思路：二分法寻找最优体素大小（voxel_size）获得指定点数量的体素下采样点云
代码：
对一个numpy array, shape=(n,3)表示的点云进行下采样
import open3d as o3d
import numpy as np
import copy
def fixedNumDownSample(vertices, desiredNumOfPoint, leftVoxelSize, rightVoxelSize):
""" Use the method voxel_down_sample defined in open3d and do bisection iteratively
to get the appropriate voxel_size which yields the points with the desired number.
INPUT:
vertices: numpy array shape (n,3)
desiredNumOfPoint: int, the desired number of points after down sampling
leftVoxelSize: float, the initial bigger voxel size to do bisection
rightVoxelSize: float, the initial smaller voxel size to do bisection
OUTPUT:
downSampledVertices: down sampled points with the original data type
"""
assert leftVoxelSize > rightVoxelSize, "leftVoxelSize should be larger than rightVoxelSize"
assert vertices.shape[0] > desiredNumOfPoint, "desiredNumOfPoint should be less than or equal to the num of points in the given array."
if vertices.shape[0] == desiredNumOfPoint:
return vertices
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(vertices)
pcd = pcd.voxel_down_sample(leftVoxelSize)
assert len(pcd.points) <= desiredNumOfPoint, "Please specify a larger leftVoxelSize."
pcd.points = o3d.utility.Vector3dVector(vertices)
pcd = pcd.voxel_down_sample(rightVoxelSize)
assert len(pcd.points) >= desiredNumOfPoint, "Please specify a smaller rightVoxelSize."
pcd.points = o3d.utility.Vector3dVector(vertices)
midVoxelSize = (leftVoxelSize + rightVoxelSize) / 2.
pcd = pcd.voxel_down_sample(midVoxelSize)
while len(pcd.points) != desiredNumOfPoint:
if len(pcd.points) < desiredNumOfPoint:
leftVoxelSize = copy.copy(midVoxelSize)
else:
rightVoxelSize = copy.copy(midVoxelSize)
midVoxelSize = (leftVoxelSize + rightVoxelSize) / 2.
pcd.points = o3d.utility.Vector3dVector(vertices)
pcd = pcd.voxel_down_sample(midVoxelSize)
# print("final voxel size: ", midVoxelSize)
downSampledVertices = np.asarray(pcd.points, dtype=vertices.dtype)
return downSampledVertices
对一个open3d.geometry.PointCloud表示的点云进行下采样
def fixedNumDownSamplePCL(initPcd, desiredNumOfPoint, leftVoxelSize, rightVoxelSize):
""" Use the method voxel_down_sample defined in open3d and do bisection iteratively
to get the appropriate voxel_size which yields the points with the desired number.
INPUT:
initPcd: open3d.geometry.PointCloud
desiredNumOfPoint: int, the desired number of points after down sampling
leftVoxelSize: float, the initial bigger voxel size to do bisection
rightVoxelSize: float, the initial smaller voxel size to do bisection
OUTPUT:
pcd: down sampled pointcloud
"""
assert leftVoxelSize > rightVoxelSize, "leftVoxelSize should be larger than rightVoxelSize"
assert len(initPcd.points) > desiredNumOfPoint, "desiredNumOfPoint should be less than or equal to the num of points in the given point cloud."
if len(initPcd.points) == desiredNumOfPoint:
return initPcd
pcd = copy.deepcopy(initPcd)
pcd = pcd.voxel_down_sample(leftVoxelSize)
assert len(pcd.points) <= desiredNumOfPoint, "Please specify a larger leftVoxelSize."
pcd = copy.deepcopy(initPcd)
pcd = pcd.voxel_down_sample(rightVoxelSize)
assert len(pcd.points) >= desiredNumOfPoint, "Please specify a smaller rightVoxelSize."
pcd = copy.deepcopy(initPcd)
midVoxelSize = (leftVoxelSize + rightVoxelSize) / 2.
pcd = pcd.voxel_down_sample(midVoxelSize)
while len(pcd.points) != desiredNumOfPoint:
if len(pcd.points) < desiredNumOfPoint:
leftVoxelSize = copy.copy(midVoxelSize)
else:
rightVoxelSize = copy.copy(midVoxelSize)
midVoxelSize = (leftVoxelSize + rightVoxelSize) / 2.
pcd = copy.deepcopy(initPcd)
pcd = pcd.voxel_down_sample(midVoxelSize)
return pcd
github链接： https://github.com/SJTUzhou/downSamplePointsWithDesiredNum
