/GymLytics

Visual Analytics of different exercises for humans 🏋️

Primary LanguagePythonMIT LicenseMIT

GymLytics 🏋️

Visual Analytics of different exercises for humans

Code Requirements 🦄

You can install Conda for python which resolves all the dependencies for machine learning.

pip install requirements.txt

Description 🏃

Exercise is any bodily activity that enhances or maintains physical fitness and overall health and wellness.

It is performed for various reasons, to aid growth and improve strength, preventing aging, developing muscles and the cardiovascular system, honing athletic skills, weight loss or maintenance, improving health and also for enjoyment. Many individuals choose to exercise outdoors where they can congregate in groups, socialize, and enhance well-being.

Python Implementation 👨‍🔬

Supported Exercise types

  • Pushup
  • Squat
  • Lunges
  • Shoulder Taps
  • Plank

Source

  • '0' for webcam
  • Any other source for a prerecorded video

If you face any problem, kindly raise an issue

Setup 🖥️

  1. First, record the exercise you want to perform analytics on; or you can setup your webcam so that it can stream your exercise in runtime.
  2. Select the type of exercise you want to perform. (Look above for the supported exercises)
  3. Run the GymLytics.py file with your current configuration

Execution 🐉

python3 GymLytics.py --type pushup --source resources/push_aks.mov

Results 📊

References 🔱

  • Ivan Grishchenko and Valentin Bazarevsky, Research Engineers, Google Research. Mediapipe by Google