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* FROM nvcr.io/nvidia/pytorch:22.04-py3 * Update Docker * Update Docker * Update Docker * Update Docker * Update TRT auto-install * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Cleanup * Cleanup * Cleanup cpu * Cleanup cpu Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
38 lines
1.4 KiB
Plaintext
38 lines
1.4 KiB
Plaintext
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
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# Start FROM Ubuntu image https://hub.docker.com/_/ubuntu
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FROM ubuntu:20.04
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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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RUN DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt install -y tzdata
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RUN apt install -y python3-pip git zip curl htop screen libgl1-mesa-glx libglib2.0-0
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# RUN alias python=python3
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# Install pip packages
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COPY requirements.txt .
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RUN python3 -m pip install --upgrade pip
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RUN pip install --no-cache -r requirements.txt albumentations gsutil notebook \
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coremltools onnx onnx-simplifier onnxruntime openvino-dev tensorflow-cpu tensorflowjs \
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torch torchvision --extra-index-url https://download.pytorch.org/whl/cpu
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# Create working directory
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RUN mkdir -p /usr/src/app
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WORKDIR /usr/src/app
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# Copy contents
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COPY . /usr/src/app
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RUN git clone https://github.com/ultralytics/yolov5 /usr/src/yolov5
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# Usage Examples -------------------------------------------------------------------------------------------------------
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# Build and Push
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# t=ultralytics/yolov5:latest-cpu && sudo docker build -f utils/docker/Dockerfile-cpu -t $t . && sudo docker push $t
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# Pull and Run
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# t=ultralytics/yolov5:latest-cpu && sudo docker pull $t && sudo docker run -it --ipc=host -v "$(pwd)"/datasets:/usr/src/datasets $t
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