mirror of https://github.com/FoundationVision/GLEE
46 lines
1.3 KiB
Markdown
46 lines
1.3 KiB
Markdown
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## Use the container (with docker ≥ 19.03)
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```
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cd docker/
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# Build:
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docker build --build-arg USER_ID=$UID -t detectron2:v0 .
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# Launch (require GPUs):
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docker run --gpus all -it \
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--shm-size=8gb --env="DISPLAY" --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
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--name=detectron2 detectron2:v0
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# Grant docker access to host X server to show images
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xhost +local:`docker inspect --format='{{ .Config.Hostname }}' detectron2`
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```
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## Use the container (with docker-compose ≥ 1.28.0)
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Install docker-compose and nvidia-docker-toolkit, then run:
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```
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cd docker && USER_ID=$UID docker-compose run detectron2
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```
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## Use the deployment container (to test C++ examples)
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After building the base detectron2 container as above, do:
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```
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# Build:
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docker build -t detectron2-deploy:v0 -f deploy.Dockerfile .
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# Launch:
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docker run --gpus all -it detectron2-deploy:v0
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```
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#### Using a persistent cache directory
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You can prevent models from being re-downloaded on every run,
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by storing them in a cache directory.
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To do this, add `--volume=$HOME/.torch/fvcore_cache:/tmp:rw` in the run command.
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## Install new dependencies
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Add the following to `Dockerfile` to make persistent changes.
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```
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RUN sudo apt-get update && sudo apt-get install -y vim
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```
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Or run them in the container to make temporary changes.
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