参考：
使用OpenCV进行模糊检测（拉普拉斯算子）

代码：

# import the necessary packages
from imutils import paths
import argparse
import cv2
import os

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("-o", "--output", required=True, help="path to output directory for saving results")
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())

# create output directories if they don't exist
blurry_dir = os.path.join(args["output"], "blurry")
not_blurry_dir = os.path.join(args["output"], "not_blurry")
os.makedirs(blurry_dir, exist_ok=True)
os.makedirs(not_blurry_dir, exist_ok=True)

# 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)
    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"
        outputPath = os.path.join(blurry_dir, os.path.basename(imagePath))
    else:
        outputPath = os.path.join(not_blurry_dir, os.path.basename(imagePath))
    
    # annotate and save the image
    cv2.putText(image, "{}: {:.2f}".format(text, fm), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
    cv2.imwrite(outputPath, image)

print("Processing complete. Blurry images saved to", blurry_dir)
print("Not blurry images saved to", not_blurry_dir)

结果：