Update app.py

app.py

@@ -172,19 +172,18 @@ def recognize_face_optimal(image_path):
         for name, data in ref.get().items():
             known_encoding = np.array(data["encoding"])
             similarity_score = face_recognition.face_distance([known_encoding], unknown_encoding[0])[0]
+            if similarity_score < 0.50:  # Adjust the threshold as needed
+                continue  # Skip this match if similarity score is below 50.00%
             matches.append((name, similarity_score))
 
         if matches:
             best_match = min(matches, key=lambda x: x[1])
             best_name, best_score = best_match
-            if best_score > 0.48:  # Adjust the threshold as needed
-                info = ref.child(best_name).child("info").get()
-                insta_handle = info["instagram_handle"]
-                insta_link = info["instagram_link"]
-                insta_link_html = f'<a href="{insta_link}" target="_blank"><font color="red">{insta_handle}</font></a>'
-                return f"Best match: {best_name} with a similarity score of {1 - best_score:.2%}. Insta handle: {insta_link_html}"
-            else:
-                return "Face not found."
+            info = ref.child(best_name).child("info").get()
+            insta_handle = info["instagram_handle"]
+            insta_link = info["instagram_link"]
+            insta_link_html = f'<a href="{insta_link}" target="_blank"><font color="red">{insta_handle}</font></a>'
+            return f"Best match: {best_name} with a similarity score of {1 - best_score:.2%}. Insta handle: {insta_link_html}"
         else:
             return "Face not found in the database."
     except Exception as e: