python 相机标定并获取点云图像代码
时间: 2023-08-12 19:13:55 浏览: 39
以下是一个简单的 Python 代码示例,展示如何进行相机标定并获取点云图像:
```
import cv2
import numpy as np
import open3d as o3d
# 准备相机标定板
pattern_size = (9, 6) # 标定板上的内角点数量
square_size = 0.02 # 标定板上每个方格的大小,单位为米
objp = np.zeros((pattern_size[0] * pattern_size[1], 3), np.float32)
objp[:, :2] = np.mgrid[0:pattern_size[0], 0:pattern_size[1]].T.reshape(-1, 2) * square_size
# 拍摄标定板的多张照片
image_paths = ['img1.jpg', 'img2.jpg', 'img3.jpg', ...]
objpoints = [] # 存储标定板上的三维坐标
imgpoints = [] # 存储照片中的二维像素坐标
for image_path in image_paths:
img = cv2.imread(image_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, pattern_size, None)
if ret:
objpoints.append(objp)
imgpoints.append(corners)
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
# 畸变矫正
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, gray.shape[::-1], 1, gray.shape[::-1])
mapx, mapy = cv2.initUndistortRectifyMap(mtx, dist, None, newcameramtx, gray.shape[::-1], 5)
img = cv2.imread('img.jpg')
dst = cv2.remap(img, mapx, mapy, cv2.INTER_LINEAR)
# 点云转换
K = newcameramtx
P = np.hstack((K, np.zeros((3, 1))))
points3d = cv2.triangulatePoints(P, P, imgpoints[0].T, imgpoints[1].T)
points3d /= points3d[3]
points3d = points3d[:3].T
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(points3d)
# 可视化
o3d.visualization.draw_geometries([pcd])
```
需要注意的是,这只是一个简单的示例代码,实际操作中可能会涉及到更多的细节和问题,需要根据具体情况进行调整和修改。