Workout Verify

Authors: Patrick Tourniaire & Justin Regef

This is a project for automatically detecting if a person in a video is performing a squat or a pull-up somewhere in the video. Which is used to then give local feedback on the execution of the exercise(s) performed.

Setup

First you have to install the poetry dependencies and implicitly setup a venv with those deps.

$ pip install poetry
$ poetry install

Then you have to set8up MMPose to be able to load and infer on the pose estimation models.

$ poetry run mim install mmengine "mmcv>=2.0.1" "mmdet>=3.1.0" "mmpose>=1.1.0"

Running

After running the above setup, you should be able to simply provide an input video to the main.py file using the --input_video argument.

Note: the processing time for extracting the pose skeletons can take a long time, therefore, we also have some example data of us performing exercises under data/examples/* which has cached pickle files for the computed skeletons.

$ poetry run python main.py --input_video <path_to_video>

If you want to run based on a cached sequence of skeletons then you can simply run this command, and refer to a specific pickle file which you want to test.

$ poetry run python main.py --input_video cache/<video_name>.pickle # Without the _kpts_hands or _kpts_joints ending

Issues & Contact

If you experience any issues when running this project, feel free to contact us:

Justin Regef: [email protected]

Patrick Tourniaire: [email protected]

Side Note

This project relies on the pypipeline package which is to publicly available yet but was developed by Patrick Tourniaire, and is available in the deps/ folder as a wheel file. However, running poetry install will take care of this, but if you decide not to use poetry then it is important to also install this package.