CODEWITHSUNDEEP
pythonopencvimage-processingdistancedepth
Anna1994
Anna1994

Reputation: 150

Python: How to get real depth from disparity map

I am a complete beginner I am trying to obtain real depth map from left and right image. I've used OpenCV to get the disparity map via block matching as you can see in the code bellow.

import cv2
import cv2.cv as cv
import sys
import numpy as np

def getDisparity(imgLeft, imgRight, method="BM"):

gray_left = cv2.cvtColor(imgLeft, cv.CV_BGR2GRAY)
gray_right = cv2.cvtColor(imgRight, cv.CV_BGR2GRAY)
print gray_left.shape
c, r = gray_left.shape
if method == "BM":
    sbm = cv.CreateStereoBMState()
    disparity = cv.CreateMat(c, r, cv.CV_32F)
    sbm.SADWindowSize = 11
    sbm.preFilterType = 1
    sbm.preFilterSize = 5
    sbm.preFilterCap = 61
    sbm.minDisparity = -50
    sbm.numberOfDisparities = 112
    sbm.textureThreshold = 507
    sbm.uniquenessRatio= 0
    sbm.speckleRange = 8
    sbm.speckleWindowSize = 0

    gray_left = cv.fromarray(gray_left)
    gray_right = cv.fromarray(gray_right)

    cv.FindStereoCorrespondenceBM(gray_left, gray_right, disparity, sbm)
    disparity_visual = cv.CreateMat(c, r, cv.CV_8U)
    cv.Normalize(disparity, disparity_visual, 0, 255, cv.CV_MINMAX)
    disparity_visual = np.array(disparity_visual)

elif method == "SGBM":
    sbm = cv2.StereoSGBM()
    sbm.SADWindowSize = 9;
    sbm.numberOfDisparities = 0;
    sbm.preFilterCap = 63;
    sbm.minDisparity = -21;
    sbm.uniquenessRatio = 7;
    sbm.speckleWindowSize = 0;
    sbm.speckleRange = 8;
    sbm.disp12MaxDiff = 1;
    sbm.fullDP = False;

    disparity = sbm.compute(gray_left, gray_right)
    disparity_visual = cv2.normalize(disparity, alpha=0, beta=255, norm_type=cv2.cv.CV_MINMAX, dtype=cv2.cv.CV_8U)

return disparity_visual

imgLeft = cv2.imread('1.png')
imgRight = cv2.imread('2.png')
try:
    method = "BM"
except IndexError:
    method = "BM"

disparity = getDisparity(imgLeft, imgRight, method)
cv2.imshow("disparity", disparity)
#cv2.imshow("left", imgLeft)
#cv2.imshow("right", imgRight)
cv2.waitKey(0)

My question is what is the easiest way to obtain real depth map (distance) from disparity using python?

Upvotes: 3

Views: 9318

Answers (2)

Vincent Vidal
Vincent Vidal

Reputation: 333

Assuming your cameras are calibrated, the images rectified, you can use the formula provided by this tutorial which is:

disparity = Baseline * focal-lens / depth

So, 

depth = Baseline * focal-lens / disparity

Upvotes: 0

Photon
Photon

Reputation: 3222

In order to calculate depth for stereo, you need to know the translation and rotation between the cameras. If you have that, you can take each disparity value and use triangulation to calculate the depth for that 3D point.

I recommend reading http://www.robots.ox.ac.uk/~vgg/hzbook/ for a detailed explanation.

Upvotes: 2

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