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 (closest_points, distances, 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, cloud_original, cloud_close]) # show the scene wusing scene.show()