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# ----------------------------------------------------------------------------
# - Open3D: www.open3d.org -
# ----------------------------------------------------------------------------
# Copyright (c) 2018-2024 www.open3d.org
# SPDX-License-Identifier: MIT
# ----------------------------------------------------------------------------
import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import sys
if __name__ == "__main__":
cube = o3d.t.geometry.TriangleMesh.from_legacy(
o3d.geometry.TriangleMesh.create_box().translate([-1.2, -1.2, 0]))
sphere = o3d.t.geometry.TriangleMesh.from_legacy(
o3d.geometry.TriangleMesh.create_sphere(0.5).translate([0.7, 0.8, 0]))
scene = o3d.t.geometry.RaycastingScene()
# Add triangle meshes and remember ids.
mesh_ids = {}
mesh_ids[scene.add_triangles(cube)] = 'cube'
mesh_ids[scene.add_triangles(sphere)] = 'sphere'
# Compute range.
xyz_range = np.linspace([-2, -2, -2], [2, 2, 2], num=64)
# Query_points is a [64,64,64,3] array.
query_points = np.stack(np.meshgrid(*xyz_range.T),
axis=-1).astype(np.float32)
closest_points = scene.compute_closest_points(query_points)
distance = np.linalg.norm(query_points - closest_points['points'].numpy(),
axis=-1)
rays = np.concatenate([query_points, np.ones_like(query_points)], axis=-1)
intersection_counts = scene.count_intersections(rays).numpy()
is_inside = intersection_counts % 2 == 1
distance[is_inside] *= -1
signed_distance = distance
closest_geometry = closest_points['geometry_ids'].numpy()
# We can visualize the slices of the distance field and closest geometry directly with matplotlib.
fig, axes = plt.subplots(1, 2)
print(
"Visualizing sdf and closest geometry at each point for a cube and sphere ..."
)
def show_slices(i=int):
print(f"Displaying slice no.: {i}")
if i >= 64:
sys.exit()
axes[0].imshow(signed_distance[:, :, i])
axes[1].imshow(closest_geometry[:, :, i])
animator = anim.FuncAnimation(fig, show_slices, interval=100)
plt.show()
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