rebase: feat: use line-mapping logic

src/cv_analysis/table_parsing.py

@@ -178,17 +178,21 @@ def detect_endpoints(
 
         return (dist_a < 15) and (dist_b < 15) and overlap
 
-    points = cv2.HoughLinesP(
-        image,  # Input edge image
-        1,  # Distance resolution in pixels
-        np.pi / 180,  # Angle resolution in radians
-        threshold=100,  # Min number of votes for valid line
-        minLineLength=200,  # Min allowed length of line
-        maxLineGap=10,  # Max allowed gap between line for joining them
-    )
-    points = points if points is not None else []
 
-    lines = list(map(lambda x: tuple(x[0]), points))
+    lines = list(
+        map(
+            lambda x: tuple(x[0]),
+            cv2.HoughLinesP(
+                image,  # Input edge image
+                1,  # Distance resolution in pixels
+                np.pi / 180,  # Angle resolution in radians
+                threshold=100,  # Min number of votes for valid line
+                minLineLength=200,  # Min allowed length of line
+                maxLineGap=10,  # Max allowed gap between line for joining them
+            ),
+        )
+    )
+
     if not lines:
         return lines
     index = int(is_horizontal)