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import cv2
import numpy as np

# List of file paths for the images to analyze
image_paths = ["image1.jpg", "image2.jpg", "image3.jpg"]

# Threshold for determining if an image is blurry
threshold = 100

# List of blurry images
blurry_images = []

# Iterate through the list of image paths
for path in image_paths:
    # Read the image
    image = cv2.imread(path)

    # Convert the image to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Compute the Laplacian of the image
    laplacian = cv2.Laplacian(gray, cv2.CV_64F)

    # Compute the absolute value of the Laplacian
    abs_laplacian = np.abs(laplacian)

    # If the max value of the absolute Laplacian is less than the threshold,
    # the image is considered blurry
    if abs_laplacian.max() < threshold:
        # Add the image to the list of blurry images
        blurry_images.append(image)

# Print the list of blurry images
print(blurry_images)