In today's world, a healthy lifestyle is becoming increasingly relevant, and with it, interest in sports activities is growing. However, gaining experience and knowledge in this field can be a challenging task for many people. In this context, the application of artificial intelligence (AI) in the sports sector becomes a key element of successful training, analysis, and development of sports teams and individual athletes.
This repository provides a set of tools to help you improve your technique for the following exercises: front squats, wide-arm push-ups, biceps push-ups, reverse push-ups. This intelligent assistant analyzes your technique in real time, evaluates your posture using an AI model (yolov8-pose) and gives you feedback on your form.
A counter for correctly completed sets and so-called attempts to perform the exercise correctly has also been added. This will help you better understand your exercise statistics.
- Clone repository.
git clone https://github.com/KKopilka/AI-FinessTrainer.git
- Install the requirements.
pip install -r requirements.txt
- Run the script.
python manual.py <exercise_name>
- It is possible to run the project with streamlit.
streamlit run app/live.py
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Train a model for human pose estimation.
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Integration of the model into the project, processing of key points.
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Add exercises for major muscle groups.
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Add a counter for approaches and attempts.
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Run locally or through a browser (streamlit).
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Launching via Docker.
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Convert the project to an .exe file.
This project is not a fully finished version, so it can still be finalized.
Here are some ideas on how to improve this project are as follows:
- Add more exercises.
- Add more statistics to the program.
- Add a web/mobile app.
- Add sound accompaniment.