Dockerfile

# Use the official lightweight Python image.
# https://hub.docker.com/_/python
FROM python:3.10-slim

# Copy local code to the container image.
ENV APP_HOME /app
WORKDIR $APP_HOME
# COPY . ./

RUN apt update && apt install -y \
    libgl1-mesa-glx \
    libglib2.0-dev \
    git

# Install production dependencies.
RUN pip install --upgrade pip

RUN git clone https://github.com/LiteraturePro/MODNet.git

RUN cp -r MODNet/* ./

RUN pip install -r requirements.txt

# CPU
#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
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

# Run the web service on container startup. Here we use the gunicorn
# webserver, with one worker process and 8 threads.
# For environments with multiple CPU cores, increase the number of workers
# to be equal to the cores available.
# CMD exec gunicorn --bind 0.0.0.0:7860 --workers 1 --threads 8 --timeout 0 app:app

# CMD exec gunicorn --bind 0.0.0.0:$PORT --workers 1 --threads 8 --timeout 0 app:app

CMD ["streamlit run streamlit_app.py", "--server.port","7860"]