Import, export, process, analyze and view triangular meshes.
Project description
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.
Installation
The easiest and recommended way to get the most functionality out of Trimesh is to install a conda environment, then:
# cyassimp is a fast binding for the assimp importers
conda install -c menpo/label/master cyassimp
# install modules for spatial indexing, polygon manipulation, and fast ray-mesh queries
conda install -c conda-forge rtree shapely
# install Trimesh and soft dependancies that are easy to install
pip install trimesh[easy]
Or, for only minimal dependencies (no ray queries, vector path handling, mesh creation, viewer, etc):
pip install trimesh
Features
Import binary/ASCII STL, Wavefront OBJ, ASCII OFF, binary/ASCII PLY, XAML, 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, and moment of inertia (.246 s)
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.
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?
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()
# find groups of coplanar adjacent faces
facets, facets_area = mesh.facets(return_area=True)
# set each facet to a random color
# colors are 8 bit RGBA by default (n,4) np.uint8
for facet in 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)
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 dependancies are available on docker hub. For an image with all dependancies:
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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