Squatify

Inspiration

We all love working out and as there is an influx in the number of people who have begun going to the gym, we believe its crucial for newcomers to be able to prevent injury and learn good form when lifting weights.

What it does

Squatify tracks your movement using OpenCV and then uses the angles between certain joints to see if your technique is good or needs some improvement. We use a weighted average on certain joints to prioritize emphasis.

How we built it

We used Python, OpenCV, and MatPlotLib to create Squatify as these all made it incredibly easy to both track the user as well as create the data-driven decisions that we make.

Challenges we ran into

The main challenge that we ran into was the integration of the frontend as we were struggling with a real time video analysis that was embedded in the webpage.

Accomplishments that we're proud of

Overall we are most proud of successfully creating a robust system to record the angles between joints as well as output the data. Additionally, the clean and objective method of analysis that was used was critical.

What we learned

We learned an incredible amount about working under pressure, teamwork, and other soft skills of the sort. On the technical side, we learned about OpenCV, different Python frontend functionalities such as streamlit, and MatPlotLib.

What's next for Squatify

We would love for people to become interested in using science and data to improve their health and wellbeing. We truly think that Squatify is one small step towards acheiving the goal of leading to a more conscious society.