cv2.stereoBM + WLS

matplotlib을 3d로 그려보는 것 까지 통합완료. 이제 SGBM만 해보면 될 듯

WLS 필터 미적용	WLS 필터 적용

 

 

import numpy as np import cv2 as cv from matplotlib import pyplot as plt imgL = cv.imread('tsukuba_l.png', cv.IMREAD_GRAYSCALE) imgR = cv.imread('tsukuba_r.png', cv.IMREAD_GRAYSCALE) max_disparity=16 stereo = cv.StereoBM_create(max_disparity, blockSize=15) disparity = stereo.compute(imgL,imgR) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') # X, Y 좌표 생성 height, width = imgL.shape x = np.arange(0, width, 1) y = np.arange(0, height, 1) x, y = np.meshgrid(x, y) # 깊이 맵을 사용하여 Z 좌표 생성 z = disparity # 3D 그래프에 표시 ax.plot_surface(x, y, z, cmap='viridis') plt.show() # WLS 필터 적용 right_matcher = cv.ximgproc.createRightMatcher(stereo); left_disp = stereo.compute(imgL, imgR); right_disp = right_matcher.compute(imgR, imgL); # Now create DisparityWLSFilter wls_filter = cv.ximgproc.createDisparityWLSFilter(stereo); sigma = 1.5 lmbda = 8000.0 wls_filter.setLambda(lmbda); wls_filter.setSigmaColor(sigma); filtered_disp = wls_filter.filter(left_disp, imgL, disparity_map_right=right_disp); fig = plt.figure() ax = fig.add_subplot(111, projection='3d') z = filtered_disp # 3D 그래프에 표시 ax.plot_surface(x, y, z, cmap='viridis') plt.show()