Question

我有立体声图像（来自picryl.com），我想将它们转换为可以上传到Facebook（.glb格式）的3D图像

尝试生成深度图并将其转换为3D模型。

import numpy as np
from sklearn.preprocessing import normalize
import cv2

print('loading images...')
imgL = cv2.imread('l_active.png')  # downscale images for faster processing
imgR = cv2.imread('r_active.png')

# 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=32,    #160         # max_disp has to be dividable by 16 f. E. HH 192, 256
    blockSize=5,
    P1=8 * 5 * 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) 
//save here

最终的3D模型甚至看起来都不像原始的

如何从立体图像中获取Facebook 3D图像

0 个答案: