## Inspiration

Due to a lot of work and family problems, People often forget to take care of their health and food. Common health problems people know a day's faces are BP, heart problems, and Diabetics. Most people face mental health problems, due to studies, jobs, or any other problems. This Project can help people find out their health problems.
It helps people in easy recycling of items, as they are divided into 12 different classes.
It will help people who do not have any knowledge of plants and predict if the plant is having any diseases or not.

## What it does

On the Garbage page, When we upload an image it classifies which kind of garbage it is. It helps people with easy recycling.
On the mental health page, When we answer some of the questions. It will predict If we are facing some kind of mental health issue.
The Health Page is divided into three parts. One page predicts if you are having heart disease or not. The second page predicts if you are having Diabetics or not. The third page predicts if you are having BP or not.
Covid 19 page classify if you are having covid or not
Plant\_Disease page predicts if a plant is having a disease or not.

## How we built it

I built it using streamlit and OpenCV.

## Challenges we ran into

Deploying the website to Heroku was very difficult because I generally deploy it. Most of this was new to us except for deep learning and ML so it was very difficult overall due to the time restraint. The overall logic and finding out how we should calculate everything was difficult to determine within the time limit. Overall, time was the biggest constraint.

## Accomplishments that we're proud of

## What we learned

Tensorflow, Streamlit, Python, HTML5, CSS3, Opencv, Machine learning, Deep learning, and using different python packages.

## What's next for Arogya
## Inspiration

Over 70 million people around the world use sign language as their native form of communication. 70 million voices who were unable to be fully recognized in today’s society. This disparity inspired our team to develop a program that will allow for real-time translation of sign language into a text display monitor. Allowing for more inclusivity among those who do not know sign language to be able to communicate with a new community by breaking down language barriers.

## What it does

It translates sign language into text in real-time processing.

## How we built it

We set the environment by installing different packages (Open cv, mediapipe, scikit-learn), and set a webcam.
-Data preparation: We collected data for our ML model by capturing a few sign language letters through the webcam that takes the whole image frame to collect it into different categories to classify the letters.
-Data processing: We use the media pipe computer vision inference to capture the hand gestures to localize the landmarks of your fingers.
-Train/ Test model: We trained our model to detect the matches between the trained images and hand landmarks captured in real time.

## Challenges we ran into

The challenges we ran into first began with our team struggling to come up with a topic to develop. Then we ran into the issue of developing a program to integrate our sign language detection code with the hardware due to our laptop lacking the ability to effectively process the magnitude of our code.

## Accomplishments that we're proud of

The accomplishment that we are most proud of is that we were able to implement hardware in our project as well as Machine Learning with a focus on computer vision.

## What we learned

At the beginning of our project, our team was inexperienced with developing machine learning coding. However, through our extensive research on machine learning, we were able to expand our knowledge in under 36 hrs to develop a fully working program.
## 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