batch scanning script

extract_photos.py

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+# import required libraries
+import cv2
+import sys
+
+# read the input image
+img = cv2.imread('hires_test.png')
+
+
+if not img:
+    print("unable to read image")
+    sys.exit(-1)
+
+print("read done")
+
+# convert the image to grayscale
+gray = cv2.cvtColor(img, 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)
+
+# 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
+
+    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
+            y = y + 5
+            w = w - 10
+            h = h - 10 
+
+            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)
+
+# 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()
+