Face-Meet-master.zip

# Face Meet Are anonymous interruptions in your video meeting driving you crazy? Do you need a security solution that lets real people attend your meeting? Do not worry; we have you covered. We now present **Face Meet**. A GenZ video calling platform called **Face Meet** provides 2FA (Two Factor Authentication), which consists of **face recognition** and **email password verification** technology. Only those who have registered are allowed to join meetings after a successful image verification. Therefore, before setting up a meet, a user must register on our site with an email address, a password, and a photo. Users who want to attend the meeting must complete the registration process as well. To ensure that a real individual really attended the meet, a face verification is done after registration. Build with help of **Face Recognition Library** in Python, it gives an accuracy of **99.38%.** Want to host or join a meet, just register and you are good to go. ## Demo [Video Link](https://youtu.be/DrJIoRPJRB0) ## Meet Glance <img src="https://i.ibb.co/N1C2q8c/HomePage.png" alt="HomePage" border="0" > | Register Page | Login Page | | :---------------------: | :----------------------: | | <img src="https://i.ibb.co/2thThWB/Register.png" alt="Register" border="0" width=400> | <img src="https://i.ibb.co/8MGBTn5/login.png" alt="login" border="0" width=400> | | Face Verification | Video Meet | | :--------------------: | :---------------------: | | <img src="https://i.ibb.co/hdmtPfq/Faa.png" alt="Faa" border="0" width=400> | <img src="https://i.ibb.co/xSTzc1v/meet.png" alt="meet" border="0" width=400> | ## Table of Contents - [Features](#features) - [TechStack](#techstack) - [Installation](#installation) - [Appendix](#appendix) - [APIReference](#apireference) - [Documentation](#documentation) - [Optimizations](#optimizations) ## Features - **Video conferencing** - Hassle free group calls - Total capacity of 50+ users. - In Meet messaging - Screen Sharing - **Security Control (X-factor / Flagship)** - 2FA with Email Verification and Face Recogniton. - **Cloud Storage** - Implemented cloud storage for data, no need for local DB. - Grid FS for storing large size image. - **PWA** - **Download** and add to homescreen/desktop for ease of access. - Smooth installation, native-like behaviour and access to device hardware. - **Authentication** - Login using gmail account. - Auth check in meet to **prevent unauthorized** users from entering. ## TechStack  1. Front End / Client Side - ReactJS - Bootstrap - CSS and other components - React Webcam - Capture User's Image 2. BackEnd Server: - For Face Recognition - Face Recognition Library - calculate encodings - Open CV - Compare Image on basis of encodings. - For video calling - Twilio Video API - Create Real-Time Video App - Twilio Cloud - Connect room participants. 3. Data Management (Databases): - MongoDB Atlas - Data management and user details - Grid FS - Storing image with base64 data. ## Installation ### Pre-Requisites: 1. Install Git Version Control [ https://git-scm.com/ ] 2. Install Python Latest Version [ https://www.python.org/downloads/ ] 3. Install Pip (Package Manager) [ https://pip.pypa.io/en/stable/installing/ ] 4. Install MongoDB Compass and connect it to localhost **27017** [ Atlas Connection is quite slow and may not work everytime ] - Uncomment the following code in app.py to change the connection as per requirement. <img src="https://user-images.githubusercontent.com/85401522/183743315-a766d3a9-f7ff-4797-a162-68849f134134.png" alt="Faa" border="0" width=400> ### Clone the project: ```bash git clone https://github.com/rajprem4214/Face-Meet.git ``` Go to the project directory ```bash cd Face-Meet ``` **Backend Server:** Go to backend folder ```bash cd backend ``` #### Create a Virtual Environment and Activate: Install Virtual Environment ```bash pip install virtualenv ``` Create Virtual Environment: ```bash virtualenv venv ``` Go to venv folder and Activate virtual enviroment ```bash cd venv ``` Run the following command ```bash .\Scripts\activate.ps1 ``` Go back to backend folder ```bash cd .. ``` Install Requirements from 'requirements.txt' ```bash pip install -r requirements.txt ``` Start the backend server ```bash flask run ``` **Frontend Server:** Go to frontend folder ```bash cd frontend ``` Install all dependencies ```bash npm install ``` Start frontend server ```bash npm run start ``` #### Local Url for Server: - Frontend is running on http://localhost:3000 - Backend is running on http://127.0.0.1:5000 ## Environment Variables To run this project, you will need to add the following environment variables to your .env file ``` TWILIO_ACCOUNT_SID=AC612f9ab098d697e6d572725234130052 TWILIO_API_KEY_SID=SKf1a116bd7f1c50a6e6988e875c9b85a2 TWILIO_API_KEY_SECRET=YPe9sOZP25xzUxnMd6xLXBKfigNmTJRC ``` ## Appendix ### MongoDB Cloud Credentials: ``` Database Name: images Collections Name: image ``` ## APIReference #### Verify User Image: ```http POST /api ``` #### Register User: ```http GET POST /create ``` #### Create or join room: ```http POST /join-room ``` ## Documentation [PPT Documentation](https://1drv.ms/p/s!AhTIcIxUOCw5gyXOWfkauH9saktA?e=gUVzT3) <img src="https://i.ibb.co/1z41N4b/regppt.png" alt="regppt" border="0"> <img src="https://i.ibb.co/wc4nZXD/logppt.png" alt="logppt" border="0"> <img src="https://i.ibb.co/t3JYwNk/twilppt.png" alt="twilppt" border="0"> ## Optimizations - Reduced time in image encoding by not taking encodings of whole image DB. - Instead, retrieve image id during login and match that particular image with cam image. ## Future Aspects - Add user id in URLs for each user for more authentication. - Store image in IPFS distributed storage for privacy concerns. ## Authors - [Prem Raj](https://www.github.com/rajprem4214)