A collection of computer vision tasks and experiments implemented in Python, exploring classical image-processing and feature-detection techniques through hands-on Jupyter notebooks.
This repository brings together several small, self-contained computer vision projects. Each explores a fundamental technique — from corner detection to image filtering and feature engineering — with a focus on understanding the underlying methods rather than relying on high-level abstractions.
| Item | Description |
|---|---|
Harris_Corner_Detector/ |
Implementation of the Harris corner detection algorithm for identifying interest points in images. |
Image_Filtering |
Experiments with image convolution and filtering techniques. |
Quadratic_Features.ipynb |
Notebook demonstrating quadratic feature construction for image data. |
Self_Learnings |
Notes and exploratory work capturing key takeaways. |
- Python 3.x
- Jupyter Notebook
- Common scientific Python libraries (e.g., NumPy, OpenCV, Matplotlib)
Install the typical dependencies with:
pip install numpy opencv-python matplotlib jupyterClone the repository and launch Jupyter to explore the notebooks:
git clone https://github.com/GreenMouth/computer-vision-tasks.git
cd computer-vision-tasks
jupyter notebookNo license has been specified for this repository. Please contact the author before reuse.