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 = 5
sbm.preFilterType = 1
sbm.preFilterSize = 5
sbm.preFilterCap = 30
sbm.minDisparity = 0
sbm.numberOfDisparities = 16
sbm.textureThreshold = 0
sbm.uniquenessRatio = 0
sbm.speckleRange = 2
sbm.speckleWindowSize = 100
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 = 5
#Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range.
sbm.numberOfDisparities = 16
#con valori piu alti tipo 112 viene il contorno nero
sbm.preFilterCap = 1
sbm.minDisparity = 0
#con altri valori smongola
sbm.uniquenessRatio = 7
sbm.speckleWindowSize = 100
sbm.speckleRange = 2
sbm.disp12MaxDiff = 1
sbm.fullDP = False
#a True runna il full-scale two-pass dynamic programming algorithm
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
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 = 9
sbm.preFilterType = 1
sbm.preFilterSize = 5
sbm.preFilterCap = 61
sbm.minDisparity = -39
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 = 96
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
def stereo_depth_map(rectified_pair):
c, r = rectified_pair[0].shape
disparity = cv.CreateMat(c, r, cv.CV_32F)
sbm = cv.CreateStereoBMState()
sbm.SADWindowSize = SWS
sbm.preFilterType = 1
sbm.preFilterSize = PFS
sbm.preFilterCap = PFC
sbm.minDisparity = MDS
sbm.numberOfDisparities = NOD
sbm.textureThreshold = TTH
sbm.uniquenessRatio= UR
sbm.speckleRange = SR
sbm.speckleWindowSize = SPWS
dmLeft = cv.fromarray (rectified_pair[0])
dmRight = cv.fromarray (rectified_pair[1])
cv.FindStereoCorrespondenceBM(dmLeft, dmRight, disparity, sbm)
disparity_grayscale = cv.CreateMat(c, r, cv.CV_8UC1)
cv.Normalize(disparity, disparity_grayscale, 0, 255, cv2.NORM_MINMAX)
disparity_grayscale = np.array(disparity_grayscale, dtype=np.uint8) #without UINT8 returns grayscale
disparity_color = cv2.applyColorMap(disparity_grayscale, cv2.COLORMAP_JET)
return disparity_color
def stereo_depth_map(rectified_pair):
print ('SWS='+str(SWS)+' PFS='+str(PFS)+' PFC='+str(PFC)+' MDS='+\
str(MDS)+' NOD='+str(NOD)+' TTH='+str(TTH))
print(' UR=' + str(UR) + ' SR=' + str(SR) + ' SPWS=' + str(SPWS))
c, r = rectified_pair[0].shape
disparity = cv.CreateMat(c, r, cv.CV_32F)
sbm = cv.CreateStereoBMState()
sbm.SADWindowSize = SWS
sbm.preFilterType = 1
sbm.preFilterSize = PFS
sbm.preFilterCap = PFC
sbm.minDisparity = MDS
sbm.numberOfDisparities = NOD
sbm.textureThreshold = TTH
sbm.uniquenessRatio = UR
sbm.speckleRange = SR
sbm.speckleWindowSize = SPWS
dmLeft = cv.fromarray(rectified_pair[0])
dmRight = cv.fromarray(rectified_pair[1])
cv.FindStereoCorrespondenceBM(dmLeft, dmRight, 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)
return disparity_visual