| --- | |
| title: Image Forgery Detector | |
| emoji: 🛡️ | |
| colorFrom: blue | |
| colorTo: red | |
| sdk: streamlit | |
| sdk_version: 1.35.0 | |
| python_version: 3.11 | |
| app_file: app.py | |
| pinned: false | |
| # Image Forgery Detector | |
| This application detects tampering in images using a Dual-Branch CNN architecture. | |
| ## How it works: | |
| 1. **RGB Branch:** Uses a pretrained ResNet50 to extract semantic features from the original image. | |
| 2. **ELA Branch:** Computes Error Level Analysis (ELA) to detect JPEG compression inconsistencies. | |
| 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](https://huggingface.co/spaces/usamaalam/image-forgery-detector) | |
| ## Repository: | |
| - **GitHub:** [https://github.com/salmanzaman777/image-forgery-detector](https://github.com/salmanzaman777/image-forgery-detector) | |
| - **Branch:** `usama` (latest with M3 model trained on CASIA v2) | |
| ## Documents: | |
| - [Project Report](documents/Project_Report_Digital_Image_Forgery_Detector.docx) | |