add preprocess
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@@ -129,22 +129,7 @@ class ReconstructionUtil:
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runner_name = status_info["runner_name"]
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sm.set_progress(app_name, runner_name, "processed view", len(point_cloud_list), len(point_cloud_list))
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return view_sequence, remaining_views, down_sampled_combined_point_cloud
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@staticmethod
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def filter_points(points, points_normals, cam_pose, voxel_size=0.005, theta=75):
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sampled_points = PtsUtil.voxel_downsample_point_cloud(points, voxel_size)
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kdtree = cKDTree(points_normals[:,:3])
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_, indices = kdtree.query(sampled_points)
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nearest_points = points_normals[indices]
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normals = nearest_points[:, 3:]
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camera_axis = -cam_pose[:3, 2]
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normals_normalized = normals / np.linalg.norm(normals, axis=1, keepdims=True)
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cos_theta = np.dot(normals_normalized, camera_axis)
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theta_rad = np.deg2rad(theta)
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filtered_sampled_points= sampled_points[cos_theta > np.cos(theta_rad)]
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return filtered_sampled_points[:, :3]
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@staticmethod
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def generate_scan_points(display_table_top, display_table_radius, min_distance=0.03, max_points_num = 100, max_attempts = 1000):
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