55 lines
1.8 KiB
Docker
55 lines
1.8 KiB
Docker
# Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
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FROM nvcr.io/nvidia/pytorch:20.12-py3
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# Install linux packages
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RUN apt update && apt install -y zip screen libgl1-mesa-glx
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# Install python dependencies
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RUN python -m pip install --upgrade pip
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COPY requirements.txt .
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RUN pip install -r requirements.txt gsutil
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# Create working directory
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RUN mkdir -p /usr/src/app
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WORKDIR /usr/src/app
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# Copy contents
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COPY . /usr/src/app
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# Copy weights
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#RUN python3 -c "from models import *; \
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#attempt_download('weights/yolov5s.pt'); \
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#attempt_download('weights/yolov5m.pt'); \
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#attempt_download('weights/yolov5l.pt')"
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# --------------------------------------------------- Extras Below ---------------------------------------------------
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# Build and Push
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# t=ultralytics/yolov5:latest && sudo docker build -t $t . && sudo docker push $t
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# for v in {300..303}; do t=ultralytics/coco:v$v && sudo docker build -t $t . && sudo docker push $t; done
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# Pull and Run
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# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all $t
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# Pull and Run with local directory access
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# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/coco:/usr/src/coco $t
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# Kill all
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# sudo docker kill $(sudo docker ps -q)
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# Kill all image-based
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# sudo docker kill $(sudo docker ps -qa --filter ancestor=ultralytics/yolov5:latest)
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# Bash into running container
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# sudo docker exec -it 5a9b5863d93d bash
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# Bash into stopped container
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# id=$(sudo docker ps -qa) && sudo docker start $id && sudo docker exec -it $id bash
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# Send weights to GCP
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# python -c "from utils.general import *; strip_optimizer('runs/train/exp0_*/weights/best.pt', 'tmp.pt')" && gsutil cp tmp.pt gs://*.pt
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# Clean up
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# docker system prune -a --volumes
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