| title: MFFT AI Image Detector API | |
| emoji: 🔍 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| license: mit | |
| # MFFT — Multi-Frequency Fusion Transformer, Detection API | |
| FastAPI inference server for AI-generated image detection. Three model | |
| variants are served and selectable per request. | |
| > **Demo checkpoints:** these are *pilot* models (1 training epoch on a 5K | |
| > subset) published for pipeline demonstration. Full-scale weights will | |
| > replace them after the training campaign completes. | |
| ## Endpoints | |
| - `GET /` — health | |
| - `GET /models` — available variants (`tiny` 372K, `base` 1.62M, `large` 6.30M) | |
| - `POST /predict?model=base` — multipart `file=<image>`; returns prediction, | |
| probabilities, anomaly heatmap (base64 PNG), frequency band contributions | |
| - `POST /predict/batch?model=large` — multiple files | |
| ## Example | |
| ```bash | |
| curl -X POST "https://mohsineli-mfft-api.hf.space/predict?model=large" \ | |
| -H "Authorization: Bearer free" \ | |
| -F "file=@image.jpg" | |
| ``` | |