车辆检测、人流量检查、人识别

.idea/deployment.xml

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="PublishConfigData" autoUpload="Always" serverName="192.168.11.7" remoteFilesAllowedToDisappearOnAutoupload="false">
+  <component name="PublishConfigData" serverName="192.168.11.7" remoteFilesAllowedToDisappearOnAutoupload="false">
     <serverData>
       <paths name="10.21">
         <serverdata>
@@ -89,6 +89,5 @@
         </serverdata>
       </paths>
     </serverData>
-    <option name="myAutoUpload" value="ALWAYS" />
   </component>
 </project>

.idea/workspace.xml

@@ -5,8 +5,21 @@
   </component>
   <component name="ChangeListManager">
     <list default="true" id="4f7dccd9-8f92-4a6e-90cc-33890d102263" name="Changes" comment="Changes">
+      <change beforePath="$PROJECT_DIR$/.idea/deployment.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/deployment.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/concurrency/IntelligentRecognitionProcess.py" beforeDir="false" afterPath="$PROJECT_DIR$/concurrency/IntelligentRecognitionProcess.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/dsp_application.yml" beforeDir="false" afterPath="$PROJECT_DIR$/dsp_application.yml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/enums/ExceptionEnum.py" beforeDir="false" afterPath="$PROJECT_DIR$/enums/ExceptionEnum.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/enums/ModelTypeEnum.py" beforeDir="false" afterPath="$PROJECT_DIR$/enums/ModelTypeEnum.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/image/1.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/image/11.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/image/2.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/image/22.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/util/AliyunSdk.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/AliyunSdk.py" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/util/Cv2Utils.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/Cv2Utils.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/util/ImageUtils.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/ImageUtils.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/util/ModelUtils.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/ModelUtils.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/util/OcrBaiduSdk.py" beforeDir="false" afterPath="$PROJECT_DIR$/util/OcrBaiduSdk.py" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />
     <option name="HIGHLIGHT_CONFLICTS" value="true" />
@@ -132,7 +145,7 @@
     <property name="WebServerToolWindowPanel.toolwindow.show.date" value="false" />
     <property name="WebServerToolWindowPanel.toolwindow.show.permissions" value="false" />
     <property name="WebServerToolWindowPanel.toolwindow.show.size" value="false" />
-    <property name="last_opened_file_path" value="$PROJECT_DIR$" />
+    <property name="last_opened_file_path" value="$PROJECT_DIR$/../../code/dsp/tuoheng_dsp" />
     <property name="node.js.detected.package.eslint" value="true" />
     <property name="node.js.detected.package.tslint" value="true" />
     <property name="node.js.selected.package.eslint" value="(autodetect)" />
@@ -146,32 +159,33 @@
   </component>
   <component name="RecentsManager">
     <key name="CopyFile.RECENT_KEYS">
-      <recent name="D:\work\alg_new\tuoheng_alg\test\ffmpeg11" />
+      <recent name="D:\work\alg_new\tuoheng_alg\enums" />
       <recent name="D:\work\alg_new\tuoheng_alg\util" />
+      <recent name="D:\work\alg_new\tuoheng_alg\test\ffmpeg11" />
       <recent name="D:\work\alg\tuoheng_alg\test\ffmpeg11" />
       <recent name="D:\work\alg\tuoheng_alg\data" />
-      <recent name="D:\work\alg\tuoheng_alg\test" />
     </key>
     <key name="MoveFile.RECENT_KEYS">
+      <recent name="D:\work\alg_new\tuoheng_alg\test\image" />
       <recent name="D:\work\alg\tuoheng_alg\test\水印" />
       <recent name="D:\work\alg\tuoheng_alg\image" />
     </key>
   </component>
-  <component name="RunManager" selected="Python.ffmpeg13">
-    <configuration name="aa" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
+  <component name="RunManager" selected="Python.ImgBaiduSdk">
+    <configuration name="ImgBaiduSdk" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
       <module name="tuoheng_alg" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
       <envs>
         <env name="PYTHONUNBUFFERED" value="1" />
       </envs>
-      <option name="SDK_HOME" value="sftp://dell@192.168.10.12:22/home/dell/anaconda3/envs/prod/bin/python3.8" />
-      <option name="WORKING_DIRECTORY" value="/home/chenyukun/algSch/test/ffmpeg11" />
+      <option name="SDK_HOME" value="$PROJECT_DIR$/../../../software/anaconda/envs/test/python.exe" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/util" />
       <option name="IS_MODULE_SDK" value="false" />
       <option name="ADD_CONTENT_ROOTS" value="true" />
       <option name="ADD_SOURCE_ROOTS" value="true" />
       <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="/home/chenyukun/algSch/test/ffmpeg11/aa.py" />
+      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/util/ImgBaiduSdk.py" />
       <option name="PARAMETERS" value="" />
       <option name="SHOW_COMMAND_LINE" value="false" />
       <option name="EMULATE_TERMINAL" value="false" />
@@ -180,20 +194,20 @@
       <option name="INPUT_FILE" value="" />
       <method v="2" />
     </configuration>
-    <configuration name="ffmpeg12" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
+    <configuration name="editImage" type="PythonConfigurationType" factoryName="Python" nameIsGenerated="true">
       <module name="tuoheng_alg" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
       <envs>
         <env name="PYTHONUNBUFFERED" value="1" />
       </envs>
-      <option name="SDK_HOME" value="D:\software\anaconda\envs\chenyukun\python.exe" />
-      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test/ffmpeg11" />
+      <option name="SDK_HOME" value="$PROJECT_DIR$/../../../software/anaconda/envs/test/python.exe" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test/editimage" />
       <option name="IS_MODULE_SDK" value="false" />
       <option name="ADD_CONTENT_ROOTS" value="true" />
       <option name="ADD_SOURCE_ROOTS" value="true" />
       <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/ffmpeg11/ffmpeg12.py" />
+      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/editimage/editImage.py" />
       <option name="PARAMETERS" value="" />
       <option name="SHOW_COMMAND_LINE" value="false" />
       <option name="EMULATE_TERMINAL" value="false" />
@@ -202,7 +216,7 @@
       <option name="INPUT_FILE" value="" />
       <method v="2" />
     </configuration>
-    <configuration name="ffmpeg13" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
+    <configuration name="ffmpeg12" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
       <module name="tuoheng_alg" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
@@ -215,7 +229,7 @@
       <option name="ADD_CONTENT_ROOTS" value="true" />
       <option name="ADD_SOURCE_ROOTS" value="true" />
       <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/ffmpeg11/ffmpeg13.py" />
+      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/ffmpeg11/ffmpeg12.py" />
       <option name="PARAMETERS" value="" />
       <option name="SHOW_COMMAND_LINE" value="false" />
       <option name="EMULATE_TERMINAL" value="false" />
@@ -224,20 +238,20 @@
       <option name="INPUT_FILE" value="" />
       <method v="2" />
     </configuration>
-    <configuration name="mysqltest" type="PythonConfigurationType" factoryName="Python" nameIsGenerated="true">
+    <configuration name="ffmpeg13" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
       <module name="tuoheng_alg" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
       <envs>
         <env name="PYTHONUNBUFFERED" value="1" />
       </envs>
-      <option name="SDK_HOME" value="" />
-      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test" />
-      <option name="IS_MODULE_SDK" value="true" />
+      <option name="SDK_HOME" value="D:\software\anaconda\envs\chenyukun\python.exe" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test/ffmpeg11" />
+      <option name="IS_MODULE_SDK" value="false" />
       <option name="ADD_CONTENT_ROOTS" value="true" />
       <option name="ADD_SOURCE_ROOTS" value="true" />
       <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/mysqltest.py" />
+      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/ffmpeg11/ffmpeg13.py" />
       <option name="PARAMETERS" value="" />
       <option name="SHOW_COMMAND_LINE" value="false" />
       <option name="EMULATE_TERMINAL" value="false" />
@@ -246,20 +260,20 @@
       <option name="INPUT_FILE" value="" />
       <method v="2" />
     </configuration>
-    <configuration name="producer_start1" type="PythonConfigurationType" factoryName="Python" temporary="true">
+    <configuration name="mysqltest" type="PythonConfigurationType" factoryName="Python" nameIsGenerated="true">
       <module name="tuoheng_alg" />
       <option name="INTERPRETER_OPTIONS" value="" />
       <option name="PARENT_ENVS" value="true" />
       <envs>
         <env name="PYTHONUNBUFFERED" value="1" />
       </envs>
-      <option name="SDK_HOME" value="$PROJECT_DIR$/../../../software/anaconda/envs/test/python.exe" />
-      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test/kafka" />
-      <option name="IS_MODULE_SDK" value="false" />
+      <option name="SDK_HOME" value="" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/test" />
+      <option name="IS_MODULE_SDK" value="true" />
       <option name="ADD_CONTENT_ROOTS" value="true" />
       <option name="ADD_SOURCE_ROOTS" value="true" />
       <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
-      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/kafka/producer_start.py" />
+      <option name="SCRIPT_NAME" value="$PROJECT_DIR$/test/mysqltest.py" />
       <option name="PARAMETERS" value="" />
       <option name="SHOW_COMMAND_LINE" value="false" />
       <option name="EMULATE_TERMINAL" value="false" />
@@ -291,20 +305,19 @@
       <method v="2" />
     </configuration>
     <list>
+      <item itemvalue="Python.editImage" />
       <item itemvalue="Python.mysqltest" />
-      <item itemvalue="Python.aa" />
-      <item itemvalue="Python.producer_start1" />
       <item itemvalue="Python.test" />
       <item itemvalue="Python.ffmpeg12" />
       <item itemvalue="Python.ffmpeg13" />
+      <item itemvalue="Python.ImgBaiduSdk" />
     </list>
     <recent_temporary>
       <list>
+        <item itemvalue="Python.ImgBaiduSdk" />
         <item itemvalue="Python.ffmpeg13" />
         <item itemvalue="Python.ffmpeg12" />
         <item itemvalue="Python.test" />
-        <item itemvalue="Python.producer_start1" />
-        <item itemvalue="Python.aa" />
       </list>
     </recent_temporary>
   </component>
@@ -409,6 +422,8 @@
       <workItem from="1677632498068" duration="4279000" />
       <workItem from="1677654510460" duration="2082000" />
       <workItem from="1677727307545" duration="438000" />
+      <workItem from="1678153491396" duration="9573000" />
+      <workItem from="1678253386456" duration="45394000" />
     </task>
     <servers />
   </component>
@@ -450,8 +465,10 @@
   <component name="com.intellij.coverage.CoverageDataManagerImpl">
     <SUITE FILE_PATH="coverage/tuoheng_alg$cv2test1__1_.coverage" NAME="cv2test1 覆盖结果" MODIFIED="1665820653649" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$test.coverage" NAME="test 覆盖结果" MODIFIED="1675048794635" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test/str" />
+    <SUITE FILE_PATH="coverage/tuoheng_alg$ImgBaiduSdk.coverage" NAME="ImgBaiduSdk 覆盖结果" MODIFIED="1678355024003" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/util" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$mysqltest.coverage" NAME="mysqltest Coverage Results" MODIFIED="1660868712851" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$ffmpeg33.coverage" NAME="ffmpeg33 覆盖结果" MODIFIED="1670489109246" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test/ffmpeg11" />
+    <SUITE FILE_PATH="coverage/tuoheng_alg$editImage.coverage" NAME="editImage 覆盖结果" MODIFIED="1678348350574" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test/editimage" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$asnyc.coverage" NAME="asnyc Coverage Results" MODIFIED="1663459033435" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$asnyc__1_.coverage" NAME="asnyc (1) Coverage Results" MODIFIED="1663458917599" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test" />
     <SUITE FILE_PATH="coverage/tuoheng_alg$1.coverage" NAME="协程1 覆盖结果" MODIFIED="1667866542122" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/test/协程" />

concurrency/IntelligentRecognitionProcess.py

@@ -1,26 +1,29 @@
 # -*- coding: utf-8 -*-
 import asyncio
+import base64
 import json
 import os
+import sys
 import time
 import copy
 from concurrent.futures import ThreadPoolExecutor, as_completed
 
 import cv2
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
 
 from common import Constant
 from multiprocessing import Process, Queue
 from loguru import logger
 
 from concurrency.FileUpdateThread import build_image_name
-from concurrency.HeartbeatThread import Heartbeat
 from concurrency.PullVideoStreamProcess import OnlinePullVideoStreamProcess, OfflinePullVideoStreamProcess
 from entity import FeedBack
 from enums.AnalysisStatusEnum import AnalysisStatus
 from enums.AnalysisTypeEnum import AnalysisType
 from enums.ExceptionEnum import ExceptionType
 from enums.ModelTypeEnum import ModelType
-from util import LogUtils, TimeUtils, ImageUtils, ModelUtils
+from util import LogUtils, TimeUtils, ImageUtils
 from util.AliyunSdk import AliyunOssSdk
 from util.Cv2Utils import Cv2Util
 from entity.FeedBack import message_feedback
@@ -29,7 +32,11 @@ from concurrency.CommonThread import Common
 from exception.CustomerException import ServiceException
 from util.ImageUtils import PictureWaterMark, url2Array
 from util.OcrBaiduSdk import OcrBaiduSdk
+from util.ModelUtils import MODEL_CONFIG
 
+from enums.BaiduSdkEnum import VehicleEnumVALUE
+from enums.ModelTypeEnum import BaiduModelTarget
+sys.path.extend(['..', '../font'])
 
 class IntelligentRecognitionProcess(Process):
     def __init__(self, cfg):
@@ -151,9 +158,8 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
         pullProcess.sendCommand({"command": "stop_pull_stream"})
         if not os.path.exists(self.orFilePath) or not os.path.exists(self.aiFilePath):
             logger.error("原视频或AI视频不存在！requestId:{}", self.msg.get("request_id"))
-            raise ServiceException(ExceptionType.VIDEO_ADDRESS_EXCEPTION.value[0],
-                                   ExceptionType.VIDEO_ADDRESS_EXCEPTION.value[1])
-
+            raise ServiceException(ExceptionType.PUSH_STREAM_TIME_EXCEPTION.value[0],
+                                   ExceptionType.PUSH_STREAM_TIME_EXCEPTION.value[1])
         params1 = (self.orFilePath, "orOnLineVideo", self.content, logger, self.msg.get("request_id"))
         or_update_thread = Common(content=self.content, func=AliyunSdk.get_play_url, args=params1)
         params2 = (self.aiFilePath, "aiOnLineVideo", self.content, logger, self.msg.get("request_id"))
@@ -187,9 +193,11 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
             # 程序开始时间
             LogUtils.init_log(self.content)
             self.sendhbMessage(AnalysisStatus.WAITING.value, "0.0000", AnalysisType.ONLINE.value)
-            mod, model_type_code = get_model((str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id")))
+            mod, model_type_code = get_model(
+                (str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id"), self.content))
             # 结果反馈进程启动
-            pullProcess = OnlinePullVideoStreamProcess(self.msg, self.content, self.pullQueue, self.fbQueue, self.hbQueue,
+            pullProcess = OnlinePullVideoStreamProcess(self.msg, self.content, self.pullQueue, self.fbQueue,
+                                                       self.hbQueue,
                                                        self.imageQueue)
             pullProcess.daemon = True
             pullProcess.start()
@@ -246,8 +254,8 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                 if r[1] is None or not r[1]:
                                     t.shutdown(wait=False)
                                     loop.close()
-                                    raise ServiceException(ExceptionType.WRITE_STREAM_EXCEPTION.value[0],
-                                                           ExceptionType.WRITE_STREAM_EXCEPTION.value[1])
+                                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
                                 if p_result[2] is not None and len(p_result[2]) > 0:
                                     for ai_analyse_result in p_result[2]:
                                         order = str(int(ai_analyse_result[0]))
@@ -469,8 +477,8 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
         pullProcess.sendCommand({"command": "stop_pull_stream"})
         if not os.path.exists(self.aiFilePath):
             logger.error("AI视频不存在！requestId:{}", self.msg.get("request_id"))
-            raise ServiceException(ExceptionType.VIDEO_ADDRESS_EXCEPTION.value[0],
-                                   ExceptionType.VIDEO_ADDRESS_EXCEPTION.value[1])
+            raise ServiceException(ExceptionType.PUSH_STREAM_TIME_EXCEPTION.value[0],
+                                   ExceptionType.PUSH_STREAM_TIME_EXCEPTION.value[1])
         params2 = (self.aiFilePath, "aiOffLineVideo", self.content, logger, self.msg.get("request_id"))
         ai_update_thread = Common(content=self.content, func=AliyunSdk.get_play_url, args=params2)
         ai_update_thread.setDaemon(True)
@@ -498,8 +506,10 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
             # 程序开始时间
             LogUtils.init_log(self.content)
             self.sendhbMessage(AnalysisStatus.WAITING.value, "0.0000", AnalysisType.OFFLINE.value)
-            mod, model_type_code = get_model((str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id")))
-            pullProcess = OfflinePullVideoStreamProcess(self.msg, self.content, self.pullQueue, self.fbQueue, self.hbQueue,
+            mod, model_type_code = get_model(
+                (str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id"), self.content))
+            pullProcess = OfflinePullVideoStreamProcess(self.msg, self.content, self.pullQueue, self.fbQueue,
+                                                        self.hbQueue,
                                                         self.imageQueue)
             pullProcess.daemon = True
             pullProcess.start()
@@ -559,9 +569,10 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                 if r[1] is None or not r[1]:
                                     t.shutdown(wait=False)
                                     loop.close()
-                                    raise ServiceException(ExceptionType.WRITE_STREAM_EXCEPTION.value[0],
-                                                           ExceptionType.WRITE_STREAM_EXCEPTION.value[1])
-                                if frame_all[0].get("cct_frame") % 600 == 0 and float(frame_all[0].get("cct_frame")) <= float(frame_all[0].get("all_frame")):
+                                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
+                                if frame_all[0].get("cct_frame") % 600 == 0 and float(
+                                        frame_all[0].get("cct_frame")) <= float(frame_all[0].get("all_frame")):
                                     task_process = str(format(
                                         float(frame_all[0].get("cct_frame")) / float(frame_all[0].get("all_frame")),
                                         '.4f'))
@@ -758,25 +769,26 @@ def image_recognition(imageUrl, mod, content, pic, msg, fbQueue, model_type_code
         # logger.info("算法模型调度时间：{}s, requestId:{}", time.time() - time00, self.msg.get("request_id"))
         # 原视频保存本地、AI视频保存本地
         if content["video"]["video_add_water"]:
-            frame = pic.common_water_1(image, pic.logo)
+            # frame = pic.common_water_1(image, pic.logo)
             p_result[1] = pic.common_water_1(p_result[1], pic.logo)
         aliyunOssSdk = AliyunOssSdk(content, logger, msg.get("request_id"))
         aliyunOssSdk.get_oss_bucket()
         loop = asyncio.new_event_loop()
         asyncio.set_event_loop(loop)
-        or_image = cv2.imencode(".jpg", frame)[1]
+        # or_image = cv2.imencode(".jpg", frame)[1]
         ai_image = cv2.imencode(".jpg", p_result[1])[1]
         # 定义上传图片名称
         random_num = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
         time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
         if p_result[2] is not None and len(p_result[2]) > 0:
             # 图片名称待后期修改
-            or_image_name = build_image_name(msg.get('results_base_dir'), time_now, str(0), str(0), random_num,
-                                             'image', msg.get('request_id'), "OR")
+            # or_image_name = build_image_name(msg.get('results_base_dir'), time_now, str(0), str(0), random_num,
+            #                                  'image', msg.get('request_id'), "OR")
             ai_image_name = build_image_name(msg.get('results_base_dir'), time_now,
                                              str(0), str(0), random_num, 'image', msg.get('request_id'), "AI")
-            loop.run_until_complete(asyncio.wait([upload_file(aliyunOssSdk, or_image_name, or_image),
-                                                  upload_file(aliyunOssSdk, ai_image_name, ai_image)]))
+            # loop.run_until_complete(asyncio.wait([upload_file(aliyunOssSdk, or_image_name, or_image),
+            #                                       upload_file(aliyunOssSdk, ai_image_name, ai_image)]))
+            loop.run_until_complete(asyncio.wait([upload_file(aliyunOssSdk, ai_image_name, ai_image)]))
             order = []
             for ai_analyse_result in p_result[2]:
                 order.append(str(int(ai_analyse_result[0])))
@@ -785,7 +797,8 @@ def image_recognition(imageUrl, mod, content, pic, msg, fbQueue, model_type_code
                                                                AnalysisStatus.RUNNING.value,
                                                                AnalysisType.IMAGE.value, "", "",
                                                                '',
-                                                               or_image_name,
+                                                               # or_image_name,
+                                                               imageUrl,
                                                                ai_image_name,
                                                                model_type_code,
                                                                ",".join(set(order)),
@@ -835,7 +848,7 @@ def epidemic_prevention(imageUrl, mod, content, orc, msg, fbQueue, model_type_co
                 else:
                     carCode = result.get("words_result").get("number")
             if len(carCode) > 0:
-                plate_result = {'type': str(3), 'carUrl': imageUrl, 'carCode': carCode, 'score': score}
+                plate_result = {'type': str(3), 'modelCode': model_type_code, 'carUrl': imageUrl, 'carCode': carCode, 'score': score}
                 fbQueue.put({"feedback": FeedBack.message_feedback(msg.get('request_id'),
                                                                    AnalysisStatus.RUNNING.value,
                                                                    AnalysisType.IMAGE.value, "", "",
@@ -876,6 +889,7 @@ def epidemic_prevention(imageUrl, mod, content, orc, msg, fbQueue, model_type_co
                         cityRecognition = city.get("words_result")
                 if len(phoneNumberRecognition) > 0 or len(cityRecognition) > 0:
                     trip_result = {'type': str(1),
+                                   'modelCode': model_type_code,
                                    'imageUrl': imageUrl,
                                    'phoneNumberRecognition': phoneNumberRecognition,
                                    'phone_sorce': phone_score,
@@ -929,6 +943,7 @@ def epidemic_prevention(imageUrl, mod, content, orc, msg, fbQueue, model_type_co
                         hsRecognition = hs.get("words_result")
                 if len(nameRecognition) > 0 or len(phoneNumberRecognition) > 0 or len(hsRecognition) > 0:
                     healthy_result = {'type': str(2),
+                                      'modelCode': model_type_code,
                                       'imageUrl': imageUrl,
                                       'color': dataBack.get("color"),
                                       'nameRecognition': nameRecognition,
@@ -953,6 +968,134 @@ def epidemic_prevention(imageUrl, mod, content, orc, msg, fbQueue, model_type_co
         logger.exception("模型分析异常: {}, requestId: {}", e, msg.get("request_id"))
         return False
 
+def mark(content, info, img, color):
+    # score = info.get("probability")
+    # if score is None:
+    #     score = info.get("location").get("score")
+    # text = "%s: %.2f]" % (content, score)
+    # text_xy = (info.get("location").get("left"), info.get("location").get("top") - 30)
+    img_lu = (info.get("location").get("left"), info.get("location").get("top"))
+    img_rd = (info.get("location").get("left") + info.get("location").get("width"),
+              info.get("location").get("top") + info.get("location").get("height"))
+    # cv2.putText(img, text, text_xy, cv2.FONT_HERSHEY_SIMPLEX, 1.0, color, 1, cv2.LINE_AA)
+    count = 1
+    if img.shape[1] > 1600:
+        count = 2
+    cv2.rectangle(img, img_lu, img_rd, color, count)
+    return img
+
+
+def baidu_recognition(imageUrl, mod, msg, content, fbQueue, model_type_code):
+    try:
+        # 检查检测目标
+        if mod.allowedList is None or len(mod.allowedList) == 0:
+            return True
+        img = url2Array(imageUrl)
+        aliyunOssSdk = AliyunOssSdk(content, logger, msg.get('request_id'))
+        aliyunOssSdk.get_oss_bucket()
+        for target in mod.allowedList:
+            result = mod.process(target, imageUrl)
+            if target == BaiduModelTarget.VEHICLE_DETECTION.value[1] and result is not None:
+                vehicleInfo = result.get("vehicle_info")
+                if vehicleInfo is not None and len(vehicleInfo) > 0:
+                    aiIamge = None
+                    for i, info in enumerate(vehicleInfo):
+                        value = VehicleEnumVALUE.get(info.get("type"))
+                        if value is None:
+                            logger.error("车辆识别出现未支持的目标类型！type:{}, requestId:{}", info.get("type"), msg.get('request_id'))
+                            raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                                   ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
+                        aiIamge = mark("["+str(i) + "][" + value.value[1], info, img, (255, 0, 255))
+                        info["id"] = str(i)
+                    if aiIamge is not None and len(aiIamge) > 0:
+                        random_num = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
+                        time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
+                        ai_image_name = build_image_name(msg.get('results_base_dir'), time_now,
+                                                         str(0),
+                                                         str(0),
+                                                         random_num,
+                                                         AnalysisType.IMAGE.value,
+                                                         msg.get('request_id'), "AI")
+                        ai_result, ai_image = cv2.imencode(".jpg", aiIamge)
+                        aliyunOssSdk.sync_upload_file(ai_image_name, ai_image.tobytes())
+                        result["type"] = str(target)
+                        result["modelCode"] = model_type_code
+                        fbQueue.put({"feedback": FeedBack.message_feedback(msg.get('request_id'),
+                                                                           AnalysisStatus.RUNNING.value,
+                                                                           AnalysisType.IMAGE.value, "", "",
+                                                                           '',
+                                                                           imageUrl,
+                                                                           ai_image_name,
+                                                                           model_type_code,
+                                                                           str(target),
+                                                                           TimeUtils.now_date_to_str(),
+                                                                           json.dumps(result))})
+            # 人体识别
+            if target == BaiduModelTarget.HUMAN_DETECTION.value[1] and result is not None:
+                personInfo = result.get("person_info")
+                personNum = result.get("person_num")
+                if personNum is not None and personNum > 0 and personInfo is not None and len(personInfo) > 0:
+                    personImage = None
+                    for i, info in enumerate(personInfo):
+                        personImage = mark("[" + str(i) + "][人", info, img, (255, 0, 0))
+                        info["id"] = str(i)
+                    if  personImage is not None and len(personImage) > 0:
+                        random_num = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
+                        time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
+                        ai_image_name = build_image_name(msg.get('results_base_dir'), time_now,
+                                                         str(0),
+                                                         str(0),
+                                                         random_num,
+                                                         AnalysisType.IMAGE.value,
+                                                         msg.get('request_id'), "AI")
+                        ai_result, ai_image = cv2.imencode(".jpg", personImage)
+                        aliyunOssSdk.sync_upload_file(ai_image_name, ai_image.tobytes())
+                        result["type"] = str(target)
+                        result["modelCode"] = model_type_code
+                        fbQueue.put({"feedback": FeedBack.message_feedback(msg.get('request_id'),
+                                                                           AnalysisStatus.RUNNING.value,
+                                                                           AnalysisType.IMAGE.value, "", "",
+                                                                           '',
+                                                                           imageUrl,
+                                                                           ai_image_name,
+                                                                           model_type_code,
+                                                                           str(target),
+                                                                           TimeUtils.now_date_to_str(),
+                                                                           json.dumps(result))})
+
+            # 人流量
+            if target == BaiduModelTarget.PEOPLE_COUNTING.value[1] and result is not None:
+                base64Image = result.get("image")
+                if base64Image is not None and len(base64Image) > 0:
+                    baiduImage = base64.b64decode(base64Image)
+                    random_num = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
+                    time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
+                    ai_image_name = build_image_name(msg.get('results_base_dir'), time_now,
+                                                     str(0),
+                                                     str(0),
+                                                     random_num,
+                                                     AnalysisType.IMAGE.value,
+                                                     msg.get('request_id'), "AI")
+                    aliyunOssSdk.sync_upload_file(ai_image_name, baiduImage)
+                    result["type"] = str(target)
+                    result["modelCode"] = model_type_code
+                    del result["image"]
+                    fbQueue.put({"feedback": FeedBack.message_feedback(msg.get('request_id'),
+                                                                       AnalysisStatus.RUNNING.value,
+                                                                       AnalysisType.IMAGE.value, "", "",
+                                                                       '',
+                                                                       imageUrl,
+                                                                       ai_image_name,
+                                                                       model_type_code,
+                                                                       str(target),
+                                                                       TimeUtils.now_date_to_str(),
+                                                                       json.dumps(result))})
+        logger.info("算法分析结果: {}", result)
+        return True
+    except Exception as e:
+        logger.exception("百度AI分析异常: {}, requestId: {}", e, msg.get("request_id"))
+        return False
+
 
 '''
 图片识别
@@ -990,6 +1133,19 @@ class PhotosIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                     result = False
         return result
 
+    def baiduRecognition(self, imageUrls, mod, model_type_code):
+        result = True
+        with ThreadPoolExecutor(max_workers=5) as t:
+            obj_list = []
+            for imageUrl in imageUrls:
+                obj = t.submit(baidu_recognition, imageUrl, mod, self.msg, self.content, self.fbQueue, model_type_code)
+                obj_list.append(obj)
+            for future in as_completed(obj_list):
+                data = future.result()
+                if not data:
+                    result = False
+        return result
+
     def run(self):
         try:
             # 初始化日志
@@ -1000,11 +1156,15 @@ class PhotosIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                                           AnalysisType.IMAGE.value,
                                                           progress='0.0000',
                                                           analyse_time=TimeUtils.now_date_to_str())})
+
             # 加载模型
-            mod, model_type_code = get_model((str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id")))
+            mod, model_type_code = get_model(
+                (str(self.gpu_ids[0]), self.msg["models"], self.msg.get("request_id"), self.content))
             # 获取所有图片信息
             imageUrls = self.msg.get("image_urls")
-            if model_type_code == ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]:
+            if model_type_code == ModelType.BAIDU_MODEL.value[1]:
+                result = self.baiduRecognition(imageUrls, mod, model_type_code)
+            elif model_type_code == ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]:
                 result = self.epidemicPrevention(imageUrls, mod, model_type_code)
             elif model_type_code == ModelType.PLATE_MODEL.value[1]:
                 result = self.epidemicPrevention(imageUrls, mod, model_type_code)
@@ -1054,43 +1214,19 @@ class PhotosIntelligentRecognitionProcess(IntelligentRecognitionProcess):
 
 def get_model(args):
     logger.info("######################开始加载模型######################")
-    model_config = {
-        # 加载河道模型
-        ModelType.WATER_SURFACE_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.WATER_SURFACE_MODEL), ModelType.WATER_SURFACE_MODEL.value[1]),
-        # 加载林场模型
-        ModelType.FOREST_FARM_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.FOREST_FARM_MODEL), ModelType.FOREST_FARM_MODEL.value[1]),
-        # 加载交通模型
-        ModelType.TRAFFIC_FARM_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.TRAFFIC_FARM_MODEL), ModelType.TRAFFIC_FARM_MODEL.value[1]),
-        # 加载防疫模型
-        ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.IMModel(x, y, z, r, ModelType.EPIDEMIC_PREVENTION_MODEL), ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]),
-        # 加载车牌模型
-        ModelType.PLATE_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.IMModel(x, y, z, r, ModelType.PLATE_MODEL), ModelType.PLATE_MODEL.value[1]),
-        # 加载车辆模型
-        ModelType.VEHICLE_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.VEHICLE_MODEL), ModelType.VEHICLE_MODEL.value[1]),
-        # 加载行人模型
-        ModelType.PEDESTRIAN_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.PEDESTRIAN_MODEL), ModelType.PEDESTRIAN_MODEL.value[1]),
-        # 加载烟火模型
-        ModelType.SMOGFIRE_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.SMOGFIRE_MODEL), ModelType.SMOGFIRE_MODEL.value[1]),
-        # 加载钓鱼游泳模型
-        ModelType.ANGLERSWIMMER_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.ANGLERSWIMMER_MODEL), ModelType.ANGLERSWIMMER_MODEL.value[1]),
-        # 加载乡村模型
-        ModelType.COUNTRYROAD_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.COUNTRYROAD_MODEL), ModelType.COUNTRYROAD_MODEL.value[1]),
-        # 加载船只模型
-        ModelType.SHIP_MODEL.value[1]: (lambda x, y, z, r: ModelUtils.Model(x, y, z, r, ModelType.SHIP_MODEL), ModelType.SHIP_MODEL.value[1])
-    }
     for model in args[1]:
         try:
             code = model.get("code")
             needed_objectsIndex = [int(category.get("id")) for category in model.get("categories")]
             logger.info("code:{}, 检查目标：{}, gpuId:{}", code, needed_objectsIndex, args[0])
-            model_method = model_config.get(code)
+            model_method = MODEL_CONFIG.get(code)
             if model_method is not None:
-                return model_method[0](args[0], needed_objectsIndex, logger, args[2]), model_method[1]
+                return model_method[0](args[0], needed_objectsIndex, logger, args[2], args[3]), model_method[1]
             else:
                 logger.error("未匹配到对应的模型")
                 raise ServiceException(ExceptionType.AI_MODEL_MATCH_EXCEPTION.value[0],
                                        ExceptionType.AI_MODEL_MATCH_EXCEPTION.value[1])
         except Exception as e:
             logger.exception("获取模型配置异常: {}", e)
-            raise ServiceException(ExceptionType.AI_MODEL_CONFIG_EXCEPTION.value[0],
-                                   ExceptionType.AI_MODEL_CONFIG_EXCEPTION.value[1])
+            raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                   ExceptionType.SERVICE_INNER_EXCEPTION.value[1])

dsp_application.yml

@@ -134,10 +134,22 @@ service:
   timeout: 21600 # 一次识别任务超时时间，单位秒，默认6个小时
   cv2_pull_stream_timeout: 3600 # 直播开始视频未推流超时时间
   cv2_read_stream_timeout: 1800 # 直播读流中超时时间
-baiduocr:
-  APP_ID: 28173504
-  API_KEY: kqrFE7VuygIaFer7z6cRxzoi
-  SECRET_KEY: yp7xBokyl4TItyGhay7skAN1cMwfvEXf
+baidu:
+  orc:
+    APP_ID: 28173504
+    API_KEY: kqrFE7VuygIaFer7z6cRxzoi
+    SECRET_KEY: yp7xBokyl4TItyGhay7skAN1cMwfvEXf
+  # 车辆检测
+  vehicle:
+    APP_ID: 31096670
+    API_KEY: Dam3O4tgPRN3qh4OYE82dbg7
+    SECRET_KEY: 1PGZ9LAXRR5zcT5MN9rHcW8kLBIS5DAa
+  # 人
+  person:
+    APP_ID: 31096755
+    API_KEY: CiWrt4iyxOly36n3kR7utiAG
+    SECRET_KEY: K7y6V3XTGdyXvgtCNCwTGUEooxxDuX9v
+
 # 日志设置
 log:
   # 是否开启文件输出 True：开启 False：关闭

enums/BaiduSdkEnum.py

@@ -0,0 +1,175 @@
+from enum import Enum, unique
+
+'''
+    官方文档: https://ai.baidu.com/ai-doc/VEHICLE/rk3inf9tj
+    参数1: 异常编号
+    参数2: 异常英文描述
+    参数3: 异常中文描述
+    参数4: 0-异常信息统一输出为内部异常 
+          1-异常信息可以输出
+          2-输出空的异常信息
+    参数5: 指定异常重试的次数
+'''
+
+
+# 异常枚举
+@unique
+class BaiduSdkErrorEnum(Enum):
+
+    UNKNOWN_ERROR = (1, "Unknown error", "未知错误", 0, 0)
+
+    SERVICE_TEMPORARILY_UNAVAILABLE = (2, "Service temporarily unavailable", "服务暂不可用，请再次请求", 0, 3)
+
+    UNSUPPORTED_OPENAPI_METHOD = (3, "Unsupported openapi method", "调用的API不存在", 0, 0)
+
+    API_REQUEST_LIMIT_REACHED = (4, "Open api request limit reached", "请求量限制, 请稍后再试!", 1, 5)
+
+    NO_PERMISSION_TO_ACCESS_DATA = (6, "No permission to access data", "无权限访问该用户数据", 1, 0)
+
+    GET_SERVICE_TOKEN_FAILED = (13, "Get service token failed", "获取token失败", 0, 2)
+
+    IAM_CERTIFICATION_FAILED = (14, "IAM Certification failed", "IAM 鉴权失败", 0, 2)
+
+    APP_NOT_EXSITS_OR_CREATE_FAILED = (15, "app not exsits or create failed", "应用不存在或者创建失败", 0, 0)
+
+    API_DAILY_REQUEST_LIMIT_REACHED = (17, "Open api daily request limit reached", "每天请求量超限额!", 1, 5)
+
+    API_QPS_REQUEST_LIMIT_REACHED = (18, "Open api qps request limit reached", "QPS超限额!", 1, 5)
+
+    API_TOTAL_REQUEST_LIMIT_REACHED = (19, "Open api total request limit reached", "请求总量超限额!", 1, 2)
+
+    INVALID_TOKEN = (100, "Invalid parameter", "无效的access_token参数，token拉取失败", 0, 2)
+
+    ACCESS_TOKEN_INVALID_OR_NO_LONGER_VALID = (110, "Access token invalid or no longer valid", "access_token无效，token有效期为30天", 0, 2)
+
+    ACCESS_TOKEN_EXPIRED = (111, "Access token expired", "access token过期，token有效期为30天", 0, 2)
+
+    INTERNAL_ERROR = (282000, "internal error", "服务器内部错误", 0, 1)
+
+    INVALID_PARAM = (216100, "invalid param", "请求中包含非法参数!", 0, 0)
+
+    NOT_ENOUGH_PARAM = (216101, "not enough param", "缺少必须的参数!", 0, 0)
+
+    SERVICE_NOT_SUPPORT = (216102, "service not support", "请求了不支持的服务，请检查调用的url", 0, 0)
+
+    PARAM_TOO_LONG = (216103, "param too long", "请求中某些参数过长!", 1, 0)
+
+    APPID_NOT_EXIST = (216110, "appid not exist", "appid不存在", 0, 0)
+
+    EMPTY_IMAGE = (216200, "empty image", "图片为空!", 1, 0)
+
+    IMAGE_FORMAT_ERROR = (216201, "image format error", "上传的图片格式错误，现阶段我们支持的图片格式为：PNG、JPG、JPEG、BMP", 1, 0)
+
+    IMAGE_SIZE_ERROR = (216202, "image size error", "上传的图片大小错误，现阶段我们支持的图片大小为：base64编码后小于4M，分辨率不高于4096*4096", 1, 0)
+
+    IMAGE_SIZE_BASE_ERROR = (216203, "image size error", "上传的图片base64编码有误", 1, 0)
+
+    RECOGNIZE_ERROR = (216630, "recognize error", "识别错误", 2, 3)
+
+    DETECT_ERROR = (216634, "detect error", "检测错误", 2, 3)
+
+    MISSING_PARAMETERS = (282003, "missing parameters: {参数名}", "请求参数缺失", 0, 0)
+
+    BATCH_ROCESSING_ERROR = (282005, "batch processing error", "处理批量任务时发生部分或全部错误", 0, 5)
+
+    BATCH_TASK_LIMIT_REACHED = (282006, "batch task limit reached", "批量任务处理数量超出限制，请将任务数量减少到10或10以下", 1, 5)
+
+    IMAGE_TRANSCODE_ERROR = (282100, "image transcode error", "图片压缩转码错误", 0, 1)
+
+    IMAGE_SPLIT_LIMIT_REACHED = (282101, "image split limit reached", "长图片切分数量超限!", 1, 1)
+
+    TARGET_DETECT_ERROR = (282102, "target detect error", "未检测到图片中识别目标!", 2, 1) #
+
+    TARGET_RECOGNIZE_ERROR = (282103, "target recognize error", "图片目标识别错误!", 2, 1)
+
+    URL_SIZE_ERROR = (282114, "url size error", "URL长度超过1024字节或为0!", 1, 0)
+
+    REQUEST_ID_NOT_EXIST = (282808, "request id: xxxxx not exist", "request id xxxxx 不存在", 0, 0)
+
+    RESULT_TYPE_ERROR = (282809, "result type error", "返回结果请求错误（不属于excel或json）", 0, 0)
+
+    IMAGE_RECOGNIZE_ERROR = (282810, "image recognize error", "图像识别错误", 2, 1)
+
+    INVALID_ARGUMENT = (283300, "Invalid argument", "入参格式有误，可检查下图片编码、代码格式是否有误", 1, 0)
+
+    INTERNAL_ERROR_2 = (336000, "Internal error", "服务器内部错误", 0, 0)
+
+    INVALID_ARGUMENT_2 = (336001, "Invalid Argument", "入参格式有误，比如缺少必要参数、图片base64编码错误等等，可检查下图片编码、代码格式是否有误", 1, 0)
+
+    SDK_IMAGE_SIZE_ERROR = ('SDK100', "image size error", "图片大小超限，要求base64编码后大小不超过4M，最短边至少50px，最长边最大4096px ，建议长宽比3：1以内，图片请求格式支持：PNG、JPG、BMP", 1, 0)
+
+    SDK_IMAGE_LENGTH_ERROR = ('SDK101', "image length error", "图片边长不符合要求，最短边至少50px，最长边最大4096px ，建议长宽比3：1以内", 1, 0)
+
+    SDK_READ_IMAGE_FILE_ERROR = ('SDK102', "read image file error", "读取图片文件错误", 0, 1)
+
+    SDK_CONNECTION_OR_READ_DATA_TIME_OUT = ('SDK108', "connection or read data time out", "连接超时或读取数据超时，请检查本地网络设置、文件读取设置", 0, 3)
+
+    SDK_UNSUPPORTED_IMAGE_FORMAT = ('SDK109', "unsupported image format", "不支持的图片格式，当前支持以下几类图片：PNG、JPG、BMP", 1, 0)
+
+
+BAIDUERRORDATA = {
+    BaiduSdkErrorEnum.UNKNOWN_ERROR.value[0]: BaiduSdkErrorEnum.UNKNOWN_ERROR,
+    BaiduSdkErrorEnum.SERVICE_TEMPORARILY_UNAVAILABLE.value[0]: BaiduSdkErrorEnum.SERVICE_TEMPORARILY_UNAVAILABLE,
+    BaiduSdkErrorEnum.UNSUPPORTED_OPENAPI_METHOD.value[0]: BaiduSdkErrorEnum.UNSUPPORTED_OPENAPI_METHOD,
+    BaiduSdkErrorEnum.API_REQUEST_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.API_REQUEST_LIMIT_REACHED,
+    BaiduSdkErrorEnum.NO_PERMISSION_TO_ACCESS_DATA.value[0]: BaiduSdkErrorEnum.NO_PERMISSION_TO_ACCESS_DATA,
+    BaiduSdkErrorEnum.GET_SERVICE_TOKEN_FAILED.value[0]: BaiduSdkErrorEnum.GET_SERVICE_TOKEN_FAILED,
+    BaiduSdkErrorEnum.IAM_CERTIFICATION_FAILED.value[0]: BaiduSdkErrorEnum.IAM_CERTIFICATION_FAILED,
+    BaiduSdkErrorEnum.APP_NOT_EXSITS_OR_CREATE_FAILED.value[0]: BaiduSdkErrorEnum.APP_NOT_EXSITS_OR_CREATE_FAILED,
+    BaiduSdkErrorEnum.API_DAILY_REQUEST_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.API_DAILY_REQUEST_LIMIT_REACHED,
+    BaiduSdkErrorEnum.API_QPS_REQUEST_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.API_QPS_REQUEST_LIMIT_REACHED,
+    BaiduSdkErrorEnum.API_TOTAL_REQUEST_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.API_TOTAL_REQUEST_LIMIT_REACHED,
+    BaiduSdkErrorEnum.INVALID_TOKEN.value[0]: BaiduSdkErrorEnum.INVALID_TOKEN,
+    BaiduSdkErrorEnum.ACCESS_TOKEN_INVALID_OR_NO_LONGER_VALID.value[0]: BaiduSdkErrorEnum.ACCESS_TOKEN_INVALID_OR_NO_LONGER_VALID,
+    BaiduSdkErrorEnum.ACCESS_TOKEN_EXPIRED.value[0]: BaiduSdkErrorEnum.ACCESS_TOKEN_EXPIRED,
+    BaiduSdkErrorEnum.INTERNAL_ERROR.value[0]: BaiduSdkErrorEnum.INTERNAL_ERROR,
+    BaiduSdkErrorEnum.INVALID_PARAM.value[0]: BaiduSdkErrorEnum.INVALID_PARAM,
+    BaiduSdkErrorEnum.NOT_ENOUGH_PARAM.value[0]: BaiduSdkErrorEnum.NOT_ENOUGH_PARAM,
+    BaiduSdkErrorEnum.SERVICE_NOT_SUPPORT.value[0]: BaiduSdkErrorEnum.SERVICE_NOT_SUPPORT,
+    BaiduSdkErrorEnum.PARAM_TOO_LONG.value[0]: BaiduSdkErrorEnum.PARAM_TOO_LONG,
+    BaiduSdkErrorEnum.APPID_NOT_EXIST.value[0]: BaiduSdkErrorEnum.APPID_NOT_EXIST,
+    BaiduSdkErrorEnum.EMPTY_IMAGE.value[0]: BaiduSdkErrorEnum.EMPTY_IMAGE,
+    BaiduSdkErrorEnum.IMAGE_FORMAT_ERROR.value[0]: BaiduSdkErrorEnum.IMAGE_FORMAT_ERROR,
+    BaiduSdkErrorEnum.IMAGE_SIZE_ERROR.value[0]: BaiduSdkErrorEnum.IMAGE_SIZE_ERROR,
+    BaiduSdkErrorEnum.IMAGE_SIZE_BASE_ERROR.value[0]: BaiduSdkErrorEnum.IMAGE_SIZE_BASE_ERROR,
+    BaiduSdkErrorEnum.RECOGNIZE_ERROR.value[0]: BaiduSdkErrorEnum.RECOGNIZE_ERROR,
+    BaiduSdkErrorEnum.DETECT_ERROR.value[0]: BaiduSdkErrorEnum.DETECT_ERROR,
+    BaiduSdkErrorEnum.MISSING_PARAMETERS.value[0]: BaiduSdkErrorEnum.MISSING_PARAMETERS,
+    BaiduSdkErrorEnum.BATCH_ROCESSING_ERROR.value[0]: BaiduSdkErrorEnum.BATCH_ROCESSING_ERROR,
+    BaiduSdkErrorEnum.BATCH_TASK_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.BATCH_TASK_LIMIT_REACHED,
+    BaiduSdkErrorEnum.IMAGE_TRANSCODE_ERROR.value[0]: BaiduSdkErrorEnum.IMAGE_TRANSCODE_ERROR,
+    BaiduSdkErrorEnum.IMAGE_SPLIT_LIMIT_REACHED.value[0]: BaiduSdkErrorEnum.IMAGE_SPLIT_LIMIT_REACHED,
+    BaiduSdkErrorEnum.TARGET_DETECT_ERROR.value[0]: BaiduSdkErrorEnum.TARGET_DETECT_ERROR,
+    BaiduSdkErrorEnum.TARGET_RECOGNIZE_ERROR.value[0]: BaiduSdkErrorEnum.TARGET_RECOGNIZE_ERROR,
+    BaiduSdkErrorEnum.URL_SIZE_ERROR.value[0]: BaiduSdkErrorEnum.URL_SIZE_ERROR,
+    BaiduSdkErrorEnum.REQUEST_ID_NOT_EXIST.value[0]: BaiduSdkErrorEnum.REQUEST_ID_NOT_EXIST,
+    BaiduSdkErrorEnum.RESULT_TYPE_ERROR.value[0]: BaiduSdkErrorEnum.RESULT_TYPE_ERROR,
+    BaiduSdkErrorEnum.IMAGE_RECOGNIZE_ERROR.value[0]: BaiduSdkErrorEnum.IMAGE_RECOGNIZE_ERROR,
+    BaiduSdkErrorEnum.INVALID_ARGUMENT.value[0]: BaiduSdkErrorEnum.INVALID_ARGUMENT,
+    BaiduSdkErrorEnum.INTERNAL_ERROR_2.value[0]: BaiduSdkErrorEnum.INTERNAL_ERROR_2,
+    BaiduSdkErrorEnum.INVALID_ARGUMENT_2.value[0]: BaiduSdkErrorEnum.INVALID_ARGUMENT_2,
+    BaiduSdkErrorEnum.SDK_IMAGE_SIZE_ERROR.value[0]: BaiduSdkErrorEnum.SDK_IMAGE_SIZE_ERROR,
+    BaiduSdkErrorEnum.SDK_IMAGE_LENGTH_ERROR.value[0]: BaiduSdkErrorEnum.SDK_IMAGE_LENGTH_ERROR,
+    BaiduSdkErrorEnum.SDK_READ_IMAGE_FILE_ERROR.value[0]: BaiduSdkErrorEnum.SDK_READ_IMAGE_FILE_ERROR,
+    BaiduSdkErrorEnum.SDK_CONNECTION_OR_READ_DATA_TIME_OUT.value[0]: BaiduSdkErrorEnum.SDK_CONNECTION_OR_READ_DATA_TIME_OUT,
+    BaiduSdkErrorEnum.SDK_UNSUPPORTED_IMAGE_FORMAT.value[0]: BaiduSdkErrorEnum.SDK_UNSUPPORTED_IMAGE_FORMAT,
+}
+
+@unique
+class VehicleEnum(Enum):
+    CAR = ("car", "car")
+    TRICYCLE = ("tricycle", "tricycle")
+    MOTORBIKE = ("motorbike", "motorbike")
+    CARPLATE = ("carplate", "carplate")
+    TRUCK = ("truck", "truck")
+    BUS = ("bus", "bus")
+
+
+VehicleEnumVALUE={
+    VehicleEnum.CAR.value[0]: VehicleEnum.CAR,
+    VehicleEnum.TRICYCLE.value[0]: VehicleEnum.TRICYCLE,
+    VehicleEnum.MOTORBIKE.value[0]: VehicleEnum.MOTORBIKE,
+    VehicleEnum.CARPLATE.value[0]: VehicleEnum.CARPLATE,
+    VehicleEnum.TRUCK.value[0]: VehicleEnum.TRUCK,
+    VehicleEnum.BUS.value[0]: VehicleEnum.BUS
+}

enums/ExceptionEnum.py

@@ -5,62 +5,36 @@ from enum import Enum, unique
 @unique
 class ExceptionType(Enum):
 
-    VIDEO_UPDATE_EXCEPTION = ("SP000", "Video upload exception!")
+    OR_VIDEO_ADDRESS_EXCEPTION = ("SP000", "拉取原视频失败!")
 
-    OR_VIDEO_ADDRESS_EXCEPTION = ("SP001", "Original Video Address Error!")
+    ANALYSE_TIMEOUT_EXCEPTION = ("SP001", "AI分析超时!")
 
-    ANALYSE_TIMEOUT_EXCEPTION = ("SP002", "Analysis Timeout Exception!")
+    PULLSTREAM_TIMEOUT_EXCEPTION = ("SP002", "原视频拉流超时!")
 
-    PULLSTREAM_TIMEOUT_EXCEPTION = ("SP003", "Pull Stream Timeout Exception!")
+    READSTREAM_TIMEOUT_EXCEPTION = ("SP003", "原视频读取视频流超时!")
 
-    READSTREAM_TIMEOUT_EXCEPTION = ("SP004", "READ Stream Timeout Exception!")
+    GET_VIDEO_URL_EXCEPTION = ("SP004", "获取原视频播放地址失败!")
 
-    GET_VIDEO_URL_EXCEPTION = ("SP005", "Get Video Url Exception!")
+    GET_VIDEO_URL_TIMEOUT_EXCEPTION = ("SP005", "获取原视频播放地址超时!")
 
-    GET_VIDEO_URL_TIMEOUT_EXCEPTION = ("SP006", "Get Video Url Timeout Exception!")
+    PULL_STREAM_URL_EXCEPTION = ("SP006", "拉流地址不能为空!")
 
-    PULL_STREAM_URL_EXCEPTION = ("SP007", "Pull Stream Address Is Empty!")
+    PUSH_STREAM_URL_EXCEPTION = ("SP007", "推流地址不能为空!")
 
-    PULL_PIPELINE_INIT_EXCEPTION = ("SP008", "Pull Stream PIPELINE Exception!")
+    PUSH_STREAM_TIME_EXCEPTION = ("SP008", "推流时间或原视频时间太短, 未生成分析结果, 建议延长推流时间或原视频时间!")
 
-    PUSH_STREAM_URL_EXCEPTION = ("SP009", "Push Stream Address Is Empty!")
+    AI_MODEL_MATCH_EXCEPTION = ("SP009", "未匹配到对应的AI模型!")
 
-    CV2_IS_NULL_EXCEPTION = ("SP010", "The CV2 Is Empty!")
+    ILLEGAL_PARAMETER_FORMAT = ("SP010", "非法参数格式!")
 
-    OR_WRITE_OBJECT_EXCEPTION = ("SP011", "The Original Video Writing Object Is Empty!")
+    PUSH_STREAMING_CHANNEL_IS_OCCUPIED = ("SP011", "推流通道被占用, 请稍后再试!")
 
-    AI_WRITE_OBJECT_EXCEPTION = ("SP012", "The Ai Video Writing Object Is Empty!")
+    VIDEO_RESOLUTION_EXCEPTION = ("SP012", "不支持该分辨率类型的视频，请切换分辨率再试!")
 
-    VIDEO_ADDRESS_EXCEPTION = ("SP013", "The Video Address Does Not Exist!")
+    READ_IAMGE_URL_EXCEPTION = ("SP013", "未能解析图片地址!")
 
-    AI_VIDEO_ADDRESS_EXCEPTION = ("SP014", "AI Video Address Error!")
-
-    OFFLINE_RETRY_TIMEOUT_EXCEPTION = ("SP015", "Offline Retry Timeout Exception!")
-
-    AI_MODEL_CONFIG_EXCEPTION = ("SP016", "AI Model Config Exception!")
-
-    AI_MODEL_MATCH_EXCEPTION = ("SP017", "The AI Model Is Not Matched!")
-
-    VIDEO_MERGE_EXCEPTION = ("SP018", "The Video Merge Exception!")
-
-    VIDEO_ANALYSIS_EXCEPTION = ("SP019", "Video Analysis Failed!")
-
-    PUSH_STREAM_URL_E_EXCEPTION = ("SP020", "Push Stream URL Exception!")
-
-    VIDEO_CONFIG_EXCEPTION = ("SP021", "Video Config Exception!")
-
-    ILLEGAL_PARAMETER_FORMAT = ("SP022", "Illegal Parameter Format!")
-
-    REQUEST_TYPE_NOT_MATCHED = ("SP023", "Request Type Not Matched!")
-
-    MODEL_ANALYSIS_EXCEPTION = ("SP024", "Model Analysis Exception!")
-
-    PUSH_STREAMING_CHANNEL_IS_OCCUPIED = ("SP025", "推流通道被占用, 请稍后再试!")
-
-    WRITE_STREAM_EXCEPTION = ("SP026", "视频写流异常, 请联系工程师定位处理!")
-
-    VIDEO_RESOLUTION_EXCEPTION = ("SP027", "不支持该分辨率类型的视频，请切换分辨率再试!")
+    DETECTION_TARGET_TYPES_ARE_NOT_SUPPORTED = ("SP014", "不支持该类型的检测目标!")
 
     NO_GPU_RESOURCES = ("SP998", "暂无GPU资源可以使用，请稍后再试!")
 
-    SERVICE_INNER_EXCEPTION = ("SP999", "系统内部异常, 请联系工程师定位处理！")
+    SERVICE_INNER_EXCEPTION = ("SP999", "系统内部异常!")

enums/ModelTypeEnum.py

@@ -1,10 +1,9 @@
 from enum import Enum, unique
 
-
 # 异常枚举
+
 @unique
 class ModelType(Enum):
-
     WATER_SURFACE_MODEL = ("1", "001", "河道模型", 'river')
 
     FOREST_FARM_MODEL = ("2", "002", "森林模型", 'forest2')
@@ -27,8 +26,34 @@ class ModelType(Enum):
 
     SHIP_MODEL = ("11", "011", "船只模型", 'ship')
 
+    BAIDU_MODEL = ("12", "012", "百度AI图片识别模型", None)
+
     def checkCode(code):
         for model in ModelType:
             if model.value[1] == code:
                 return True
-        return False
+        return False
+
+
+'''
+    参数1: 检测目标名称
+    参数2: 检测目标
+    参数3: 初始化百度检测客户端
+'''
+
+
+@unique
+class BaiduModelTarget(Enum):
+    VEHICLE_DETECTION = ("车辆检测", 0, lambda client0, client1, url, request_id: client0.vehicleDetectUrl(url, request_id))
+
+    HUMAN_DETECTION = ("人体检测与属性识别", 1, lambda client0, client1, url, request_id: client1.bodyAttr(url, request_id))
+
+    PEOPLE_COUNTING = ("人流量统计", 2, lambda client0, client1, url, request_id: client1.bodyNum(url, request_id))
+
+BAIDU_MODEL_TARGET_CONFIG = {
+    BaiduModelTarget.VEHICLE_DETECTION.value[1]: BaiduModelTarget.VEHICLE_DETECTION,
+    BaiduModelTarget.HUMAN_DETECTION.value[1]: BaiduModelTarget.HUMAN_DETECTION,
+    BaiduModelTarget.PEOPLE_COUNTING.value[1]: BaiduModelTarget.PEOPLE_COUNTING
+}
+
+

test/editimage/editImage.py

@@ -0,0 +1,45 @@
+from io import BytesIO
+
+import cv2
+import matplotlib.pyplot as plt
+import matplotlib.patches as pat
+import numpy as np
+import requests
+from PIL import ImageDraw, Image
+
+from util.ImageUtils import url2Array
+
+url = "https://www.2008php.com/2015_Website_appreciate/2015-12-06/20151206234254.jpg"
+
+color= (255, 255, 0)
+#( 蓝, 绿, 红)
+# 红色 (0, 0, 255)
+# 洋红色 (255, 0, 255)
+# 青色 (255, 255, 0)
+# 黑色 (0, 0, 0)
+# 蓝色 (255, 0, 0)
+# 绿色 (0, 255, 0)
+# 黄色 (0, 255, 255) # 不考虑
+img = url2Array(url)
+cv2.putText(img,"Hello World", (100,100), cv2.FONT_HERSHEY_SIMPLEX, 1.0,color, 1, cv2.LINE_AA)
+# rectangle 坐标的参数格式为左上角（x1, y1），右下角（x2, y2）, 颜色 , 粗细
+cv2.rectangle(img, (100, 110), (400, 310), color, 2)
+cv2.imshow('img', img)
+cv2.waitKey()
+
+# fig, ax = plt.subplots(1)
+# ax.imshow(img)
+# # Rectangle 坐标的参数格式为左上角（x, y），width, height。
+# rec = pat.Rectangle((386, 144), 1049, 760, linewidth=2, edgecolor='r', facecolor='None')
+# ax.add_patch(rec)
+# plt.imshow(img)
+# plt.show()
+# response = requests.get(url)
+# image = Image.open(BytesIO(response.content))
+# a = ImageDraw.ImageDraw(image)
+# # rectangle 坐标的参数格式为左上角（x1, y1），右下角（x2, y2）。
+# a.rectangle(((386, 144), (1435, 904)), fill=None, outline='red', width=2)
+# image.show()
+
+
+

test/str/test.py

@@ -1,29 +1,9 @@
-# a=None
-# for i in range(12):
-#     if a is None:
-#         a = str(i)
-#     else:
-#         a = '%s,%s' % (a, str(i))
-# print(a)
-# a=[1,2,3,4,5,8, 9]
-# b=[1,3,2]
-# if set(a) >= set(b):
-#     print("a")
-# else:
-#     print("b")
-from enums.ModelTypeEnum import ModelType
 
-if ModelType.WATER_SURFACE_MODEL == ModelType.FOREST_FARM_MODEL:
-    print("aaaaa")
-else:
-    print("bbbbbbbbbb")
 
-if isinstance(ModelType.WATER_SURFACE_MODEL, ModelType):
-    print("aaaaa")
-else:
-    print("bbbbbbbbbb")
 
-if type(ModelType.WATER_SURFACE_MODEL)==ModelType.FOREST_FARM_MODEL:
-    print("aaaaa")
-else:
-    print("bbbbbbbbbb")
+aaa={"1":"1","2":"2","3":"3","4": {"1": "4"}}
+for i,v in aaa.items():
+    if i =="4":
+       v["1"] = "5"
+
+print(aaa)

util/AliyunSdk.py

@@ -26,6 +26,25 @@ class AliyunOssSdk():
                                       self.content["aliyun"]["oss"]["bucket"],
                                       connect_timeout=self.content["aliyun"]["oss"]["connect_timeout"])
 
+    def sync_upload_file(self, updatePath, fileByte):
+        self.logger.info("开始上传文件到oss, requestId:{}", self.requestId)
+        self.get_oss_bucket()
+        MAX_RETRIES = 3
+        retry_count = 0
+        while True:
+            try:
+                self.bucket.put_object(updatePath, fileByte)
+                self.logger.info("上传文件到oss成功! requestId:{}", self.requestId)
+                break
+            except Exception as e:
+                retry_count += 1
+                time.sleep(1)
+                self.logger.info("上传文件到oss失败, 重试次数：{}, requestId:{}", retry_count, self.requestId)
+                if retry_count > MAX_RETRIES:
+                    self.logger.exception("上传文件到oss重试失败:{}, requestId:{}", e, self.requestId)
+                    raise e
+
+
     async def put_object(self, updatePath, fileByte):
         self.bucket.put_object(updatePath, fileByte)
 
@@ -118,8 +137,8 @@ class ThAliyunVodSdk():
                 self.logger.error("vod视频上传失败，重试次数：{}, requestId:{}", retry_count, self.requestId)
                 if retry_count >= MAX_RETRIES:
                     self.logger.exception("vod视频上传重试失败: {}, requestId:{}", e, self.requestId)
-                    raise ServiceException(ExceptionType.VIDEO_UPDATE_EXCEPTION.value[0],
-                                           ExceptionType.VIDEO_UPDATE_EXCEPTION.value[1])
+                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
 
 
 def get_play_url(args):

util/Cv2Utils.py

@@ -475,20 +475,23 @@ class Cv2Util():
     def build_write(self):
         try:
             if self.fps is None or self.width is None or self.height is None:
-                raise ServiceException(ExceptionType.VIDEO_CONFIG_EXCEPTION.value[0],
-                                       ExceptionType.VIDEO_CONFIG_EXCEPTION.value[1])
+                logger.error("fps、 width、 height为空, requestId:{}", self.requestId)
+                raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                       ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
             if self.orFilePath is not None and self.or_video_file is None:
                 self.or_video_file = cv2.VideoWriter(self.orFilePath, cv2.VideoWriter_fourcc(*'mp4v'), self.fps,
                                                      (int(self.wn), int(self.hn)))
                 if self.or_video_file is None:
-                    raise ServiceException(ExceptionType.OR_WRITE_OBJECT_EXCEPTION.value[0],
-                                           ExceptionType.OR_WRITE_OBJECT_EXCEPTION.value[1])
+                    logger.error("or_video_file为空, requestId:{}", self.requestId)
+                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
             if self.aiFilePath is not None and self.ai_video_file is None:
                 self.ai_video_file = cv2.VideoWriter(self.aiFilePath, cv2.VideoWriter_fourcc(*'mp4v'), self.fps,
                                                      (int(self.wn * 2), int(self.hn)))
                 if self.ai_video_file is None:
-                    raise ServiceException(ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[0],
-                                           ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[1])
+                    logger.error("ai_video_file为空, requestId:{}", self.requestId)
+                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
         except ServiceException as s:
             logger.exception("构建文件写对象异常: {}, requestId:{}", s, self.requestId)
             raise s
@@ -506,27 +509,20 @@ class Cv2Util():
     def getP(self):
         if self.p is None:
             logger.error("获取管道为空, requestId:{}", self.requestId)
-            raise ServiceException(ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[0],
-                                   ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[1])
+            raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                   ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
         return self.p
 
-    def getCap(self):
-        if self.cap is None:
-            logger.error("获取cv2为空, requestId:{}", self.requestId)
-            raise ServiceException(ExceptionType.CV2_IS_NULL_EXCEPTION.value[0],
-                                   ExceptionType.CV2_IS_NULL_EXCEPTION.value[1])
-        return self.cap
-
     def getOrVideoFile(self):
         if self.or_video_file is None:
             logger.error("获取原视频写入对象为空, requestId:{}", self.requestId)
-            raise ServiceException(ExceptionType.OR_WRITE_OBJECT_EXCEPTION.value[0],
-                                   ExceptionType.OR_WRITE_OBJECT_EXCEPTION.value[1])
+            raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                   ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
         return self.or_video_file
 
     def getAiVideoFile(self):
         if self.ai_video_file is None:
             logger.error("获取AI视频写入对象为空, requestId:{}", self.requestId)
-            raise ServiceException(ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[0],
-                                   ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[1])
+            raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                   ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
         return self.ai_video_file

util/ImageUtils.py

@@ -155,37 +155,41 @@ class PictureWaterMark:
             dst_channels[i][ul_points[0]: dr_points[0], ul_points[1]: dr_points[1]] = dst_channels[i][
                                                                                       ul_points[0]: dr_points[0],
                                                                                       ul_points[1]: dr_points[1]] * (
-                                                                                              255.0 - mask_channels[3] * alpha) / 255
+                                                                                              255.0 - mask_channels[
+                                                                                          3] * alpha) / 255
             dst_channels[i][ul_points[0]: dr_points[0], ul_points[1]: dr_points[1]] += np.array(
                 mask_channels[i] * (mask_channels[3] * alpha / 255), dtype=np.uint8)
         dst_img = cv2.merge(dst_channels)
         return dst_img
 
-#差值感知算法
+
+# 差值感知算法
 def dHash(image):
-    #缩放9*8
-    image=cv2.resize(image,(9,8),interpolation=cv2.INTER_CUBIC)
-    #转换灰度图
-    image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
+    # 缩放9*8
+    image = cv2.resize(image, (9, 8), interpolation=cv2.INTER_CUBIC)
+    # 转换灰度图
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     #     print(image.shape)
-    hash=[]
-    #每行前一个像素大于后一个像素为1，相反为0，生成哈希
+    hash = []
+    # 每行前一个像素大于后一个像素为1，相反为0，生成哈希
     for i in range(8):
         for j in range(8):
-            if image[i,j]>image[i,j+1]:
+            if image[i, j] > image[i, j + 1]:
                 hash.append(1)
             else:
                 hash.append(0)
     return hash
 
-#计算汉明距离
-def Hamming_distance(hash1,hash2):
+
+# 计算汉明距离
+def Hamming_distance(hash1, hash2):
     num = 0
     for index in range(len(hash1)):
         if hash1[index] != hash2[index]:
             num += 1
     return num
 
+
 def url2Array(url):
     response = requests.get(url)
     image = Image.open(BytesIO(response.content))
@@ -193,36 +197,68 @@ def url2Array(url):
     img_bgr = cv2.cvtColor(image1, cv2.COLOR_RGB2BGR)
     return img_bgr
 
-if __name__ == '__main__':
-    # img = cv2.imread("../test/a.jpg", -1)
-    # fontcolor = 'yellow'
-    #
-    # water = TextWaterMark()
-    # text = "hello world"
-    #
-    # # fill_img = water.common_water(img, text, position=4, fontface='../font/庞门正道标题体2.0增强版.ttf', fontsize=20, fontcolor='black')
-    # fill_img = water.fill_water(img, text, 20)
-    # # 一定要保存为png格式
-    # cv2.imshow('result', fill_img)
-    # cv2.waitKey(111111110)
-    # print('finish')
-    pic = PictureWaterMark()
-    image = cv2.imread("a.jpg")
-    logo = cv2.imread("../image/logo.png", -1)
-    # print(image, logo)
-    start = time.time()
-    frame = pic.common_water(image, logo)
-    print(time.time() - start)
-    start1 = time.time()
-    frame1 = pic.common_water_1(image, logo)
-    # cv2.imwrite("watermarked.jpg", frame1)
-    print(time.time() - start1)
-    # cap = cv2.VideoCapture("../data/111111.mp4")
-    # logo = cv2.imread("../image/logo.png", -1)
-    # while True:
-    #         is_opened, frame = cap.read()
-    #         frame = pic.common_water(frame, logo)
-    #         cv2.imshow('frame', frame)
-    #         cv2.waitKey(1)  # 等待输入任何按键
-    # # 关闭
-    # cap.release()
+def url2Content(url):
+    response = requests.get(url)
+    return response.content
+
+def url2Image(url):
+    response = requests.get(url)
+    image = Image.open(BytesIO(response.content))
+    image1 = np.array(image)
+    img_bgr = cv2.cvtColor(image1, cv2.COLOR_RGB2BGR)
+    img = Image.fromarray(img_bgr)
+    return img
+
+
+def url2Byte(url):
+    response = requests.get(url)
+    return BytesIO(response.content)
+
+def markRectangle(url, text, textCoordinate, imageLeftUpCoordinate, imageRightDownCoordinate, color):
+    img = url2Array(url)
+    #( 蓝, 绿, 红)
+    # 红色 (0, 0, 255)
+    # 洋红色 (255, 0, 255)
+    # 青色 (255, 255, 0)
+    # 黑色 (0, 0, 0)
+    # 蓝色 (255, 0, 0)
+    # 绿色 (0, 255, 0)
+    # 黄色 (0, 255, 255) # 不考虑
+    cv2.putText(img, text, textCoordinate, cv2.FONT_HERSHEY_SIMPLEX, 1.0, color, 1, cv2.LINE_AA)
+    # rectangle 坐标的参数格式为左上角（x1, y1），右下角（x2, y2）, 颜色 , 粗细
+    cv2.rectangle(img, imageLeftUpCoordinate, imageRightDownCoordinate, color, 2)
+    return img
+
+# if __name__ == '__main__':
+#     # img = cv2.imread("../test/a.jpg", -1)
+#     # fontcolor = 'yellow'
+#     #
+#     # water = TextWaterMark()
+#     # text = "hello world"
+#     #
+#     # # fill_img = water.common_water(img, text, position=4, fontface='../font/庞门正道标题体2.0增强版.ttf', fontsize=20, fontcolor='black')
+#     # fill_img = water.fill_water(img, text, 20)
+#     # # 一定要保存为png格式
+#     # cv2.imshow('result', fill_img)
+#     # cv2.waitKey(111111110)
+#     # print('finish')
+#     pic = PictureWaterMark()
+#     image = cv2.imread("a.jpg")
+#     logo = cv2.imread("../image/logo.png", -1)
+#     # print(image, logo)
+#     start = time.time()
+#     frame = pic.common_water(image, logo)
+#     print(time.time() - start)
+#     start1 = time.time()
+#     frame1 = pic.common_water_1(image, logo)
+#     # cv2.imwrite("watermarked.jpg", frame1)
+#     print(time.time() - start1)
+#     # cap = cv2.VideoCapture("../data/111111.mp4")
+#     # logo = cv2.imread("../image/logo.png", -1)
+#     # while True:
+#     #         is_opened, frame = cap.read()
+#     #         frame = pic.common_water(frame, logo)
+#     #         cv2.imshow('frame', frame)
+#     #         cv2.waitKey(1)  # 等待输入任何按键
+#     # # 关闭
+#     # cap.release()

util/ImgBaiduSdk.py

@@ -0,0 +1,240 @@
+import base64
+import time
+from threading import Lock
+
+import yaml
+from aip import AipImageClassify, AipBodyAnalysis
+from loguru import logger
+
+from enums.BaiduSdkEnum import BAIDUERRORDATA
+from enums.ExceptionEnum import ExceptionType
+from exception.CustomerException import ServiceException
+from util.ImageUtils import url2Byte, url2Content
+
+
+class AipImageClassifyClient:
+
+    def __init__(self, content):
+        self.__content = content
+        self.__client = None
+        self.init_client()
+        # self.lock = Lock()
+
+    def init_client(self):
+        if self.__client is None:
+            self.__client = AipImageClassify(str(self.__content["baidu"]["vehicle"]["APP_ID"]),
+                                             self.__content["baidu"]["vehicle"]["API_KEY"],
+                                             self.__content["baidu"]["vehicle"]["SECRET_KEY"])
+
+    '''
+        车辆检测
+    '''
+
+    def vehicleDetectUrl(self, url, request_id, options={}):
+        self.init_client()
+        # try:
+        #     self.lock.acquire()
+        reply_num = 0
+        reply_value = None
+        while True:
+            try:
+                options["show"] = "true"
+                res_image = self.__client.vehicleDetectUrl(url, options)
+                error_code = res_image.get("error_code")
+                if error_code:
+                    enum = BAIDUERRORDATA.get(error_code)
+                    # 如果异常编码未知, 返回空值
+                    if enum is None:
+                        logger.error("百度云车辆检测异常！error_code:{}, request_id: {}", error_code, request_id)
+                        return None
+                    # 重试指定次数后，还是异常，输出统一内部异常
+                    if enum.value[3] == 0:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        logger.error("百度云车辆检测异常！error_code:{}, error_msg:{}, reply_num:{}, request_id: {}",
+                                     enum.value[0], enum.value[2], reply_num, request_id)
+                        raise Exception()
+                    # 重试指定次数后，还是异常，输出对应的异常
+                    if enum.value[3] == 1:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        raise ServiceException(str(enum.value[0]), enum.value[2])
+                    # 重试指定次数后，还是异常，输出空
+                    if enum.value[3] == 2:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        if reply_num >= reply_value:
+                            return None
+                return res_image
+            except Exception as e:
+                logger.exception("车辆检测失败: {}, 当前重试次数：{}, request_id: {}", e, reply_num, request_id)
+                time.sleep(1)
+                reply_num += 1
+                self.init_client()
+                if reply_num > reply_value:
+                    if isinstance(e, ServiceException):
+                        raise ServiceException(e.code, e.msg)
+                    logger.exception("车辆检测识别失败: {}, request_id: {}", e, request_id)
+                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
+        # except Exception as ee:
+        #     logger.exception("车辆检测加锁异常: {}, request_id: {}", ee, request_id)
+        #     raise ServiceException(ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[0],
+        #                            ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[1])
+        # finally:
+        #     self.lock.release()
+
+
+class AipBodyAnalysisClient:
+
+    def __init__(self, content):
+        self.__content = content
+        self.__client = None
+        self.init_client()
+        # self.lock = Lock()
+
+    def init_client(self):
+        if self.__client is None:
+            self.__client = AipBodyAnalysis(str(self.__content["baidu"]["person"]["APP_ID"]),
+                                            self.__content["baidu"]["person"]["API_KEY"],
+                                            self.__content["baidu"]["person"]["SECRET_KEY"])
+
+    '''
+        人体检测与属性识别
+    '''
+
+    def bodyAttr(self, url, request_id, options={}):
+        self.init_client()
+        image = self.readImage(url, request_id)
+        # try:
+        #     self.lock.acquire()
+        reply_num = 0
+        reply_value = None
+        while True:
+            try:
+                options["show"] = "true"
+                res_image = self.__client.bodyAttr(image, options)
+                error_code = res_image.get("error_code")
+                if error_code:
+                    enum = BAIDUERRORDATA.get(error_code)
+                    # 如果异常编码未知, 返回空值
+                    if enum is None:
+                        logger.error("百度云人体检测与属性识别异常！error_code:{}, request_id: {}", error_code, request_id)
+                        return None
+                    # 重试指定次数后，还是异常，输出统一内部异常
+                    if enum.value[3] == 0:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        logger.error("百度云人体检测与属性识别异常！error_code:{}, error_msg:{}, reply_num:{}, request_id: {}",
+                                     enum.value[0], enum.value[2], reply_num, request_id)
+                        raise Exception()
+                    # 重试指定次数后，还是异常，输出对应的异常
+                    if enum.value[3] == 1:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        raise ServiceException(str(enum.value[0]), enum.value[2])
+                    # 重试指定次数后，还是异常，输出空
+                    if enum.value[3] == 2:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        if reply_num >= reply_value:
+                            return None
+                return res_image
+            except Exception as e:
+                logger.exception("人体检测与属性识别失败: {}, 当前重试次数：{}, request_id: {}", e, reply_num, request_id)
+                time.sleep(0.5)
+                reply_num += 1
+                self.init_client()
+                if reply_num > reply_value:
+                    if isinstance(e, ServiceException):
+                        raise ServiceException(e.code, e.msg)
+                    logger.exception("人体检测与属性识别失败: {}, request_id: {}", e, request_id)
+                    raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
+                                           ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
+        # except Exception as ee:
+        #     logger.exception("车辆检测加锁异常: {}, request_id: {}", ee, request_id)
+        #     raise ServiceException(ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[0],
+        #                            ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[1])
+        # finally:
+        #     self.lock.release()
+
+    '''
+        人流量统计
+    '''
+
+    def bodyNum(self, url, request_id, options={}):
+        self.init_client()
+        image = self.readImage(url, request_id)
+        # try:
+        #     self.lock.acquire()
+        reply_num = 0
+        reply_value = None
+        while True:
+            try:
+                options["show"] = "true"
+                res_image = self.__client.bodyNum(image, options)
+                error_code = res_image.get("error_code")
+                if error_code:
+                    enum = BAIDUERRORDATA.get(error_code)
+                    # 如果异常编码未知, 返回空值
+                    if enum is None:
+                        logger.error("百度云人流量统计异常！error_code:{}, request_id: {}", error_code, request_id)
+                        return None
+                    # 重试指定次数后，还是异常，输出统一内部异常
+                    if enum.value[3] == 0:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        logger.error("百度云人流量统计异常！error_code:{}, error_msg:{}, reply_num:{}, request_id: {}",
+                                     enum.value[0], enum.value[2], reply_num, request_id)
+                        raise Exception()
+                    # 重试指定次数后，还是异常，输出对应的异常
+                    if enum.value[3] == 1:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        raise ServiceException(str(enum.value[0]), enum.value[2])
+                    # 重试指定次数后，还是异常，输出空
+                    if enum.value[3] == 2:
+                        if reply_value is None:
+                            reply_value = enum.value[4]
+                        if reply_num >= reply_value:
+                            return None
+                return res_image
+            except ServiceException as e:
+                raise ServiceException(e.code, e.msg)
+            except Exception as e:
+                logger.exception("人流量统计失败: {}, 当前重试次数：{}, request_id: {}", e, reply_num, request_id)
+                time.sleep(0.5)
+                reply_num += 1
+                self.init_client()
+                if reply_num > reply_value:
+                    if isinstance(e, ServiceException):
+                        raise ServiceException(e.code, e.msg)
+                    logger.exception("人流量统计失败: {}, request_id: {}", e, request_id)
+                    raise ServiceException(ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[0],
+                                           ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[1])
+        # except Exception as ee:
+        #     logger.exception("车辆检测加锁异常: {}, request_id: {}", ee, request_id)
+        #     raise ServiceException(ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[0],
+        #                            ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[1])
+        # finally:
+        #     self.lock.release()
+
+    def readImage(self, url, request_id):
+        try:
+            return url2Content(url)
+        except Exception as e:
+            logger.exception("读取图片异常！url: {}, request_id: {}", url, request_id, e)
+            raise ServiceException(ExceptionType.READ_IAMGE_URL_EXCEPTION.value[0],
+                                   ExceptionType.READ_IAMGE_URL_EXCEPTION.value[1])
+
+# if __name__ == '__main__':
+#     with open(r"D:\work\alg_new\tuoheng_alg\dsp_application.yml", "r", encoding='utf-8') as f:
+#         file_content = f.read()
+#     content = yaml.load(file_content, yaml.FullLoader)
+#     aipImageClassifyClient = AipImageClassifyClient(content)
+#     aipBodyAnalysisClient = AipBodyAnalysisClient(content)
+#     url = "https://pic.52112.com/180623/JPG-180623-12/c4cyivkxEh_small.jpg"
+#     # result = aipImageClassifyClient.vehicleDetectUrl(url, "1111111")
+#     result = aipBodyAnalysisClient.bodyNum(url, "1111111")
+#     iamge = base64.b64decode(result.get("image"))
+#     print(iamge)

util/ModelUtils.py

@@ -1,28 +1,33 @@
 # -*- coding: utf-8 -*-
+import base64
 import sys
 
-from enums.ModelTypeEnum import ModelType
+from enums.ExceptionEnum import ExceptionType
+from enums.ModelTypeEnum import ModelType, BAIDU_MODEL_TARGET_CONFIG, BaiduModelTarget
+from exception.CustomerException import ServiceException
 from util.GPUtils import get_all_gpu_ids
+from util.ImgBaiduSdk import AipBodyAnalysisClient, AipImageClassifyClient
 
 sys.path.extend(['..', '../AIlib2'])
-from AI import AI_process,AI_process_forest,get_postProcess_para
-import cv2,os,time
+from AI import AI_process, AI_process_forest, get_postProcess_para
+import cv2, os, time
 from segutils.segmodel import SegModel
 from models.experimental import attempt_load
 from utils.torch_utils import select_device
-from utilsK.queRiver import get_labelnames,get_label_arrays,save_problem_images
+from utilsK.queRiver import get_labelnames, get_label_arrays, save_problem_images
 import numpy as np
-import torch,glob
+import torch, glob
 import tensorrt as trt
 from utilsK.masterUtils import get_needed_objectsIndex
-from utilsK.jkmUtils import pre_process,post_process,get_return_data
+from utilsK.jkmUtils import pre_process, post_process, get_return_data
 
 
 # 统一模型入口
 class Model:
-    def __init__(self, device, allowedList=None, logger=None, requestId=None, modeType=None):
+    def __init__(self, device, allowedList=None, logger=None, requestId=None, modeType=None, content=None):
         try:
-            logger.info("########################加载{}########################, requestId:{}", modeType.value[2], requestId)
+            logger.info("########################加载{}########################, requestId:{}", modeType.value[2],
+                        requestId)
             self.modeType = modeType
             self.allowedList = allowedList
             self.trtFlag_det = True,  # 检测模型是否采用TRT
@@ -56,7 +61,7 @@ class Model:
                 'segPar': {
                     'modelSize': (640, 360),
                     'mean': (0.485, 0.456, 0.406),
-                    'std' : (0.229, 0.224, 0.225),
+                    'std': (0.229, 0.224, 0.225),
                     'numpy': False,
                     'RGB_convert_first': True
                 },  # 分割模型预处理参数
@@ -80,8 +85,8 @@ class Model:
             Detweights = par.get('Detweights')  # 升级后的检测模型
             if self.trtFlag_det:
                 with open(Detweights, "rb") as f, trt.Runtime(trt.Logger(trt.Logger.ERROR)) as runtime:
-                    self.model = runtime.deserialize_cuda_engine(f.read())# 输入trt本地文件，返回ICudaEngine对象
-                    print('####load TRT model :%s'%(Detweights))
+                    self.model = runtime.deserialize_cuda_engine(f.read())  # 输入trt本地文件，返回ICudaEngine对象
+                    print('####load TRT model :%s' % (Detweights))
             else:
                 self.model = attempt_load(Detweights, map_location=self.device)  # load FP32 model
                 if self.half:
@@ -118,7 +123,6 @@ class Model:
             logger.exception("异常：{}, requestId:{}", ee, requestId)
             raise ee
 
-
     def process(self, frame, width=1920):
         if self.label_arraylist is None:
             fontsize = int(width / 1920 * 40)
@@ -145,6 +149,7 @@ class Model:
                                      self.rainbows, self.half, self.device, self.conf_thres, self.iou_thres,
                                      self.allowedList, font=self.digitFont, trtFlag_det=self.trtFlag_det)
 
+
 # # 河道模型
 # class SZModel:
 #     def __init__(self, device, allowedList=None, logger=None, requestId=None):
@@ -685,20 +690,21 @@ class Model:
 # 车牌分割模型、健康码、行程码分割模型
 class IMModel:
 
-    def __init__(self, device, allowedList=None, logger=None, requestId=None, modeType=None):
+    def __init__(self, device, allowedList=None, logger=None, requestId=None, modeType=None, content=None):
         logger.info("########################加载{}########################, requestId:{}", modeType.value[2], requestId)
         self.allowedList = allowedList
         if ModelType.EPIDEMIC_PREVENTION_MODEL == modeType:
             self.img_type = 'code'  ## code,plate
         if ModelType.PLATE_MODEL == modeType:
             self.img_type = 'plate'  ## code,plate
-        self.par = {'code': {'weights': '../AIlib2/weights/conf/jkm/health_yolov5s_v3.jit', 'img_type': 'code', 'nc': 10},
-                    'plate': {'weights': '../AIlib2/weights/conf/jkm/plate_yolov5s_v3.jit', 'img_type': 'plate', 'nc': 1},
-                    'conf_thres': 0.4,
-                    'iou_thres': 0.45,
-                    'device': 'cuda:%s' % device,
-                    'plate_dilate': (0.5, 0.3)
-                    }
+        self.par = {
+            'code': {'weights': '../AIlib2/weights/conf/jkm/health_yolov5s_v3.jit', 'img_type': 'code', 'nc': 10},
+            'plate': {'weights': '../AIlib2/weights/conf/jkm/plate_yolov5s_v3.jit', 'img_type': 'plate', 'nc': 1},
+            'conf_thres': 0.4,
+            'iou_thres': 0.45,
+            'device': 'cuda:%s' % device,
+            'plate_dilate': (0.5, 0.3)
+            }
         self.device = torch.device(self.par['device'])
         self.model = torch.jit.load(self.par[self.img_type]['weights'])
 
@@ -708,4 +714,72 @@ class IMModel:
         boxes = post_process(pred, padInfos, self.device, conf_thres=self.par['conf_thres'],
                              iou_thres=self.par['iou_thres'], nc=self.par[self.img_type]['nc'])  # 后处理
         dataBack = get_return_data(frame, boxes, modelType=self.img_type, plate_dilate=self.par['plate_dilate'])
-        return dataBack
+        return dataBack
+
+
+# 百度AI图片识别模型
+class BaiduAiImageModel:
+
+    def __init__(self, device=None, allowedList=None, logger=None, requestId=None, modeType=None, content=None):
+        logger.info("########################加载{}########################, requestId:{}", modeType.value[2], requestId)
+        self.allowedList = allowedList
+        self.__requestId = requestId
+        self.__logger = logger
+        self.__aipBodyAnalysisClient = AipBodyAnalysisClient(content)
+        self.__aipImageClassifyClient = AipImageClassifyClient(content)
+
+    def process(self, target, url):
+        baiduEnum = BAIDU_MODEL_TARGET_CONFIG.get(target)
+        if baiduEnum is None:
+            raise ServiceException(ExceptionType.DETECTION_TARGET_TYPES_ARE_NOT_SUPPORTED.value[0],
+                                   ExceptionType.DETECTION_TARGET_TYPES_ARE_NOT_SUPPORTED.value[1]
+                                   + " target: " + target)
+        return baiduEnum.value[2](self.__aipImageClassifyClient, self.__aipBodyAnalysisClient, url, self.__requestId)
+
+
+MODEL_CONFIG = {
+    # 加载河道模型
+    ModelType.WATER_SURFACE_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.WATER_SURFACE_MODEL),
+        ModelType.WATER_SURFACE_MODEL.value[1]),
+    # 加载林场模型
+    ModelType.FOREST_FARM_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.FOREST_FARM_MODEL),
+        ModelType.FOREST_FARM_MODEL.value[1]),
+    # 加载交通模型
+    ModelType.TRAFFIC_FARM_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.TRAFFIC_FARM_MODEL),
+        ModelType.TRAFFIC_FARM_MODEL.value[1]),
+    # 加载防疫模型
+    ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]: (
+        lambda x, y, z, r: IMModel(x, y, z, r, ModelType.EPIDEMIC_PREVENTION_MODEL),
+        ModelType.EPIDEMIC_PREVENTION_MODEL.value[1]),
+    # 加载车牌模型
+    ModelType.PLATE_MODEL.value[1]: (
+        lambda x, y, z, r: IMModel(x, y, z, r, ModelType.PLATE_MODEL), ModelType.PLATE_MODEL.value[1]),
+    # 加载车辆模型
+    ModelType.VEHICLE_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.VEHICLE_MODEL), ModelType.VEHICLE_MODEL.value[1]),
+    # 加载行人模型
+    ModelType.PEDESTRIAN_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.PEDESTRIAN_MODEL),
+        ModelType.PEDESTRIAN_MODEL.value[1]),
+    # 加载烟火模型
+    ModelType.SMOGFIRE_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.SMOGFIRE_MODEL), ModelType.SMOGFIRE_MODEL.value[1]),
+    # 加载钓鱼游泳模型
+    ModelType.ANGLERSWIMMER_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.ANGLERSWIMMER_MODEL),
+        ModelType.ANGLERSWIMMER_MODEL.value[1]),
+    # 加载乡村模型
+    ModelType.COUNTRYROAD_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.COUNTRYROAD_MODEL),
+        ModelType.COUNTRYROAD_MODEL.value[1]),
+    # 加载船只模型
+    ModelType.SHIP_MODEL.value[1]: (
+        lambda x, y, z, r: Model(x, y, z, r, ModelType.SHIP_MODEL), ModelType.SHIP_MODEL.value[1]),
+    # 百度AI图片识别模型
+    ModelType.BAIDU_MODEL.value[1]: (
+        lambda x, y, z, r, t: BaiduAiImageModel(x, y, z, r, ModelType.BAIDU_MODEL, t),
+        ModelType.BAIDU_MODEL.value[1])
+}

util/OcrBaiduSdk.py

@@ -17,8 +17,8 @@ class OcrBaiduSdk:
         # self.lock = Lock()
 
     def init_client(self):
-        self.client = AipOcr(str(self.content["baiduocr"]["APP_ID"]), self.content["baiduocr"]["API_KEY"],
-                                 self.content["baiduocr"]["SECRET_KEY"])
+        self.client = AipOcr(str(self.content["baidu"]["orc"]["APP_ID"]), self.content["baidu"]["orc"]["API_KEY"],
+                             self.content["baidu"]["orc"]["SECRET_KEY"])
 
     '''
     {
@@ -31,6 +31,7 @@ class OcrBaiduSdk:
         ]
     }
     '''
+
     def universal_text_recognition(self, image, request_id):
         # try:
         #     self.lock.acquire()
@@ -67,6 +68,7 @@ class OcrBaiduSdk:
         #                            ExceptionType.UNIVERSAL_TEXT_RECOGNITION_FAILED.value[1])
         # finally:
         #     self.lock.release()
+
     '''
     {
         "log_id": 3583925545,
@@ -76,6 +78,7 @@ class OcrBaiduSdk:
         }
     }
     '''
+
     def license_plate_recognition(self, image, request_id):
         # try:
         #     self.lock.acquire()
@@ -112,5 +115,3 @@ class OcrBaiduSdk:
         #                            ExceptionType.ABNORMAL_LICENSE_PLATE_RECOGNITION.value[1])
         # finally:
         #     self.lock.release()
-
-