RANSAC算法拟合平面 python

以下是使用Python实现RANSAC算法拟合平面的示例代码：

import numpy as np

def fit_plane_RANSAC(points, iterations=50, threshold=0.01):
    best_inliers = None
    best_params = None
    
    for i in range(iterations):
        # Randomly select three points to define a plane
        indices = np.random.choice(points.shape[0], size=3, replace=False)
        p1, p2, p3 = points[indices, :]
        
        # Compute plane normal and d parameter
        v1 = p2 - p1
        v2 = p3 - p1
        normal = np.cross(v1, v2)
        normal /= np.linalg.norm(normal)
        d = -np.dot(normal, p1)
        
        # Compute distance from all points to plane
        distances = np.abs(np.dot(points, normal) + d)
        
        # Count inliers
        inliers = points[distances < threshold, :]
        if inliers.shape[0] > best_inliers.shape[0]:
            best_inliers = inliers
            best_params = (normal, d)
            
    return best_params, best_inliers

该函数接受一个Nx3的点云数组作为输入，并返回一个元组，其中包含平面的参数（法向量和d参数）以及在阈值内的最佳内点。iterations参数控制随机选择点的次数，threshold参数控制内点的最大距离