Separate projects with their own code, results and setup instructions.
| Project | Code and guide | Stack | Status |
|---|---|---|---|
| Menu Detector | Open project | PyTorch, MobileNetV2, CLIP | 93.7% validation accuracy; 94.8% balanced accuracy |
| Webcam Face Detection | Open project | Python, OpenCV, Haar Cascades | Laptop webcam demo; also tested on a phone-displayed photo |
| Unity AR Face Tracking | Open project | C#, AR Foundation, ARCore | Original Android coursework tested; reconstructed scripts await device retest |
| Learning notebooks | Open notebooks | OpenCV, PyTorch, Matplotlib | Foundational exercises |
- Menu Detector: Open in Colab, then follow its README.
- Webcam detector: follow the local Python setup. A GitHub link opens source code, not your camera.
- Unity AR: follow the Android coursework setup; this is not a ready-to-install APK.
Unity AR face tracking and OpenCV face detection are separate implementations. Neither module identifies who a person is.
Jurabek (Juno) Khodiboev - developer based in Seoul.