Duino-Lidar
| Property | Value |
|---|---|
| Author | Duino |
| Model URL | https://huggingface.co/Duino/Duino-Lidar |
| Type | 3D Mapping System |
What is Duino-Lidar?
Duino-Lidar is an innovative end-to-end system for creating interactive 3D maps of indoor environments using mobile video footage. The system uniquely combines state-of-the-art monocular depth estimation using DPT models with semantic understanding powered by the PaLiGemma vision-language model, creating rich, context-aware 3D reconstructions.
Implementation Details
The system operates through a sophisticated pipeline that processes video input through multiple stages. It uses Python-based implementation with key dependencies including transformers, PyTorch, OpenCV, and Open3D. The core processing includes depth map generation, 3D point cloud reconstruction, and semantic labeling, all accessible through a user-friendly Gradio interface.
- Implements DPT-based depth estimation for accurate spatial mapping
- Utilizes PaLiGemma for semantic scene understanding
- Features a complete 3D reconstruction pipeline with point cloud generation
- Provides interactive visualization through Open3D and Plotly
Core Capabilities
- Mobile video processing and key frame extraction
- High-quality depth map generation from 2D images
- 3D point cloud reconstruction with color information
- Semantic scene labeling and enrichment
- Interactive 3D visualization through web interface
Frequently Asked Questions
Q: What makes this model unique?
Duino-Lidar stands out by combining vision-based depth estimation with semantic understanding in a single, accessible system. It's one of the few solutions that provides both geometric reconstruction and contextual scene interpretation through its integration of DPT and PaLiGemma models.
Q: What are the recommended use cases?
The system is ideal for indoor navigation, augmented reality applications, automated scene understanding, interior design, and robotics. It's particularly useful for creating semantically enriched 3D maps of indoor spaces without specialized hardware requirements.
