退购1.1定位算法
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jiajie555
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docker/Dockerfile
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docker/Dockerfile
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# 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:2.0.0-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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# g++ required to build '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-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 -e . albumentations comet tensorboard
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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 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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docker/Dockerfile-arm64
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docker/Dockerfile-arm64
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Builds ultralytics/ultralytics:latest-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Image is aarch64-compatible for Apple M1 and other ARM architectures i.e. Jetson Nano and Raspberry Pi
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# Start FROM Ubuntu image https://hub.docker.com/_/ubuntu
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FROM arm64v8/ubuntu:22.10
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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 \
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&& apt install --no-install-recommends -y python3-pip git zip curl htop gcc libgl1-mesa-glx libglib2.0-0 libpython3-dev
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# RUN alias python=python3
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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 -e .
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/ultralytics:latest-arm64 && sudo docker build --platform linux/arm64 -f docker/Dockerfile-arm64 -t $t . && sudo docker push $t
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# Pull and Run
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# t=ultralytics/ultralytics:latest-arm64 && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t
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37
docker/Dockerfile-cpu
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docker/Dockerfile-cpu
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Builds ultralytics/ultralytics:latest-cpu image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Image is CPU-optimized for ONNX, OpenVINO and PyTorch YOLOv8 deployments
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# Start FROM Ubuntu image https://hub.docker.com/_/ubuntu
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FROM ubuntu:22.10
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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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# g++ required to build 'tflite_support' package
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RUN apt update \
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&& apt install --no-install-recommends -y python3-pip 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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# 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 -e . --extra-index-url https://download.pytorch.org/whl/cpu
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/ultralytics:latest-cpu && sudo docker build -f docker/Dockerfile-cpu -t $t . && sudo docker push $t
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# Pull and Run
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# t=ultralytics/ultralytics:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t
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47
docker/Dockerfile-jetson
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47
docker/Dockerfile-jetson
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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# Builds ultralytics/ultralytics:jetson image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
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# Supports JetPack for YOLOv8 on Jetson Nano, TX1/TX2, Xavier NX, AGX Xavier, AGX Orin, and Orin NX
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# Start FROM https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-pytorch
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FROM nvcr.io/nvidia/l4t-pytorch:r35.2.1-pth2.0-py3
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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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# g++ required to build '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-mesa-glx libglib2.0-0 libpython3-dev gnupg g++
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# RUN alias python=python3
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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 manually for TensorRT compatibility https://github.com/NVIDIA/TensorRT/issues/2567
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RUN python3 -m pip install --upgrade pip wheel
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RUN pip install --no-cache tqdm matplotlib pyyaml psutil thop pandas onnx "numpy==1.23"
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RUN pip install --no-cache -e .
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# Resolve duplicate OpenCV installation issues in https://github.com/ultralytics/ultralytics/issues/2407
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RUN apt-get remove `dpkg -l | grep opencv | awk '{print $2}'`
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RUN pip uninstall -y opencv-python
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RUN rm /usr/local/lib/python3.8/dist-packages/cv2 # Optional
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RUN pip install "opencv-python<4.7"
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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-jetson && sudo docker build --platform linux/arm64 -f docker/Dockerfile-jetson -t $t . && sudo docker push $t
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# Pull and Run
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# t=ultralytics/ultralytics:jetson && sudo docker pull $t && sudo docker run -it --runtime=nvidia $t
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