Introduction
The purpose of this app is to counting repetition for specific exercise that user
selected and track total number of repetition had been performed by user.
The app accept either a pre-record video clip or stream from camera. By these
two options, users is able to use pre-record video clip to count repetition for
their exercise or use stream from camera to achieve real-time exercise repetition
counting.
Motivation & Purpose
Counting exercise repetition required human intervention either self or other person
in order to properly track number of repetition of an exercise been performed. Person
who is responsible for counting repetition might miss or neglect count accidently or
due to human error that counting incompleted exercise into final sum of repetitions.
As result final total repetitions for an exercise is incorrect.
The app can be used as an assistant tool to help exerciser to tracked number of
exercise repetition had been performed. As result reduce human intervention and human
errors.
More
There are 2 primary methods involved to develop the app. First is deep learning model which
can track human body joints per frame. Second is signal processing that is used to determine
exercise repetition.
There are two options for video source:
1. Video clip : A pre-record video clip
2. Camera : Real-Time video stream from camera
Frameworks were used to build this app:
🧰 Tensorflow : Deep learning framework for the model
🧰 ONNX Runtime : Deep learning model inference on device
🧰 PyQt : Application interface
Note
❗️ Dynamic environment lighting could interfere and degrade the app
overall performance
❗️ The app target only one exerciser not multiple
❗️ The app tolrate certain level of human body outside of camera but
can decrease performance if too much
Support platform
🖥 MacOSX
🖥 Windows
🖥 Linux
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