Mesh Analysis and Visualization for Research

A powerful 3D mesh and point cloud analysis and visualization toolkit built with OpenGL and Python. Load, inspect, and analyze 3D mesh and point cloud files with real-time rendering and comprehensive geometric analysis.

Overview

This project provides two complementary visualization applications for 3D data research and analysis:

Application	Purpose	Formats	Use Cases
main.py (Mesh Viewer)	Full topology analysis and mesh visualization	OBJ, STL, PLY, GLB, OFF	Mesh validation, defect detection, multi-mesh comparison
main_pc.py (Point Cloud Viewer)	Large-scale point cloud visualization	XYZ	LiDAR analysis, point cloud inspection, multi-cloud comparison

Installation

Requirements

• Python 3.7+
• OpenGL 3.3+ capable graphics card

Setup

Running with Repo

git clone https://github.com/KhoiDOO/meshinfo.git
cd meshinfo
python main.py -h

Install dependencies manually:

pip install glfw PyOpenGL numpy pyrr pillow trimesh python-fcl colorama

Install as Python Package:

pip install git+https://github.com/KhoiDOO/meshinfo.git

Getting Started

Mesh Viewer

python main.py
# Press O to open a mesh file
# See docs/VIEWER.md for full documentation

Enable mesh intersection checking (can be expensive on large meshes):

python main.py --intersect

Enable non-manifold vertex checking:

python main.py --nonmanifold

Enable additional analysis flags:

python main.py --components --geometry --topology

Point Cloud Viewer

python main_pc.py
# Press O to open a point cloud file
# See docs/POINT_CLOUD_VIEWER.md for full documentation

Mesh Anlysis

In case you want to just analyze your mesh w/o viewing it, we provide APIs to do. First install as a Python package, then

from meshinfo import MeshInfo

mesh_path = "your_mesh_file"
filename = os.path.basename(mesh_path).split(".")[0]
mesh = trimesh.load()
mesh_info = MeshInfo(
    mesh,
    check_intersection=True,
    check_components=True,
    check_nonmanifold_vertices=True,
    check_geometry=True,
    check_topology=True,
    verbose=True
)

mesh_stat_path = os.path.join(test_dir, f"{filename}_stat.json")
mesh_dict = mesh_info.to_dict(nested=True)

Features at a Glance

Mesh Viewer (main.py)

• ✅ Multi-mesh loading with automatic grid layout
• ✅ Topology analysis: self-intersections, non-manifold detection
• ✅ Visualization: face/vertex normals, point clouds, wireframe overlays
• ✅ Comprehensive mesh statistics in console output
• ✅ Side-by-side mesh comparison

Point Cloud Viewer (main_pc.py)

• ✅ Multi-cloud loading with synchronized views
• ✅ GPU-optimized rendering for millions of points
• ✅ Support for colored point clouds (RGB)
• ✅ Adaptive point sizing and camera controls
• ✅ Multi-format support (XYZ, LAS, LAZ, PLY)

Documentation

Detailed documentation for each application:

• Mesh Viewer Documentation - Full guide for main.py

  • Mesh topology analysis features
  • Keyboard controls and usage workflow
  • Supported formats and sample meshes
  • Performance optimization tips

• Point Cloud Viewer Documentation - Full guide for main_pc.py

  • Point cloud loading and visualization
  • Keyboard controls and camera management
  • Format specifications and examples
  • Creating point cloud files from various sources

Sample Data

Both applications include sample data for testing:

• Mesh Samples (samples/mesh/)

  • Test meshes with known topology issues
  • Good for validation and demonstration
  • See samples/mesh/README.md

• Point Cloud Samples (samples/pc/)

  • Example point clouds in XYZ format
  • Ready to load and visualize
  • See samples/pc/README.md

Architecture

Technologies Used

• Rendering: OpenGL 3.3 Core Profile with GLSL shaders
• Mesh Processing: Trimesh library for geometry operations
• Collision Detection: FCL (Flexible Collision Library) BVH
• GUI: GLFW for window management and input
• File I/O: NumPy, Trimesh, Laspy (optional)

License

See LICENSE file for details.