This repository serves as a structured archive of everything I’ve been learning — from foundational techniques to modern deep learning-based approaches.
This repository is organized by topic. Each subdirectory focuses on a specific concept or technique and includes relevant code, explanations, and references.
The goal is to not just follow tutorials, but to:
- Understand why each technique works.
- Recreate important methods from scratch where possible.
- Document the learning process clearly and thoroughly.
This is a reference for both myself and others who want a hands-on approach to mastering computer vision.
- Python
- OpenCV
- NumPy
- PIL
- Matplotlib
- Jupyter Notebooks
- PyTorch or TensorFlow (for deep learning sections)
- Clone the repository.
- Navigate to any topic folder to get started.
- Each section contains well-commented scripts and, where relevant, Jupyter notebooks.
- Experiment with parameters, inputs, and variations to strengthen understanding.