Mesh Analysis and Visualization for Research

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

Overview

Diagnostic & Comparison

Analysis Dashboard	Multi-mesh Comparison	Non-manifold Detection

Visualization Modes

Solid & Wireframe Modes	Self-intersection	Point Cloud
Face Normals	Vertex Normals	Point Cloud Normals

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

Create conda env

conda create -n meshviewer python=3.10
conda activate meshviewer
pip install .

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

Mesh Analysis API

In case you want to just analyze your mesh w/o viewing it, we provide a clean API.

import trimesh
import os
from meshinfo import MeshInfo

mesh_path = "your_mesh_file.obj"
filename = os.path.basename(mesh_path).split(".")[0]
mesh = trimesh.load(mesh_path, process=False)

mesh_info = MeshInfo(
    mesh,
    name=filename,
    check_intersection=True,
    check_components=True,
    check_nonmanifold_vertices=True,
    check_geometry=True,
    check_topology=True,
    verbose=True
)

# Export all metrics as a dictionary
mesh_dict = mesh_info.to_dict(nested=True)

Features at a Glance

Mesh Viewer (main.py)

• ✅ Interactive Analysis Dashboard: Real-time side panel (Press G to toggle).
• ✅ Comparison Table: Side-by-side metrics for multiple meshes.
• ✅ Advanced Camera Calibration: Adjust FOV, Focal Length (35mm equivalent), and Clipping Planes.
• ✅ Orbital Navigation: Intuitive 3D rotation targeting the origin (Arrow keys).
• ✅ Dynamic Layouts: Automatically arrange multiple meshes in Grid or Line modes.
• ✅ Topology Analysis: Detect self-intersections, non-manifold edges/vertices, and genus.
• ✅ Visualization: Face/vertex normals, point clouds, and high-DPI screenshot export.

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
  • Camera calibration and navigation
  • Keyboard controls and usage workflow
  • Topology analysis algorithms
  • Performance optimization tips

Sample Data

Both applications include sample data for testing:

• Mesh Samples (samples/mesh)
  • Test meshes with known topology issues (self-intersections, non-manifold edges).
  • See samples/mesh/README.md.

Acknowledgement

This project is built upon several powerful open-source libraries:

• Rendering: ModernGL (OpenGL 3.3 Core Profile)
• Geometry & Mesh Processing: Trimesh
• Self-Intersection Detection: MeshLib
• GUI Framework: Dear ImGui (via pyimgui)
• Window Management: GLFW (via pyglfw)
• Numerical Computation: NumPy
• Math Utilities: Pyrr
• Image Processing: Pillow (for screenshots)
• Terminal Styling: Colorama

License

See LICENSE file for details.