双目相机标定与校正python
时间: 2023-10-14 17:06:58 浏览: 96
双目相机标定与校正通常需要使用计算机视觉库,比如OpenCV。下面是一个使用Python和OpenCV进行双目相机标定与校正的简单示例代码:
1. 导入库
```
import cv2
import numpy as np
import glob
```
2. 定义棋盘格参数
```
# 棋盘格大小
chessboard_size = (9, 6)
# 棋盘格格点之间的距离
square_size = 0.026
```
3. 获取棋盘格角点
```
# 检测角点的最大尝试次数
max_attempts = 10
# 用于存储角点的数组
obj_points = []
img_points_left = []
img_points_right = []
# 获取所有棋盘格图像的文件名
image_filenames_left = glob.glob('left*.jpg')
image_filenames_right = glob.glob('right*.jpg')
# 遍历所有图像
for image_filename_left, image_filename_right in zip(image_filenames_left, image_filenames_right):
# 读取图像
img_left = cv2.imread(image_filename_left)
img_right = cv2.imread(image_filename_right)
# 转换为灰度图像
gray_left = cv2.cvtColor(img_left, cv2.COLOR_BGR2GRAY)
gray_right = cv2.cvtColor(img_right, cv2.COLOR_BGR2GRAY)
# 查找棋盘格角点
found_left, corners_left = cv2.findChessboardCorners(gray_left, chessboard_size, None)
found_right, corners_right = cv2.findChessboardCorners(gray_right, chessboard_size, None)
# 如果角点被找到
if found_left and found_right:
# 定义角点坐标
objp = np.zeros((chessboard_size[0] * chessboard_size[1], 3), np.float32)
objp[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2) * square_size
# 亚像素级别的精确化
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
corners_left = cv2.cornerSubPix(gray_left, corners_left, (11, 11), (-1, -1), criteria)
corners_right = cv2.cornerSubPix(gray_right, corners_right, (11, 11), (-1, -1), criteria)
# 保存角点
obj_points.append(objp)
img_points_left.append(corners_left)
img_points_right.append(corners_right)
```
4. 双目相机标定
```
# 标定相机
retval, camera_matrix_left, dist_coeffs_left, camera_matrix_right, dist_coeffs_right, R, T, E, F = cv2.stereoCalibrate(
obj_points, img_points_left, img_points_right, None, None, None, None, img_left.shape[::-1], flags=cv2.CALIB_FIX_INTRINSIC)
```
5. 双目相机校正
```
# 生成双目校正映射
R_left, R_right, P_left, P_right, Q, _, _ = cv2.stereoRectify(
camera_matrix_left, dist_coeffs_left, camera_matrix_right, dist_coeffs_right, img_left.shape[::-1], R, T)
left_map_1, left_map_2 = cv2.initUndistortRectifyMap(camera_matrix_left, dist_coeffs_left, R_left, P_left, img_left.shape[::-1], cv2.CV_16SC2)
right_map_1, right_map_2 = cv2.initUndistortRectifyMap(camera_matrix_right, dist_coeffs_right, R_right, P_right, img_left.shape[::-1], cv2.CV_16SC2)
```
这样,你就可以使用生成的校正映射对双目图像进行校正了。
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