# MaximeHerpin/modular_tree

Repository: https://github.com/MaximeHerpin/modular_tree
Canonical: https://ross.abutalabs.com/products/modular_tree
Language: C++
License: GPL-3.0
License Family: copyleft
Last push: 2024-09-03T21:33:28+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3676, "days_push": 729, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1287, forks 235 (observed 2026-08-28T04:04:14.985632+00:00)

## What it is
Mtree is a C++ library for procedurally generating 3D tree models through composable tree functions and meshing. It is distributed primarily as a Blender addon, but the core C++ library can be used standalone.

## Use cases
- generate procedural 3d trees for blender scenes
- create tree meshes programmatically in c++
- model branching structures like trunks and branches
- add random variation to tree geometry
- export tree geometry as vertices and triangles

## When to choose
- you need procedural tree generation in Blender
- you want a C++ library for generating tree meshes in your own pipeline
- you need fine control over trunk, branch, and growth parameters

## When to avoid
- you need general-purpose procedural modeling beyond trees
- you need a ready-made library of prebuilt tree assets rather than generation
- you work outside Blender and C++ ecosystems

## Facets
- artifact type: library
- maturity: active
- function: graphics, simulation, sdk
- domain: graphics, simulation
- platform: cpp, cross-platform
- tags: procedural-generation, 3d-trees, blender-addon, mesh-generation, procedural-modeling, game-development, desktop

## Member repositories
- MaximeHerpin/modular_tree (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:14.985632+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:55:50.467125+00:00, confidence not recorded.
  - readme: https://github.com/MaximeHerpin/modular_tree (fetched 2026-08-28T04:04:14.985632+00:00, sha 0c48ba724c33)
- Data as of 2026-08-30T08:39:29.467469+00:00.