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| title: Patch-MFFT Tampering Forensics API | |
| emoji: 🛡️ | |
| colorFrom: red | |
| colorTo: indigo | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| license: mit | |
| # Patch-MFFT: Dual-Branch Radial Frequency Transformer API | |
| Production FastAPI forensics service engineered for localized generative inpainting, composite blackmail splicing, and style tampering detection. | |
| ## Dual-Task Forensics Features | |
| 1. **3-Way Holistic Forensic Triage**: | |
| - `[0] Authentic Camera Capture`: Optical photon shot noise & Bayer demosaicing consistency | |
| - `[1] Holistic Generative AI`: Entire-frame deconvolution checkerboard harmonics | |
| - `[2] Localized Spliced / Inpainted Tampering`: Boundary phase incoherencies & local inpainting artifacts | |
| 2. **Pixel-Wise Tampering Localization**: | |
| - Real-time dense anomaly probability mask $\hat{\\mathbf{M}} \in [0, 1]^{384 \\times 384}$ returned as a Base64-encoded PNG heatmap. | |
| 3. **Radial Annular Fourier Decomposition**: | |
| - Concentric Low, Mid, and High frequency band energy distribution analysis. | |
| ## Models Served | |
| - **Patch-MFFT Tiny**: 563K parameters (~4.2 ms GPU, 14.8 ms CPU, optimized for edge/mobile forensics) | |
| - **Patch-MFFT Base**: 3.28M parameters (97.84% accuracy, 81.00% mIoU localization score) | |
| - **Patch-MFFT Large**: 13.94M parameters (Maximum precision for subtle inpainting & blackmail composite detection) | |
| ## API Endpoints | |
| - `GET /` — Healthcheck and status of loaded model variants | |
| - `GET /models` — Specifications and parameter counts of all variants | |
| - `POST /predict?model=large` — Multi-task forensic analysis on uploaded image | |
| ```bash | |
| curl -X POST "https://mohsinelis-patch-mfft-api.hf.space/predict?model=large" \\ | |
| -F "file=@sample.jpg" | |
| ``` | |