测试捕捉框

face_rec.py

@@ -1279,7 +1279,7 @@ class FaceRecognitionSystem:
         img = cv2.cvtColor(np.array(img_pil), cv2.COLOR_RGB2BGR)
         return img
 
-    def draw_info_on_frame(self, frame: np.ndarray, mirrored: bool = False) -> np.ndarray:
+    def draw_info_on_frame(self, frame: np.ndarray) -> np.ndarray:
         """在帧上绘制检测和识别信息"""
         display_frame = frame.copy()
         h, w = display_frame.shape[:2]
@@ -1292,11 +1292,6 @@ class FaceRecognitionSystem:
             x_max = int(box['x_max'])
             y_max = int(box['y_max'])
 
-            # 镜像翻转时调整坐标
-            if mirrored:
-                x_min = w - 1 - x_max
-                x_max = w - 1 - x_min
-
             # 根据识别状态选择颜色
             if self.display_info['person_name']:
                 # 已识别 - 绿色
@@ -1820,8 +1815,17 @@ class FaceRecognitionSystem:
                 # 镜像翻转：使画面与实际场景一致（在绘制信息之前）
                 frame = cv2.flip(frame, 1)
 
-                # 绘制信息（传入镜像状态，由 draw_info_on_frame 内部处理坐标翻转）
-                display_frame = self.draw_info_on_frame(frame, mirrored=True)
+                # 调整 face_box 坐标以适应镜像翻转
+                if self.display_info['face_detected'] and self.display_info['face_box']:
+                    h_flip, w_flip = frame.shape[:2]
+                    box = self.display_info['face_box']
+                    x_min = int(box['x_min'])
+                    x_max = int(box['x_max'])
+                    # 水平翻转坐标
+                    self.display_info['face_box']['x_min'] = w_flip - 1 - x_max
+                    self.display_info['face_box']['x_max'] = w_flip - 1 - x_min
+
+                # 绘制信息
                 display_frame = self.draw_info_on_frame(frame)
 
                 # 绘制人脸轮廓引导框（屏幕中央）