diff --git a/README.md b/README.md
index d631195..ab6a537 100644
--- a/README.md
+++ b/README.md
@@ -13,4 +13,9 @@ scanimage --progress --output-file 01.png --format=png --mode Color --resolution
 ```
 pip install opencv-python-headless
 
+zypper install avif-tools
+
 ```
+
+
+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/
\ No newline at end of file
diff --git a/extract_photos.py b/extract_photos.py
index 6670e51..9be5c04 100644
--- a/extract_photos.py
+++ b/extract_photos.py
@@ -1,67 +1,127 @@
-# import required libraries
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+""" Author:                     Hendrik Schutter, mail@hendrikschutter.com
+"""
+
 import cv2
 import sys
+import os
 
-# read the input image
-img = cv2.imread('hires_test.png')
+def convert_to_avif(input, output):
+    # print("input: " + str(input))
+    # print("output: " + str(output))
+    temp = subprocess.Popen(
+        ["avifenc", "--jobs", "all", input, output], stdout=subprocess.PIPE
+    )
+    # get the output as a string
+    # output = str(temp.communicate())
+    # print(output)
+    temp = subprocess.Popen(
+        [
+            "sync",
+        ],
+        stdout=subprocess.PIPE,
+    )
 
+def auto_crop_scan(src_path, output_dir):
+    # read the input image
+    img_src = cv2.imread(src_path)
 
-if not img:
-    print("unable to read image")
-    sys.exit(-1)
+    if not img_src:
+        print("unable to read image")
+        sys.exit(-1)
 
-print("read done")
+    print("read done")
 
-# convert the image to grayscale
-gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-print("convert to gray done")
+    # convert the image to grayscale
+    img_gray = cv2.cvtColor(img_src, cv2.COLOR_BGR2GRAY)
+    print("convert to gray done")
 
-# apply thresholding on the gray image to create a binary image
-ret,thresh = cv2.threshold(gray,127,255,0)
+    # apply thresholding on the gray image to create a binary image
+    ret, thresh = cv2.threshold(img_gray, 127, 255, 0)
 
-# find the contours
-contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    # find the contours
+    contours, hierarchy = cv2.findContours(
+        thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE
+    )
 
-areas = list()
-
-for cnt in contours:
-    #print(cv2.contourArea(cnt))
-    areas.append(cv2.contourArea(cnt))
-
-areas.sort(reverse=True)
-
-#print(areas)
-
-if (len(areas) >= 5):
-    outer = areas[0]
-    inter_min = areas[4]
-    print("Outer area: " + str(outer))
-    print("Inner area: " + str(inter_min))
-
-    index = 0
+    areas = list()
 
     for cnt in contours:
-        area = cv2.contourArea(cnt)
-        if( (area < outer) and (area >= inter_min)):
-            # compute the bounding rectangle of the contour
-            x,y,w,h = cv2.boundingRect(cnt)
-            # draw the bounding rectangle
-            #imgView = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
+        # print(cv2.contourArea(cnt))
+        areas.append(cv2.contourArea(cnt))
 
-            x = x + 5
-            y = y + 5
-            w = w - 10
-            h = h - 10 
+    areas.sort(reverse=True)
 
-            crop_img = img[y:y+h, x:x+w]
-            #cv2.imshow("cropped", crop_img)
-            cv2.imwrite("export_"+str(index)+".png", crop_img)
-            index = index + 1
-            #cv2.waitKey(0)
+    # print(areas)
 
-# display the image with bounding rectangle drawn on it
-#imgDownscaled = cv2.resize(imgView, (410, 876)) 
-#cv2.imshow("Bounding Rectangle", imgDownscaled)
-#cv2.waitKey(0)
-#cv2.destroyAllWindows()
+    if len(areas) >= 5:
+        outer = areas[0]
+        inter_min = areas[4]
+        print("Outer area: " + str(outer))
+        print("Inner area: " + str(inter_min))
 
+        index = 0
+
+        for cnt in contours:
+            area = cv2.contourArea(cnt)
+            if (area < outer) and (area >= inter_min):
+                # compute the bounding rectangle of the contour
+                x, y, w, h = cv2.boundingRect(cnt)
+                # draw the bounding rectangle
+                # imgView = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
+
+                x = x + 5  # TODO
+                y = y + 5  # TODO
+                w = w - 10  # TODO
+                h = h - 10  # TODO
+
+                img_crop = img_src[y : y + h, x : x + w]
+                # cv2.imshow("cropped", crop_img)
+
+                export_file_name = (
+                    os.path.splitext(os.path.basename(os.path.normpath(src_path)))[0]
+                    + "-"
+                    + str(index)
+                    + ".png"
+                )
+                print(export_file_name)
+
+                export_file_path = os.path.join(output_dir, export_file_name)
+                print(export_file_path)
+
+                cv2.imwrite(export_file_path, img_crop)
+                index = index + 1
+                # cv2.waitKey(0)
+
+
+def main():
+    print("starting ...")
+
+    destination_dir_path = -1
+    source_dir_path = -1
+    tmp_dir_path = -1
+
+    for argument in sys.argv:
+        if argument.startswith("destination_dir"):
+            destination_dir_path = argument.split("=")[1]
+        if argument.startswith("source_dir"):
+            source_dir_path = argument.split("=")[1]
+        if argument.startswith("tmp_dir"):
+            tmp_dir_path = argument.split("=")[1]
+
+    if (destination_dir_path == -1) or (source_dir_path == -1) or (tmp_dir_path == -1):
+        print("Unable to parse config!")
+        print("Example usage:")
+        print(
+            "     python extract_photos.py source_dir=scans/ destination_dir=photos/ tmp_dir=tmp/"
+        )
+        sys.exit(-1)
+
+    for path in os.listdir(source_dir_path):
+        if os.path.isfile(os.path.join(source_dir_path, path)):
+            print(path)
+
+
+if __name__ == "__main__":
+    main()