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117 lines
4.6 KiB
Python
117 lines
4.6 KiB
Python
import argparse
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import sys
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import cv2
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import numpy as np
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import os
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def find_photo_boundaries(image, background_color, tolerance=30, min_area=10000, min_contour_area=500):
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mask = cv2.inRange(image, background_color - tolerance, background_color + tolerance)
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mask = cv2.bitwise_not(mask)
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kernel = np.ones((5,5),np.uint8)
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mask = cv2.dilate(mask, kernel, iterations=2)
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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photo_boundaries = []
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for contour in contours:
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x, y, w, h = cv2.boundingRect(contour)
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area = w * h
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contour_area = cv2.contourArea(contour)
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if area >= min_area and contour_area >= min_contour_area:
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photo_boundaries.append((x, y, w, h))
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return photo_boundaries
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def estimate_background_color(image, sample_points=5):
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h, w, _ = image.shape
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points = [
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(0, 0),
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(w - 1, 0),
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(w - 1, h - 1),
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(0, h - 1),
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(w // 2, h // 2),
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]
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colors = []
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for x, y in points:
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colors.append(image[y, x])
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return np.median(colors, axis=0)
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def auto_rotate(image, angle_threshold=1):
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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edges = cv2.Canny(gray, 50, 150, apertureSize=3)
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lines = cv2.HoughLines(edges, 1, np.pi / 180, 200)
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if lines is None:
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return image
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# compute the median angle of the lines
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angles = []
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for rho, theta in lines[:, 0]:
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angles.append((theta * 180) / np.pi - 90)
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angle = np.median(angles)
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if abs(angle) < angle_threshold:
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return image
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(h, w) = image.shape[:2]
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center = (w // 2, h // 2)
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M = cv2.getRotationMatrix2D(center, angle, 1.0)
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return cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
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def crop_borders(image, border_color, tolerance=30):
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mask = cv2.inRange(image, border_color - tolerance, border_color + tolerance)
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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if len(contours) == 0:
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return image
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largest_contour = max(contours, key=cv2.contourArea)
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x, y, w, h = cv2.boundingRect(largest_contour)
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return image[y:y+h, x:x+w]
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def split_photos(input_file, output_directory, tolerance=30, min_area=10000, min_contour_area=500, angle_threshold=10, border_size=0):
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image = cv2.imread(input_file)
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background_color = estimate_background_color(image)
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# Add a constant border around the image
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image = cv2.copyMakeBorder(image, border_size, border_size, border_size, border_size, cv2.BORDER_CONSTANT, value=background_color)
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photo_boundaries = find_photo_boundaries(image, background_color, tolerance)
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if not os.path.exists(output_directory):
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os.makedirs(output_directory)
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# Get the input file's base name without the extension
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input_file_basename = os.path.splitext(os.path.basename(input_file))[0]
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for idx, (x, y, w, h) in enumerate(photo_boundaries):
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cropped_image = image[y:y+h, x:x+w]
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cropped_image = auto_rotate(cropped_image, angle_threshold)
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# Remove the added border
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cropped_image = cropped_image[border_size:-border_size, border_size:-border_size]
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output_path = os.path.join(output_directory, f"{input_file_basename}_{idx+1}.png")
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cv2.imwrite(output_path, cropped_image)
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print(f"Saved {output_path}")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Split photos in an image")
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parser.add_argument("input_file", help="The input scanned image containing multiple photos.")
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parser.add_argument("output_directory", help="The directory where the result images should be placed.")
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parser.add_argument("--tolerance", type=int, default=30, help="Determines the range of color variation around the estimated background color (default: 30).")
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parser.add_argument("--min_area", type=int, default=10000, help="Sets the minimum area threshold for a photo (default: 10000).")
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parser.add_argument("--min_contour_area", type=int, default=500, help="Sets the minimum contour area threshold for a photo (default: 500).")
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parser.add_argument("--angle_threshold", type=int, default=10, help="Sets the minimum absolute angle required for the image to be rotated (default: 10).")
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parser.add_argument("--border_size", type=int, default=0, help="Sets the size of the border added and removed to prevent white borders in the output (default: 0).")
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args = parser.parse_args()
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split_photos(args.input_file, args.output_directory, tolerance=args.tolerance, min_area=args.min_area, min_contour_area=args.min_contour_area, angle_threshold=args.angle_threshold, border_size=args.border_size)
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