Project Info

FlowState

Inspiration

As computer science students we are often busy hunched over our computers making our ideas into projects. Its really helpful to take a break and stretch every once in a while, so we create this application to promote yoga and stretching.

What it does

Users can select which pose they want to perform on our app, and the camera will open up and our awesome and cool mascot will indicate how accurate the user's pose is. The user will also receive helpful advice on how to perform the pose they chose.

How we built it

We used OpenCV and Mediapipe to capture the camera input and obtain the coordinates of a person in front of the camera. We then created helper functions to help us calcuate the angles between 8 major joints in the body. We used images of people doing the pose to help us find the ideal angles, and we created more helper functions to calculate the accuracy of the pose given the coordinates of a person.

Challenges we ran into

We had some issues with calling the LLM we chose for our advice. We also had some issues with merge conflicts and communication between frontend and backend, but we're glad we were able to resolve those in the end!

Accomplishments we're proud of

We are proud of how we were able to connect the dataflow from the backend to an image in the frontend as our first project with computer vision. We were also happy to create actionable health feedback from camera input.

What we learned

We learned a lot more about how OpenCV and Mediapipe worked, and also more about how to integrate frontend and backend together.

What's next

We would like to be able to add more yoga poses to our app, and we would also like to be able for users to create a guided yoga routine, and to be able to save the routines.

This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

Then, run the fastAPI server:

source /Users/dir-name/yoga-app/venv/bin/activate
python -m uvicorn main:app --host 127.0.0.1 --port 8000

It opens on http://localhost:8000.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.

Learn More

To learn more about Next.js, take a look at the following resources:

Next.js Documentation - learn about Next.js features and API.
Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.

Analysis

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Technology

Found in codeClaimed only

CSSIn code
FastAPIIn code
FlaskIn code
HTMLIn code
Hugging FaceIn code
Next.jsIn code
OpenAIIn code
PythonIn code
PyTorchIn code
ReactIn code
Tailwind CSSIn code
TypeScriptIn code
Google GeminiClaimed

12 of 13 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

64 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.