preprocessing.py 文件源码

def findSignificantContours(img, sobel_8u, sobel):
    image, contours, heirarchy = cv2.findContours(sobel_8u, \
                                                  cv2.RETR_EXTERNAL, \
                                                  cv2.CHAIN_APPROX_SIMPLE)
    mask = np.ones(image.shape[:2], dtype="uint8") * 255

    level1 = []
    for i, tupl in enumerate(heirarchy[0]):

        if tupl[3] == -1:
            tupl = np.insert(tupl, 0, [i])
            level1.append(tupl)
    significant = []
    tooSmall = sobel_8u.size * 10 / 100
    for tupl in level1:
        contour = contours[tupl[0]];
        area = cv2.contourArea(contour)
        if area > tooSmall:
            cv2.drawContours(mask, \
                             [contour], 0, (0, 255, 0), \
                             2, cv2.LINE_AA, maxLevel=1)
            significant.append([contour, area])
    significant.sort(key=lambda x: x[1])
    significant = [x[0] for x in significant];
    peri = cv2.arcLength(contour, True)
    approx = cv2.approxPolyDP(contour, 0.02 * peri, True)
    mask = sobel.copy()
    mask[mask > 0] = 0
    cv2.fillPoly(mask, significant, 255, 0)
    mask = np.logical_not(mask)
    img[mask] = 0;

    return img