Emojify: Create Your Own Emoji with Deep Learning

Our project focuses on real-time human emotion detection using deep learning and maps facial expressions to emojis for intuitive feedback.

✨ Project Highlights

• Trained a Convolutional Neural Network (CNN) on the FER2013 dataset to classify facial expressions into seven categories: angry, disgust, fear, happy, neutral, sad, and surprise.
• Developed a prototype that captures real-time webcam video, detects faces, classifies their emotions, and maps them to emojis.
• Explored the applications of emojis in digital communication, marketing, and sentiment analysis.
• Our research was accepted by the International Journal of Scientific & Engineering Research (IJSER).

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🧩 Key Features

✅ Real-time webcam face detection using OpenCV
✅ CNN-based emotion classification using TensorFlow/Keras
✅ Emoji mapping and display
✅ Detailed documentation of methodology, dataset, and design

🚧 Current Status

• Published.