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This project aims to develop a comprehensive fitness assessment and workout planning system to assist users in achieving their fitness goals effectively. The system will allow users to register and undergo an initial assessment to determine their fitness level and goals. Based on the assessment results, the system will recommend personalized workou

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X_Fit: Empowering fitness with AI.

X-Fit

Introduction

X_Fit is a Python-based fitness application designed to guide users towards their fitness goals. It provides personalized workout plans and tracks progress using a combination of assessments, rule-based recommendations, and machine learning models.

Features

Individualized Assessments: Assess fitness level, identify strengths and weaknesses, and recommend appropriate workout phases. OPT Model Implementation: Structures workout phases based on the Optimum Performance Training (OPT) model principles. Personalized Workouts: Generates customized workout plans tailored to individual goals, preferences, and fitness levels. Progress Tracking: Monitor your progress and make adjustments to the workout plan as needed. Variety of Training Types: Includes flexibility, core, balance, plyometric, SAQ (speed, agility, quickness), and resistance training. Installation

Clone the repository:

git clone https://github.com/your-username/X_Fit.git Use code with caution.

Install dependencies: pip install -r requirements.txt Use code with caution.

Run the main script: python src/main.py Use code with caution.

Follow the prompts: Provide your information and complete the initial assessment. Receive your personalized workout plan: Review the plan and start working towards your goals. Track your progress: Log your workouts and monitor your improvements over time.

Contributing

This project is currently not open source for contributions.

Documentation

The project's documentation is available within this README and the code comments. A more comprehensive documentation may be added in the future.

License

The project's license is not yet defined.

Acknowledgements

We thank the developers of the libraries used in this project, including pandas, scikit-learn, and pymongo.

Contact

For any questions or inquiries, please contact [your email address]

Support

For support or troubleshooting, please refer to the project's GitHub repository issues page.

Develop a graphical user interface for improved usability. Implement machine learning models for more advanced workout recommendations. Expand exercise database and offer a wider range of workout options. Integrate with wearable devices and fitness trackers for data collection. Changelog v1.0.0: Initial release with core functionalities.

About

This project aims to develop a comprehensive fitness assessment and workout planning system to assist users in achieving their fitness goals effectively. The system will allow users to register and undergo an initial assessment to determine their fitness level and goals. Based on the assessment results, the system will recommend personalized workou

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