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72 lines
2.7 KiB
72 lines
2.7 KiB
# Ultralytics YOLO 🚀, 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 YOLOv8 single/multi-GPU training and inference |
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# Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch or nvcr.io/nvidia/pytorch:23.03-py3 |
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FROM pytorch/pytorch:2.0.0-cuda11.7-cudnn8-runtime |
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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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ENV DEBIAN_FRONTEND noninteractive |
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RUN apt update |
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RUN TZ=Etc/UTC apt install -y tzdata |
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RUN apt install --no-install-recommends -y gcc git zip curl htop libgl1-mesa-glx libglib2.0-0 libpython3-dev gnupg g++ |
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# RUN alias python=python3 |
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# Security updates |
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# https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796 |
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RUN apt upgrade --no-install-recommends -y openssl tar |
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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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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt /usr/src/ultralytics/ |
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# Install pip packages |
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RUN python3 -m pip install --upgrade pip wheel |
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RUN pip install --no-cache '.[export]' albumentations comet gsutil notebook |
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# Set environment variables |
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ENV OMP_NUM_THREADS=1 |
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# Cleanup |
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ENV DEBIAN_FRONTEND teletype |
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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 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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# sudo 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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