Science Score: 44.0%

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  • Scientific vocabulary similarity
    Low similarity (6.0%) to scientific vocabulary
Last synced: 9 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: jamesafful
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 11.7 KB
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Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

PyNeuroMesh

PyNeuroMesh is a hybrid meshing pipeline that integrates neural implicit surface representations with classical mesh generation. It uses neural networks to learn signed distance functions (SDFs) and adaptive refinement fields to guide high-quality mesh generation using GMSH.


🔑 Features

  • Neural SDF Models — Learn continuous geometry via MLPs.
  • GMSH Integration — Surface extraction via marching cubes, meshing with GMSH.
  • Adaptive Refinement — Use RefineNet to predict local mesh size.
  • Training Pipelines — Includes synthetic and simulation-aware training scripts.
  • Python + CLI Access — Scriptable modules and runnable command-line tools.

📦 Installation

```bash git clone https://github.com/jamesafful/pyneuromesh.git cd pyneuromesh pip install -r requirements.txt

Owner

  • Name: James Afful
  • Login: jamesafful
  • Kind: user
  • Company: Iowa State University

Mechanical Engineering Grad 🎓 | Passionate about #CFD, #HPC, and #ML 🚀 | Exploring intersections of Engineering and Tech | #OpenSource Enthusiast | Learner!

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use PyNeuroMesh in your research, please cite this work."
title: "PyNeuroMesh: Neural Signed Distance Fields for Adaptive Meshing"
authors:
  - family-names: Afful
    given-names: James
    affiliation: "Independent Researcher"
    orcid: "https://orcid.org/0000-0001-6967-1740" 
date-released: 2024-06-01
version: "0.1"
repository-code: "https://github.com/jamesafful/pyneuromesh"

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Dependencies

requirements.txt pypi
  • gmsh *
  • matplotlib *
  • numpy *
  • scikit-image *
  • torch *
  • trimesh *
setup.py pypi
  • gmsh *
  • matplotlib *
  • numpy *
  • torch *
  • trimesh *