https://github.com/chetnas8/emojify-deep-learning

Deep learning-based emoji generator using CNN and FER2013 dataset
https://github.com/chetnas8/emojify-deep-learning

computer-vision deep-learning emoji emotion-recognition facial-recognition fer2013 keras opencv real-time tensorflow

Last synced: 3 months ago
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Deep learning-based emoji generator using CNN and FER2013 dataset

• Host: GitHub
• URL: https://github.com/chetnas8/emojify-deep-learning
• Owner: Chetnas8
• License: mit
• Created: 2025-05-31T05:08:15.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-05-31T05:33:13.000Z (about 1 year ago)
• Last Synced: 2025-05-31T16:56:27.324Z (about 1 year ago)
• Topics: computer-vision, deep-learning, emoji, emotion-recognition, facial-recognition, fer2013, keras, opencv, real-time, tensorflow
• Homepage: https://ijirt.org/Article?manuscript=168243
• Size: 8.67 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# 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.