Python cv2.GC_INIT_WITH_RECT Examples

The following are 2 code examples of cv2.GC_INIT_WITH_RECT(). 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: image_segmentation.py    From OpenCV-3-x-with-Python-By-Example with MIT License 7 votes vote down vote up 
def run_grabcut(img_orig, rect_final): 
    # Initialize the mask 
    mask = np.zeros(img_orig.shape[:2],np.uint8) 
 
    # Extract the rectangle and set the region of 
    # interest in the above mask 
    x,y,w,h = rect_final 
    mask[y:y+h, x:x+w] = 1 
 
    # Initialize background and foreground models 
    bgdModel = np.zeros((1,65), np.float64) 
    fgdModel = np.zeros((1,65), np.float64) 
 
    # Run Grabcut algorithm 
    cv2.grabCut(img_orig, mask, rect_final, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT) 
 
    # Extract new mask 
    mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8') 
 
    # Apply the above mask to the image 
    img_orig = img_orig*mask2[:,:,np.newaxis] 
 
    # Display the image 
    cv2.imshow('Output', img_orig)
Example #2
Source File: grab_cut.py    From Interactive-image-segmentation-opencv-qt with MIT License 4 votes vote down vote up 
def image_matting(self, image_file, shape, iteration=10):
        points = shape['points']
        xmin, ymin, xmax, ymax = Grab_cut.convertPoints2BndBox(points)
        self.width = xmax - xmin
        self.height = ymax - ymin

        src_img = cv2.imread(image_file)

        mask = np.zeros(src_img.shape[:2], np.uint8)
        bgdModel = np.zeros((1, 65), np.float64)
        fgdModel = np.zeros((1, 65), np.float64)
        rect = (xmin, ymin, self.width, self.height)

        # Grabcut
        cv2.grabCut(src_img, mask, rect, bgdModel, fgdModel,
                    iteration, cv2.GC_INIT_WITH_RECT)

        r_channel, g_channel, b_channel = cv2.split(src_img)
        a_channel = np.where((mask == 2) | (mask == 0), 0, 255).astype('uint8')

        # crop image space
        for row in range(ymin, ymax):
            if sum(r_channel[row, xmin:xmax + 1]) > 0:
                out_ymin = row
                break
        for row in range(ymin, ymax)[::-1]:
            if sum(r_channel[row, xmin:xmax + 1]) > 0:
                out_ymax = row + 1
                break
        for col in range(xmin, xmax):
            if sum(a_channel[ymin:ymax + 1, col]) > 0:
                out_xmin = col
                break
        for col in range(xmin, xmax)[::-1]:
            if sum(a_channel[ymin:ymax + 1, col]) > 0:
                out_xmax = col + 1
                break

        # output image
        img_RGBA = cv2.merge((r_channel[out_ymin:out_ymax, out_xmin:out_xmax],
                              g_channel[out_ymin:out_ymax, out_xmin:out_xmax],
                              b_channel[out_ymin:out_ymax, out_xmin:out_xmax],
                              a_channel[out_ymin:out_ymax, out_xmin:out_xmax]))

        return img_RGBA