Linting

shenzhen_solitaire/cv/card_finder.py

@@ -102,8 +102,8 @@ def find_square(search_square: np.ndarray,
             best_square = square
             best_count = count
             best_coord = coord
-    assert best_square
-    assert best_coord
+    assert isinstance(best_square, np.ndarray)
+    assert isinstance(best_coord, tuple)
     cv2.imshow("Window", best_square -
                search_square[best_coord[0]:best_coord[0] +
                              best_square.shape[0], best_coord[1]:best_coord[1] +

test/cv_helper.py

@@ -1,10 +1,11 @@
+import itertools
+from typing import Tuple, List, Dict
+import numpy  # type: ignore
+import cv2  # type: ignore
+
 from .context import shenzhen_solitaire
 from shenzhen_solitaire.cv import adjustment
 from shenzhen_solitaire.cv import card_finder
-from typing import Tuple, List, Dict
-import cv2
-import numpy
-import itertools
 
 
 def pixelcount(image: numpy.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
@@ -18,6 +19,7 @@ def pixelcount(image: numpy.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
     B = sorted(p.items(), key=lambda x: x[1])
     return B
 
+
 def simplify(image: numpy.ndarray) -> None:
     cv2.imshow("Window", image)
     cv2.waitKey(0)
@@ -46,7 +48,8 @@ def main() -> None:
     for i in range(10, 20):
         image_squares[i], _ = card_finder.simplify(image_squares[i])
         print("Finding...")
-        found_image, certainty = card_finder.find_square(image_squares[i], squares)
+        found_image, certainty = card_finder.find_square(
+            image_squares[i], squares)
 
 
 if __name__ == "__main__":