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64 lines
2.4 KiB
64 lines
2.4 KiB
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license |
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# Builds ultralytics/ultralytics:latest image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics |
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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:22.12-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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# Create working directory |
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RUN mkdir -p /usr/src/ultralytics |
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WORKDIR /usr/src/ultralytics |
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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/ultralytics /usr/src/ultralytics |
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# Install pip packages |
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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 ultralytics albumentations comet 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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# Set environment variables |
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ENV OMP_NUM_THREADS=1 |
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# Usage Examples ------------------------------------------------------------------------------------------------------- |
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# Build and Push |
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# t=ultralytics/ultralytics: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/ultralytics: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/ultralytics: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/ultralytics:latest) |
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# DockerHub tag update |
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# t=ultralytics/ultralytics:latest tnew=ultralytics/ultralytics: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/ultralytics:latest
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