README.md

metadata

title: DeepShield Detection API
emoji: 🛡️
colorFrom: purple
colorTo: blue
sdk: docker
app_port: 7860
pinned: false

DeepShield — Deepfake Detection API

Flask backend for the DeepShield media-forensics dashboard. Classifies images, video, and audio as real or AI-generated using an ensemble of pretrained transformer models:

• Image/video: prithivMLmods/Deep-Fake-Detector-v2-Model (face-forgery ViT)
  • Organika/sdxl-detector (general diffusion-image detector), blended with pixel-level forensic heuristics.
• Audio: garystafford/wav2vec2-deepfake-voice-detector, blended with acoustic forensic heuristics.

API

• POST /api/detect — image/video upload, returns a deepfake report.
• POST /api/detect/audio — audio upload, returns a voice-deepfake report.
• GET /api/status/<task_id> — poll progress for async video/audio jobs.
• GET /api/history — recent analysis history.
• GET /api/health — health check.

Configuration

Set these as Space secrets/variables (Settings → Variables and secrets):

• FRONTEND_ORIGINS — comma-separated allowed CORS origins, e.g. your Netlify URL. Defaults to * if unset.
• HF_TOKEN — optional, avoids anonymous Hugging Face Hub rate limits.
• FIREBASE_CREDENTIALS_JSON — optional, enables persistent Firestore history/caching instead of the in-memory fallback.

This Space is built from the repository's backend/ directory — the Dockerfile pre-downloads all three models at build time so cold starts don't depend on the HF Hub being reachable.