Ray Casting¶
ray_casting_closest_geometry.py¶
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | 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¶
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | 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¶
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | 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() |