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import open3d as o3d
import numpy as np
def downsample_and_filter(pcd_file):
pcd = o3d.io.read_point_cloud(pcd_file, max_bound_div = 750, neighbor_num = 8)
point_num = len(pcd.points)
if (point_num > 10000000):
voxel_down_pcd = o3d.geometry.PointCloud.uniform_down_sample(pcd, int(point_num / 10000000)+1)
else:
voxel_down_pcd = pcd
max_bound = voxel_down_pcd.get_max_bound()
ball_radius = np.linalg.norm(max_bound) / max_bound_div
pcd_filter, _ = voxel_down_pcd.remove_radius_outlier(neighbor_num, ball_radius)
print('filtered size', len(pcd_filter.points), 'pre size:', len(pcd.points))
o3d.io.write_point_cloud(pcd_file[:-4] + '_filtered.ply', pcd_filter)
if __name__ == "__main__":
import os
dir_path = './data/demo_pcd'
for pcd_file in os.listdir(dir_path):
#if 'jonathan' in pcd_file: set max_bound_div to 300 and neighbot_num to 8
downsample_and_filter(os.path.join(dir_path, pcd_file))
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