相机标定和计算立体视差图的问题

Question

我正在做一个项目，我需要使用立体视觉来计算人和物体与相机的深度和距离。我使用的是 OpenCV 和 Waveshare 的 IMX219-83 相机，与 Jetson Nano 开发人员套件集成。左摄像头，另一个来自右摄像头。我提供了带有校准参数的 XML 文件，但是当我运行代码时，出现了一个问题：图像向右倾斜，视差有噪声，导致无法识别更近的物体；这只是一个模糊。图像帧大小为 640x480。任何测试图像都会出现此问题。下面是校准代码和视差代码。 （如果问题不够清楚，请让我知道，因为我是使用该平台的新手。） 棋盘图像存储库的链接：https://drive.google.com/drive/folders/1jYZWDD02vziBKb2vnG1CTdzMo64xEUJI?usp=share_link

from __future__ import print_function

//code of disparity -----------------------------
//-----------------------------------------------------------

import numpy as np
import cv2


def main():
    cv_file = cv2.FileStorage()
    cv_file.open('stereoMap.xml', cv2.FILE_STORAGE_READ)
    stereoMapL_x = cv_file.getNode('stereoMapL_x').mat()
    stereoMapL_y = cv_file.getNode('stereoMapL_y').mat()
    stereoMapR_x = cv_file.getNode('stereoMapR_x').mat()
    stereoMapR_y = cv_file.getNode('stereoMapR_y').mat()
    imgL = cv2.imread("EpipolarGeometryAndStereoVision/left-images/left/fotoeditada.jpg", 0)
    imgL = cv2.resize(imgL, (640, 480))
    imgL = cv2.remap(imgL, stereoMapL_x, stereoMapL_y, 0, 0, 0)

    imgR = cv2.imread("EpipolarGeometryAndStereoVision/right-images/right/fotoeditadaright.jpg", 0)
    # imgR = cv2.resize(imgR, (640, 480))
    imgR = cv2.remap(imgR, stereoMapR_x, stereoMapR_y,  0, 0, 0)

    
    

    # Setting parameters for StereoSGBM algorithm
    minDisparity = 1
    numDisparities = 60 - minDisparity
    blockSize = 5
    uniquenessRatio = 1
    speckleWindowSize = 3
    speckleRange = 3
    disp12MaxDiff = 100
    # width = 640
    # baseline = 0.6
    P1 = 8 * 3 * blockSize ** 2
    P2 = 32 * 3 * blockSize ** 2

    stereo = cv2.StereoSGBM_create(
        minDisparity=minDisparity,
        numDisparities=numDisparities,
        blockSize=blockSize,
        uniquenessRatio=uniquenessRatio,
        speckleWindowSize=speckleWindowSize,
        speckleRange=speckleRange,
        disp12MaxDiff=disp12MaxDiff,
        P1=P1,
        P2=P2
    )

    # Calculating disparith using the StereoSGBM algorithm
    disparity = stereo.compute(imgL, imgR).astype(np.float32) / 16.0

    cv2.imshow('leftview',imgL)
    cv2.imshow('rightview', imgR)
    cv2.imshow('disparity', (disparity - minDisparity) / numDisparities)
    cv2.waitKey()


if __name__ == '__main__':
    main()
    cv2.destroyAllWindows()


//code of stereo camera calibration ---------------------------------------
//---------------------------------------------------------------------------

import numpy as np
import cv2 as cv
import glob

#####find chessboard corners - objecr points and image points

chessboardSize = (8,6)
frameSize = (480, 640)

#termination criteria

criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)


#prepare objetcs points

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

objp = objp * 24
print(objp)

# arrays to store object points and image points from all the images

objpoints = [] #3d point in the real world space
imgpointsL = [] # 2d points in image plane
imgpointsR = [] #2d points in image plane

imagesLeft = glob.glob('calibration/camera1/*.jpg')
# print(imagesLeft)
imagesRight = glob.glob('calibration/camera0/*.jpg')


for imgLeft, imgRight in zip(imagesLeft, imagesRight):
    imgL = cv.imread(imgLeft)
    imgR = cv.imread(imgRight)
    grayL = cv.cvtColor(imgL, cv.COLOR_BGR2GRAY)
    grayR = cv.cvtColor(imgR, cv.COLOR_BGR2GRAY)

    #find the chessboard corners
    retL, cornersL = cv.findChessboardCorners(grayL, chessboardSize, None)
    retR, cornersR = cv.findChessboardCorners(grayR, chessboardSize, None)

    #if found, add object points, images points (after refining them)

    if retL and retR == True:

        objpoints.append(objp)

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

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

        #Draw and display the coorners

        cv.drawChessboardCorners(grayL, chessboardSize, cornersL, retL)
        cv.imshow('img left', grayL)
        cv.drawChessboardCorners(grayR, chessboardSize, cornersR, retR)
        cv.imshow('img right', grayR)
        cv.waitKey(1000)

cv.destroyAllWindows()

####################### CALIIBRATION 

retL, cameraMatrixL, distL, rvecsL, tvecsL = cv.calibrateCamera(objpoints, imgpointsL, frameSize, None, None)
heightL, widthL, channelsL = imgL.shape
newCameraMatrixL, roi_L = cv.getOptimalNewCameraMatrix(cameraMatrixL, distL, (widthL, heightL), 1, (widthL, heightL))

retR, cameraMatrixR, distR, rvecsR, tvecsR = cv.calibrateCamera(objpoints, imgpointsR, frameSize, None, None)
heightR, widthR, channelsR = imgR.shape
newCameraMatrixR, roi_R = cv.getOptimalNewCameraMatrix(cameraMatrixR, distR, (widthR, heightR), 1, (widthR, heightR))

############ STEREO VISION CALIBRATION #######

flags = 0
flags |= cv.CALIB_FIX_INTRINSIC

#here we fix the intrisic camara matrixes so that only rot, trns, emat and fmat are calculated
#hence intriscic parameters are the same

criteria_stereo = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)

#this step is performed to transformation between the two cameras and calculate essential and fundamental matrix

retStereo, newCameraMatrixL, distL, newCameraMatrixR, distR, rot, trans, essentialMatrix, fundamentalMatrix = cv.stereoCalibrate(objpoints, imgpointsL, imgpointsR, newCameraMatrixL, distL, newCameraMatrixR, distR, grayL.shape[::-1], criteria_stereo, flags)

########## Stereo Rectification #################################################

rectifyScale= 1
rectL, rectR, projMatrixL, projMatrixR, Q, roi_L, roi_R = cv.stereoRectify(newCameraMatrixL, distL, newCameraMatrixR, distR, grayL.shape[::-1], rot, trans, rectifyScale,(0,0))

stereoMapL = cv.initUndistortRectifyMap(newCameraMatrixL, distL, rectL, projMatrixL, grayL.shape[::-1], cv.CV_16SC2)
stereoMapR = cv.initUndistortRectifyMap(newCameraMatrixR, distR, rectR, projMatrixR, grayR.shape[::-1], cv.CV_16SC2)

print("Saving parameters!")
cv_file = cv.FileStorage('stereoMap.xml', cv.FILE_STORAGE_WRITE)

cv_file.write('stereoMapL_x',stereoMapL[0])
cv_file.write('stereoMapL_y',stereoMapL[1])
cv_file.write('stereoMapR_x',stereoMapR[0])
cv_file.write('stereoMapR_y',stereoMapR[1])

cv_file.release()