GESTURE CONTROL

For Part-1

Real-Time Hand Gesture Control UI

This Python application leverages your webcam to provide real-time control over a graphical user interface using hand gestures. It is built with OpenCV for video capture, MediaPipe for advanced hand tracking, and Tkinter for the UI.

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✨ Key Features

• Real-time Hand Tracking: Utilizes Google's MediaPipe to accurately detect 21 hand landmarks.
• Gesture-Based UI Control: Navigate menus, lock/unlock the interface, and trigger actions using intuitive hand poses.
• Swipe Navigation: Quickly move your hand left or right to switch between different UI menus.
• Customizable Security:
  • Lock the UI with a closed fist.
  • Set a custom multi-gesture sequence as your password to unlock.
• Custom Gesture Creator: Define, name, and save your own unique hand gestures to be recognized by the application.
• Rotation Invariance: Gesture detection remains robust even when your hand is tilted, thanks to coordinate normalization.
• Clean UI: A simple and modern interface built with Tkinter.

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🔧 Requirements

Make sure you have Python 3 installed. You will need the following libraries:

• opencv-python
• mediapipe
• Pillow (PIL)

⚙️ Installation

1. Clone the repository:

   git clone <your-repository-url>
   cd <your-repository-directory>

2. Install the required packages using pip:

   pip install opencv-python mediapipe Pillow

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▶️ How to Run

Simply execute the main.py script from your terminal:

For Part-2

Gesture Control for Your Computer

This Python script transforms your webcam into a powerful input device, allowing you to control your computer's mouse, clicks, scrolling, and window management using intuitive hand gestures. It's built with OpenCV for video processing and Google's MediaPipe for robust, real-time hand tracking.

The entire system is designed to be highly configurable through a simple config.ini file, so you can easily tune sensitivity and other parameters to your liking without touching the code.

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✨ Features

• Mouse Pointer Control: Move your cursor by moving your index finger.
• Clicking & Dragging: Pinch your thumb and index finger together to perform a left-click. Hold the pinch to drag and drop.
• Right-Click: Make a closed fist to perform a right-click.
• Scrolling: Use a "four fingers up" gesture to enter scroll mode. Move your hand up and down to scroll.
• Window Management:
  • Minimize: Show your index and middle fingers to minimize the active window.
  • Maximize: Make a "rock on" gesture (index and pinky up) to maximize the window.
• High Performance: Optimized for speed with a lightweight hand tracking model and configurable resolution.
• Customizable Settings: Easily adjust mouse sensitivity, scrolling speed, click distance, and smoothing via the config.ini file.
• Cross-Platform: Works on Windows, macOS, and Linux.

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🔧 Setup and Installation

Prerequisites

• Python 3.6 or newer
• A webcam

Installation Steps

1. Clone the Repository

   git clone <your-repository-url>
   cd <your-repository-directory>

2. Install Required Libraries Install all necessary Python packages using pip.

   pip install opencv-python mediapipe pyautogui numpy

3. Create a Configuration File Create a file named config.ini in the same directory as the script. Copy and paste the following content into it. You can adjust these values later to fine-tune performance.

   [Sensitivity]
   # Higher value means a smaller hand movement covers the whole screen. Must be >= 1.0
   mouse = 1.2
   # Controls how fast the page scrolls.
   scroll = 250.0
   
   [Clicking]
   # The distance between thumb and index finger to trigger a click (smaller is more sensitive).
   threshold = 0.045
   
   [Smoothing]
   # Controls mouse pointer smoothing. Value between 0.0 and 1.0.
   # Lower values = smoother but more lag. Higher values = more responsive but jittery.
   alpha = 0.25
   
   [Display]
   # Set to true to see the hand landmarks drawn on the camera feed for debugging.
   show_landmarks = true

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▶️ How to Run

Simply execute the main.py script from your terminal: