Ray Casting

ray_casting_closest_geometry.py

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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()

ray_casting_sdf.py

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import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import sys

if __name__ == "__main__":
    # Load mesh and convert to open3d.t.geometry.TriangleMesh .
    armadillo_data = o3d.data.ArmadilloMesh()
    mesh = o3d.io.read_triangle_mesh(armadillo_data.path)
    mesh = o3d.t.geometry.TriangleMesh.from_legacy(mesh)

    # Create a scene and add the triangle mesh.
    scene = o3d.t.geometry.RaycastingScene()
    scene.add_triangles(mesh)

    min_bound = mesh.vertex.positions.min(0).numpy()
    max_bound = mesh.vertex.positions.max(0).numpy()

    xyz_range = np.linspace(min_bound, max_bound, 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)

    # Signed distance is a [64,64,64] array.
    signed_distance = scene.compute_signed_distance(query_points)

    # We can visualize the slices of the distance field directly with matplotlib.
    fig = plt.figure()
    print("Visualizing sdf at each point for the armadillo mesh ...")

    def show_slices(i=int):
        print(f"Displaying slice no.: {i}")
        if i >= 64:
            sys.exit()
        plt.imshow(signed_distance.numpy()[:, :, i % 64])

    animator = anim.FuncAnimation(fig, show_slices, interval=100)
    plt.show()

ray_casting_to_image.py

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import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt

if __name__ == "__main__":
    # Create meshes and convert to open3d.t.geometry.TriangleMesh .
    cube = o3d.geometry.TriangleMesh.create_box().translate([0, 0, 0])
    cube = o3d.t.geometry.TriangleMesh.from_legacy(cube)
    torus = o3d.geometry.TriangleMesh.create_torus().translate([0, 0, 2])
    torus = o3d.t.geometry.TriangleMesh.from_legacy(torus)
    sphere = o3d.geometry.TriangleMesh.create_sphere(radius=0.5).translate(
        [1, 2, 3])
    sphere = o3d.t.geometry.TriangleMesh.from_legacy(sphere)

    scene = o3d.t.geometry.RaycastingScene()
    scene.add_triangles(cube)
    scene.add_triangles(torus)
    _ = scene.add_triangles(sphere)

    rays = o3d.t.geometry.RaycastingScene.create_rays_pinhole(
        fov_deg=90,
        center=[0, 0, 2],
        eye=[2, 3, 0],
        up=[0, 1, 0],
        width_px=640,
        height_px=480,
    )
    # We can directly pass the rays tensor to the cast_rays function.
    ans = scene.cast_rays(rays)
    plt.imshow(ans['t_hit'].numpy())
    plt.show()
    plt.imshow(np.abs(ans['primitive_normals'].numpy()))
    plt.show()
    plt.imshow(np.abs(ans['geometry_ids'].numpy()), vmax=3)
    plt.show()