deep-learning/image-forgery-detector-v2

Image Forgery Detector

This application detects tampering in images using a Dual-Branch CNN architecture.

How it works:

1. 1.RGB Branch: Uses a pretrained ResNet50 to extract semantic features from the original image.
2. 2.ELA Branch: Computes Error Level Analysis (ELA) to detect JPEG compression inconsistencies.
3. 3.Fused Model: Combines features from both branches to make a final prediction.

Explainability:

The app uses Grad-CAM to visualize which parts of the image the model focused on when making its decision.

Deployment:

🚀 Live on Hugging Face Spaces: image-forgery-detector

Repository:

• —GitHub: https://github.com/salmanzaman777/image-forgery-detector
• —Branch: usama (latest with M3 model trained on CASIA v2)

Documents:

• —Project Report