I play with Custom Vision Service export capability to docker file for RP3 today. There are several things I need to do to make it work, at least as of today.
I believe the issue will be addressed soon, so please refer to this information only when you have issue.
I don't explain what is Custom Vision or how to export model. Please refer to official document.
Perform image classification at the edge with Custom Vision Service
Error
When I build the image, I encounter following error at step 5/9.
Step 5/9 : RUN pip install flask pillow --index-url 'https://www.piwheels.org/simple'
---> Running in 686a1e4aa7bc
Looking in indexes: https://www.piwheels.org/simple
Collecting flask
Downloading https://www.piwheels.org/simple/flask/Flask-1.1.2-py2.py3-none-any.whl (94 kB)
ERROR: Could not find a version that satisfies the requirement pillow (from versions: none)
ERROR: No matching distribution found for pillow
Dockerfile
Generated Dockerfile is below. If this is different from yours, then your issue maybe different. Key points are:
- It's from python:3.7-slim
- It misses libgl1-mesa-glx module on the first apt install.
FROM python:3.7-slim
RUN apt update && apt install -y libjpeg62-turbo libopenjp2-7 libtiff5 libatlas-base-dev
RUN pip install absl-py six protobuf wrapt gast astor termcolor keras_applications keras_preprocessing --no-deps
RUN pip install numpy==1.16 tensorflow==1.13.1 --extra-index-url 'https://www.piwheels.org/simple' --no-deps
RUN pip install flask pillow --index-url 'https://www.piwheels.org/simple'
# By default, we run manual image resizing to maintain parity with CVS webservice prediction results.
# If parity is not required, you can enable faster image resizing by uncommenting the following lines.
# RUN echo "deb http://security.debian.org/debian-security jessie/updates main" >> /etc/apt/sources.list & apt update -y
# RUN apt install -y zlib1g-dev libjpeg-dev gcc libglib2.0-bin libsm6 libxext6 libxrender1 libjasper-dev libpng16-16 libopenexr23 libgstreamer1.0-0 libavcodec58 libavformat58 libswscale5 libqtgui4 libqt4-test libqtcore4
# RUN pip install opencv-python --extra-index-url 'https://www.piwheels.org/simple'
COPY app /app
# Expose the port
EXPOSE 80
# Set the working directory
WORKDIR /app
# Run the flask server for the endpoints
CMD python -u app.py
Fix
I updated the Dockerfile as below.
FROM balenalib/raspberrypi3-debian-python:3.7
RUN apt update && apt install -y libjpeg62-turbo libopenjp2-7 libtiff5 libatlas-base-dev libgl1-mesa-glx
RUN pip install absl-py six protobuf wrapt gast astor termcolor keras_applications keras_preprocessing --no-deps
RUN pip install numpy==1.16 tensorflow==1.13.1 --extra-index-url 'https://www.piwheels.org/simple' --no-deps
RUN pip install flask pillow --index-url 'https://www.piwheels.org/simple'
# By default, we run manual image resizing to maintain parity with CVS webservice prediction results.
# If parity is not required, you can enable faster image resizing by uncommenting the following lines.
# RUN echo "deb http://security.debian.org/debian-security jessie/updates main" >> /etc/apt/sources.list & apt update -y
# RUN apt install -y zlib1g-dev libjpeg-dev gcc libglib2.0-bin libsm6 libxext6 libxrender1 libjasper-dev libpng16-16 libopenexr23 libgstreamer1.0-0 libavcodec58 libavformat58 libswscale5 libqtgui4 libqt4-test libqtcore4
# RUN pip install opencv-python --extra-index-url 'https://www.piwheels.org/simple'
COPY app /app
# Expose the port
EXPOSE 80
# Set the working directory
WORKDIR /app
# Run the flask server for the endpoints
CMD python -u app.py
Reference
I use the same base image from Custom Vision + Azure IoT Edge on a Raspberry Pi 3.
I also added "libgl1-mesa-glx" module as there is issue
Additional Info
README has section Build ARM container on x64 machine which says:
Export "ARM" Dockerfile from customvision.ai. Then build it using docker buildx command.
docker buildx build --platform linux/arm/v7 -t <your image name> --load .
I am using Windows 10 Docker Desktop v19.03.8.
I tested by running the command by enabling experimental feature which works fine, but I also try without enable experimental feature and simply run docker build which works just fine. So I am not 100% sure if we need buildx right now.
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