https://github.com/arfazrll/hand-gesture-recognition
A real-time hand gesture recognition system using Python, MediaPipe, and OpenCV for dynamic applications like finger counting and gesture based control using Neural Network
https://github.com/arfazrll/hand-gesture-recognition
computer-vision hand-gesture-recognition neural-networks opencv python
Last synced: 6 months ago
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A real-time hand gesture recognition system using Python, MediaPipe, and OpenCV for dynamic applications like finger counting and gesture based control using Neural Network
- Host: GitHub
- URL: https://github.com/arfazrll/hand-gesture-recognition
- Owner: Arfazrll
- License: mit
- Created: 2024-12-15T10:36:10.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-12-15T11:10:47.000Z (10 months ago)
- Last Synced: 2025-04-09T00:07:14.936Z (6 months ago)
- Topics: computer-vision, hand-gesture-recognition, neural-networks, opencv, python
- Language: Python
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🤖 Hand Gesture Recognition with Python
**Hand Gesture Recognition** is a real-time system that detects and recognizes hand gestures using **MediaPipe** and **OpenCV**. This project demonstrates the potential of computer vision for dynamic, interactive applications such as finger counting and gesture-based control.
---
## ✨ Key Features
- **🔍 Real-Time Hand Tracking**: Accurately detects and tracks hand landmarks in video streams.
- **✋ Gesture Recognition**: Counts the number of fingers raised dynamically.
- **🌐 Cross-Platform Compatibility**: Works on any system supporting Python, OpenCV, and MediaPipe.
---
## ⚙️ Requirements
- Python 3.7+
- OpenCV
- MediaPipe
---
## 🚀 Installation
### 1. Clone the Repository
```bash
git clone https://github.com/Arfazrll/Hand-Gesture-Recognition.git
cd your-repo-name
```
### 2. Create and Activate a Virtual Environment
```bash
python -m venv HandTracking-env
HandTracking-env\Scripts\Activate
```
### 3. Install Dependencies
```bash
pip install opencv-python mediapipe
```
---
## 📊 Usage
### 1. Run the Application
```bash
python HandsTrackingAI.py
```
### 2. Interact
- Allow camera access to start hand tracking.
- Observe the live feed with hand landmarks highlighted and the number of raised fingers printed in the console.
### 3. Exit
- Press `q` to close the application.
---
## 🔑 Code Highlights
### **Hand Tracking with MediaPipe**
The system leverages the MediaPipe Hands solution for robust hand detection:
```python
mp_hands = mp.solutions.hands
hands = mp_hands.Hands(
static_image_mode=False,
max_num_hands=2,
min_detection_confidence=0.5,
min_tracking_confidence=0.5
)
```
---
## 🌟 Future Enhancements
- Add recognition for specific gestures (e.g., thumbs up, peace sign).
- Support multiple hand tracking simultaneously.
- Optimize for mobile deployment using TensorFlow Lite.
---
## 🛠️ Technologies Used
- **🐍 Python**: Core programming language.
- **📦 MediaPipe**: For hand landmark detection.
- **📊 OpenCV**: For video processing and visualization.
---
## 🤝 Contributions
Feel free to fork this repository, submit pull requests, or open issues for suggestions and improvements. Thank You :)
---
## 🙏 Acknowledgments
- [MediaPipe by Google](https://mediapipe.dev/)
- [OpenCV Library](https://opencv.org/)