This project explores the effectiveness of modern computer vision models when trained exclusively on synthetic datasets generated using Unity's Perception package.
The foundation of this project follows Unity's comprehensive tutorial for synthetic data generation: https://docs.unity3d.com/Packages/com.unity.perception@1.0/manual/Tutorial/Phase1.html
To create a unique test case, I 3D scanned a wooden cobra sculpture using a high-resolution Creality Raptor 3D scanner, capturing intricate details for realistic synthetic training data.
The scanned cobra model was integrated into Unity scenes to automatically generate a comprehensive dataset of 10,000 synthetic images with varied lighting, backgrounds, and camera angles.
