cleanup
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@ -13,4 +13,9 @@ scanimage --progress --output-file 01.png --format=png --mode Color --resolution
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```
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pip install opencv-python-headless
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zypper install avif-tools
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```
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rsync -Pav -e "ssh -i $HOME/.ssh/SDS" /home/hendrik/git/ultimate-photo-digitizer/scans/ hendrik@10.0.0.25:/home/hendrik/git/ultimate-photo-digitizer/scans/
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@ -1,67 +1,127 @@
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# import required libraries
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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""" Author: Hendrik Schutter, mail@hendrikschutter.com
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"""
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import cv2
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import sys
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import os
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# read the input image
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img = cv2.imread('hires_test.png')
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def convert_to_avif(input, output):
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# print("input: " + str(input))
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# print("output: " + str(output))
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temp = subprocess.Popen(
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["avifenc", "--jobs", "all", input, output], stdout=subprocess.PIPE
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)
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# get the output as a string
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# output = str(temp.communicate())
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# print(output)
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temp = subprocess.Popen(
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[
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"sync",
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],
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stdout=subprocess.PIPE,
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)
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def auto_crop_scan(src_path, output_dir):
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# read the input image
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img_src = cv2.imread(src_path)
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if not img:
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print("unable to read image")
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sys.exit(-1)
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if not img_src:
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print("unable to read image")
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sys.exit(-1)
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print("read done")
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print("read done")
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# convert the image to grayscale
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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print("convert to gray done")
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# convert the image to grayscale
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img_gray = cv2.cvtColor(img_src, cv2.COLOR_BGR2GRAY)
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print("convert to gray done")
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# apply thresholding on the gray image to create a binary image
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ret,thresh = cv2.threshold(gray,127,255,0)
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# apply thresholding on the gray image to create a binary image
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ret, thresh = cv2.threshold(img_gray, 127, 255, 0)
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# find the contours
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contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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# find the contours
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contours, hierarchy = cv2.findContours(
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thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE
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)
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areas = list()
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for cnt in contours:
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#print(cv2.contourArea(cnt))
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areas.append(cv2.contourArea(cnt))
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areas.sort(reverse=True)
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#print(areas)
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if (len(areas) >= 5):
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outer = areas[0]
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inter_min = areas[4]
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print("Outer area: " + str(outer))
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print("Inner area: " + str(inter_min))
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index = 0
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areas = list()
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for cnt in contours:
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area = cv2.contourArea(cnt)
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if( (area < outer) and (area >= inter_min)):
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# compute the bounding rectangle of the contour
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x,y,w,h = cv2.boundingRect(cnt)
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# draw the bounding rectangle
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#imgView = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
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# print(cv2.contourArea(cnt))
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areas.append(cv2.contourArea(cnt))
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x = x + 5
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y = y + 5
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w = w - 10
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h = h - 10
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areas.sort(reverse=True)
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crop_img = img[y:y+h, x:x+w]
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#cv2.imshow("cropped", crop_img)
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cv2.imwrite("export_"+str(index)+".png", crop_img)
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index = index + 1
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#cv2.waitKey(0)
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# print(areas)
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# display the image with bounding rectangle drawn on it
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#imgDownscaled = cv2.resize(imgView, (410, 876))
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#cv2.imshow("Bounding Rectangle", imgDownscaled)
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#cv2.waitKey(0)
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#cv2.destroyAllWindows()
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if len(areas) >= 5:
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outer = areas[0]
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inter_min = areas[4]
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print("Outer area: " + str(outer))
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print("Inner area: " + str(inter_min))
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index = 0
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for cnt in contours:
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area = cv2.contourArea(cnt)
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if (area < outer) and (area >= inter_min):
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# compute the bounding rectangle of the contour
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x, y, w, h = cv2.boundingRect(cnt)
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# draw the bounding rectangle
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# imgView = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
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x = x + 5 # TODO
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y = y + 5 # TODO
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w = w - 10 # TODO
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h = h - 10 # TODO
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img_crop = img_src[y : y + h, x : x + w]
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# cv2.imshow("cropped", crop_img)
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export_file_name = (
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os.path.splitext(os.path.basename(os.path.normpath(src_path)))[0]
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+ "-"
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+ str(index)
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+ ".png"
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)
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print(export_file_name)
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export_file_path = os.path.join(output_dir, export_file_name)
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print(export_file_path)
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cv2.imwrite(export_file_path, img_crop)
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index = index + 1
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# cv2.waitKey(0)
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def main():
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print("starting ...")
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destination_dir_path = -1
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source_dir_path = -1
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tmp_dir_path = -1
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for argument in sys.argv:
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if argument.startswith("destination_dir"):
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destination_dir_path = argument.split("=")[1]
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if argument.startswith("source_dir"):
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source_dir_path = argument.split("=")[1]
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if argument.startswith("tmp_dir"):
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tmp_dir_path = argument.split("=")[1]
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if (destination_dir_path == -1) or (source_dir_path == -1) or (tmp_dir_path == -1):
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print("Unable to parse config!")
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print("Example usage:")
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print(
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" python extract_photos.py source_dir=scans/ destination_dir=photos/ tmp_dir=tmp/"
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)
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sys.exit(-1)
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for path in os.listdir(source_dir_path):
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if os.path.isfile(os.path.join(source_dir_path, path)):
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print(path)
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if __name__ == "__main__":
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main()
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