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86 lines
3.9 KiB
86 lines
3.9 KiB
# Ultralytics YOLO 🚀, AGPL-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:2.2.2-cuda12.1-cudnn8-runtime |
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RUN pip install --no-cache-dir nvidia-tensorrt --index-url https://pypi.ngc.nvidia.com |
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# Set environment variables |
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ENV APP_HOME /usr/src/ultralytics |
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# Avoid DDP error "MKL_THREADING_LAYER=INTEL is incompatible with libgomp.so.1 library" https://github.com/pytorch/pytorch/issues/37377 |
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ENV MKL_THREADING_LAYER=GNU |
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# Downloads to user config dir |
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ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \ |
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https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \ |
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/root/.config/Ultralytics/ |
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# Install linux packages |
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# g++ required to build 'tflite_support' and 'lap' packages, libusb-1.0-0 required for 'tflite_support' package |
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# libsm6 required by libqxcb to create QT-based windows for visualization; set 'QT_DEBUG_PLUGINS=1' to test in docker |
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RUN apt update \ |
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&& apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg g++ libusb-1.0-0 libsm6 |
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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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WORKDIR $APP_HOME |
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# Copy contents and assign permissions |
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COPY . $APP_HOME |
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RUN git remote set-url origin https://github.com/ultralytics/ultralytics.git |
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ADD https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt $APP_HOME |
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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-dir -e ".[export]" "albumentations>=1.4.6" comet pycocotools |
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# Run exports to AutoInstall packages |
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# Edge TPU export fails the first time so is run twice here |
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RUN yolo export model=tmp/yolov8n.pt format=edgetpu imgsz=32 || yolo export model=tmp/yolov8n.pt format=edgetpu imgsz=32 |
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RUN yolo export model=tmp/yolov8n.pt format=ncnn imgsz=32 |
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# Requires <= Python 3.10, bug with paddlepaddle==2.5.0 https://github.com/PaddlePaddle/X2Paddle/issues/991 |
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RUN pip install --no-cache-dir "paddlepaddle>=2.6.0" x2paddle |
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# Fix error: `np.bool` was a deprecated alias for the builtin `bool` segmentation error in Tests |
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RUN pip install --no-cache-dir numpy==1.23.5 |
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# Remove exported models |
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RUN rm -rf tmp |
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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 with access to all GPUs |
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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 access to GPUs 2 and 3 (inside container CUDA devices will appear as 0 and 1) |
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# t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus '"device=2,3"' $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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