在Python上的OpenCV中进行StereoCalibration [英] StereoCalibration in OpenCV on Python

问题描述

我是OpenCV的新手，无法在Python上找到有关stereoCalibration的常规教程.如果您有样品，请分享.

I am new in OpenCV, and could not find normal tutorial for stereoCalibration on Python. If you have some samples, please share.

我对每个摄像机都进行一次校准，所以我有下一个问题.左一个:

I do single calibration for each of cameras, and i have next problem. The left one:

正确的一个:

PS:我正在做深度图，从它的高度看，我收到了不好的图.

PS: I'm doing Depth-map and by the metter of it, i received bad map.

更新:我已经从

UPDATE: I have ported the C++ version from https://github.com/jayrambhia/Vision/blob/master/OpenCV/C%2B%2B/stereocalibrate.cpp Yeah, it has no error but it return only fully black images Ported cod:

import numpy as np
import cv2

print "Welcome\n"

numBoards = 30  #how many boards would you like to find
board_w = 7
board_h = 6

board_sz = (7,6)
board_n = board_w*board_h

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

# Arrays to store object points and image points from all the images.
object_points = [] # 3d point in real world space
imagePoints1 = [] # 2d points in image plane.
imagePoints2 = [] # 2d points in image plane.

corners1 = []
corners2 = []

#obj = []
#for j in range(0,board_n):
    #obj.append(np.(j/board_w, j%board_w, 0.0))
obj = np.zeros((6*7,3), np.float32)
obj[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)



vidStreamL = cv2.VideoCapture(0)  # index of your camera
vidStreamR = cv2.VideoCapture(1)  # index of your camera
success = 0
k = 0
found1 = False
found2 = False

while (success < numBoards):

   retL, img1 = vidStreamL.read()
   height, width, depth  = img1.shape
   retR, img2 = vidStreamR.read()
   #resize(img1, img1, Size(320, 280));
   #resize(img2, img2, Size(320, 280));
   gray1 = cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)
   gray2 = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)

   found1, corners1 = cv2.findChessboardCorners(img1, board_sz)
   found2, corners2 = cv2.findChessboardCorners(img2, board_sz)

   if (found1):
       cv2.cornerSubPix(gray1, corners1, (11, 11), (-1, -1),criteria)
       cv2.drawChessboardCorners(gray1, board_sz, corners1, found1)

   if (found2):
       cv2.cornerSubPix(gray2, corners2, (11, 11), (-1, -1), criteria)
       cv2.drawChessboardCorners(gray2, board_sz, corners2, found2)

   cv2.imshow('image1', gray1)
   cv2.imshow('image2', gray2)

   k = cv2.waitKey(100)
   print k
   if (k == 27):
       break
   if (k == 32 and found1 != 0 and found2 != 0):

       imagePoints1.append(corners1);
       imagePoints2.append(corners2);
       object_points.append(obj);
       print "Corners stored\n"
       success+=1

       if (success >= numBoards):
           break

cv2.destroyAllWindows()
print "Starting Calibration\n"
cameraMatrix1 = cv2.cv.CreateMat(3, 3, cv2.CV_64FC1)
cameraMatrix2 = cv2.cv.CreateMat(3, 3, cv2.CV_64FC1)

retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F = cv2.stereoCalibrate(object_points, imagePoints1, imagePoints2, (width, height))
## , cv2.cvTermCriteria(cv2.CV_TERMCRIT_ITER+cv2.CV_TERMCRIT_EPS, 100, 1e-5),   cv2.CV_CALIB_SAME_FOCAL_LENGTH | cv2.CV_CALIB_ZERO_TANGENT_DIST)
#cv2.cv.StereoCalibrate(object_points, imagePoints1, imagePoints2, pointCounts, cv.fromarray(K1), cv.fromarray(distcoeffs1), cv.fromarray(K2), cv.fromarray(distcoeffs2), imageSize, cv.fromarray(R), cv.fromarray(T), cv.fromarray(E), cv.fromarray(F), flags = cv.CV_CALIB_FIX_INTRINSIC)
#FileStorage fs1("mystereocalib.yml", FileStorage::WRITE);
# fs1 << "CM1" << CM1;
#fs1 << "CM2" << CM2;
# #fs1 << "D1" << D1;
#fs1 << "D2" << D2;
#fs1 << "R" << R;
#fs1 << "T" << T;
#fs1 << "E" << E;
#fs1 << "F" << F;
print "Done Calibration\n"
print "Starting Rectification\n"
R1 = np.zeros(shape=(3,3))
R2 = np.zeros(shape=(3,3))
P1 = np.zeros(shape=(3,3))
P2 = np.zeros(shape=(3,3))

#(roi1, roi2) = cv2.cv.StereoRectify(cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,(width, height), R, T, R1, R2, P1, P2, Q=None, flags=cv2.cv.CV_CALIB_ZERO_DISPARITY, alpha=-1, newImageSize=(0, 0))
cv2.stereoRectify(cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,(width, height), R, T, R1, R2, P1, P2, Q=None, flags=cv2.cv.CV_CALIB_ZERO_DISPARITY, alpha=-1, newImageSize=(0,0))
#stereoRectify(cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,(width, height), R, T)

#fs1 << "R1" << R1;
#fs1 << "R2" << R2;
#fs1 << "P1" << P1;
#fs1 << "P2" << P2;
#fs1 << "Q" << Q;

print "Done Rectification\n"
print "Applying Undistort\n"



map1x, map1y = cv2.initUndistortRectifyMap(cameraMatrix1, distCoeffs1, R1, P1, (width, height), cv2.CV_32FC1)
map2x, map2y = cv2.initUndistortRectifyMap(cameraMatrix2, distCoeffs2, R2, P2, (width, height), cv2.CV_32FC1)

print "Undistort complete\n"

while(True):
    retL, img1 = vidStreamL.read()
    retR, img2 = vidStreamR.read()
    imgU1 = np.zeros((height,width,3), np.uint8)
    imgU1 = cv2.remap(img1, map1x, map1y, cv2.INTER_LINEAR, imgU1, cv2.BORDER_CONSTANT, 0)
    imgU2 = cv2.remap(img2, map2x, map2y, cv2.INTER_LINEAR)
    cv2.imshow("imageL", img1);
    cv2.imshow("imageR", img2);
    cv2.imshow("image1L", imgU1);
    cv2.imshow("image2R", imgU2);
    k = cv2.waitKey(5);
    if(k==27):
        break;

推荐答案

P1和P2的大小应为3,4用3,3初始化时，它们会变空P1 = np.zeros(形状=(3,4))P2 = np.zeros(shape =(3,4))

P1 and P2 should be size 3,4 when initialized with 3,3 you get them back empty P1 = np.zeros(shape=(3,4)) P2 = np.zeros(shape=(3,4))

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