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Код — Изменил ли размер всех моих входных изображений, все еще получающих высокую дисперсию для некоторых размытых изображений?? как добиться хорошей точности с помощью лапласианского оператора opencv

 


def variance_of_laplacian(image):
    # compute the Laplacian of the image and then return the focus
    # measure, which is simply the variance of the Laplacian
    return cv2.Laplacian(image, cv2.CV_64F).var()


# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--images", required=True,
    help="path to input directory of images")
ap.add_argument("-t", "--threshold", type=float, default=700.0,
    help="focus measures that fall below this value will be considered 'blurry'")
args = vars(ap.parse_args())


# loop over the input images
for imagePath in paths.list_images(args["images"]):
    # load the image, convert it to grayscale, and compute the
    # focus measure of the image using the Variance of Laplacian
    # method
    image = cv2.imread(imagePath)
    image = cv2.resize(image, (500,300))
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    fm = variance_of_laplacian(gray)
    text = "Not Blurry"
    # if the focus measure is less than the supplied threshold,
    # then the image should be considered "blurry"
    if fm < args["threshold"]:
        text = "Blurry"
    # show the image
    cv2.putText(image, "{}: {:.2f}".format(text, fm), (10, 30),
        cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
    cv2.imshow("Image", image)
    key = cv2.waitKey(0)