交通模型修改

.idea/workspace.xml

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-      <change beforePath="$PROJECT_DIR$/util/Cv2Utils.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/Cv2Utils.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/concurrency/IntelligentRecognitionProcess.py" beforeDir="false" afterPath="$PROJECT_DIR$/concurrency/IntelligentRecognitionProcess.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/util/ModelUtils.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/ModelUtils.py" afterDir="false" />
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       <workItem from="1663545195142" duration="3595000" />
       <workItem from="1663631838059" duration="7995000" />
-      <workItem from="1664253194092" duration="67000" />
+      <workItem from="1664253194092" duration="121000" />
+      <workItem from="1664253821529" duration="612000" />
+      <workItem from="1664268388633" duration="867000" />
     </task>
     <servers />
   </component>

concurrency/IntelligentRecognitionProcess.py

                 logger.info("######################加载林场模型######################")
                 return ModelUtils.LCModel(args[1], needed_objectsIndex), code, args[0].get("lc")
             elif code == ModelType.TRAFFIC_FARM_MODEL.value[1]:
-                logger.info("######################加载林场模型######################")
-                return ModelUtils.LCModel(args[1], needed_objectsIndex), code, args[0].get("rf")
+                logger.info("######################加载交通模型######################")
+                return ModelUtils.RFModel(args[1], needed_objectsIndex), code, args[0].get("rf")
             else:
                 logger.error("未匹配到对应的模型")
                 raise ServiceException(ExceptionType.AI_MODEL_MATCH_EXCEPTION.value[0],

util/ModelUtils.py

         super().__init__(device, allowedList)
         self.device = select_device(self.device_)
         self.half = self.device.type != 'cpu'  # half precision only supported on CUDA
-        self.model = attempt_load("../AIlib/weights/load/best.pt", map_location=self.device)  # load FP32 model
+        self.model = attempt_load("../AIlib/weights/road/best.pt", map_location=self.device)  # load FP32 model
         if self.half:
             self.model.half()
         self.segmodel = None