# marcomusy/vedo

A python module for scientific analysis of 3D data based on VTK and Numpy

Repository: https://github.com/marcomusy/vedo
Canonical: https://ross.abutalabs.com/products/vedo
Homepage: https://vedo.embl.es
Language: Python
License: MIT
License Family: permissive
Topics: 3d-graphics, vtk, 3d, mesh, simulations, scientific-visualization, finite-elements, python, visualization, scientific-research, numpy
Last push: 2026-08-04T14:34:23+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 39, longevity 100
- inputs: {"age_days": 3218, "days_push": 29, "days_rel": 198, "gap_med": 190.5, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2263, forks 277 (observed 2026-08-28T04:06:31.998566+00:00)

## What it is
vedo is a Python library for scientific analysis and visualization of 3D objects, meshes, point clouds, and volumetric data, built on top of VTK and NumPy. It provides an intuitive API for interactive rendering, mesh editing, geometric analysis, and publication-quality plotting.

## Use cases
- visualize 3d meshes and point clouds in python
- analyze and edit polygonal mesh geometry
- render volumetric data and scalar fields
- create publication-quality scientific 3d figures
- slice and inspect volumetric datasets interactively
- convert between mesh file formats like stl obj vtk
- compute mesh metrics like volume area and curvature

## When to choose
- you want a simple, pythonic API over VTK for 3D scientific visualization
- you need to work with meshes, point clouds, and volumes in one toolkit
- you need publication-quality rendering and interactive exploration with minimal code

## When to avoid
- you need raw, low-level access to the full VTK pipeline
- you need high-performance GPU rendering of massive datasets beyond VTK's typical scale
- you need web-based 3D visualization rather than desktop rendering

## Facets
- artifact type: library
- maturity: active
- function: data-visualization, image-processing, simulation, graphics, math
- domain: data-visualization, data-science, graphics, simulation
- platform: python, cross-platform, cli
- tags: vtk, numpy, 3d-meshes, point-clouds, volumetric-data, scientific-visualization, finite-elements, publication-quality-rendering, scientific-research

## Member repositories
- marcomusy/vedo (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:31.998566+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 2026-08-30T02:42:29.212770+00:00, confidence not recorded.
  - readme: https://github.com/marcomusy/vedo (fetched 2026-08-28T04:06:31.998566+00:00, sha 8b4f12015372)
  - homepage: https://vedo.embl.es (fetched 2026-08-29T10:22:58.501252+00:00, sha 0a7cc85ea503)
  - registry_pypi: https://pypi.org/pypi/vedo/json (fetched 2026-08-29T10:22:58.512547+00:00, sha 2b860ebed912)
  - site_page: https://vedo.embl.es/site/api (fetched 2026-08-29T10:22:58.510765+00:00, sha 364f2bda196c)
- Data as of 2026-08-30T08:39:29.467469+00:00.