An example showing nearest point queries, sampling the volume of box primitives generated from the oriented bounds and using PointCloud objects for visualization.

import trimesh
import numpy as np
# load a large- ish PLY model with colors
mesh = trimesh.load('../models/cycloidal.ply')
# we can sample the volume of Box primitives
points = mesh.bounding_box_oriented.sample_volume(count=10)
# find the closest point on the mesh to each random point
 triangle_id) = mesh.nearest.on_surface(points)
# distance from point to surface of meshdistances
# create a PointCloud object out of each (n,3) list of points
cloud_original = trimesh.points.PointCloud(points)
cloud_close    = trimesh.points.PointCloud(closest_points)

# create a unique color for each point
cloud_colors = np.array([trimesh.visual.random_color() for i in points])

# set the colors on the random point and its nearest point to be the same
cloud_original.vertices_color = cloud_colors
cloud_close.vertices_color    = cloud_colors

# create a scene containing the mesh and two sets of points
scene = trimesh.Scene([mesh,

# show the scene wusing