Record the relevant codes of the Ministry of Industry and Information Technology's medical image evaluation.
Public warehouse image pull
docker pull ai-hub.3incloud.com/library/pytorch/pytorch:1.2-cuda10.0-cudnn7-runtime
package
docker run -it (image ID) /bin/bash
pip install torch1.7.0+cu101 torchvision0.8.1+cu101 torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
pip install albumments opencv-contrib-python segmentation-models-pytorch
copy
docker cp (pwd) (container ID ):/workspace/
bash file
docker commit (container ID) ai-hub.3incloud.com/comp_18/eye
docker tag (image:1.0) ai-hub.3incloud.com/username/official
upload private mirror warehouse
docker login ai- hub.3incloud.com
docker push ai-hub.3incloud.com/comp_18/eye
sandbox
docker pull docker pull ai-hub.3incloud.com/username/classify:latest
docker run --gpus all -it -v /data/ data1/eye surface disease data: /workspace/data_eye ai-hub.3incloud.com/comp_18/eye /bin/bash
sudo docker cp (container ID):/workspace/pipeline/result.csv /data/result.csv
sftp上传
sftp [email protected]
cd sandbox_result/
put ./result.csv ./
Delete image
docker rmi (image ID)/ ( dockerimages − q ) − f delete container docker rm ( container ID ) / (docker images -q) -f delete container docker rm (container ID)/(dockerimages−q)−f delete container d o ck e r r m ( c o n t a i n e r I D ) / (docker ps -aq)
stop/start/restart container docker stop/ start
/restart (container ID)
no Close and exit the container
Ctrl+P+Q
to enter the running container
docker attach
docker19 supports running GPU environment
Install Nvidia-container-runtime
curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
sudo apt-get update
sudo apt nvidia-container-runtime
run command
docker run --gpus all -it -v /data/data1/眼表疾病数据:/workspace/data_eye ai-hub.3incloud.com/comp_18/eye /bin/bash
python classify_dataset_new.py --data_dir ***** --save_csv “result.csv” --device “gpu”
Nvidia-container-runtime