This repository provides a structured collection of Jupyter notebooks designed to teach the core concepts of Computer Vision through practical, easy-to-follow Python examples.
All requirements can be found in the requirements.txt file. This also includes the installation of Jupyter Notebook and OpenCV.
You can install them using pip:
pip install -r requirements.txtThe notebooks are organized into chapters. Each chapter focuses on a specific topic from image processing basics to advanced subjects like stereoscopic vision and 3D reconstruction.
To execute the notebooks, you can use Jupyter Notebook or JupyterLab. Start Jupyter by running:
python -m jupyter notebookThen navigate to the desired notebook and start learning!
⚠️ WarningThis work was carried out in 2020, which means several dependencies rely on older versions.
Some functions may now have newer or more efficient alternatives.
However, since the goal of this material is to teach fundamental theory, the underlying mathematics has not changed.
The explanations and concepts remain fully valid for learning computer vision.