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metadata
title: GeoSpatial-LiDAR-3D Point Cloud Visualizer
emoji: 🌎
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false

GeoSpatial-LiDAR-3D Point Cloud Visualizer

A web application for visualizing and analyzing LiDAR point cloud data in 3D.

Python Gradio License

Features

  • LAS/LAZ Format Support: Load and visualize LiDAR point cloud files
  • Multiple Color Modes: RGB original colors, elevation-based colormaps, intensity visualization, and instance segmentation
  • Elevation Colormaps: Choose from viridis, terrain, plasma, inferno, Spectral, and coolwarm
  • Instance Segmentation: Visualize segmentation data with distinct colors for each instance
  • Interactive 3D Viewer: Rotate, zoom, and pan through your point cloud data
  • Smart Subsampling: Handle large datasets by limiting display points with customizable limits
  • Detailed Statistics: View point counts, coordinate ranges, RGB presence, and segmentation information
  • Example Files: Explore sample data with pre-loaded example point clouds
  • Public Sharing: Generate and share live links to your visualizations
  • MCP Server Support: Can run as an MCP (Model Context Protocol) server for integration with other tools and agents

Supported Formats

Format Extension Description
LAS .las Standard uncompressed LiDAR format
LAZ .laz Compressed LiDAR format (recommended for large files)

Color Modes

  • RGB (Original): Display the original RGB colors from the point cloud file. Falls back to elevation colors if RGB data is unavailable
  • Instance Segmentation: Color points based on their instance ID (PredInstance field). Assigns distinct colors to different instances
  • Elevation: Color points by their height (Z coordinate) using your selected colormap
  • Intensity: Display intensity values as grayscale, showing the reflectance properties of points

Available Colormaps

The following colormaps are available for elevation and fallback visualization:

  • viridis: Perceptually uniform colors that work well for colorblind viewers
  • terrain: Classic elevation visualization with natural colors
  • plasma: Warm colors from purple to yellow
  • inferno: Dark to bright colors from black to yellow
  • Spectral: Full rainbow spectrum for maximum contrast
  • coolwarm: Cool to warm colors for intuitive interpretation

Visualization Options

  • Max Points to Display: Adjust the number of points displayed (50,000 to 2,000,000). Larger files are automatically subsampled for performance
  • Example Files: Load pre-packaged sample files to quickly explore the visualizer's capabilities

MCP Server Integration

This application can function as an MCP (Model Context Protocol) server, allowing it to be integrated with AI agents and other tools.

To enable MCP server mode:

  1. Via launch parameter:
demo.launch(mcp_server=True)
  1. Via environment variable:
GRADIO_MCP_SERVER=True python app.py

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.

Contributing

We welcome contributions to improve this project. You can help by:

  • Adding support for additional file formats
  • Improving visualization performance
  • Enhancing the user interface
  • Adding more colormaps or visualization modes