問題描述

我有興趣找到一個場景的視差圖.首先，我使用以下代碼進(jìn)行了立體校準(zhǔn)(我在 Google 的幫助下自己編寫了它，在沒有找到任何用 Python 編寫的 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).

我在兩個相機(jī)上同時拍攝了棋盤的圖像，并將它們保存為 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))

如何糾正圖像?在繼續(xù)查找視差圖之前，我還應(yīng)該執(zhí)行哪些其他步驟?我在某處讀到，在計算視差圖時，在兩幀上檢測到的特征應(yīng)該位于同一水平線上.請幫幫我.任何幫助將非常感激.

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.

推薦答案

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()

所以在腳本的其余部分粘貼:

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)

希望這能讓你開始下一件事，可能是計算視差圖"；)

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

參考:

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

這篇關(guān)于立體校準(zhǔn) Opencv Python 和視差圖的文章就介紹到這了，希望我們推薦的答案對大家有所幫助，也希望大家多多支持html5模板網(wǎng)！