detect_blur.py

# 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 -- 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=130.0,
	help="focus measures that fall below this value will be considered 'blurry'")
ap.add_argument("-d", "--delete", type=bool, default="false",
	help="whether to delete 'blurry' images or not")
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)
    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"

    # print out the Focus Measure and 
    # result -- 'Blurry'/'Not Blurry'
    print(imagePath)
    print('focus measure', fm)     
    print('result', text)
    
    
    # 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)
    cv2.imwrite("blur_test_result/"+imagePath.split("/",1)[1] , image)
    key = cv2.waitKey(0)

    # based on whether the 'delete' flag is set
    # delete the Blurry image 
    if(args["delete"] == "true") :
        if(text == "Blurry"):
            try: 
                os.remove(imagePath)
            except: pass