Real-Time Hand Detection with MediaPipe

A real-time hand detection and hand landmark tracking application built using Python, OpenCV, and MediaPipe.

Overview

This project uses a webcam to detect and track hand landmarks in real time. The detected landmarks are displayed on the video feed, allowing visualization of hand movements and finger positions.

Features

• Real-time webcam hand detection
• Hand landmark tracking
• Multiple hand support
• Landmark connection visualization
• FPS (Frames Per Second) display
• Lightweight and efficient processing

Technologies Used

• Python
• OpenCV
• MediaPipe

Installation

Clone the repository

git clone https://github.com/devv2308/face_and_hand_detect_together.py.git
cd face_and_hand_detect_together.py

Install dependencies

pip install mediapipe opencv-python

Required Model

Place the following model file in the project directory:

hand_landmarker.task

Run the Project

python main.py

Project Structure

face_and_hand_detect_together.py/
│
├── main.py
├── hand_landmarker.task
└── README.md

Output

The application opens your webcam and:

• Detects hands in real time
• Draws hand landmarks
• Connects landmarks to form a hand skeleton
• Displays tracking results on the video stream

Future Improvements

• Gesture recognition
• Sign language detection
• Hand-controlled applications
• Virtual mouse control
• AI-powered hand action classification

Author

Devv2308

License

This project is available for educational and learning purposes.