Update utils/emotion_detection_brainai.py

utils/emotion_detection_brainai.py

@@ -39,17 +39,17 @@ class EmotionModel:
         
         return input_img
 
-    def detect_faces(self, img, conf = 0.5)
+    def detect_faces(self, img, conf = 0.5):
         result_face = self.face_compiled_model([input_img])[self.face_output_layer]
-        boxes = self.post_process_face(result_face, uploaded_img_cv, conf=0.5)
+        boxes = self.post_process_face(result_face, uploaded_img_cv, conf)
 
         return boxes
 
     def post_process_face(self, result_face, img, conf=0.5):
         boxes = []
         h,w,_ = img.shape
-        predictions = result_face[0][0]       # 하위 집합 데이터 프레임
-        confidence = predictions[:,2]    # conf 값 가져오기 [img_id, label, conf, x_min, y_min, x_max, y_max]
+        result = result_face[0][0]       # 하위 집합 데이터 프레임
+        confidence = result[:,2]    # conf 값 가져오기 [img_id, label, conf, x_min, y_min, x_max, y_max]
       
         top_predictions = predictions[(confidence>conf)]         # 임계값보다 큰 conf 값을 가진 예측만 선택
         for detection in top_predictions: