Add type hints

OCR/image-alignment/deskew.py

@@ -12,7 +12,7 @@
 import cv2 as cv
 
 
-def order_points(inn):
+def order_points(inn: np.ndarray) -> np.ndarray:
     "Reorder points such that the points go in order from top left, top right, bottom right, and bottom left."
     inn = inn.reshape(4, 2)
     out = np.zeros([4, 2]).astype(np.float32)
@@ -25,7 +25,7 @@ def order_points(inn):
     return out
 
 
-def dewarp(img):
+def dewarp(img: np.ndarray) -> np.ndarray:
     # compute contours for an image and find the biggest one by area
     cnts, hier = cv.findContours(img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)[-2:]
     biggest_contour = functools.reduce(
@@ -37,13 +37,13 @@ def dewarp(img):
     approx = cv.approxPolyDP(biggest_contour, 0.01 * peri, True)
 
     h, w = img.shape
-    dest = np.float32([[0, 0], [w, 0], [w, h], [0, h]])
+    dest = np.array([[0, 0], [w, 0], [w, h], [0, h]], dtype=np.float32)
 
     M = cv.getPerspectiveTransform(order_points(approx), dest)
     return cv.warpPerspective(img, M, (w, h))
 
 
-def parse_args():
+def parse_args() -> argparse.Namespace:
     p = argparse.ArgumentParser(
         description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter
     )

OCR/image-alignment/perspective-transform.py

@@ -26,7 +26,7 @@ def parse_args():
     return p.parse_args()
 
 
-def make_tform(distortion_scale: float):
+def make_tform(distortion_scale: float) -> object:
     return transforms.Compose(
         [
             transforms.RandomPerspective(distortion_scale=distortion_scale, p=1),