trimesh


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Trimesh is a pure Python (2.7- 3.3+) library for loading and using triangular meshes with an emphasis on watertight meshes. The goal of the library is to provide a fully featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the 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.

Pull requests are hugely appreciated and responded to promptly! If you’d like to contribute, here is an up to date list of potential enhancements although things not on that list are also welcome. Also, some general advice for writing mesh code in Python and Numpy.

Basic Installation

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

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

pip install trimesh

For more functionality, the easiest way to get a full trimesh install is a conda environment:

# this will install all soft dependencies available on your current platform
conda install -c conda-forge 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

# attach to logger so trimesh messages will be printed to console
trimesh.util.attach_to_log()

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

# is the current mesh watertight?
mesh.is_watertight

# what's the euler number for the mesh?
mesh.euler_number

# 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?
mesh.moment_inertia

# 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
mesh.split()

# 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
mesh.show()

# transform method can be passed a (4,4) matrix and will cleanly apply the transform
mesh.apply_transform(trimesh.transformations.random_rotation_matrix())

# axis aligned bounding box is available
mesh.bounding_box.extents

# 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
mesh.bounding_box_oriented.primitive.extents
mesh.bounding_box_oriented.primitive.transform

# 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.
print(mesh.bounding_box_oriented.volume,
      mesh.bounding_cylinder.volume,
      mesh.bounding_sphere.volume)

Features

  • Import meshes from binary/ASCII STL, Wavefront OBJ, ASCII OFF, binary/ASCII PLY, GLTF/GLB 2.0, 3MF, XAML, 3DXML, etc.
  • Import and export 2D or 3D vector paths from/to DXF or SVG files
  • Export meshes as binary STL, binary PLY, ASCII OFF, GLTF/GLB 2.0, COLLADA, dictionaries, JSON- serializable dictionaries (base64 encoded arrays), MSGPACK- serializable dictionaries (binary string arrays)
  • Preview meshes using pyglet
  • Preview meshes in- line in jupyter notebooks using three.js
  • Automatic hashing of numpy arrays for change tracking (MD5, zlib CRC, and xxhash)
  • Internal caching of computed values validated using numpy hashes
  • Fast loading of binary files through importers written by defining custom numpy dtypes
  • Calculate things like face adjacencies, face angles, vertex defects, etc.
  • Calculate cross sections (IE the slicing operation used in 3D printing)
  • 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
  • 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, convex, etc.
  • 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
  • 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
  • Calculate nearest point on mesh surface and signed distance
  • Determine if a point lies inside or outside of a mesh using signed distance
  • Create primitive objects (Box, Cylinder, Sphere, Extrusion) which are subclassed Trimesh objects and have all the same features (inertia, viewers, etc)
  • Simple scene graph and transform tree which can be rendered (pyglet window or three.js in a jupyter notebook) or exported.
  • Numerous utility functions, such as transforming points, unitizing vectors, tracking arrays for changes, grouping rows, etc.

Design Use Case

The trimesh.Trimesh object is most useful on single body, watertight meshes that represent a volume. The design use case is around analysis of geometry exported from a CAD system into a mesh format, for applications related to robotics and manufacturing.

This can be seen in the data model of Trimesh, where the emphasis is on faces and vertices and things derived from them, rather than other visual properties or metadata.

It is hopefully useful in other applications, but most of the core effort is around the design use case.

Viewer

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

Containers

If you want to deploy something in a container that uses trimesh, automated builds containing trimesh and its dependencies are available on Docker Hub:

docker pull mikedh/trimesh

Examples