content: #############################################################################################
  # Copyright (c) Microsoft Corporation.
  # Licensed under the MIT license.
  # Purpose:  This Dockerfile is for use with Azure ML TF Object Detection experiments.
  # It's the base of an Environment image for training object detection models.
  # The base is from a build of the TensorFlow Object Detection API.
  # Additionally, the following is built into the image:
  # - Miniconda (custom Dockerfile method with Azure ML expects conda)
  # - Azure ML SDK
  #############################################################################################
  FROM nvidia/cuda:10.0-cudnn7-runtime
  
  ENV DEBIAN_FRONTEND noninteractive
  
  RUN apt-get update \
        && apt-get install --no-install-recommends --no-install-suggests -y \
        libopencv-dev \
        python3-opencv \
        build-essential \
        gnupg2  \
        ca-certificates \
        libopencv-highgui3.2 \
        wget \
        bzip2 \
        git \
        ffmpeg \
        libsm6 \
        libxext6 \
        unzip \
        curl \
        protobuf-compiler \
        python-tk \
        && rm -rf /var/lib/apt/lists/*
  
  # Get Python in the form of Miniconda
  RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
  	bash ~/miniconda.sh -b -p /opt/conda && \
  	rm ~/miniconda.sh
  
  ENV PATH /opt/conda/bin:$PATH
  
  # Update package installers
  RUN conda install python=3.6 && conda update conda -y
  
  # Install Python packages
  RUN python -m pip install --upgrade pip==19.0 setuptools
  RUN python -m pip install azureml-core==1.25.0
  RUN python -m pip install tensorflow-gpu==1.15
  RUN python -m pip install tf-slim
  RUN python -m pip install Cython \
                  contextlib2 \
                  pillow \
                  lxml \
                  matplotlib \
                  PyDrive \
                  pycocotools \
                  build \
                  utils \
                  dataclasses \
                  install \
                  azure-iot-device \
                  azure-iot-hub \
                  numpy==1.17
  
  # Update protocol buffers for TF object detection API
  RUN curl -OL 'https://github.com/google/protobuf/releases/download/v3.2.0/protoc-3.2.0-linux-x86_64.zip' \
      && unzip -o protoc-3.2.0-linux-x86_64.zip -d protoc3 \
      && mv protoc3/bin/* /usr/local/bin/ \
      && mv protoc3/include/* /usr/local/include/
  
  WORKDIR /home/
  
  # Install TensorFlow models and scripts; compile contents of protos folder
  RUN git clone --depth 1 --branch v1.13.0 https://github.com/tensorflow/models.git \
      && export PYTHONPATH=`pwd`/models/research:`pwd`/models/research/slim:`pwd`:$PYTHONPATH \
      && cd models/research \
      && /usr/local/bin/protoc object_detection/protos/*.proto --python_out=. \
      && python setup.py build \
      && python setup.py install \
      && python object_detection/builders/model_builder_test.py
  
  RUN mkdir data \
      && cd data \
      && curl -OL 'http://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz'
  
  
  