GitGud-f/Delta
📦 Open Source ProjectGitGud-f
A lightweight, distilled depth estimation model optimized for near-real-time performance on edge devices.
Delta addresses the critical need for efficient spatial awareness in edge computing environments. While state-of-the-art models like DepthAnythingV2 offer exceptional accuracy, their heavy computational requirements often preclude them from running on mobile or embedded systems. Delta solves this by employing knowledge distillation, where the smaller student model learns to mimic the complex feature representations of the larger teacher model. This process retains high-fidelity depth maps while significantly reducing the parameter count and inference time. The project is implemented using Jupyter Notebooks, providing a clear workflow for training, distillation, and deployment. It is specifically optimized for scenarios where power efficiency and speed are paramount, such as robotics, augmented reality, and autonomous navigation on edge platforms.
💡Highlights
- ├─Distilled from DepthAnythingV2
- ├─Optimized for edge devices
- └─Near-real-time inference
🎯For
- ├─Computer Vision Engineers
- └─Edge AI Developers