content: FROM pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
  
  WORKDIR /home
  
  ## Install git
  RUN apt update -o Acquire::https::developer.download.nvidia.com::Verify-Peer=false
  
  # Required by OpenCV
  RUN apt install libglib2.0-0 libgl1 libglx-mesa0 libgl1-mesa-glx -y
  
  # RUN apt install -y git
  RUN apt install -y gfortran libopenblas-dev liblapack-dev
  
  # Update Python 
  RUN apt install python3.8 python3.8-distutils python3-venv curl -y
  RUN python3.8 --version
  RUN curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
  RUN python3.8 get-pip.py
  
  ## Install base dependencies
  RUN python3.8 -m pip install torch torchvision tqdm opencv-python pillow pytorch-ignite --trusted-host=developer.download.nvidia.com
  
  ## Add Kafka Python library
  RUN python3.8 -m pip install kafka-python --trusted-host=developer.download.nvidia.com
  
  # ONNX
  RUN pip install onnx protobuf==3.16.0
  
  ## SEDNA SECTION ##
  
  COPY ./lib/requirements.txt /home
  RUN python3.8 -m pip install -r /home/requirements.txt --trusted-host=developer.download.nvidia.com
  
  # This instructions should make Sedna reachable from the dertorch code part
  ENV PYTHONPATH "${PYTHONPATH}:/home/lib"
  
  WORKDIR /home/work
  COPY ./lib /home/lib
  
  # Add M3L imports
  COPY examples/multiedgeinference/pedestrian_tracking/feature_extraction /home/work
  
  ENV PYTHONPATH "${PYTHONPATH}:/home/work"
  ENV LOG_LEVEL="INFO"
  
  ENTRYPOINT ["python3.8"]
  CMD ["worker.py"]
  