66 lines
2.4 KiB
Docker
66 lines
2.4 KiB
Docker
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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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# Builds ultralytics/yolov5:latest image on DockerHub https://hub.docker.com/r/ultralytics/yolov5
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# Image is CUDA-optimized for YOLOv5 single/multi-GPU training and inference
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# Start FROM NVIDIA PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
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FROM nvcr.io/nvidia/pytorch:22.07-py3
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RUN rm -rf /opt/pytorch # remove 1.2GB dir
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# Downloads to user config dir
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ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Arial.Unicode.ttf /root/.config/Ultralytics/
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# Install linux packages
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RUN apt update && apt install --no-install-recommends -y zip htop screen libgl1-mesa-glx
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# Install pip packages
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COPY requirements.txt .
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RUN python -m pip install --upgrade pip wheel
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RUN pip uninstall -y Pillow torchtext torch torchvision
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RUN pip install --no-cache -r requirements.txt albumentations wandb gsutil notebook Pillow>=9.1.0 \
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'opencv-python<4.6.0.66' \
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--extra-index-url https://download.pytorch.org/whl/cu113
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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 (issues as not a .git directory)
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RUN git clone https://github.com/ultralytics/yolov5 /usr/src/app
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# Set environment variables
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ENV OMP_NUM_THREADS=8
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/yolov5:latest && sudo docker build -f utils/docker/Dockerfile -t $t . && sudo docker push $t
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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)"/datasets:/usr/src/datasets $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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# DockerHub tag update
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# t=ultralytics/yolov5:latest tnew=ultralytics/yolov5:v6.2 && sudo docker pull $t && sudo docker tag $t $tnew && sudo docker push $tnew
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# Clean up
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# docker system prune -a --volumes
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# Update Ubuntu drivers
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# https://www.maketecheasier.com/install-nvidia-drivers-ubuntu/
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# DDP test
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# python -m torch.distributed.run --nproc_per_node 2 --master_port 1 train.py --epochs 3
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# GCP VM from Image
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# docker.io/ultralytics/yolov5:latest
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