OpenCV4 Stereo matching

Stereo matchingは古くからある重要な手法。
僕も、いろいろな場面で使っている。
OpenCV4をセットアップしたあと、cpp ディレクトリーに移動

g++  `pkg-config opencv4 --cflags --libs` stereo_match.cpp -o stereo_match -std=c++11 -latomic

stereo_match ../data/aloeL.jpg ../data/aloeR.jpg --algorithm=sgbm --blocksize=3 --max-disparity=128

こんな感じでbuild とコンパイル

で、いろいろパラメータ変えるとこんな感じ

更にフィルターをかけて、、

 pip3 install scikit-learn

 sudo apt install python3-sklearn

import numpy as np

from sklearn.preprocessing import normalize

import cv2

print('loading images...')

imgL = cv2.imread('../data/aloeLs.jpg')  # downscale images for faster processing if you like

imgR = cv2.imread('../data/aloeRs.jpg')

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

window_size = 3

left_matcher = cv2.StereoSGBM_create(

    minDisparity=0,

    numDisparities=80,

    blockSize=1,

    P1=8 * 3 * window_size ** 2,

    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()

Peace!!

stm1 imgKittyl.bmp imgKitty.bmp  --algorithm=sgbm --blocksize=1 --max-disparity=64

stm1 imgKittyl.bmp imgKitty.bmp  --algorithm=sgbm --blocksize=1 --max-disparity=80

stm1 imgKittyl.bmp imgKitty.bmp  --algorithm=sgbm --blocksize=9 --max-disparity=64