Hand Tracking Project using Python

This project uses your webcam to detect and trace hand landmarks in real time using MediaPipe and OpenCV.

📦 Requirements

• Python 3.7+: The programming language used for this project.
• OpenCV (opencv-python): For capturing webcam video, image processing, and displaying results.
• MediaPipe (mediapipe): For detecting and tracking hand and face landmarks.

Install all dependencies with:

pip install -r requirements.txt

🛠 Installation

python -m venv venv
# Activate the virtual environment:<img width="1896" height="1037" alt="Screenshot 2025-07-14 111112" src="https://github.com/user-attachments/assets/83e9a6d3-723e-4f3a-bdd0-75cddee54092" />

# On PowerShell:
.\venv\Scripts\Activate.ps1
# On CMD:
venv\Scripts\activate.bat

pip install -r requirements.txt

Press Esc to exit.

📸 Features

• Live webcam detection: Real-time hand and face detection using your webcam.
• Finger count: Counts and displays the number of fingers shown, both on screen and in the terminal.
• Face detection notice: Alerts when a face is detected in the frame.
• Hand landmark tracing: Visualizes hand landmarks and connections for each detected hand.
• Extensible utilities: Placeholder for saving hand trace data for further analysis.

📦 Why these packages?

• OpenCV: Handles all video capture, frame manipulation, and display tasks.

• MediaPipe: Provides robust, real-time hand and face landmark

• <img width="1870" height="984" alt="Screenshot 2025-07-14 111055" src="https://github.com/ user-attachments/assets/9846ad0c-1c57-4584-9601-cef9eb28a6b3" />