Chrome 扩展 image-reality-check:离线检测 AI 生成图像与美颜滤镜
Timbered-manse640/image-reality-check
开源 Chrome 扩展 image-reality-check 可在浏览器本地检测 AI 生成图像、美颜滤镜与修图痕迹,全程离线、零网络请求。它通过频域、噪声、色彩、纹理、对称性、边缘 6 个维度识别 AI 图像,并用 ELA 热力图标记篡改区域,借助 BlazeFace 分析面部皮肤纹理方差判断美颜滤镜,同时自动跳过截图。
Chrome extension that automatically detects AI-generated images, beauty filters, and photo manipulation — all offline, all client-side.
Features
- AI-Generated Image Detection — 6-dimension analysis (frequency spectrum, noise, color, texture, symmetry, edges)
- Error Level Analysis (ELA) — Colored heatmap revealing tampered or edited regions
- Face Detection — BlazeFace-powered face detection + skin smoothness analysis
- Beauty Filter Detection — Detects skin smoothing filters via texture variance
- Screenshot Detection — Automatically skips screenshots and non-photo images
- Auto-Detection — Scans all images on any webpage with progress indicator
- Stamp Results — Marks suspicious images directly on the page (AI / Beauty Filter / Edited)
- Face-Only Mode — Only analyze images containing faces (default ON)
- Right-Click Analysis — Deep analysis of any image via context menu
- Settings Toggle — Enable/disable auto-detection and face-only mode
Privacy
All processing happens locally in your browser. No images are uploaded. No data is sent to any server. Zero network requests. Your images never leave your device.
Installation
Developer Mode
- Download the latest release and unzip
- Open
chrome://extensions/in Chrome - Enable Developer mode (top right)
- Click Load unpacked and select the unzipped directory
Chrome Web Store
Coming soon
How It Works
ELA (Error Level Analysis)
Re-compresses the image at a known quality level and compares the difference. Edited regions show higher error levels, visualized as a colored heatmap.
Skin Smoothness Detection
Uses BlazeFace to detect faces, then analyzes skin texture variance in face regions (forehead, cheeks, chin). Unnaturally low variance indicates beauty filter usage.
AI Generation Detection
Scores images across 6 dimensions:
- Frequency Spectrum — AI images have steeper high-frequency falloff
- Noise Uniformity — AI images have unnaturally uniform noise distribution
- Color Distribution — AI images have smoother color histograms
- Texture Regularity — AI images have more regular LBP texture patterns
- Facial Symmetry — AI-generated faces tend to be more symmetrical
- Edge Coherence — Detects AI-typical edge artifacts
Screenshot Detection
Identifies screenshots via flat color block ratio, color diversity, and noise level. Screenshots are automatically skipped in auto-detection mode.
Tech Stack
- Manifest V3 — Modern Chrome extension architecture
- TensorFlow.js — Client-side ML inference
- BlazeFace — Real-time face detection model
- Canvas API — Image pixel manipulation and analysis
- Pure JavaScript — No build step, no frameworks
Contributing
Contributions are welcome!
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
MIT License © 2026
来源:GitHub · github.com