add if statement if the Model could not predict exactly the breed

app.py

@@ -17,11 +17,15 @@ def tensor2labels(img):
     category = categories[index]
     print(category)
     if 'dog' in category:
-      category.remove('dog')
-      return f"This is a Dog and belongs to the breed: {category.pop()}"
+        category.remove('dog')
+        if len(category)==0:
+           return f"This is a Dog and I am not smart enough to know what breed it is :(("
+        return f"This is a Dog and belongs to the breed: {category.pop()}"
     elif 'cat' in category:
-      category.remove('cat')
-      return f"This is a Cat and belongs to the breed: {category.pop()}"
+        category.remove('cat')
+        if len(category)==0:
+            return f"This is a Cat and I am not smart enough to know what breed it is :(("
+        return f"This is a Cat and belongs to the breed: {category.pop()}"
     else:
       raise Exception