https://github.com/yakupzengin/fitness-trainer-pose-estimation

An AI-powered fitness tracker that uses real-time pose estimation to count reps, monitor form, and provide instant feedback for exercises like squats, push-ups, and bicep curls. Designed for accuracy, motivation, and adaptability
https://github.com/yakupzengin/fitness-trainer-pose-estimation

artificial-intelligence computer-vision computer-vision-opencv computer-vision-tools fitness-app fitness-tracker fitness-trainer image-processing opencv pose-detection pose-estimation

Last synced: 17 days ago
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An AI-powered fitness tracker that uses real-time pose estimation to count reps, monitor form, and provide instant feedback for exercises like squats, push-ups, and bicep curls. Designed for accuracy, motivation, and adaptability

• Host: GitHub
• URL: https://github.com/yakupzengin/fitness-trainer-pose-estimation
• Owner: yakupzengin
• Created: 2024-08-28T11:46:57.000Z (3 months ago)
• Default Branch: master
• Last Pushed: 2024-09-08T00:14:56.000Z (2 months ago)
• Last Synced: 2024-10-10T17:42:18.919Z (about 1 month ago)
• Topics: artificial-intelligence, computer-vision, computer-vision-opencv, computer-vision-tools, fitness-app, fitness-tracker, fitness-trainer, image-processing, opencv, pose-detection, pose-estimation
• Language: Python
• Homepage:
• Size: 17.1 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# AI-Powered Fitness Trainer Pose Estimation







This project brings an AI-powered workout tracking system that leverages pose estimation technology to count and monitor exercises in real-time. It provides instant feedback on your form, tracks repetitions, and motivates you to push through each set. Whether you're doing bicep curls, squats, or push-ups, this system ensures that every rep is counted and your technique is refined.

## Key Features

- **Real-Time Exercise Counting**: Uses advanced pose estimation to track and count your reps with high precision.

- **Stage Monitoring**: Tracks the "up" and "down" phases of each exercise and keeps you updated on your progress.

- **Progress Bar**: Visual progress bar tracks your sets and reps, motivating you to finish your workout strong.

- **Gauge Meter**: Provides feedback on limb angles, displayed on a gauge meter for real-time form analysis.

- **Customizable**: Supports adding new exercise types and metrics to suit your workout needs.

## Installation

To install and run the **AI-Powered Fitness Trainer Pose Estimation** project, follow these steps:

### Step 1: Clone the Repository

Clone the repository from GitHub to your local machine using the following command:

```bash

git clone https://github.com/yakupzengin/fitness-trainer-pose-estimation.git

cd fitness-trainer-pose-estimation

```

### Step 2: Install Dependencies

Ensure you have Python installed. Then, install the necessary dependencies using the following command:

```bash

pip install -r requirements.txt

```

### Step 3: Run the Application

Once all dependencies are installed, run the main script to start tracking exercises:

```bash

python main.py

```

## Project Structure

Here’s an overview of the folders and files in this project, along with their purposes:

* **assets/** : This folder contains sounds assets used for the user interface and feedback displays.

* **data/**: Holds any datasets or configuration files needed for the pose estimation or workout tracking.

* **exercises/**: Contains individual scripts for tracking different exercises.

  * `hammer_curl.py`: Handles tracking and counting of hammer curl exercises.

  * `push_up.py`: Monitors push-up repetitions and form.

  * `squat.py`: Tracks squats, including form and repetition counting.

* **feedback/**:Handles the visual and informational feedback provided to the user during exercises.

  * `indicators.py`: Displays real-time feedback indicators, such as rep counts and form status.

  * `information.py`: Provides detailed feedback and stats about exercise performance.

  * `layout.py`: Manages how feedback is laid out on the screen, including progress bars and indicators.

* **output/**: Stores output data or video files that capture your workout sessions and provide detailed analysis.

* **pose_estimation/**: This folder contains the core logic for the pose estimation process.

  * `angle_calculation.py`: Responsible for calculating the angles of joints during exercises, providing real-time feedback on form.

  * `estimation.py`: Handles the pose estimation process using machine learning models to track your movements.

* **utils/**: Ekranda geri bildirim çizmek ve görüntülemek için yardımcı fonksiyonlar bulunur.

  * `draw_text_with_background.py`: Utility functions for drawing and displaying feedback on the screen.

    * `drawing_utils.py`: Helper functions for drawing elements on the video frame, such as progress bars and limb angles.

* **main.py**: The main script that initializes the entire system. It starts video capture, loads the pose estimation model, and processes your workout, providing real-time feedback and performance tracking.

## Future Improvements

As this project evolves, the following features are planned for future releases:

- **Advanced Exercise Recognition**: Expanding the system to support a wider range of exercises, including compound movements and stretches.

- **Performance Analytics**: Adding detailed post-workout analytics to help users track progress over time and improve their form.

- **Voice Feedback**: Implementing voice feedback for form corrections and motivational cues during exercises.

- **Mobile Support**: Developing a mobile version of the application for more convenience during workouts.

## Contributing

Contributions to improve this project are welcome! If you would like to contribute, please fork the repository and submit a pull request. You can also report any issues or suggest new features by opening an issue on GitHub.

1. Fork the repository.

2. Create a new branch.

3. Make your changes.

4. Submit a pull request.