34 lines
1.1 KiB
Docker
34 lines
1.1 KiB
Docker
# Start from Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
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FROM nvcr.io/nvidia/pytorch:19.08-py3
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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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# Install dependencies (pip or conda)
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# RUN pip install -U -r requirements.txt
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# RUN conda update -n base -c defaults conda
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# RUN conda install -y -c anaconda future numpy opencv matplotlib tqdm pillow
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# RUN conda install -y -c conda-forge scikit-image tensorboard pycocotools
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# conda install pytorch torchvision -c pytorch
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# Move model into container
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# RUN mv yolov3-spp.pt ./weights
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# --------------------------------------------------- Extras Below ---------------------------------------------------
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# Build container
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# rm -rf yolov3 # Warning: remove existing
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# git clone https://github.com/ultralytics/yolov3 && cd yolov3 && python3 detect.py
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# sudo docker image prune -af && sudo docker build -t ultralytics/yolov3:v0 .
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# Run container
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# time sudo nvidia-docker run ultralytics/yolov3:v0 python3 detect.py
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# Push container to https://hub.docker.com/u/ultralytics
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# sudo docker push ultralytics/xview:v30
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