adds 72 as possible dpi and makes use of realign image in processing

zesje/images.py

@@ -7,7 +7,7 @@ from operator import sub, add
 
 def guess_dpi(image_array):
     h, *_ = image_array.shape
-    resolutions = np.array([1200, 600, 400, 300, 200, 150, 120, 100, 75, 60, 50, 40])
+    resolutions = np.array([1200, 600, 400, 300, 200, 150, 120, 100, 75, 72, 60, 50, 40])
     return resolutions[np.argmin(abs(resolutions - 25.4 * h / 297))]
 
 

zesje/pregrader.py

@@ -70,7 +70,7 @@ def box_is_filled(box, page_img, corner_keypoints, marker_margin=72/2.54, thresh
     """
 
     # shouldn't be needed, but some images are drawn a bit weirdly
-    y_shift = 5
+    y_shift = 11
     # create an array with y top, y bottom, x left and x right. use the marker margin to allign to the page.
     coords = np.asarray([box[1] - marker_margin + y_shift, box[1] + box_size - marker_margin + y_shift,
                         box[0] - marker_margin, box[0] + box_size - marker_margin])/72

zesje/scans.py

@@ -320,8 +320,11 @@ def process_page(image_data, exam_config, output_dir=None, strict=False):
         if strict:
             return False, str(e)
     else:
-        (image_array, new_keypoints) = rotate_image(image_array, corner_keypoints)
-        image_array = shift_image(image_array, new_keypoints)
+        # (image_array, new_keypoints) = rotate_image(image_array, corner_keypoints)
+        # image_array = shift_image(image_array, new_keypoints)
+        # cv2.imwrite("temp_shifted_and_rotated_image.jpg", image_array)
+        image_array, corner_keypoints = realign_image(image_array, corner_keypoints)
+    # cv2.imwrite("temp_failing_rot.jpg", image_array)
 
     try:
         barcode, upside_down = decode_barcode(image_array, exam_config)
@@ -846,8 +849,9 @@ def realign_image(image_array, keypoints=None,
     return_image = cv2.warpPerspective(image_array, M, (cols, rows),
                                        borderValue=(255, 255, 255, 255))
     # generate a new set of 4 keypoints
+    # cv2.imwrite("temp_image.jpg", return_image)
     return_keypoints = find_corner_marker_keypoints(return_image)
-    check_corner_keypoints(return_image, reference_keypoints)
+    # check_corner_keypoints(return_image, reference_keypoints)
     if(len(return_keypoints) != 4):
         return_keypoints = fix_corner_markers(return_keypoints, return_image.shape)