python利用八叉树分割三维点云代码

以下是利用八叉树分割三维点云的Python代码示例：

import numpy as np
from sklearn.neighbors import KDTree

class Octree:
    def __init__(self, points, max_points_per_node=16, max_depth=8):
        self.points = points
        self.max_points_per_node = max_points_per_node
        self.max_depth = max_depth
        self.min_bounds = np.min(points, axis=0)
        self.max_bounds = np.max(points, axis=0)
        self.center = (self.min_bounds + self.max_bounds) / 2
        self.children = None
        self.depth = 0

        if len(points) > max_points_per_node and max_depth > 0:
            self.split()

    def split(self):
        self.children = []
        for i in range(8):
            mask = np.array([i & 1, i & 2, i & 4])
            bounds_min = np.where(mask, self.center, self.min_bounds)
            bounds_max = np.where(mask, self.max_bounds, self.center)
            indices = self.get_indices(bounds_min, bounds_max)
            if len(indices) > 0:
                child = Octree(self.points[indices], self.max_points_per_node, self.max_depth - 1)
                child.min_bounds = bounds_min
                child.max_bounds = bounds_max
                child.depth = self.depth + 1
                self.children.append(child)

    def get_indices(self, min_bounds, max_bounds):
        indices = []
        for i, point in enumerate(self.points):
            if (point >= min_bounds).all() and (point <= max_bounds).all():
                indices.append(i)
        return indices

    def get_points_in_sphere(self, center, radius):
        indices = self.get_indices(center - radius, center + radius)
        if self.children is None:
            return indices
        else:
            result = []
            for child in self.children:
                if (center - child.center).dot(center - child.center) < radius * radius:
                    result += child.get_points_in_sphere(center, radius)
            return result

    def get_points_in_box(self, min_bounds, max_bounds):
        indices = self.get_indices(min_bounds, max_bounds)
        if self.children is None:
            return indices
        else:
            result = []
            for child in self.children:
                if (min_bounds <= child.max_bounds).all() and (max_bounds >= child.min_bounds).all():
                    result += child.get_points_in_box(min_bounds, max_bounds)
            return result

    def get_points_in_cube(self, center, size):
        return self.get_points_in_box(center - size / 2, center + size / 2)

def octree_from_points(points, max_points_per_node=16, max_depth=8):
    return Octree(points, max_points_per_node, max_depth)

def octree_from_kd_tree(kd_tree, max_points_per_node=16, max_depth=8):
    return Octree(kd_tree.data, max_points_per_node, max_depth)

def octree_from_file(filename, max_points_per_node=16, max_depth=8):
    points = np.loadtxt(filename)
    return Octree(points, max_points_per_node, max_depth)

def kd_tree_from_points(points):
    return KDTree(points)

def kd_tree_from_file(filename):
    points = np.loadtxt(filename)
    return KDTree(points)

这个Octree类实现了八叉树的基本功能，包括分割点云、获取半径内的点、获取包含在指定盒子中的点等。可以使用octree_from_points、octree_from_kd_tree和octree_from_file函数来创建Octree对象。也可以使用kd_tree_from_points和kd_tree_from_file函数来创建KDTree对象。