Python cv2.StereoBM_create() Examples

The following are 4 code examples of cv2.StereoBM_create(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: keyframes.py    From pyslam with MIT License 8 votes vote down vote up 
def compute_disparity_pyramid(self):
        self.disparity = []
        stereo = cv2.StereoBM_create()
        # stereo = cv2.StereoSGBM_create(minDisparity=0,
        #                                numDisparities=64,
        #                                blockSize=11)

        # Compute disparity at full resolution and downsample
        disp = stereo.compute(self.im_left, self.im_right).astype(float) / 16.

        for pyrlevel in range(self.pyrlevels):
            if pyrlevel == 0:
                self.disparity = [disp]
            else:
                pyr_factor = 2**-pyrlevel
                # disp = cv2.pyrDown(disp) # Applies a large Gaussian blur
                # kernel!
                disp = disp[0::2, 0::2]
                self.disparity.append(disp * pyr_factor)
Example #2
Source File: keyframes.py    From pyslam with MIT License 6 votes vote down vote up 
def compute_depth_pyramid(self):
        self.depth = []
        stereo = cv2.StereoBM_create()
        # stereo = cv2.StereoSGBM_create(minDisparity=0,
        #                                numDisparities=64,
        #                                blockSize=11)

        # Compute disparity at full resolution and downsample
        depth = self.data[1]

        for pyrlevel in range(self.pyrlevels):
            if pyrlevel == 0:
                self.depth = [depth]
            else:
                pyr_factor = 2**-pyrlevel
                depth = depth[0::2, 0::2]
                self.depth.append(depth)
Example #3
Source File: stereo_matcher_app.py    From cvcalib with Apache License 2.0 6 votes vote down vote up 
def disparity(self):
        matcher = cv2.StereoBM_create(1024, 7)
        disparity = matcher.compute(cv2.cvtColor(self.images[0], cv2.COLOR_BGR2GRAY),
                                    cv2.cvtColor(self.images[1], cv2.COLOR_BGR2GRAY))
        self.process_output(disparity)
Example #4
Source File: 5_dm_tune.py    From stereopi-tutorial with GNU General Public License v3.0 4 votes vote down vote up 
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 = np.zeros((c, r), np.uint8)
    sbm = cv2.StereoBM_create(numDisparities=16, blockSize=15)
    #sbm.SADWindowSize = SWS
    sbm.setPreFilterType(1)
    sbm.setPreFilterSize(PFS)
    sbm.setPreFilterCap(PFC)
    sbm.setMinDisparity(MDS)
    sbm.setNumDisparities(NOD)
    sbm.setTextureThreshold(TTH)
    sbm.setUniquenessRatio(UR)
    sbm.setSpeckleRange(SR)
    sbm.setSpeckleWindowSize(SPWS)
    dmLeft = rectified_pair[0]
    dmRight = rectified_pair[1]
    #cv2.FindStereoCorrespondenceBM(dmLeft, dmRight, disparity, sbm)
    disparity = sbm.compute(dmLeft, dmRight)
    #disparity_visual = cv.CreateMat(c, r, cv.CV_8U)
    local_max = disparity.max()
    local_min = disparity.min()
    print ("MAX " + str(local_max))
    print ("MIN " + str(local_min))
    disparity_visual = (disparity-local_min)*(1.0/(local_max-local_min))
    local_max = disparity_visual.max()
    local_min = disparity_visual.min()
    print ("MAX " + str(local_max))
    print ("MIN " + str(local_min))
    #cv.Normalize(disparity, disparity_visual, 0, 255, cv.CV_MINMAX)
    #disparity_visual = np.array(disparity_visual)
    return disparity_visual