Jolly Audience - Post-Event Photo Generator

Capturing the essence of joyous moments is at the heart of every event. Jolly Audience, an innovative post-event photo generator, goes beyond traditional event photography to curate a vibrant collection of smiles and laughter. Imagine reliving the happiest moments from your event through a personalized gallery, showcasing the genuine expressions of your audience.

Transforming Events into Timeless Memories

Jolly Audience is not just a photo generator; it's a storyteller that encapsulates the spirit of your event. It employs advanced facial recognition technology and intelligent similarity checks to craft a unique narrative through carefully selected frames. The result? A gallery that radiates joy, inclusivity, and the unforgettable atmosphere of your event.

Features that Set Us Apart

1. Happy Face Detection

Utilizing cutting-edge Haar Cascade classifiers, Jolly Audience identifies not just faces but the radiant smiles that light up each frame of your event video.

2. Multiple Happy Faces

We believe in inclusivity. Jolly Audience extracts frames featuring a minimum number of happy faces, guaranteeing that every moment is a shared moment.

3. Effortless Web Interface

Uploading event videos has never been easier. Jolly Audience provides a user-friendly web interface, allowing you to effortlessly upload videos and receive a meticulously curated collection of happy frames.

Team members

Aaron Jacob [https://github.com/aaron-jacob]
Abhishek S [https://github.com/abhi-s-03]
Mathew V Kariath [https://github.com/MVK2803]
Rajath Thomas Kurian [https://github.com/rajath-tk]

Link to product walkthrough

https://drive.google.com/file/d/1azxYALrSyxMjSUFqh4edVg25WxYShu-w/view?usp=sharing

How it Works ?

Happy Face Detection: Utilizes Haar Cascade classifiers for face and smile detection to identify happy faces in each frame of a given video.
Multiple Happy Faces: Extracts frames with a minimum number of happy faces, enhancing the inclusivity of the generated photos.
Easy-to-Use Web Interface: The web interface allows you to upload event videos effortlessly and receive a collection of curated happy frames.

Libraries used

Flask: Backend web framework for Python - Version 3.0.0
React: Frontend JavaScript library for building user interfaces - Version 18.2.0
OpenCV: Computer vision library for facial detection - Version 4.8.1.78
concurrent.futures: Library for parallelizing tasks in Python

How to configure

Prerequisites

Before running the application, ensure you have the following installed:

Python 3.10.6
pip (Python package installer)

Installation

Clone the repository to your local machine:

git clone https://github.com/abhi-s-03/SHN-OpenCV

Navigate to the project directory:
```
cd SHN-OpenCV
```
Install the required Python dependencies:
```
pip install -r requirements.txt
```

How to Run

Run the Flask backend:
```
python app.py
```
This will start the backend server at http://localhost:5000.
Open a new terminal window, navigate to the frontend directory, and run the React frontend:
```
cd frontend
pnpm install
pnpm run dev
```

aaron-jacob/Jolly-Audience