mask_GMM.py 文件源码

def cropCircle(img):
    '''
    there many imaged taken thresholded, which means many images is
    present as a circle with black surrounded. This function is to
    find the largest inscribed rectangle to the thresholed image and
    then crop the image to the rectangle.

    input: img - the cv2 module

    return: img_crop, rectangle, tile_size
    '''
    if(img.shape[0] > img.shape[1]):
        tile_size = (int(img.shape[1]*256/img.shape[0]),256)
    else:
        tile_size = (256, int(img.shape[0]*256/img.shape[1]))

    img = cv2.resize(img, dsize=tile_size)

    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY);
    _, thresh = cv2.threshold(gray, 10, 255, cv2.THRESH_BINARY)

    _, contours, _ = cv2.findContours(thresh.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)

    main_contour = sorted(contours, key = cv2.contourArea, reverse = True)[0]

    ff = np.zeros((gray.shape[0],gray.shape[1]), 'uint8')
    cv2.drawContours(ff, main_contour, -1, 1, 15)
    ff_mask = np.zeros((gray.shape[0]+2,gray.shape[1]+2), 'uint8')
    cv2.floodFill(ff, ff_mask, (int(gray.shape[1]/2), int(gray.shape[0]/2)), 1)

    rect = maxRect(ff)
    rectangle = [min(rect[0],rect[2]), max(rect[0],rect[2]), min(rect[1],rect[3]), max(rect[1],rect[3])]
    img_crop = img[rectangle[0]:rectangle[1], rectangle[2]:rectangle[3]]
    cv2.rectangle(ff,(min(rect[1],rect[3]),min(rect[0],rect[2])),(max(rect[1],rect[3]),max(rect[0],rect[2])),3,2)

    return [img_crop, rectangle, tile_size]