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				https://github.com/THU-MIG/yolov10.git
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			86 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Docker
		
	
	
	
	
	
			
		
		
	
	
			86 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Docker
		
	
	
	
	
	
| # 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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| 
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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:2.2.0-cuda12.1-cudnn8-runtime
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| RUN pip install --no-cache nvidia-tensorrt --index-url https://pypi.ngc.nvidia.com
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| 
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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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| 
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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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| 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 build-essential
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| 
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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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| 
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| # Create working directory
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| WORKDIR /usr/src/ultralytics
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| 
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| # Copy contents
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| # COPY . /usr/src/ultralytics  # git permission issues inside container
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| RUN git clone https://github.com/ultralytics/ultralytics -b main /usr/src/ultralytics
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| ADD https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8n.pt /usr/src/ultralytics/
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| 
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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 -e ".[export]" albumentations comet pycocotools
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| 
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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 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 numpy==1.23.5
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| # Remove exported models
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| RUN rm -rf tmp
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| 
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| # Set environment variables
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| ENV OMP_NUM_THREADS=1
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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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| 
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| 
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| # Usage Examples -------------------------------------------------------------------------------------------------------
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| # Kill all
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| # sudo docker kill $(sudo docker ps -q)
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| 
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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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| 
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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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| 
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| # Clean up
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| # sudo docker system prune -a --volumes
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| 
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| # Update Ubuntu drivers
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| # https://www.maketecheasier.com/install-nvidia-drivers-ubuntu/
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| 
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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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| 
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| # GCP VM from Image
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| # docker.io/ultralytics/ultralytics:latest
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