立体声校准Opencv Python和视差图

Question

我有兴趣找到一个场景的视差图。首先，我使用以下代码进行了立体声校准（我自己写了一些来自Google的帮助，因为没有找到任何有用的教程，用于在OpenCV 2.4.10的python中编写）。

我在两台摄像机上同时拍摄了棋盘图像，并将它们保存为左* .jpg和右* .jpg。

import numpy as np
import cv2
import glob

# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*9,3), np.float32)
objp[:,:2] = np.mgrid[0:9,0:6].T.reshape(-1,2)


# Arrays to store object points and image points from all the images.
objpointsL = [] # 3d point in real world space
imgpointsL = [] # 2d points in image plane.
objpointsR = []
imgpointsR = []

images = glob.glob('left*.jpg')

for fname in images:
    img = cv2.imread(fname)
    grayL = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    # Find the chess board corners
    ret, cornersL = cv2.findChessboardCorners(grayL, (9,6),None)
    # If found, add object points, image points (after refining them)
    if ret == True:
        objpointsL.append(objp)

        cv2.cornerSubPix(grayL,cornersL,(11,11),(-1,-1),criteria)
        imgpointsL.append(cornersL)


images = glob.glob('right*.jpg')

for fname in images:
    img = cv2.imread(fname)
    grayR = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    # Find the chess board corners
    ret, cornersR = cv2.findChessboardCorners(grayR, (9,6),None)

    # If found, add object points, image points (after refining them)
    if ret == True:
        objpointsR.append(objp)

        cv2.cornerSubPix(grayR,cornersR,(11,11),(-1,-1),criteria)
        imgpointsR.append(cornersR)



retval,cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F = cv2.stereoCalibrate(objpointsL, imgpointsL, imgpointsR, (320,240))

如何纠正图像？在继续查找视差图之前，我还应该采取哪些其他步骤？我在某处读到，在计算视差图时，在两个帧上检测到的特征应该位于同一水平线上。请帮帮我。任何帮助将非常感激。

Answer 1

cameraMatrix1你需要distCoeffs1，cameraMatrix2，distCoeffs2，cv2.undistort()和“newCameraMatrix”

你可以使用cv2.getOptimalNewCameraMatrix()获得“newCameraMatrix”

所以在你的脚本的其余部分粘贴这个：

# Assuming you have left01.jpg and right01.jpg that you want to rectify
lFrame = cv2.imread('left01.jpg')
rFrame = cv2.imread('right01.jpg')
w, h = lFrame.shape[:2] # both frames should be of same shape
frames = [lFrame, rFrame]

# Params from camera calibration
camMats = [cameraMatrix1, cameraMatrix2]
distCoeffs = [distCoeffs1, distCoeffs2]

camSources = [0,1]
for src in camSources:
    distCoeffs[src][0][4] = 0.0 # use only the first 2 values in distCoeffs

# The rectification process
newCams = [0,0]
roi = [0,0]
for src in camSources:
    newCams[src], roi[src] = cv2.getOptimalNewCameraMatrix(cameraMatrix = camMats[src], 
                                                           distCoeffs = distCoeffs[src], 
                                                           imageSize = (w,h), 
                                                           alpha = 0)



rectFrames = [0,0]
for src in camSources:
        rectFrames[src] = cv2.undistort(frames[src], 
                                        camMats[src], 
                                        distCoeffs[src])

# See the results
view = np.hstack([frames[0], frames[1]])    
rectView = np.hstack([rectFrames[0], rectFrames[1]])

cv2.imshow('view', view)
cv2.imshow('rectView', rectView)

# Wait indefinitely for any keypress
cv2.waitKey(0)

希望能让你走向可能正在计算“视差图”的下一件事;）

参考：

http://www.janeriksolem.net/2014/05/how-to-calibrate-camera-with-opencv-and.html

Answer 2

试试这段代码，我已经能够解决这个错误：

retVal, cm1, dc1, cm2, dc2, r, t, e, f = cv2.stereoCalibrate(objpointsL, imgpointsL, imgpointsR, (320, 240), None, None,None,None)

Answer 3

首先，使用opencv校准应用程序或matlab calibration toolbox来计算相机参数。使用参数，您可以纠正您的图像。

在整改之后，请参考opencv的代码库中的python示例（samples / python / stereo_match.py​​）来计算视差图。