Whats the problem with my script?

Python
,
1

im trying to use cv2.StereoSGBMcreate to make depthmap

this is my code

import numpy as np

from sklearn.preprocessing import normalize

import cv2

 

print('loading images...')

imgL = cv2.imread('imgl.jpg')  # downscale images for faster processing

imgR = cv2.imread('imgr.jpg')

 

# SGBM Parameters -----------------

window_size = 3                     # wsize default 3; 5; 7 for SGBM reduced size image; 15 for SGBM full size image (1300px and above); 5 Works nicely

 

left_matcher = cv2.StereoSGBM_create(

    minDisparity=0,

    numDisparities=160,             # max_disp has to be dividable by 16 f. E. HH 192, 256

    blockSize=5,

    P1=8 * 3 * window_size ** 2,    # wsize default 3; 5; 7 for SGBM reduced size image; 15 for SGBM full size image (1300px and above); 5 Works nicely

    P2=32 * 3 * window_size ** 2,

    disp12MaxDiff=1,

    uniquenessRatio=15,

    speckleWindowSize=0,

    speckleRange=2,

    preFilterCap=63,

    mode=cv2.STEREO_SGBM_MODE_SGBM_3WAY

)

 

right_matcher = cv2.ximgproc.createRightMatcher(left_matcher)

 

# FILTER Parameters

lmbda = 80000

sigma = 1.2

visual_multiplier = 1.0

 

wls_filter = cv2.ximgproc.createDisparityWLSFilter(matcher_left=left_matcher)

wls_filter.setLambda(lmbda)

wls_filter.setSigmaColor(sigma)

 

print('computing disparity...')

displ = left_matcher.compute(imgL, imgR)  # .astype(np.float32)/16

dispr = right_matcher.compute(imgR, imgL)  # .astype(np.float32)/16

displ = np.int16(displ)

dispr = np.int16(dispr)

filteredImg = wls_filter.filter(displ, imgL, None, dispr)  # important to put "imgL" here!!!

 

filteredImg = cv2.normalize(src=filteredImg, dst=filteredImg, beta=0, alpha=255, norm_type=cv2.NORM_MINMAX);

filteredImg = np.uint8(filteredImg)

cv2.imshow('Disparity Map', filteredImg)

cv2.waitKey()

cv2.destroyAllWindows()

and this is my result

result
result1152×648 7.69 KB

plz can anyone hlep?