Mood Master

Description

Mood Master is a website that helps people with bipolar disorder learn more about their actions and emotions. It uses a video software to capture and analyze the facial expressions of the user and provide personalized feedback and suggestions. It also uses a message analysis tool to detect the tone and sentiment of the user’s texts and offer guidance and support.

My motivation for creating Mood Master was to help people with bipolar disorder learn more about their actions and emotions, and to use the power of technology to make this tool more accessible and engaging for the users.

I learned a lot from building this project, such as how to use facial detection and emotion classification algorithms, how to use message analysis tools, how to design a user-friendly and interactive interface, how to optimize the performance and efficiency of the website, and how to publish the website on the internet.

Table of Contents

• Setup
• Features
• Screenshots
• Frameworks
• License

Setup

Optimized for 1920 x 1080 resolution. No guarantee for other resolutions.

To run this project, follow these steps, must have python (3.11 preferred) and pip installed:

1. Use git clone https://github.com/AnSingh1/Mood-Master.git to clone the repo to your local machine
2. Run pip install -r requirements.txt to install the dependencies
3. Enter in the following fields in the .env file:

API_KEY: Enter your OpenAI api key
PATH_TO_TEXT: Replace the absolutePath with the absolute path to the Mood Master folder, make sure it is followed by /text/model
FIREBASE_URL: Enter your firebase url
FIREBASE_API_KEY: Enter your firebase api key, should be in a json format.

4. Run python app.py to start the server
5. Open http://localhost:5000 in your browser

Features

• Mood View: Mood View is a feature that uses a video software to capture and analyze the facial expressions of the user in real time or with a video/image upload. It uses a facial detection algorithm to detect the user’s face and a facial expression classification algorithm to classify the user’s facial expression.

demo_tracking.mp4

Classified video through Mood View

• MoodBot: MoodBot is an interactive chatbot that can provide personalized feedback and suggestions to the user. It uses the results from Mood View to help the user learn more about their actions and emotions. Powered by OpenAI.

• Mood Text: Mood Text is a feature that uses a message analysis tool to detect the tone and sentiment of the user’s texts and offer guidance and support. Powered by OpenAI.

• Login system: The login system allows the user to create an account and login to their account. It uses Fernet encryption and can withstand brute force attacks. Powered by Firebase.

Screenshots

! Main Page

App Page

Mood View Demo

Mood Text

About Page

Frameworks

Python: Backend Language

Flask: Backend Microframework

Firebase: Login System

Javascript: Frontend Language

Keras: Facial Detection and Emotion Classification

OpenCV: Image Manipulation

OpenAI: Chatbot functionality

NumPy: Encoding handling

Tensorflow: Facial Detection and Emotion Classification

jQuery: Frontend Element Manipulation

Jinja: Frontend to backend calls

Typekit: Custom Fonts

HTML: Frontend Structure

CSS: Frontend Styling

License

The Mood Master website is licensed under the MIT License. This means that you can use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the website, as long as you include the original license notice and a list of changes in any modified copies.