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Import, export, process, analyze and view triangular meshes.

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Trimesh is a Python (2.7-3*) library for loading and using triangular meshes. The goal of the library is to provide a fully featured Trimesh object which allows for easy manipulation and analysis, in the style of the excellent Polygon object in the Shapely library.

The API is mostly stable, but this should not be relied on and is not guaranteed; install a specific version if you plan on deploying something using trimesh as a backend.

Basic Installation

The minimum set of packages required to import trimesh are numpy, scipy and networkx. Installing other packages mentioned adds functionality but is not required.

The easiest and recommended way to get the most functionality out of Trimesh is to install a conda environment, then:

# install modules for spatial indexing and  polygon manipulation
# these generally install cleanly on Linux, Windows, and OSX
conda install -c conda-forge rtree shapely

# install pyembree for fast ray queries
# Linux and OSX only
conda install -c conda-forge pyembree

# install Trimesh and soft dependencies that are easy to install
# these generally install cleanly on Linux, Windows, and OSX
pip install trimesh[easy]

Or, for the easiest install with only minimal dependencies (slower ray queries, no vector path handling, mesh creation, viewer, etc):

pip install trimesh

Further information is available in the advanced installation documentation.

Quick Start

Here is an example of loading a mesh from file and colorizing its faces. Here is a nicely formatted ipython notebook version of this example. Also check out the cross section example or possibly the integration of a function over a mesh example.

import numpy as np
import trimesh

# load a file by name or from a buffer
mesh = trimesh.load_mesh('../models/featuretype.STL')

# is the current mesh watertight?

# what's the euler number for the mesh?

# the convex hull is another Trimesh object that is available as a property
# lets compare the volume of our mesh with the volume of its convex hull
np.divide(mesh.volume, mesh.convex_hull.volume)

# since the mesh is watertight, it means there is a
# volumetric center of mass which we can set as the origin for our mesh
mesh.vertices -= mesh.center_mass

# what's the moment of inertia for the mesh?

# if there are multiple bodies in the mesh we can split the mesh by
# connected components of face adjacency
# since this example mesh is a single watertight body we get a list of one mesh

# facets are groups of coplanar adjacent faces
# set each facet to a random color
# colors are 8 bit RGBA by default (n,4) np.uint8
for facet in mesh.facets:
    mesh.visual.face_colors[facet] = trimesh.visual.random_color()

# preview mesh in an opengl window if you installed pyglet with pip

# transform method can be passed a (4,4) matrix and will cleanly apply the transform

# axis aligned bounding box is available

# a minimum volume oriented bounding box also available
# primitives are subclasses of Trimesh objects which automatically generate
# faces and vertices from data stored in the 'primitive' attribute

# show the mesh appended with its oriented bounding box
# the bounding box is a trimesh.primitives.Box object, which subclasses
# Trimesh and lazily evaluates to fill in vertices and faces when requested
# (press w in viewer to see triangles)
(mesh + mesh.bounding_box_oriented).show()

# bounding spheres and bounding cylinders of meshes are also
# available, and will be the minimum volume version of each
# except in certain degenerate cases, where they will be no worse
# than a least squares fit version of the primitive.


  • Import binary/ASCII STL, Wavefront OBJ, ASCII OFF, binary/ASCII PLY, XAML, 3DXML, etc.
  • Import additional mesh formats using assimp (requires pyassimp or cyassimp)
  • Import and export 2D or 3D vector paths from/to DXF or SVG files
  • Export meshes as binary STL, binary PLY, ASCII OFF, COLLADA, dictionaries, JSON- serializable dictionaries (base64 encoded arrays), MSGPACK- serializable dictionaries (binary string arrays)
  • Preview meshes (requires pyglet)
  • Internal caching of computed values (validated with a zlib.adler32 CRC on face/vertex data)
  • Fast loading of binary files through importers written by defining custom numpy dtypes
  • Calculate face adjacencies quickly (for 234,230 face mesh .248 s)
  • Calculate cross sections (.146 s)
  • Split mesh based on face connectivity using networkx, graph-tool, or scipy.sparse
  • Calculate mass properties, including volume, center of mass, moment of inertia, and principal components of inertia
  • Find coplanar and adjacent groups of faces (.454 s)
  • Fix triangle winding and normals to be consistent
  • Find convex hulls of meshes
  • Compute a rotation/translation/tessellation invariant identifier for meshes
  • Determine duplicate meshes from identifier
  • Determine if a mesh is watertight
  • Determine if a mesh is convex
  • Repair single triangle and single quad holes
  • Uniformly sample the surface of a mesh
  • Ray-mesh queries including location, triangle id, etc.
  • Boolean operations on meshes (intersection, union, difference) using OpenSCAD or Blender as backend
  • Voxelize watertight meshes
  • Unit conversions
  • Subdivide faces of a mesh
  • Minimum volume oriented bounding boxes for meshes
  • Minimum volume bounding sphere / n-spheres
  • Symbolic integration of function(x,y,z) over a triangle
  • Quick (sympy-numpy lambda) evaluation of symbolic integral result over a mesh
  • Calculate nearest point on mesh surface and signed distance
  • Determine if a point lies inside or outside of a mesh using signed distance
  • Create meshes with primitive objects (Extrude, Box, Sphere) which are subclasses of Trimesh
  • Simple scene graph and transform tree which can be rendered (pyglet) or exported.
  • Numerous utility functions, such as transforming points, unitizing vectors, tracking arrays for changes, grouping rows, etc.


Trimesh includes an optional pyglet- based viewer for debugging/inspecting. In the mesh view window:

  • dragging rotates the view
  • ctl + drag pans
  • mouse wheel zooms
  • ‘z’ returns to the base view
  • ‘w’ toggles wireframe mode
  • ‘c’ toggles backface culling


If you want to deploy something in a container that uses trimesh, automated builds containing trimesh and its dependencies are available on docker hub. For an image with all dependencies:

docker pull mikedh/trimesh

Or, for a much smaller image with no boolean operations and slightly slower graph operations (no graph-tool installed, trimesh will fall back to scipy or networkx):

docker pull mikedh/trimesh_minimal

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