README.md

metadata

title: MFFT AI Image Detector API
emoji: 🛡️
colorFrom: indigo
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
license: mit

MFFT: Multi-Frequency Fusion Transformer — Production Detection API

FastAPI inference server for AI-generated image and deepfake detection based on radial Fourier frequency sub-band decomposition and Frequency-Guided Attention (FGA).

Three verified production models trained for 20 epochs on 120,000 images are served concurrently:

• MFFT-Tiny (372K params, 1.49 MB FP16): 98.59% accuracy, 99.88% AUC-ROC (~3.2 ms latency)
• MFFT-Base (1.62M params, 6.49 MB FP16): 98.37% accuracy, 99.87% AUC-ROC (5-seed replication average: 98.58% ± 0.13%)
• MFFT-Large (6.30M params, 25.21 MB FP16): 98.11% accuracy, 99.68% AUC-ROC (Default production profile)

Endpoints

• GET / — Healthcheck and loaded model status
• GET /models — Available model profiles and specifications
• POST /predict?model=large — Single image forensic analysis with anomaly heatmap (base64 PNG) and radial Fourier frequency band breakdown
• POST /predict/batch?model=large — Multi-image batch inference

Example Usage

curl -X POST "https://mohsinelis-mfft-api.hf.space/predict?model=large" \
  -H "Authorization: Bearer free" \
  -F "file=@image.jpg"