更新更新

entity/FeedBack.py

     result_msg["original_url"] = original_url
     result_msg["sign_url"] = sign_url
     result_msg["model_type_code"] = model_type_code
-    result_msg["model_detection_coden"] = model_detection_code
+    result_msg["model_detection_code"] = model_detection_code
     result_msg["analyse_time"] = analyse_time
     results.append(result_msg)
     taskfb["results"] = results

enums/ModelTypeEnum.py

+from enum import Enum, unique
+
+
+# 异常枚举
+@unique
+class ModelType(Enum):
+
+    WATER_SURFACE_MODEL = ("1", "001", "水面模型")
+
+    FOREST_FARM_MODEL = ("2", "002", "林场模型")
+
+    def checkCode(code):
+        for model in ModelType:
+            if model.value[1] == code:
+                return True
+        return False

util/Cv2Utils.py

                                            ExceptionType.OR_VIDEO_ADDRESS_EXCEPTION.value[1])
 
                 self.or_video_file = cv2.VideoWriter(self.orFilePath, cv2.VideoWriter_fourcc(*'mp4v'), self.fps, (self.width, self.height))
-            self.ai_video_file = cv2.VideoWriter(self.aiFilePath, cv2.VideoWriter_fourcc(*'mp4v'), self.fps, (self.width, int(self.height/2)))
+            self.ai_video_file = cv2.VideoWriter(self.aiFilePath, cv2.VideoWriter_fourcc(*'mp4v'), self.fps, (self.width * 2, self.height))
         except ServiceException as s:
             raise s
         except Exception as e:
             logger.exception(e)
 
     def video_merge(self, frame1, frame2):
-        frameLeft = cv2.resize(frame1, (int(self.width / 2), int(self.height / 2)), interpolation=cv2.INTER_LINEAR)
-        frameRight = cv2.resize(frame2, (int(self.width / 2), int(self.height / 2)), interpolation=cv2.INTER_LINEAR)
+        frameLeft = cv2.resize(frame1, (int(self.width), int(self.height)), interpolation=cv2.INTER_LINEAR)
+        frameRight = cv2.resize(frame2, (int(self.width), int(self.height)), interpolation=cv2.INTER_LINEAR)
         frame_merge = np.hstack((frameLeft, frameRight))
         return frame_merge
 

util/ModelUtils.py

         self.device = select_device(self.device_)
         self.names = get_labelnames(labelnames)
         ###默认是1920，在森林巡检的高清图像中是4920
-        imageW = 4915
+        imageW = 1920
         outfontsize = int(imageW/1920*40)
         self.label_arraylist = get_label_arrays(self.names, self.rainbows, outfontsize=outfontsize, fontpath="../AIlib/conf/platech.ttf")
         self.half = self.device.type != 'cpu'  # half precision only supported on CUDA

util/YmlUtils.py

 # 从配置文件读取所有配置信息
 def getConfigs():
     print("开始读取配置文件，获取配置消息：", Constant.APPLICATION_CONFIG)
-    applicationConfigPath = "../dsp_application.yml"
-    print(applicationConfigPath)
+    applicationConfigPath = os.path.abspath(Constant.APPLICATION_CONFIG)
     if not os.path.exists(applicationConfigPath):
         raise Exception("未找到配置文件：{}".format(Constant.APPLICATION_CONFIG))
     with open(applicationConfigPath, Constant.R, encoding=Constant.UTF_8) as f: