`import pywavefront import trimesh import numpy as np from trimesh import proximity from trimesh import util from trimesh import triangles

model = pywavefront.Wavefront('C:/Users/Darija/Documents/Modell.obj', collect_faces=True)

print(model.vertices) # gibt dir alle Punkte aus

for mesh in model.mesh_list: # Die Flächen "faces" stecken in den "meshes" print(mesh.faces)

mesh = trimesh.Trimesh(model.vertices, mesh.faces)

ray_origins = np.tile(np.array([2.0,6.5,1.5]), (1000,1))

ray_directions = np.random.uniform(-1, 1, (1000,3))

print(mesh.ray.intersects_location.doc) print(ray_directions) locations, index_ray, index_tri = mesh.ray.intersects_location( ray_origins = ray_origins, ray_directions = ray_directions, multiple_hits=False)

print('Strahl trifft Mesh bei folgender Koordinate:\n', locations)

ray_visualize = trimesh.load_path(np.hstack((ray_origins, ray_origins + ray_directions*5.0)).reshape(-1, 2, 3))

unmerge so viewer doesn't smooth

mesh.unmerge_vertices()

make mesh white- ish

mesh.visual.face_colors = [255,255,255,255] mesh.visual.face_colors[index_tri] = [255, 0, 0, 255]

create a visualization scene with rays, hits, and mesh

scene = trimesh.Scene([mesh,

                   #ray_visualize])

show the visualization

scene.show()

p = np.loadtxt('C:/Users/Darija/PycharmProjects/Punktwolke/Punktwolke_Raum1_asbuilt_5000_S.txt')

faces = mesh.triangles[index_tri]

print('Triangles:', mesh.triangles)

def closest_point_naive2(mesh, points): """ Given a mesh and a list of points find the closest point on any triangle.

Does this by constructing a very large intermediate array and
comparing every point to every triangle.

Parameters
----------
mesh : Trimesh
  Takes mesh to have same interfaces as `closest_point`
points : (m, 3) float
  Points in space

Returns
----------
closest : (m, 3) float
  Closest point on triangles for each point
distance : (m,) float
  Distances between point and triangle
triangle_id : (m,) int
  Index of triangle containing closest point
"""
# get triangles from mesh
triangles = mesh.triangles[index_tri]
# establish that input points are sane
points = np.asanyarray(points, dtype=np.float64)
if not util.is_shape(triangles, (-1, 3, 3)):
    raise ValueError('triangles shape incorrect')
if not util.is_shape(points, (-1, 3)):
    raise ValueError('points must be (n,3)')

# create a giant tiled array of each point tiled len(triangles) times
points_tiled = np.tile(points, (1, len(triangles)))
on_triangle = np.array([proximity.closest_point_corresponding(
    triangles, i.reshape((-1, 3))) for i in points_tiled])

# distance squared
distance_2 = [((i - q)**2).sum(axis=1)
              for i, q in zip(on_triangle, points)]

triangle_id = np.array([i.argmin() for i in distance_2])

# closest cartesian point
closest = np.array([g[i] for i, g in zip(triangle_id, on_triangle)])
distance = np.array([g[i] for i, g in zip(triangle_id, distance_2)]) ** .5

return closest, distance, triangle_id

dist = closest_point_naive2(mesh, p)

print(index_tri)

print(mesh.triangles[index_tri])`

When I run the code it gives me triangle_ids that are not in mesh.triangles [index_tri]. I don't know where the problem is. Can someone help me?

mikedh / trimesh

Incorrect output of the triangle_id #1131