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---
title: DeepGuard AI Face Authenticator
emoji: 🛡️
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 3.50.2
app_file: app.py
pinned: false
license: mit
tags:
- deepfake-detection
- computer-vision
- tensorflow
- mlops
short_description: Deepfake detection with 88% accuracy
---
# DeepGuard: AI Face Authenticator
A production-grade deep learning system for detecting AI-generated (deepfake) faces, built with a complete MLOps pipeline.
## Overview
DeepGuard leverages transfer learning with the Xception architecture to identify synthetic faces generated by GANs (Generative Adversarial Networks). The model achieves 88% accuracy with a 95% ROC-AUC score on StyleGAN-generated content.
## Model Performance
| Metric | Value |
|--------|-------|
| Test Accuracy | 88% |
| ROC-AUC Score | 95% |
| Training Dataset | 140,000 images |
| Architecture | XceptionTransfer |
| Input Resolution | 128x128 pixels |
## FFT Frequency Analysis Interpretation
The Fast Fourier Transform visualization provides forensic insight into image authenticity.
| Pattern | Interpretation |
|---------|----------------|
| Bright center spot | Normal low-frequency content (smooth areas) |
| Radiating spokes | Edge directions in the original image |
| Random noise distribution | Natural texture typical of real photographs |
| Grid or cross artifacts | Potential GAN fingerprint indicating synthetic generation |
Note: GAN artifacts in the frequency domain are subtle and serve as a supplementary forensic tool.
## Known Limitations
This model is trained on StyleGAN-generated faces. Detection accuracy may be reduced for:
- Images from diffusion models (Stable Diffusion, Midjourney, DALL-E)
- Non-face subjects or full-body photographs
- Heavily compressed or filtered images
## MLOps Pipeline
| Component | Technology |
|-----------|------------|
| Data Versioning | DVC |
| Experiment Tracking | MLflow + DagsHub |
| Model Training | TensorFlow / Keras |
| Deployment | Hugging Face Spaces |
## Repository
[GitHub: DeepGuard-MLOps-Pipeline](https://github.com/HarshTomar1234/DeepGuard-MLOps-Pipeline)
## License
MIT License
|