Avoid line-continuation

Author: Avasam

src/AutoSplit.py

@@ -432,8 +432,10 @@ def __check_fps(self):
         self.fps_value_label.setText(str(fps))
 
     def __is_current_split_out_of_range(self):
-        return self.split_image_number < 0 \
+        return (
+            self.split_image_number < 0
             or self.split_image_number > len(self.split_images_and_loop_number) - 1
+        )
 
     def undo_split(self, navigate_image_only: bool = False):
         """Undo Split" and "Prev. Img." buttons connect to here."""

src/capture_method/__init__.py

@@ -188,16 +188,20 @@ async def get_camera_info(index: int, device_name: str):
         #     backend = video_capture.getBackendName()  # STS_ASSERT
         #     video_capture.grab()  # STS_ERROR
         # except cv2.error as error:
-        #     return CameraInfo(index, device_name, True, backend) \
-        #         if error.code in (cv2.Error.STS_ERROR, cv2.Error.STS_ASSERT) \
+        #     return (
+        #         CameraInfo(index, device_name, True, backend)
+        #         if error.code in (cv2.Error.STS_ERROR, cv2.Error.STS_ASSERT)
         #         else None
+        #     )
         # finally:
         #     video_capture.release()
 
         resolution = get_input_device_resolution(index)
-        return CameraInfo(index, device_name, False, backend, resolution) \
-            if resolution is not None \
+        return (
+            CameraInfo(index, device_name, False, backend, resolution)
+            if resolution is not None
             else None
+        )
 
     return [
         camera_info

src/compare.py

@@ -44,9 +44,11 @@ def compare_l2_norm(source: MatLike, capture: MatLike, mask: MatLike | None = No
     error = cv2.norm(source, capture, cv2.NORM_L2, mask)
 
     # The L2 Error is summed across all pixels, so this normalizes
-    max_error = sqrt(source.size) * MAXBYTE \
-        if not is_valid_image(mask)\
+    max_error = (
+        sqrt(source.size) * MAXBYTE
+        if not is_valid_image(mask)
         else sqrt(cv2.countNonZero(mask) * MASK_SIZE_MULTIPLIER)
+    )
 
     if not max_error:
         return 0.0
@@ -69,9 +71,11 @@ def compare_template(source: MatLike, capture: MatLike, mask: MatLike | None = N
 
     # matchTemplate returns the sum of square differences, this is the max
     # that the value can be. Used for normalizing from 0 to 1.
-    max_error = source.size * MAXBYTE * MAXBYTE \
-        if not is_valid_image(mask) \
+    max_error = (
+        source.size * MAXBYTE * MAXBYTE
+        if not is_valid_image(mask)
         else cv2.countNonZero(mask)
+    )
 
     return 1 - (min_val / max_error)