修改为使用预训练模型yolo11m检测人

infer.py

@@ -165,7 +165,7 @@ class DoorInference(object):
     def person_detect(self, image):
         objs  = []
         confs = []
-        results = self.human_model(image, stream=False, classes=[4], conf=self.confidence_threshold, iou=0.3, imgsz=640)
+        results = self.human_model(image, stream=False, classes=[0], conf=self.confidence_threshold, iou=0.3, imgsz=640)
         for result in results:
             boxes = result.boxes.cpu()
             for box in boxes:

main.py

@@ -26,7 +26,7 @@ async def upload_image(session, url, payload, files):
 
 async def process_stream():
     logger.info("====== Start Server =======")
-    human_model_path = "models/work_clo_person_head_hat.pt"
+    human_model_path = "models/yolo11m.pt"
     door_model_path = "models/door_classify.pt"
     test_area = [[(222, 59), (432, 3), (528, 96), (318, 198)]]
     
@@ -40,10 +40,11 @@ async def process_stream():
         for frame, ret in stream():
             if not ret: 
                 continue
-            
+            if time.time() - posttime < 30:
+                continue
             image = frame.copy()
             result = instance(image)
-            if len(result) > 0 and time.time() - posttime > 30:
+            if len(result) > 0:
                 try:
                     posttime = time.time()
                     videoTime = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())