update normal in computing strategy
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@@ -19,6 +19,12 @@ class ReconstructionUtil:
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is_covered_by_distance = distances < threshold*2
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normal_dots = np.einsum('ij,ij->i', target_normal, combined_normal[indices])
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is_covered_by_normal = normal_dots > normal_threshold
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pts_nrm_target = np.hstack([target_point_cloud, target_normal])
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np.savetxt("pts_nrm_target.txt", pts_nrm_target)
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pts_nrm_combined = np.hstack([combined_point_cloud, combined_normal])
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np.savetxt("pts_nrm_combined.txt", pts_nrm_combined)
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import ipdb; ipdb.set_trace()
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covered_points_num = np.sum(is_covered_by_distance & is_covered_by_normal)
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coverage_rate = covered_points_num / target_point_cloud.shape[0]
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@@ -145,7 +151,6 @@ class ReconstructionUtil:
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max_rec_nrm = np.vstack(normal_list)
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downsampled_max_rec_pts, idx = PtsUtil.voxel_downsample_point_cloud(max_rec_pts, threshold, require_idx=True)
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downsampled_max_rec_nrm = max_rec_nrm[idx]
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max_rec_pts_num = downsampled_max_rec_pts.shape[0]
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try:
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max_real_rec_pts_coverage, _ = ReconstructionUtil.compute_coverage_rate_with_normal(target_point_cloud, downsampled_max_rec_pts, target_normal, downsampled_max_rec_nrm, threshold)
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@@ -184,7 +189,7 @@ class ReconstructionUtil:
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new_combined_point_cloud = np.vstack([combined_point_cloud, point_cloud_list[view_index]])
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new_combined_normal = np.vstack([combined_normal, normal_list[view_index]])
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new_downsampled_combined_point_cloud = PtsUtil.voxel_downsample_point_cloud(new_combined_point_cloud,threshold)
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new_downsampled_combined_point_cloud, idx = PtsUtil.voxel_downsample_point_cloud(new_combined_point_cloud,threshold, require_idx=True)
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new_downsampled_combined_normal = new_combined_normal[idx]
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new_coverage, new_covered_num = ReconstructionUtil.compute_coverage_rate_with_normal(downsampled_max_rec_pts, new_downsampled_combined_point_cloud, downsampled_max_rec_nrm, new_downsampled_combined_normal, threshold)
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coverage_increase = new_coverage - current_coverage
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