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39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
import cv2
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import numpy as np
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import sys
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def is_blank_image(image_path, threshold=10, white_value=255, blur_size=5):
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image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
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if image is None:
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print(f"Error: Unable to read the image file: {image_path}")
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return False
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# Apply Gaussian blur to reduce noise
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blurred_image = cv2.GaussianBlur(image, (blur_size, blur_size), 0)
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_, thresholded_image = cv2.threshold(blurred_image, white_value - threshold, white_value, cv2.THRESH_BINARY)
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# Calculate the percentage of white pixels in the thresholded image
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white_pixels = np.sum(thresholded_image == white_value)
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total_pixels = thresholded_image.size
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white_pixel_percentage = (white_pixels / total_pixels) * 100
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return white_pixel_percentage > 99
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if __name__ == "__main__":
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if len(sys.argv) != 2:
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print("Usage: python detect_blank_page.py <image_path>")
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sys.exit(1)
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image_path = sys.argv[1]
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blank = is_blank_image(image_path)
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if blank:
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# Return code 1: The image is considered blank.
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sys.exit(1)
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else:
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# Return code 0: The image is not considered blank.
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sys.exit(0) |