merges latest develop

tests/test_scans.py

@@ -183,7 +183,7 @@ def apply_scan(img, rotation=0, scale=1, skew=(0, 0)):
 
 def upscale_image(image, scale=2):
     width, height = image.size
-    # standardly, the image has a dpi of 72 so 72*2=144 dpi when using the standard scale
+    # the standard dpi is 72 so 72*2=144 dpi with the standard scale.
     new_size = (int(scale * width), int(scale * height))
     image = image.resize(new_size, resample=1)
     return image

zesje/scans.py

@@ -468,104 +468,6 @@ def decode_barcode(image, exam_config):
     raise RuntimeError("No barcode found.")
 
 
-def rotate_image(image_array, corner_keypoints):
-    """Rotate an image according to the rotation of the corner markers."""
-
-    # Find two corner markers which lie in the same horizontal half.
-    # Same horizontal half is chosen as the line from one keypoint to
-    # the other shoud be 0. To get corner markers in the same horizontal half,
-    # the pair with the smallest distance is chosen.
-    distances = [(a, b, math.hypot(a[0] - b[0], a[1] - b[1]))
-                 for (a, b)
-                 in list(itertools.combinations(corner_keypoints, 2))]
-    distances.sort(key=lambda tup: tup[2], reverse=True)
-    best_keypoint_combination = distances.pop()
-
-    (coords1, coords2, dist) = best_keypoint_combination
-
-    # If the angle is downward, we have a negative angle and
-    # we want to rotate it counterclockwise
-    # However warpaffine needs a positve angle if
-    # you want to rotate it counterclockwise
-    # So we invert the angle retrieved from calc_angle
-    angle_deg = -1 * calc_angle(coords1, coords2)
-    angle_rad = math.radians(angle_deg)
-
-    h, w, *_ = image_array.shape
-    rot_origin = (w / 2, h / 2)
-
-    keyp_from_rot_origin = [(coord_x - rot_origin[0], coord_y - rot_origin[1])
-                            for (coord_x, coord_y)
-                            in corner_keypoints]
-
-    after_rot_keypoints = [((coord_y * math.sin(angle_rad) +
-                            coord_x * math.cos(angle_rad) + rot_origin[0]),
-                            (coord_y * math.cos(angle_rad) -
-                            coord_x * math.sin(angle_rad)) + rot_origin[1])
-                           for (coord_x, coord_y)
-                           in keyp_from_rot_origin]
-
-    # Create rotation matrix and rotate the image around the center
-    rot_mat = cv2.getRotationMatrix2D(rot_origin, angle_deg, 1)
-    rot_image = cv2.warpAffine(image_array, rot_mat, (w, h), cv2.BORDER_CONSTANT,
-                               borderMode=cv2.BORDER_CONSTANT,
-                               borderValue=(255, 255, 255))
-
-    return (rot_image, after_rot_keypoints)
-
-
-def shift_image(image, corner_keypoints):
-    """Roll the image such that QR occupies coords
-       specified by the template."""
-    corner_keypoints = np.array(corner_keypoints)
-    h, w, *_ = image.shape
-
-    xkeypoints = np.array([keypoint[0] for keypoint in corner_keypoints])
-    ykeypoints = np.array([keypoint[1] for keypoint in corner_keypoints])
-
-    is_left_half = xkeypoints < (w / 2)
-    is_top_half = ykeypoints < (h / 2)
-
-    # Get pixel locations to translate to. Currently only works with A4 sized
-    # paper
-    # TODO Add US letter functionality
-    x0 = 10/210 * w
-    y0 = 10/297 * h
-
-    # If there is a keypoint in the topleft, take that point as starting point
-    # for the translation
-    topleft = corner_keypoints[is_left_half & is_top_half]
-    if(len(topleft) == 1):
-        x = topleft[0][0]
-        y = topleft[0][1]
-    else:
-
-        # If there is no keypoint in the topleft, try to check if there is one
-        # in the bottom left and bottom right. If so, infer the topleft
-        # coordinates from their coordinates
-        topright = corner_keypoints[~is_left_half & is_top_half]
-        bottomleft = corner_keypoints[is_left_half & ~is_top_half]
-        if(len(topright) == 1 & len(bottomleft) == 1):
-            x = bottomleft[0][0]
-            y = topright[0][1]
-
-        else:
-            # We can only end here if something went wrong with the detection
-            # of corner markers. If so, just don't shift at all.
-            x = x0
-            y = y0
-
-    shift = np.round((y0-y, x0-x)).astype(int)
-    shifted_image = np.roll(image, shift[0], axis=0)
-    shifted_image = np.roll(shifted_image, shift[1], axis=1)
-
-    # Workaround of https://github.com/python-pillow/Pillow/issues/3109
-    if shifted_image.dtype == bool:
-        shifted_image = shifted_image * np.uint8(255)
-
-    return shifted_image
-
-
 def guess_student(exam_token, copy_number, app_config=None, force=False):
     """Update a submission with a guessed student number.
 
@@ -816,7 +718,7 @@ def realign_image(image_array, keypoints=None,
         New keypoints properly aligned.
     """
 
-    if(not keypoints):
+    if (not keypoints):
         keypoints = find_corner_marker_keypoints(image_array)
         check_corner_keypoints(image_array, keypoints)