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update Dockerfile
Browse files- Dockerfile +3 -17
Dockerfile
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@@ -1,36 +1,22 @@
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# Use the official lightweight Python image.
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# https://hub.docker.com/_/python
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FROM python:3.10-slim
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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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# COPY . ./
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RUN apt update && apt install -y \
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libgl1-mesa-glx \
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libglib2.0-dev \
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git
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RUN pip install --upgrade pip
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RUN
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RUN cp -r MODNet/* ./
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RUN pip install -r requirements.txt
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# CPU
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#RUN pip install torch==1.7.1+cpu torchvision==0.8.2+cpu torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
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RUN pip install torch==1.13.0+cpu torchvision==0.14.0+cpu torchaudio==0.13.0 --extra-index-url https://download.pytorch.org/whl/cpu
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# Run the web service on container startup. Here we use the gunicorn
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# webserver, with one worker process and 8 threads.
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# For environments with multiple CPU cores, increase the number of workers
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# to be equal to the cores available.
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# CMD exec gunicorn --bind 0.0.0.0:7860 --workers 1 --threads 8 --timeout 0 app:app
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# CMD exec gunicorn --bind 0.0.0.0:$PORT --workers 1 --threads 8 --timeout 0 app:app
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CMD ["bash", "run.sh"]
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FROM python:3.10-slim
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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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RUN apt update && apt install -y \
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libgl1-mesa-glx \
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libglib2.0-dev \
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git
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RUN git clone https://github.com/LiteraturePro/MODNet.git && cp -r MODNet/* ./
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RUN pip install --upgrade pip && pip install -r requirements.txt
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# CPU
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RUN pip install torch==1.13.0+cpu torchvision==0.14.0+cpu torchaudio==0.13.0 --extra-index-url https://download.pytorch.org/whl/cpu
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# CMD exec gunicorn --bind 0.0.0.0:7860 --workers 1 --threads 8 --timeout 0 app:app
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# CMD exec gunicorn --bind 0.0.0.0:$PORT --workers 1 --threads 8 --timeout 0 app:app
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CMD ["bash", "run.sh"]
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