| Wanted to share a project I've been working on as a solo dev. It's an Android app that runs an optimized Vision Transformer model via ONNX Runtime to detect AI-generated images and videos directly on-device. The interesting part from a technical standpoint is the Quick Tile integration. It sits in Android's notification shade and captures whatever is on screen for analysis without leaving the app you're in. Inference is extremely fast on most modern devices. The model runs fully offline with no server calls for the analysis itself. I optimized it in ONNX format to keep the footprint small enough for mobile while maintaining decent accuracy. In the attached video I'm testing it on the viral Brad Pitt vs Tom Cruise fight generated with Seedance 2.0. Obviously no detection model is perfect, especially as generative models keep improving. But I think having something quick and accessible that runs locally on your phone is better than having nothing at all. The app is called AI Detector QuickTile Analysis free on the Play Store. Would love to hear what you think! [link] [comments] |
I built an Android app that runs a ViT model on-device via ONNX to detect AI-generated content in real time from the notification shade
Reddit r/LocalLLaMA / 3/26/2026
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Key Points
- A solo developer built an Android app that performs on-device AI-generated content detection using a Vision Transformer (ViT) model exported and optimized for ONNX Runtime.
- The app integrates with Android Quick Tiles in the notification shade to capture on-screen content for fast, real-time analysis without leaving the current app.
- Inference runs fully offline with no server calls, aiming to keep the model lightweight enough for mobile while retaining usable accuracy.
- The project is positioned as a practical stopgap because current detection models are imperfect and generative content quality is rapidly improving.
- The app, “AI Detector QuickTile Analysis,” is available for free on the Google Play Store and is shared for feedback.