Docker image xeus-cling-opencv-xwidgets

A docker image with a preinstalled set of libraries, frameworks and applications with an emphasis on Computer Vision and Machine Learning specifically in C++. The common use cases are research and experimenting, creating tutorials and presentations.

Key features

It allows for the use of OpenCV 4.5.5 from C++ inside the Jupyter notebook. The UI components from xwidgets, help the creation of an even more interactive experience.

List of the more important components

• Jupyter Notebook/Lab
• Miniconda
• OpenCV 4.5.5
• Xeus-Cling
• xwidgets

Installation

• Using directly the pre-built Docker image
  • Install docker
  • docker run -it -v <Local directory to be mounted as a workspace>:/workspace -w /workspace -p 8888:8888 ssarnev/xeus-cling-opencv-xwidgets:opencv_4.5.5
• Building the image locally
  • Install docker
  • Open Git Bash
  • git clone https://github.com/ssarnev/xeus-cling-opencv-xwidgets.git <directory of your choice>
  • cd <directory of your choice>/xeus-cling-opencv-xwidgets
  • bash build.sh
  • docker run -it -v <Local directory to be mounted as a workspace>:/workspace -w /workspace -p 8888:8888 ssarnev/xeus-cling-opencv-xwidgets:opencv_4.5.5

Try it on Binder without installing anything

Demo code

• An interactive Discrete Fourier Transform image filtering
  • Directories where it can be found
    • /workspace/demo (Only in case there is no volume mounted to the workspace directory)
    • /content/demo
  • Open and run Interactive_DFT_demo.ipynb

Acknowledgement

Inspired and based on the following

• https://github.com/Seachaos/docker-python-xeus-cling
• https://github.com/Seachaos/opencv-cpp-for-xeus-cling
• https://github.com/czeni/opencv-video-minimal

References

• Xeus-Cling: Run C++ code in Jupyter Notebook, Vishwesh Shrimali, LearnOpenCV
• Miniconda
• Jupyter Notebook
• Xeus-Cling
• Cling
• xwidgets

License

Licensed under MIT license, see LICENSE file.