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Computer Vision: Machine understanding of images & video—object detection, gesture tracking, emotion recognition, etc.
A portfolio of Python / OpenCV / MediaPipe projects with live demos and clean code.
| Project | Description | Live Demo | Tech / Skills |
|---|---|---|---|
| Invisible Cloak | Use color segmentation to create Harry Potter-style cloak effect. | Streamlit Demo | OpenCV, HSV masks, real-time video |
| Finger Counter | Count number of fingers shown in camera feed. | Streamlit Demo | Contour detection, convexity defects |
| Hand Tracking / Gesture Recognition | Track complex hand movements and gestures. | Demo | MediaPipe Hands, gesture mapping |
| Face & Emotion Detector | Detect face, classify basic emotions (happy, sad, neutral, etc.). | Demo | Haar cascades or DNN, small emotion model |
To run the projects locally, install the following dependencies:
- Python 3.8+
- Libraries:
- opencv-python
- numpy
- mediapipe (for hand tracking, optional)
- streamlit (for web apps)
- torch / tensorflow (for emotion recognition models)
- scikit-learn
- matplotlib (for visualizations)
git clone https://github.com/MUKARRAM-ONE/Computer-Vision.git
cd Computer-Vision
pip install -r requirements.txt
---Install all requirements with:
pip install -r requirements.txt