## Inspiration

Mental health issues & being indoors due to the pandemic can lead to picking up yoga for better health, but with improper technique. We want to fix up improper yoga poses so our users can avoid injury, maximize benefits, and keep at their yoga routine.

## What it does

A personal instructor AI fixes up improper yoga poses in real-time by detecting and pointing out your incorrectly-angled joints, all through a phone camera. You can pick a specific pose to imitate, or go freestyle where the most familiar pose is automatically detected.

## How we built it

We built the UI using Figma. Then, using Android Studio, we integrated this UI and connected the camera to Google’s ML Kit Pose Detection API. We used popular YouTube videos as joint angle standards for proper poses and stored all of this data in Firebase. Leveraging this stored data to compare with real-time camera users’ positions, the mobile app notifies the user when matching joints between the standard and the user are angled too differently.

## Challenges we ran into

For some of us, this was our first time building an app from scratch so that was our biggest challenge, especially with such a short timeframe. Android Studio failed to work properly on all of our devices, and integrating the API into the application introduced many obstacles. While the API gives a great framework for applying itself to yoga poses, it’s ultimately up to the programmer to define each pose. Making sure we were defining poses correctly and accurately was a lot tougher than we’d initially thought.

## Accomplishments that we're proud of

We were happy about working on a project that could tackle a very relevant issue many of us are facing during this pandemic. Even at its most simple stage, YogAi has the potential to improve the well-being of users by simply encouraging them to stay active on their own. The app helps them get the most benefit from yoga, all without having to leave their home or pay for classes. Finally, getting Google’s Pose Detection API to work with our mobile application, and making the UI completely interactive were our biggest technical accomplishments.

## What we learned

How to build a mobile application from the ground up, which included working with Figma to create an aesthetically pleasing UI, integrating that with Android Studio, how to work with ML Kit, and the importance of research and collaboration.

## What's next for YogAi

We want to add more poses to the Firebase storage and user settings for a better user experience. Integrating a voice command to give the user some prompts on how to specifically improve each pose would be a specific feature we want to implement that could take YogAi to the next level.
## Inspiration

Our members of the group are interested in doing activities that require proper technique such as weightlifting and Taekwondo. However, it is difficult to tell if you're doing a specific activity incorrectly without someone more experienced helping out. Thus, the idea for Guru was formed as a way to give feedback to users on how to properly execute certain moves or poses without anyone else helping out.

## What it does

The program helps one improve their form for yoga or other related activities by recording a livestream of a person doing various yoga poses with a picture of the model as a reference, and compares it to the positions of the model. A percentage score is given as feedback on how closely the user emulates the model's pose.

## How we built it

We built the program by modifying CMU's Pose estimation software to recognize different model poses using opencv. Html, CSS, and Javascript were used to build the user interface and frontend of Guru. The backend, which processed the tracking software, was hosted in Flask, and the backend was connected to the frontend with Flask-Socket-io.

## Challenges we ran into

We had some challenges that we overcame such as learning how to connect the frontend interface with the backend using Flask-Socket-io. While working with Google Cloud, we temporarily lost access to the Google account we were using as we got 3 JSON credentials and logged onto 3 different PCs in a very short time as Google believed we were doing cryptocurrency mining, which related Google's terms of service.

## Accomplishments that we're proud of

We're proud to build an app that can help users improve their form while practicing for yoga or other similar based activities such as Taekwondo, while also learning how to work with unfamiliar technologies such as Flask-Socket-io.

## What we learned

We learned how to integrate the backend and frontend of the project using Flask-socket.io as this was our group's first time working with Flask-socket.io. We increased our knowledge of pose estimation technology using opencv and machine learning. We also learned how to use google-cloud to store our images of our reference model and skeletons so we could pull this data from anywhere.

## What's next for Guru

We hope to continue improving our tracking software to increase recognition of poses, and to continue adding support for more poses in different areas to help expand our possible user base.
## Inspiration

Amidst the hectic lives and pandemic struck world, mental health has taken a back seat. This thought gave birth to our inspiration of this web based app that would provide activities customised to a person’s mood that will help relax and rejuvenate.

## What it does

We planned to create a platform that could detect a users mood through facial recognition, recommends yoga poses to enlighten the mood and evaluates their correctness, helps user jot their thoughts in self care journal.

## How we built it

Frontend: HTML5, CSS(frameworks used:Tailwind,CSS),Javascript

Backend: Python,Javascript

Server side> Nodejs, Passport js
Database> MongoDB( for user login), MySQL(for mood based music recommendations)

## Challenges we ran into

Incooperating the open CV in our project was a challenge, but it was very rewarding once it all worked .
But since all of us being first time hacker and due to time constraints we couldn't deploy our website externally.

## Accomplishments that we're proud of

Mental health issues are the least addressed diseases even though medically they rank in top 5 chronic health conditions.
We at umang are proud to have taken notice of such an issue and help people realise their moods and cope up with stresses encountered in their daily lives. Through are app we hope to give people are better perspective as well as push them towards a more sound mind and body
We are really proud that we could create a website that could help break the stigma associated with mental health. It was an achievement that in this website includes so many features to help improving the user's mental health like making the user vibe to music curated just for their mood, engaging the user into physical activity like yoga to relax their mind and soul and helping them evaluate their yoga posture just by sitting at home with an AI instructor.
Furthermore, completing this within 24 hours was an achievement in itself since it was our first hackathon which was very fun and challenging.

## What we learned

We have learnt on how to implement open CV in projects. Another skill set we gained was on how to use Css Tailwind. Besides, we learned a lot about backend and databases and how to create shareable links and how to create to do lists.

## What's next for Umang

While the core functionality of our app is complete, it can of course be further improved .
1)We would like to add a chatbot which can be the user's guide/best friend and give advice to the user when in condition of mental distress.
2)We would also like to add a mood log which can keep a track of the user's daily mood and if a serious degradation of mental health is seen it can directly connect the user to medical helpers, therapist for proper treatement.
This lays grounds for further expansion of our website. Our spirits are up and the sky is our limit