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--- |
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title: GeoSpatial-LiDAR-3D Point Cloud Visualizer |
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emoji: 🌎 |
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colorFrom: blue |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 6.2.0 |
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app_file: app.py |
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pinned: false |
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--- |
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# GeoSpatial-LiDAR-3D Point Cloud Visualizer |
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A web application for visualizing and analyzing LiDAR point cloud data in 3D. |
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## Features |
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- **LAS/LAZ Format Support**: Load and visualize LiDAR point cloud files |
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- **Multiple Color Modes**: RGB original colors, elevation-based colormaps, intensity visualization, and instance segmentation |
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- **Elevation Colormaps**: Choose from viridis, terrain, plasma, inferno, Spectral, and coolwarm |
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- **Instance Segmentation**: Visualize segmentation data with distinct colors for each instance |
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- **Interactive 3D Viewer**: Rotate, zoom, and pan through your point cloud data |
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- **Smart Subsampling**: Handle large datasets by limiting display points with customizable limits |
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- **Detailed Statistics**: View point counts, coordinate ranges, RGB presence, and segmentation information |
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- **Example Files**: Explore sample data with pre-loaded example point clouds |
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- **Public Sharing**: Generate and share live links to your visualizations |
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- **MCP Server Support**: Can run as an MCP (Model Context Protocol) server for integration with other tools and agents |
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## Supported Formats |
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| Format | Extension | Description | |
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|--------|-----------|-------------| |
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| LAS | `.las` | Standard uncompressed LiDAR format | |
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| LAZ | `.laz` | Compressed LiDAR format (recommended for large files) | |
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## Color Modes |
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- **RGB (Original)**: Display the original RGB colors from the point cloud file. Falls back to elevation colors if RGB data is unavailable |
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- **Instance Segmentation**: Color points based on their instance ID (PredInstance field). Assigns distinct colors to different instances |
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- **Elevation**: Color points by their height (Z coordinate) using your selected colormap |
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- **Intensity**: Display intensity values as grayscale, showing the reflectance properties of points |
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## Available Colormaps |
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The following colormaps are available for elevation and fallback visualization: |
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- **viridis**: Perceptually uniform colors that work well for colorblind viewers |
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- **terrain**: Classic elevation visualization with natural colors |
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- **plasma**: Warm colors from purple to yellow |
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- **inferno**: Dark to bright colors from black to yellow |
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- **Spectral**: Full rainbow spectrum for maximum contrast |
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- **coolwarm**: Cool to warm colors for intuitive interpretation |
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## Visualization Options |
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- **Max Points to Display**: Adjust the number of points displayed (50,000 to 2,000,000). Larger files are automatically subsampled for performance |
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- **Example Files**: Load pre-packaged sample files to quickly explore the visualizer's capabilities |
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## MCP Server Integration |
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This application can function as an MCP (Model Context Protocol) server, allowing it to be integrated with AI agents and other tools. |
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To enable MCP server mode: |
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1. **Via launch parameter:** |
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```python |
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demo.launch(mcp_server=True) |
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``` |
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2. **Via environment variable:** |
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```bash |
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GRADIO_MCP_SERVER=True python app.py |
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``` |
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When running as an MCP server, each API endpoint becomes available as an MCP tool that can be called by compatible clients and AI agents. |
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## Contributing |
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We welcome contributions to improve this project. You can help by: |
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- Adding support for additional file formats |
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- Improving visualization performance |
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- Enhancing the user interface |
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- Adding more colormaps or visualization modes |
