深度相机标定python代码

以下是使用Python OpenCV库进行深度相机标定的示例代码：

import numpy as np
import cv2

# 读取标定图像
img1 = cv2.imread('calibration1.jpg')
img2 = cv2.imread('calibration2.jpg')
img3 = cv2.imread('calibration3.jpg')
img4 = cv2.imread('calibration4.jpg')
img5 = cv2.imread('calibration5.jpg')
img6 = cv2.imread('calibration6.jpg')

# 定义标定图像的棋盘格大小
rows = 9
cols = 6

# 提取棋盘格角点
objpoints = []
imgpoints = []

objp = np.zeros((rows*cols, 3), np.float32)
objp[:, :2] = np.mgrid[0:cols, 0:rows].T.reshape(-1, 2)
objp *= 25.0

gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
gray3 = cv2.cvtColor(img3, cv2.COLOR_BGR2GRAY)
gray4 = cv2.cvtColor(img4, cv2.COLOR_BGR2GRAY)
gray5 = cv2.cvtColor(img5, cv2.COLOR_BGR2GRAY)
gray6 = cv2.cvtColor(img6, cv2.COLOR_BGR2GRAY)

ret1, corners1 = cv2.findChessboardCorners(gray1, (cols, rows), None)
ret2, corners2 = cv2.findChessboardCorners(gray2, (cols, rows), None)
ret3, corners3 = cv2.findChessboardCorners(gray3, (cols, rows), None)
ret4, corners4 = cv2.findChessboardCorners(gray4, (cols, rows), None)
ret5, corners5 = cv2.findChessboardCorners(gray5, (cols, rows), None)
ret6, corners6 = cv2.findChessboardCorners(gray6, (cols, rows), None)

if ret1 and ret2 and ret3 and ret4 and ret5 and ret6:
    objpoints.append(objp)
    imgpoints.append(corners1)
    imgpoints.append(corners2)
    imgpoints.append(corners3)
    imgpoints.append(corners4)
    imgpoints.append(corners5)
    imgpoints.append(corners6)

    # 标定相机
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray1.shape[::-1], None, None)

    # 显示标定结果
    print("Camera matrix:")
    print(mtx)
    print("Distortion coefficients:")
    print(dist)
else:
    print("Failed to detect chessboard corners in one or more calibration images.")

此代码将读取六个标定图像，并使用`cv2.findChessboardCorners()`函数提取每个图像中的棋盘格角点。然后，将棋盘格角点的物理坐标和像素坐标添加到`objpoints`和`imgpoints`数组中。最后，使用`cv2.calibrateCamera()`函数计算相机的内部参数矩阵和畸变系数，并将结果打印到控制台上。