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update new_num limit

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hofee
2024-10-05 15:36:38 -05:00
parent 1a3ae15130
commit e315fd99ee
2 changed files with 20 additions and 25 deletions
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24
utils/reconstruction.py
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@@ -8,9 +8,9 @@ class ReconstructionUtil:
def compute_coverage_rate(target_point_cloud, combined_point_cloud, threshold=0.01):
kdtree = cKDTree(combined_point_cloud)
distances, _ = kdtree.query(target_point_cloud)
covered_points = np.sum(distances < threshold*2)
coverage_rate = covered_points / target_point_cloud.shape[0]
return coverage_rate
covered_points_num = np.sum(distances < threshold)
coverage_rate = covered_points_num / target_point_cloud.shape[0]
return coverage_rate, covered_points_num
@staticmethod
def compute_overlap_rate(new_point_cloud, combined_point_cloud, threshold=0.01):
@@ -46,10 +46,12 @@ class ReconstructionUtil:
downsampled_max_rec_pts = PtsUtil.voxel_downsample_point_cloud(max_rec_pts, threshold)
max_rec_pts_num = downsampled_max_rec_pts.shape[0]
max_rec_pts_coverage = ReconstructionUtil.compute_coverage_rate(target_point_cloud, downsampled_max_rec_pts, threshold)
max_real_rec_pts_coverage, _ = ReconstructionUtil.compute_coverage_rate(target_point_cloud, downsampled_max_rec_pts, threshold)
new_coverage = ReconstructionUtil.compute_coverage_rate(downsampled_max_rec_pts, combined_point_cloud, threshold)
new_coverage, new_covered_num = ReconstructionUtil.compute_coverage_rate(downsampled_max_rec_pts, combined_point_cloud, threshold)
current_coverage = new_coverage
current_covered_num = new_covered_num
remaining_views = list(range(len(point_cloud_list)))
view_sequence = [(init_view, current_coverage)]
cnt_processed_view = 0
@@ -61,6 +63,7 @@ class ReconstructionUtil:
best_view = None
best_coverage_increase = -1
best_combined_point_cloud = None
best_covered_num = 0
for view_index in remaining_views:
if point_cloud_list[view_index].shape[0] == 0:
@@ -81,25 +84,26 @@ class ReconstructionUtil:
start = time.time()
new_combined_point_cloud = np.vstack([combined_point_cloud, point_cloud_list[view_index]])
new_downsampled_combined_point_cloud = PtsUtil.voxel_downsample_point_cloud(new_combined_point_cloud,threshold)
new_coverage = ReconstructionUtil.compute_coverage_rate(downsampled_max_rec_pts, new_downsampled_combined_point_cloud, threshold)
new_coverage, new_covered_num = ReconstructionUtil.compute_coverage_rate(downsampled_max_rec_pts, new_downsampled_combined_point_cloud, threshold)
end = time.time()
#print(f"compute_coverage_rate Time: {end-start}")
coverage_increase = new_coverage - current_coverage
if coverage_increase > best_coverage_increase:
best_coverage_increase = coverage_increase
best_view = view_index
best_covered_num = new_covered_num
best_combined_point_cloud = new_downsampled_combined_point_cloud
if best_view is not None:
if best_coverage_increase <=1e-3:
if best_coverage_increase <=1e-3 or best_covered_num - current_covered_num <= 5:
break
selected_views.append(best_view)
best_rec_pts_num = best_combined_point_cloud.shape[0]
print(f"Current rec pts num: {curr_rec_pts_num}, Best rec pts num: {best_rec_pts_num}, Max rec pts num: {max_rec_pts_num}")
print(f"Current coverage: {current_coverage}, Best coverage increase: {best_coverage_increase}, Max coverage: {max_rec_pts_coverage}")
print(f"Current rec pts num: {curr_rec_pts_num}, Best rec pts num: {best_rec_pts_num}, Best cover pts: {best_covered_num}, Max rec pts num: {max_rec_pts_num}")
print(f"Current coverage: {current_coverage}, Best coverage increase: {best_coverage_increase}, Max Real coverage: {max_real_rec_pts_coverage}")
current_covered_num = best_covered_num
curr_rec_pts_num = best_rec_pts_num
combined_point_cloud = best_combined_point_cloud
remaining_views.remove(best_view)