## Inspiration

Many of us have a hard time preparing for interviews, presentations, and any other social situation. We wanted to sit down and have a real talk... with ourselves.

## What it does

The app will analyse your speech, hand gestures, and facial expressions and give you both real-time feedback as well as a complete rundown of your results after you're done.

## How We built it

We used Flask for the backend and used OpenCV, TensorFlow, and Google Cloud speech to text API to perform all of the background analyses. In the frontend, we used ReactJS and Formidable's Victory library to display real-time data visualisations.

## Challenges we ran into

We had some difficulties on the backend integrating both video and voice together using multi-threading. We also ran into some issues with populating real-time data into our dashboard to display the results correctly in real-time.

## Accomplishments that we're proud of

We were able to build a complete package that we believe is purposeful and gives users real feedback that is applicable to real life. We also managed to finish the app slightly ahead of schedule, giving us time to regroup and add some finishing touches.

## What we learned

We learned that planning ahead is very effective because we had a very smooth experience for a majority of the hackathon since we knew exactly what we had to do from the start.

## What's next for RealTalk

We'd like to transform the app into an actual service where people could log in and save their presentations so they can look at past recordings and results, and track their progress over time. We'd also like to implement a feature in the future where users could post their presentations online for real feedback from other users. Finally, we'd also like to re-implement the communication endpoints with websockets so we can push data directly to the client rather than spamming requests to the server.

![Image](https://i.imgur.com/aehDk3L.gif)

Tracks movement of hands and face to provide real-time analysis on expressions and body-language.

![Image](https://i.imgur.com/tZAM0sI.gif)
## Problem

In these times of isolation, many of us developers are stuck inside which makes it hard for us to work with our fellow peers. We also miss the times when we could just sit with our friends and collaborate to learn new programming concepts. But finding the motivation to do the same alone can be difficult.

## Solution

To solve this issue we have created an easy to connect, all in one platform where all you and your developer friends can come together to learn, code, and brainstorm together.

## About

Our platform provides a simple yet efficient User Experience with a straightforward and easy-to-use one-page interface.

We made it one page to have access to all the tools on one screen and transition between them easier.

We identify this page as a study room where users can collaborate and join with a simple URL.

Everything is Synced between users in real-time.

## Features

Our platform allows multiple users to enter one room and access tools like watching youtube tutorials, brainstorming on a drawable whiteboard, and code in our inbuilt browser IDE all in real-time. This platform makes collaboration between users seamless and also pushes them to become better developers.

## Technologies you used for both the front and back end

We use Node.js and Express the backend. On the front end, we use React. We use Socket.IO to establish bi-directional communication between them. We deployed the app using Docker and Google Kubernetes to automatically scale and balance loads.

## Challenges we ran into

A major challenge was collaborating effectively throughout the hackathon. A lot of the bugs we faced were solved through discussions. We realized communication was key for us to succeed in building our project under a time constraints. We ran into performance issues while syncing data between two clients where we were sending too much data or too many broadcast messages at the same time. We optimized the process significantly for smooth real-time interactions.

## What's next for Study Buddy

While we were working on this project, we came across several ideas that this could be a part of.
Our next step is to have each page categorized as an individual room where users can visit.
Adding more relevant tools, more tools, widgets, and expand on other work fields to increase our User demographic.
Include interface customizing options to allow User’s personalization of their rooms.

Try it live here: <http://35.203.169.42/>

Our hopeful product in the future: <https://www.figma.com/proto/zmYk6ah0dJK7yJmYZ5SZpm/nwHacks_2021?node-id=92%3A132&scaling=scale-down>

Thanks for checking us out!
## Introduction

Our innovative AI utilizes cutting-edge technology to analyze your facial expressions and speech through your webcam and microphone. Once you start interacting, the AI will adapt its responses according to your emotions and engagement level, providing a unique, immersive, and engaging conversational experience. It's not just a chat; it's a dynamic interaction crafted just for you to boost your confidence and mental health.

## Inspiration

As a group, we decided to address the issue of impostor syndrom and lack of confidence among students. We built the project with the intention of creating a unique way to boost self-esteem and emotional well-being by providing feedback for the user to improve based on.

## What it does

Our project uses both webcam analysis as well as chatbot interactions. Through these means, Fake:It aims to provide all students with valuable insight, support, and encouragement. Whether the user is struggling with self-doubt or anxiety; the main goal is to contribute to a student's well-being and personal growth.

## Technologies Employed

### Backend

#### [Flask](https://flask.palletsprojects.com/en/2.1.x/)

### Frontend

#### [React](https://reactjs.org/)

#### [Tailwind CSS](https://tailwindcss.com/)

#### [Vite](https://vitejs.dev/)

## Additional Integrations

### [TensorFlow Face API](https://www.tensorflow.org/)

### [OpenAI API](https://beta.openai.com/)

## Challenges we ran into

To begin, setting up local development environments with flask proved to take longer than expected. In addition, we faced trouble managing global React states once the project grew in complexity. Finally, our team faced trouble trying to implement a 'mood report' that would graph a users facial expressions over time after their session. Facing these challenges made this hackathon engaging and memorable.

## Accomplishments that we're proud of

We are very happy with our achievements including successfully tackling the issue of boosting self-confidence through the use of tracking various moods and making an effort to quantify them for our project, enhancing the user experience. These accomplishments reflect our commitment to providing a more empathetic and personalized platform for our users which includes tailored responses based on their moods to improve themselves. It's a significant step towards fostering emotional well-being and support within our community.

## What we learned

We gained technical expertise on challenges throughout the hackathon with tools like React, Flask, and RESTful api's. On top of this, being able to adapt and overcome certain challenges by using teamwork and collaboration is something we found to be paramount to this project's success.

## What's next for FakeIt

Next steps would be adding analytical features to the project, such as a way to display users' moods throughout their session. This could be compounded with an account system, where users could create accounts to track long term improvement in moods. Finally, adding more ai personalities the users can choose would boost engagement with our platform.