我想扭曲和纠正我的立体图像。为此,我在 Python 2.7 中使用了 Opencv 3.3。我使用的代码是:
import cv2
import numpy as np
cameraMatrixL = np.load('mtx_left.npy')
distCoeffsL = np.load('dist_left.npy')
cameraMatrixR = np.load('mtx_right.npy')
distCoeffsR = np.load('dist_right.npy')
R = np.load('R.npy')
T = np.load('T.npy')
imgleft = cv2.imread('D:\python\camera calibration and 3d const\left\left60.png',0)
imgright = cv2.imread('D:\python\camera calibration and 3d const\Right/right60.png',0)
R1,R2,P1,P2,Q,validPixROI1, validPixROI2 = cv2.stereoRectify(cameraMatrixL,distCoeffsL,cameraMatrixR,distCoeffsR,(640,480),R,T,alpha=1)
print Q
# distort images
undistort_map1, rectify_map1 = cv2.initUndistortRectifyMap(cameraMatrixL, distCoeffsR, R1, P1, (640,480), cv2.CV_16SC2)
undistort_map2, rectify_map2 = cv2.initUndistortRectifyMap(cameraMatrixR, distCoeffsR, R2, P2, (640,480), cv2.CV_16SC2)
undistor_output1 = cv2.remap(imgleft, undistort_map1, rectify_map1, cv2.INTER_LINEAR)
undistor_output2 = cv2.remap(imgright, undistort_map2, rectify_map2, cv2.INTER_LINEAR)
cv2.imshow('undistor_output1',undistor_output1)
cv2.imshow('undistor_output2',undistor_output2)
while (True):
if cv2.waitKey(1) & 0xFF == ord('q'):
break
我分别校准了我的相机,然后使用这些获得的矩阵cv2.stereoRectify
来获得R1,R2,P1,P2,Q
我在cv2.initUndistortRectifyMap
. 但我没有正确获得不失真的图像。它看起来像这样:
我的矩阵是:
Q
[[ 1.00000000e+00 0.00000000e+00 0.00000000e+00 -3.23097469e+02]
[ 0.00000000e+00 1.00000000e+00 0.00000000e+00 -2.40008609e+02]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 -7.47885268e+00]
[ 0.00000000e+00 0.00000000e+00 -1.53249612e-02 0.00000000e+00]]
cameraMartix Left
[[ 807.24668269 0. 326.78961645]
[ 0. 620.70299534 259.9187458 ]
[ 0. 0. 1. ]]
camearMatrix Right
[[ 567.37537971 0. 278.76995505]
[ 0. 558.21417195 216.22972643]
[ 0. 0. 1. ]]
Rotation
[[ 0.99973813 -0.02260904 0.00353613]
[ 0.02269951 0.99934817 -0.02807079]
[-0.00289917 0.0281437 0.99959968]]
Tranlation
[[-93.46968934]
[ -1.48741179]
[ 24.98692133]]
我已经阅读了很多答案,但没有解决我的问题。
* OpenCV (cv2) 中的 undistortPoints 与 Python 错误结果
使用 initUndistortRectifyMap 去扭曲图像点
这个问题的解决方案是什么?
谢谢。