双目相机标定python代码
时间: 2023-09-12 10:03:01 浏览: 76
以下是使用Python进行双目相机标定的示例代码:
```python
import numpy as np
import cv2
# 定义标定板的参数
board_size = (9, 6)
square_size = 0.025 # 棋盘格方块尺寸,单位为米
# 设置标定板上角点的坐标
objp = np.zeros((np.prod(board_size), 3), np.float32)
objp[:, :2] = np.indices(board_size).T.reshape(-1, 2)
objp *= square_size
# 存储棋盘格角点的世界坐标和图像坐标
objpoints = [] # 3D points in real world space
imgpoints_l = [] # 2D points in image plane.
imgpoints_r = []
# 加载左右两个相机的图像
img_l = cv2.imread('left.jpg')
img_r = cv2.imread('right.jpg')
# 转换为灰度图像
gray_l = cv2.cvtColor(img_l, cv2.COLOR_BGR2GRAY)
gray_r = cv2.cvtColor(img_r, cv2.COLOR_BGR2GRAY)
# 找到棋盘格角点
ret_l, corners_l = cv2.findChessboardCorners(gray_l, board_size, None)
ret_r, corners_r = cv2.findChessboardCorners(gray_r, board_size, None)
# 如果找到棋盘格角点则存储世界坐标和图像坐标
if ret_l and ret_r:
objpoints.append(objp)
imgpoints_l.append(corners_l)
imgpoints_r.append(corners_r)
# 标定相机
ret_l, mtx_l, dist_l, rvecs_l, tvecs_l = cv2.calibrateCamera(objpoints, imgpoints_l, gray_l.shape[::-1], None, None)
ret_r, mtx_r, dist_r, rvecs_r, tvecs_r = cv2.calibrateCamera(objpoints, imgpoints_r, gray_r.shape[::-1], None, None)
# 计算双目相机的基础矩阵和双目矫正映射
ret, mtx_l, dist_l, mtx_r, dist_r, R, T, E, F = cv2.stereoCalibrate(objpoints, imgpoints_l, imgpoints_r, mtx_l, dist_l, mtx_r, dist_r, gray_l.shape[::-1], flags=cv2.CALIB_FIX_INTRINSIC)
R1, R2, P1, P2, Q, validPixROI1, validPixROI2 = cv2.stereoRectify(mtx_l, dist_l, mtx_r, dist_r, gray_l.shape[::-1], R, T, alpha=1)
# 生成双目矫正映射
map_l_x, map_l_y = cv2.initUndistortRectifyMap(mtx_l, dist_l, R1, P1, gray_l.shape[::-1], cv2.CV_32FC1)
map_r_x, map_r_y = cv2.initUndistortRectifyMap(mtx_r, dist_r, R2, P2, gray_r.shape[::-1], cv2.CV_32FC1)
# 对左右相机的图像进行矫正
img_l_rect = cv2.remap(img_l, map_l_x, map_l_y, cv2.INTER_LINEAR)
img_r_rect = cv2.remap(img_r, map_r_x, map_r_y, cv2.INTER_LINEAR)
```
以上代码演示了如何使用OpenCV进行双目相机标定,包括棋盘格角点检测、相机参数计算、双目矫正映射生成等步骤。注意,这里的代码仅为示例,实际使用时需要根据具体情况进行修改。
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