Python AI Virtual Mouse Project
The AI Virtual Mouse project aims to develop a sophisticated and intuitive computer interaction system using artificial intelligence techniques. The primary objective is to create a virtual mouse that can emulate traditional mouse functionalities through gesture recognition and computer vision.
Key Features:
Gesture Recognition: Implement a robust gesture recognition system using computer vision techniques. This system should be capable of capturing hand movements and translating them into corresponding mouse actions such as cursor movement, clicks, and scrolls.
Machine Learning Integration: Train a machine learning model to recognize and adapt to various hand gestures. The model should be capable of learning and improving its accuracy over time based on user interactions.
Real-time Tracking: Utilize computer vision algorithms to enable real-time tracking of the user's hand movements. This ensures that the virtual mouse responds accurately and swiftly to user gestures.
Customizable Settings: Provide users with the ability to customize gestures and associated actions based on their preferences. This enhances the user experience and accommodates individual preferences for interaction.
Compatibility: Ensure compatibility with popular operating systems (Windows, macOS, Linux) and common applications to make the virtual mouse a versatile tool in various computing environments.
Accessibility Features: Implement accessibility features, such as voice commands or alternative input methods, to make the virtual mouse accessible to users with different needs and abilities.
User Interface: Design a user-friendly interface that allows users to easily configure settings, monitor the system's performance, and provide feedback for continuous improvement.
Technologies:
Python: The project will be primarily developed using the Python programming language, leveraging its extensive libraries and frameworks for computer vision and machine learning.
Computer Vision Libraries: Utilize libraries such as OpenCV to implement hand tracking and gesture recognition.
Machine Learning Frameworks: Incorporate machine learning frameworks like TensorFlow or PyTorch for training and deploying the gesture recognition model.
User Interface Development: Use GUI frameworks like Tkinter or PyQt to create an intuitive user interface for configuration and monitoring.
Expected Outcome:
The AI Virtual Mouse project aims to deliver a reliable and efficient alternative to traditional mice, enhancing user interaction with computers through advanced gesture recognition and artificial intelligence. The virtual mouse's adaptability and customization options will make it a versatile tool for users across different domains. The project will be open-source, encouraging collaboration and further development within the community.
HandTracking File Description :-
This Python script is designed to perform hand tracking and analysis using the MediaPipe library. It uses the OpenCV library for computer vision tasks, such as capturing video frames and displaying images. The primary purpose of the script is to track hand landmarks and provide information about the hand's position, fingers' status, and distance between fingers.
VirtualMouse File Description :-
This Python script uses the OpenCV library for computer vision, the autopy library for controlling the mouse, and a hand tracking module named HandTracking to perform actions based on hand gestures. The script essentially creates a virtual mouse control system using hand gestures.