial.ttf, inference may be slow due to network IO.
mkdir -p ~/.config/DuKe
cp misc/Arial.ttf ~/.config/DuKe

# one machine one gpu
python main.py --cfgs configs/task/pet.yaml

# one machine multiple gpus
CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun --nproc_per_node 4 main.py --cfgs configs/classification/pet.yaml
                                                                 --sync_bn[Option: this will lead to training slowly]
                                                                 --resume[Option: training from checkpoint]
                                                                 --load_from[Option: training from fine-tuning]