add close loop control
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@@ -121,7 +121,34 @@ class ReconstructionUtil:
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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, combined_point_cloud
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@staticmethod
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def compute_next_best_view_with_overlap(scanned_pts:list, point_cloud_list, history_indices, scan_points_indices_list, threshold=0.01, soft_overlap_threshold=0.5, hard_overlap_threshold=0.7, scan_points_threshold=5):
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max_rec_pts = np.vstack(point_cloud_list)
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downsampled_max_rec_pts = PtsUtil.voxel_downsample_point_cloud(max_rec_pts, threshold)
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best_view = None
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best_coverage = -1
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best_covered_num = 0
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for view in range(len(point_cloud_list)):
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if point_cloud_list[view].shape[0] == 0:
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continue
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new_scan_points_indices = scan_points_indices_list[view]
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if not ReconstructionUtil.check_scan_points_overlap(history_indices, new_scan_points_indices, scan_points_threshold):
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overlap_threshold = hard_overlap_threshold
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else:
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overlap_threshold = soft_overlap_threshold
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overlap_rate = ReconstructionUtil.compute_overlap_rate(point_cloud_list[view], scanned_pts, threshold)
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if overlap_rate < overlap_threshold:
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continue
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new_combined_point_cloud = np.vstack(scanned_pts + [point_cloud_list[view]])
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new_downsampled_combined_point_cloud = PtsUtil.voxel_downsample_point_cloud(new_combined_point_cloud,threshold)
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new_coverage, new_covered_num = ReconstructionUtil.compute_coverage_rate(downsampled_max_rec_pts, new_downsampled_combined_point_cloud, threshold)
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if new_coverage > best_coverage:
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best_coverage = new_coverage
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best_covered_num = new_covered_num
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best_view = view
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return best_view, best_coverage, best_covered_num
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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 = 500, max_attempts = 1000):
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points = []
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