Update app.py

app.py

@@ -38,12 +38,11 @@ def find_tip(points, convex_hull):
         if np.all(points[j] == points[indices[i - 1] - 2]):
             return tuple(points[j])
 
-def find_tail(points, convex_hull):
-    # Implement the logic to find the tail point
-    # You might need to adjust this based on the specific characteristics of your arrows
-    # This is just a simple example, and you may need to fine-tune it based on your requirements
-    tail_index = (convex_hull[0] + convex_hull[-1]) // 2
-    return tuple(points[tail_index])
+def find_tail(points, tip):
+    # Find the farthest point from the tip
+    farthest_point = max(points, key=lambda p: cv2.pointPolygonTest(np.array([tip], dtype=np.int32), tuple(p), True))
+
+    return tuple(farthest_point)
 
 def infer(image_in):
     img = cv2.imread(image_in)
@@ -58,7 +57,7 @@ def infer(image_in):
 
         if 6 > sides > 3 and sides + 2 == len(approx):
             arrow_tip = find_tip(approx[:,0,:], hull.squeeze())
-            arrow_tail = find_tail(approx[:,0,:], hull.squeeze())
+            arrow_tail = find_tail(approx[:,0,:], arrow_tip)
             
             if arrow_tip and arrow_tail:
                 cv2.drawContours(img, [cnt], -1, (0, 255, 0), 3)
@@ -66,6 +65,7 @@ def infer(image_in):
                 cv2.circle(img, arrow_tail, 3, (255, 0, 0), cv2.FILLED)
 
 
+
     cv2.imwrite("Image_result.png", img)
 
     return "Image_result.png", "1_gray.png", "2_blur.png", "3_canny.png", "4_dilate.png", "5_erode.png"