立体校准 Opencv Python 和视差图

2022-01-09 00:00:00 python opencv computer-vision image-processing camera-calibration

问题描述

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校准(我在 Google 的帮助下自己编写了它，在没有找到任何用 Python 编写的 OpenCV 2.4.10 相同的有用教程之后).

I am interested in finding the disparity map of a scene. To start with, I did stereo calibration using the following code (I wrote it myself with a little help from Google, after failing to find any helpful tutorials for the same written in python for OpenCV 2.4.10).

我在两个相机上同时拍摄了棋盘的图像，并将它们保存为 left*.jpg 和 right*.jpg.

I took images of a chessboard simultaneously on both cameras and saved them as left*.jpg and right*.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，我还应该执行哪些其他步骤?我在某处读到，在计算视差图时，在两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.

How do I rectify the images? What other steps should I do before going on to find the disparity map? I read somewhere that while calculating the disparity map, the features detected on both frames should lie on the same horizontal line. Please help me out here. Any help would be much appreciated.

解决方案

你需要cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2 和 cv2.undistort() 的newCameraMatrix"

you need cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2 and "newCameraMatrix" for cv2.undistort()

您可以使用 cv2.getOptimalNewCameraMatrix()

所以在脚本的其余部分粘贴:

so in the remainder of your script paste this:

# 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)

希望这能让你开始下一件事，可能是计算视差图"；)

hope that gets you on your way to the next thing which might be calculating "disparity maps" ;)

参考:

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

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