Form Detection

Overview

Form Detection is an AI-powered application that utilizes MediaPipe and computer vision techniques to analyze and provide real-time feedback on exercise posture and form. The system helps users maintain correct posture during workouts, reducing the risk of injuries and improving training efficiency.

Features

• Real-time exercise form detection using MediaPipe
• Provides instant feedback on user posture and movement
• Uses computer vision to track body key points and angles
• Lightweight and efficient implementation for seamless performance
• Designed for fitness enthusiasts and athletes to optimize workouts

Requirements

To run this project, install the following dependencies:

• Python (v3.8+ recommended)
• Flask for backend development
• OpenCV for computer vision tasks
• MediaPipe for pose estimation
• TensorFlow (if required for AI-based enhancements)

Install Required Packages

Run the following command to install dependencies:

pip install flask opencv-python mediapipe tensorflow

Installation

1. Clone the repository:

   git clone https://github.com/SanyamWadhwa07/Form-Detection.git
   cd Form-Detection

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   python app.py

Usage

• Start the application and allow camera access.
• Perform exercises in front of the webcam.
• The system will detect your form and provide feedback.

Technologies Used

• Backend: Flask (Python)
• Computer Vision: OpenCV, MediaPipe
• Machine Learning: TensorFlow (if applicable)
• Frontend: HTML, CSS, JavaScript (for UI)

Future Enhancements

• Add support for more exercises and postures.
• Improve real-time feedback accuracy using deep learning.
• Develop a mobile-friendly version for better accessibility.