upgraded

app.py

@@ -371,13 +371,13 @@ class UI():
                     nearest_distance = 1e100
                     nearest = 0
                     for i, known_face in enumerate(self.known_faces):
-                        if self.distance_type == "cosine":
+                        if self.distance_type.value == "cosine":
                             # Cosine distance
                             distance = self.cosine_distance(known_face["mean"], embedding)
-                        elif self.distance_type =="L1":
+                        elif self.distance_type.value =="L1":
                             # absolute distance
                             distance = np.abs(known_face["mean"]-embedding).sum()
-                        elif self.distance_type == "L2":
+                        elif self.distance_type.value == "L2":
                             # absolute distance
                             distance = np.sqrt(np.square(known_face["mean"]-embedding).sum())
                         if distance<nearest_distance:
@@ -402,6 +402,7 @@ class UI():
         fa.process(image)
 
         if fa.nb_faces>0:
+            bboxes_and_names=[]
             for j in range(fa.nb_faces):
                 try:
                     face = fa.faces[j]
@@ -413,25 +414,23 @@ class UI():
                     nearest_distance = 1e100
                     nearest = 0
                     for i, known_face in enumerate(self.known_faces):
-                        if self.distance_type == "cosine":
+                        if self.distance_type.value == "cosine":
                             # Cosine distance
                             distance = self.cosine_distance(known_face["mean"], embedding)
-                        elif self.distance_type =="L1":
+                        elif self.distance_type.value =="L1":
                             # absolute distance
                             distance = np.abs(known_face["mean"]-embedding).sum()
-                        elif self.distance_type == "L2":
+                        elif self.distance_type.value == "L2":
                             # absolute distance
                             distance = np.sqrt(np.square(known_face["mean"]-embedding).sum())
                         if distance<nearest_distance:
                             nearest_distance = distance
                             nearest = i
                             
-                    if nearest_distance>self.threshold:
-                        face.draw_bounding_box(image, thickness=1,text=f"Unknown:{nearest_distance:.3e}")
-                    else:
-                        face.draw_bounding_box(image, thickness=1,text=f"{self.known_faces_names[nearest]}:{nearest_distance:.3e}")
+                    bboxes_and_names.append([face.bounding_box, f"Unknown:{nearest_distance:.2e}" if nearest_distance>self.threshold else f"{self.known_faces_names[nearest]}:{nearest_distance:.2e}"])
                 except Exception as ex:
                     image=face_image
+            image = fa.draw_names_on_bboxes(image,bboxes_and_names,upscale=2)
 
         # Return the resulting frame
         return image