Optimized the code in detect-blank-pages.py

Made use of Numpy arrays
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EmadEldin Osman 2023-12-28 04:51:50 +03:00 committed by GitHub
parent 4e991e7ec2
commit b7f62a635d
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@ -1,10 +1,11 @@
import cv2
import sys
import argparse
import numpy as np
def is_blank_image(image_path, threshold=10, white_percent=99, white_value=255, blur_size=5):
image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
if image is None:
print(f"Error: Unable to read the image file: {image_path}")
return False
@ -15,19 +16,11 @@ def is_blank_image(image_path, threshold=10, white_percent=99, white_value=255,
_, thresholded_image = cv2.threshold(blurred_image, white_value - threshold, white_value, cv2.THRESH_BINARY)
# Calculate the percentage of white pixels in the thresholded image
white_pixels = 0
total_pixels = thresholded_image.size
for i in range(0, thresholded_image.shape[0], 2):
for j in range(0, thresholded_image.shape[1], 2):
if thresholded_image[i, j] == white_value:
white_pixels += 1
white_pixel_percentage = (white_pixels / (i * thresholded_image.shape[1] + j + 1)) * 100
if white_pixel_percentage < white_percent:
return False
white_pixels = np.sum(thresholded_image == white_value)
white_pixel_percentage = (white_pixels / thresholded_image.size) * 100
print(f"Page has white pixel percent of {white_pixel_percentage}")
return True
return white_pixel_percentage >= white_percent
if __name__ == "__main__":
@ -39,9 +32,6 @@ if __name__ == "__main__":
blank = is_blank_image(args.image_path, args.threshold, args.white_percent)
if blank:
# Return code 1: The image is considered blank.
sys.exit(1)
else:
# Return code 0: The image is not considered blank.
sys.exit(0)
# Return code 1: The image is considered blank.
# Return code 0: The image is not considered blank.
sys.exit(int(blank))