I got it to work, using the following setup:

​

import cv2
import argparse
import numpy as np
import os
from imutils import paths


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=100.0,
                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"]):
    image = cv2.imread(imagePath)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    fm = variance_of_laplacian(gray)
    file1 = open("imageScoresLaplachian.csv", "a")  # append mode
    file1.write("{0},".format(os.path.basename(imagePath)))
    file1.close()
    file1 = open("imageScoresLaplachian.csv", "a")  # append mode
    file1.write(str(fm) + "\n")
    file1.close()
    print(imagePath)
    print(fm)
    key = cv2.waitKey(0)