- Member 1: [Melwin T Joshy] - [Cochin University of Science & Technology]
- Member 2: [Prince Parmar Singh] - [Cochin University of Science & Technology]
[An interactive web application that uses facial emotion recognition to gamify the process of sharing a meal with friends. The app captures the excitement of up to four friends before they eat a grilled chicken dish called Alfahm.
Features : Emotion-Based Scoring: Users upload photos, which are then analyzed by an AI model to calculate an "excitement score" based on facial expressions like happiness and surprise. The two friends with the highest scores are crowned the winners. Their photos are transformed into a winner cards.
Shareable Output: The final winner cards, complete with animated headshots and fun titles, are downloadable and optimized for sharing on social media]
In the digital age, a simple Alfahm meal has become a complex social event. The age-old dilemma of who gets the prized chest pieces has turned into a source of friendly-yet-fierce debate. Traditional methods—rock-paper-scissors, a quick arm wrestle, or a dramatic "who's hungrier" contest—are often inconclusive, leading to awkward silences and passive-aggressive "I'm fine with the leg piece, really" comments. This is more than a food-related argument; it's a critical challenge to the harmony of friendship, one that requires an unbiased, high-tech solution.]
[Alfahm Chest Piece Decider is the definitive, AI-powered answer to this non-existent, yet universally-felt, problem. Our application uses state-of-the-art emotion recognition to objectively measure the pre-meal excitement of each friend. By analyzing facial expressions, we settle the debate with pure data, not emotional pleas. The result isn't just a decision; it's a celebration, immortalized in a dynamic, shareable winner card. We turn a simple meal into a legendary competition, ensuring that the true champions of Alfahm are recognized and their victory is digitally preserved forever.]
For Software:
- [Python , Typescript]
- [FastAPI,React,Next.js]
- [DeepFace, rembg,PILLOW, OpenCV]
- [Github,VS Code]
For Hardware:
- [List main components]
- [List specifications]
- [List tools required]
For Software:
[Frontend: Navigate to the frontend directory in your terminal and run:
npm installBackend: Navigate to the backend directory, create a virtual environment, activate it, and install the required Python packages:
python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate
pip install -r requirements.txt]
[Frontend :
npm run devBackend:
uvicorn main:app --reload]
For Software: Winner Winner Chicken Dinner is a full-stack web application designed to add a fun, AI-powered twist to a social dining experience. The app leverages a modern tech stack to handle the entire user journey, from image upload to the final, shareable winner cards.
The frontend is built with Next.js and React, providing a responsive and dynamic user interface. It handles user interactions, image uploads via a clean and animated interface, and the display of the final results. The frontend communicates with the backend through a Next.js API route, which acts as a proxy, ensuring a smooth and secure data flow.
The backend is powered by FastAPI and is the core of the application's intelligence. It receives images from the frontend and uses a set of powerful Python libraries to perform complex tasks. It employs DeepFace for facial emotion recognition to calculate an excitement score for each user. It also uses Pillow and rembg to remove image backgrounds and composite the winners' animated headshots onto pre-designed football card templates. The backend's main function is to select the most excited players and generate the final winner cards, which are then served as static files to the frontend.
- [Melwin T Joshy ]: [Deepface Implementation and Score generation function]
- [Prince Parmar Singh]: [Frontend and Backend (UI and Endpoints )]
Made with ❤️ at TinkerHub Useless Projects
