Beispiel #1
0
def depthmatch(x,y,leftimage,rightimage,roi=80,buf=50,baseline=2.7,focal_length=80):
    """depthmatch function
    x,y : (int) pixel position of target in left image
    leftimage, rightimage : (IplImage) stereo images
    roi: (int) region of interest around x,y to use in matching
    buf: (int) buffer outside of a straight horizontal search for a match
    """
    #print "Match",x,y
    info = cv.cvGetSize(leftimage)
    width = info.width
    height = info.height
    centerx = width/2
    centery = height/2
    
    (y1,x1,y2,x2) = (y-roi,x-roi,y+roi,x+roi)
    if y1<0: y1 = 0
    if x1<0: x1 = 0
    if y2>height: y2 = height
    if x2>width: x2 = width
    # copy subregion roi x roi

    template_rect = cv.cvRect(x1,y1,(x2-x1),(y2-y1))
    template = cv.cvGetSubRect(leftimage, template_rect)
    
    #(y3,x3,y4,x4) = (y-roi-buf,x-roi-buf,y+roi+buf,width) # +/- 20 pixels in vertical direction, -20 to the right edge

    (y3,x3,y4,x4) = (y-roi-buf,0,y+roi+buf,x+roi+buf) # +/- buf pixels in vertical direction, +buf to the left edge
    if x3<0: x3 = 0
    if y3<0: y3 = 0
    if x4>=width: x4 = width-1
    if y4>height: y4 = height
    #cv.cvSetImageROI(rightimage, (y3,x3,y4,x4))

    rightsub_rect = cv.cvRect(x3,y3,(x4-x3),(y4-y3))
    rightsub = cv.cvGetSubRect(rightimage, rightsub_rect)
    # result matrix should be (W - w + 1) x (H - h + 1) where WxH are template dimensions, wxh are rightsub dimensions
    W = x4-x3
    H = y4-y3
    w = x2-x1
    h = y2-y1

    resy = (y4-y3)-(y2-y1)+1
    resx = (x4-x3)-(x2-x1)+1

    resultmat = cv.cvCreateImage((resx, resy), 32, 1)
    cv.cvZero(resultmat)
    # match template image in a subportion of rightimage
    cv.cvMatchTemplate(rightsub, template, resultmat, cv.CV_TM_SQDIFF)
    min_val, max_val, min_point, max_point = cv.cvMinMaxLoc(resultmat)
    cv.cvNormalize(resultmat, resultmat, 1, 0, cv.CV_MINMAX)
    depth = plane2point(x-centerx, y-centery, x3+min_point.x+roi-centerx, y3+min_point.y+roi-centery, baseline, focal_length)
    #print "Found match at", min_point.x+x3, min_point.y+y3
    return (depth, (x,y), (x3+min_point.x+roi, y3+min_point.y+roi))
Beispiel #2
0
def matchTemplate(self, template, image):
        '''	matchTemplate(self, template, image):		\
                returns - correlation value of best match (b/w 0 & 1)	\
                top-left coord of template for the best match (cvPoint) \
        '''

        matchResultHeight = image.height-template.height+1
        matchResultWidth = image.width-template.width+1

        #print 'matchResultHeight: %d matchResultWidth %d'%(matchResultHeight, matchResultWidth)
        matchResult = cv.cvCreateMat(matchResultHeight, matchResultWidth, cv.CV_32FC1)
        cv.cvMatchTemplate(image, template, matchResult, cv.CV_TM_CCORR_NORMED)

        min_loc = cv.cvPoint(0,0)
        max_loc = cv.cvPoint(0,0)

        min_val, max_val = cv.cvMinMaxLoc(matchResult, min_loc, max_loc)

        return {'image': matchResult , 'max_val':max_val, 'max_loc':max_loc}
Beispiel #3
0
def matchTemplate(self, template, image):
    '''	matchTemplate(self, template, image):		\
                returns - correlation value of best match (b/w 0 & 1)	\
                top-left coord of template for the best match (cvPoint) \
        '''

    matchResultHeight = image.height - template.height + 1
    matchResultWidth = image.width - template.width + 1

    #print 'matchResultHeight: %d matchResultWidth %d'%(matchResultHeight, matchResultWidth)
    matchResult = cv.cvCreateMat(matchResultHeight, matchResultWidth,
                                 cv.CV_32FC1)
    cv.cvMatchTemplate(image, template, matchResult, cv.CV_TM_CCORR_NORMED)

    min_loc = cv.cvPoint(0, 0)
    max_loc = cv.cvPoint(0, 0)

    min_val, max_val = cv.cvMinMaxLoc(matchResult, min_loc, max_loc)

    return {'image': matchResult, 'max_val': max_val, 'max_loc': max_loc}
Beispiel #4
0
def depthmatch(x,y,leftimage,rightimage,roi=20,buf=10,debug=False):
    __doc__ = """depthmatch function
    x,y : (int) pixel position of target in left image
    leftimage, rightimage : (IplImage) stereo images
    roi: (int) region of interest around x,y to use in matching
    buf: (int) buffer outside of a straight horizontal search for a match
    """
    info = cv.cvGetSize(leftimage)
    width = info.width
    height = info.height

    (y1,x1,y2,x2) = (y-roi,x-roi,y+roi,x+roi)
    #template = cv.cvCreateImage((roi*2,roi*2), 8, 3)
    if y1<0: y1 = 0
    if x1<0: x1 = 0
    if y2>height: y2 = height
    if x2>width: x2 = width
    #cv.cvSetZero(template)
    # copy subregion roi x roi

    template_rect = cv.cvRect(x1,y1,(x2-x1),(y2-y1))
    template = cv.cvGetSubRect(leftimage, template_rect)
    (y3,x3,y4,x4) = (y-roi-buf,x-roi-buf,y+roi+buf,width) # +/- 20 pixels in vertical direction, -20 to the right edge
    if x3<0: x3 = 0
    if y3<0: y3 = 0
    if x4>=width: x4 = width-1
    if y4>height: y4 = height
    #cv.cvSetImageROI(rightimage, (y3,x3,y4,x4))

    rightsub_rect = cv.cvRect(x3,y3,(x4-x3),(y4-y3))
    rightsub = cv.cvGetSubRect(rightimage, rightsub_rect)
    # result matrix should be (W - w + 1) x (H - h + 1) where WxH are template dimensions, wxh are rightsub dimensions
    W = x4-x3
    H = y4-y3
    w = x2-x1
    h = y2-y1

    resy = (y4-y3)-(y2-y1)+1
    resx = (x4-x3)-(x2-x1)+1

    resultmat = cv.cvCreateImage((resx, resy), 32, 1)
    cv.cvZero(resultmat)
    # match template image in a subportion of rightimage
    cv.cvMatchTemplate(rightsub, template, resultmat, cv.CV_TM_SQDIFF)
    min_val, max_val, min_point, max_point = cv.cvMinMaxLoc(resultmat)
    cv.cvNormalize(resultmat, resultmat, 1, 0, cv.CV_MINMAX)
    depth = stereo.depth(x, x3+min_point.x, max_pixels=width/2)
    
    if debug:
        print "Input image: %ix%i, target: (%i,%i)" % (width,height,x,y)
        print "Template box: (%i,%i) to (%i,%i)" % (x1, y1, x2, y2)
        print "Search area: (%i,%i) to (%i,%i)" % (x3, y3, x4, y4)
        print "%ix%i, %ix%i" % (W,H,w,h)
        print "Result matrix %ix%i" % (resx, resy)
        print "stereo.depth(%i,%i,max_pixels=%i)" % (x, min_point.x+x3,width/2)
        if depth[0]:
            print "Depth: ", depth[0], "(cm)"
        #cv.cvRectangle(rightimage, cv.cvPoint(x1,y1), cv.cvPoint(x2,y2), (255,0,0))
        cv.cvRectangle(rightimage, cv.cvPoint(min_point.x+x3,min_point.y+y3), cv.cvPoint(min_point.x+x3+roi*2,min_point.y+y3+roi*2), (0,255,0))
        cv.cvRectangle(rightimage, cv.cvPoint(x3,y3), cv.cvPoint(x4,y4), (0,0,255))
        cv.cvRectangle(leftimage, cv.cvPoint(x1,y1), cv.cvPoint(x2,y2), (255,0,0))
        #cv.cvRectangle(leftimage, cv.cvPoint(min_point.x+x3,min_point.y+y3), cv.cvPoint(min_point.x+x3+roi*2,min_point.y+y3+roi*2), (0,255,0))
        cv.cvRectangle(leftimage, cv.cvPoint(x3,y3), cv.cvPoint(x4,y4), (0,0,255))
        if depth[0]:
            cv.cvPutText(leftimage, "%5f(cm)" % depth[0], (x1,y1), font, (255,255,255))
        highgui.cvShowImage("depthmatch - template", template)
        highgui.cvShowImage("depthmatch - match", resultmat)
        highgui.cvShowImage("depthmatch - right", rightimage)
        highgui.cvShowImage("depthmatch - left", leftimage)