This is a collection of Jupyter notebooks that is intended to provide an introduction to OpenCV's Python interface. All notebooks were initially developed and released by Hannah, with some minors changes, code update for python3, and some other customizations provided by me.
The target audience is broad and includes
- People who have done computer science (maybe to graduate level) but who have not looked at OpenCV before
- People who are studying other subjects and want to play with computer vision
The notebooks are divided by the following lessons. I also provided the estimated time required to complete each lesson, a link to the source code, and the Google Colab link where anyone can use to follow the lessons and run the examples.
| Lesson | Estimated time needed | Source Code | Colab |
|---|---|---|---|
| OpenCV fundamentals | 20 min | Open | Open |
| Image stats and image processing | 20 min | Open | Open |
| Features in computer vision | 20 min | Open | Open |
| Cascade Classification | 20 min | Open | Open |
| Total | 80 min |
This project is licensed under the MIT License - see the LICENSE file for details.
And a special thanks to Raph Trajano for reviewing and fixing the materials.