CIFAKE – AI Generated Image Detection

Overview

CIFAKE is a deep learning-based web application that detects whether an uploaded image is Real or AI-Generated using a Convolutional Neural Network (CNN). The application is built with TensorFlow, Keras, and Streamlit, providing users with an intuitive interface for image classification.

Live Demo

🔗 https://cifake-ai-image-detection.onrender.com

Features

• Detects whether an image is Real or AI-Generated
• CNN-based binary image classification
• Interactive Streamlit web interface
• Displays prediction confidence
• Supports JPG, JPEG and PNG images

Technologies Used

• Python
• TensorFlow
• Keras
• Streamlit
• NumPy
• Pillow

Project Structure

CIFAKE/
│── app.py
│── predict.py
│── gradcam.py
│── requirements.txt
│── README.md
│
├── test_images/
│
├── home.png
├── prediction.png
└── gradcam.png

Installation

pip install -r requirements.txt

Run the Application

Command Line

python predict.py

Streamlit Web App

streamlit run app.py

Sample Output

Prediction: Real

Confidence: 89.86%

Future Improvements

• Grad-CAM heatmap visualization in the web interface
• Support for multiple AI image generators
• Improve CNN accuracy with advanced architectures
• Multi-class classification for different AI models