1）新增区域入侵算法 2）火焰面积bug修复

common/Constant.py

@@ -16,7 +16,6 @@ success_progess = "1.0000"
 width = 1400
 
 COLOR = (
-    [0, 0, 255],
     [255, 0, 0],
     [211, 0, 148],
     [0, 127, 0],
@@ -35,7 +34,8 @@ COLOR = (
     [8, 101, 139],
     [171, 130, 255],
     [139, 112, 74],
-    [205, 205, 180])
+    [205, 205, 180],
+    [0, 0, 255],)
 
 ONLINE = "online"
 OFFLINE = "offline"

concurrency/FileUploadThread.py

@@ -3,6 +3,7 @@ from concurrent.futures import ThreadPoolExecutor
 from threading import Thread
 from time import sleep, time
 from traceback import format_exc
+import numpy as np
 
 from loguru import logger
 import cv2
@@ -14,18 +15,18 @@ from util.AliyunSdk import AliyunOssSdk
 from util.MinioSdk import MinioSdk
 from util import TimeUtils
 from enums.AnalysisStatusEnum import AnalysisStatus
-from util.PlotsUtils import draw_painting_joint, draw_name_ocr, draw_name_crowd
+from util.PlotsUtils import draw_painting_joint, draw_name_ocr, draw_name_crowd,draw_transparent_red_polygon
 from util.QueUtil import put_queue, get_no_block_queue, clear_queue
 import io
 from util.LocationUtils import locate_byMqtt
 
 
 class FileUpload(Thread):
-    __slots__ = ('_fb_queue', '_context', '_image_queue', '_analyse_type', '_msg', '_mqtt_list')
+    __slots__ = ('_fb_queue', '_context', '_image_queue', '_analyse_type', '_msg')
 
     def __init__(self, *args):
         super().__init__()
-        self._fb_queue, self._context, self._msg, self._image_queue, self._analyse_type, self._mqtt_list = args
+        self._fb_queue, self._context, self._msg, self._image_queue, self._analyse_type = args
         self._storage_source = self._context['service']['storage_source']
         self._algStatus = False  # 默认关闭
 
@@ -64,16 +65,29 @@ class ImageFileUpload(FileUpload):
         模型编号：modeCode
         检测目标：detectTargetCode
         '''
-        print('*' * 100, ' mqtt_list:', len(self._mqtt_list))
+        aFrame = frame.copy()
-
+        igH, igW = aFrame.shape[0:2]
         model_info = []
+        mqttPares= det_xywh['mqttPares']
+        border = None
+        gps = [None, None]
+        camParas = None
+        if mqttPares is not None:
+            if mqttPares[0] == 1:
+                border = mqttPares[1]
+            elif mqttPares[0] == 0:
+                camParas = mqttPares[1]
+        if border is not None:
+            aFrame = draw_transparent_red_polygon(aFrame, np.array(border, np.int32), alpha=0.25)
+        det_xywh.pop('mqttPares')
         # 更加模型编码解析数据
         for code, det_list in det_xywh.items():
             if len(det_list) > 0:
                 for cls, target_list in det_list.items():
                     if len(target_list) > 0:
-                        aFrame = frame.copy()
                         for target in target_list:
+                            if camParas is not None:
+                                gps = locate_byMqtt(target[1], igW, igH, camParas, outFormat='wgs84')
                             # 自研车牌模型判断
                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
                                 draw_name_ocr(target[1], aFrame, target[4])
@@ -82,15 +96,7 @@ class ImageFileUpload(FileUpload):
                                 draw_name_crowd(target[1], aFrame, target[4])
                             else:
                                 draw_painting_joint(target[1], aFrame, target[3], target[2], target[4], font_config,
-                                                    target[5])
+                                                    target[5],border)
-
-                        igH, igW = aFrame.shape[0:2]
-                        if len(self._mqtt_list) >= 1:
-                            # camParas = self._mqtt_list[0]['data']
-                            camParas = self._mqtt_list[0]
-                            gps = locate_byMqtt(target[1], igW, igH, camParas, outFormat='wgs84')
-                        else:
-                            gps = [None, None]
                         model_info.append(
                             {"modelCode": str(code), "detectTargetCode": str(cls), "aFrame": aFrame, 'gps': gps})
         if len(model_info) > 0:
@@ -133,7 +139,6 @@ class ImageFileUpload(FileUpload):
                         # 获取队列中的消息
                         image_msg = get_no_block_queue(image_queue)
                         if image_msg is not None:
-
                             if image_msg[0] == 2:
                                 logger.info("图片上传线程收到命令:{}, requestId: {}", image_msg[1], request_id)
                                 if 'stop' == image_msg[1]:

concurrency/IntelligentRecognitionProcess.py

@@ -64,6 +64,7 @@ class IntelligentRecognitionProcess(Process):
                                                    self._analyse_type, progress=init_progess), timeout=2, is_ex=True)
         self._storage_source = self._context['service']['storage_source']
         self._algStatus = False
+
     def sendEvent(self, eBody):
         put_queue(self.event_queue, eBody, timeout=2, is_ex=True)
 
@@ -127,6 +128,7 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
         or_url = upload_video_thread_or.get_result()
         ai_url = upload_video_thread_ai.get_result()
         return or_url, ai_url
+
     '''    
     @staticmethod
     def upload_video(base_dir, env, request_id, orFilePath, aiFilePath):
@@ -306,7 +308,7 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                         else:
                                             model_param = model_conf[1]
                                             # (modeType, model_param, allowedList, names, rainbows)
-                                            MODEL_CONFIG[code][2](frame_list[0].shape[1], frame_list[0].shape[0],
+                                            MODEL_CONFIG[code][2](frame_list[0][0].shape[1], frame_list[0][0].shape[0],
                                                                   model_conf)
                                             if draw_config.get("font_config") is None:
                                                 draw_config["font_config"] = model_param['font_config']
@@ -322,7 +324,7 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                 # print_cpu_status(requestId=request_id,lineNum=inspect.currentframe().f_lineno)
                                 # 多线程并发处理, 经过测试两个线程最优
                                 det_array = []
-                                for i, frame in enumerate(frame_list):
+                                for i, [frame,_] in enumerate(frame_list):
                                     det_result = t.submit(self.obj_det, self, model_array, frame, task_status,
                                                           frame_index_list[i], tt, request_id)
                                     det_array.append(det_result)
@@ -469,6 +471,7 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
         ai_url = upload_video_thread_ai.get_result()
         return ai_url
     '''
+
     @staticmethod
     def ai_normal_dtection(model, frame, request_id):
         model_conf, code = model
@@ -634,7 +637,7 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                         else:
                                             model_param = model_conf[1]
                                             # (modeType, model_param, allowedList, names, rainbows)
-                                            MODEL_CONFIG[code][2](frame_list[0].shape[1], frame_list[0].shape[0],
+                                            MODEL_CONFIG[code][2](frame_list[0][0].shape[1], frame_list[0][0].shape[0],
                                                                   model_conf)
                                             if draw_config.get("font_config") is None:
                                                 draw_config["font_config"] = model_param['font_config']
@@ -648,7 +651,7 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
 
 
                                 det_array = []
-                                for i, frame in enumerate(frame_list):
+                                for i, [frame,_] in enumerate(frame_list):
                                     det_result = t.submit(self.obj_det, self, model_array, frame, task_status,
                                                           frame_index_list[i], tt, request_id)
                                     det_array.append(det_result)
@@ -1210,7 +1213,8 @@ class PhotosIntelligentRecognitionProcess(Process):
         image_thread.setDaemon(True)
         image_thread.start()
         return image_thread
-    def check_ImageUrl_Vaild(self,url,timeout=1):
+
+    def check_ImageUrl_Vaild(self, url, timeout=1):
         try:
             # 发送 HTTP 请求，尝试访问图片
             response = requests.get(url, timeout=timeout)  # 设置超时时间为 10 秒
@@ -1243,7 +1247,6 @@ class PhotosIntelligentRecognitionProcess(Process):
 
                 return
 
-
         with ThreadPoolExecutor(max_workers=1) as t:
             try:
                 #init_log(base_dir, env)
@@ -1320,6 +1323,7 @@ class ScreenRecordingProcess(Process):
                   recording_feedback(self._msg["request_id"], RecordingStatus.RECORDING_WAITING.value[0]),
                   timeout=1, is_ex=True)
         self._storage_source = self._context['service']['storage_source']
+
     def sendEvent(self, result):
         put_queue(self._event_queue, result, timeout=2, is_ex=True)
 
@@ -1497,6 +1501,7 @@ class ScreenRecordingProcess(Process):
         upload_video_thread_ai.start()
         or_url = upload_video_thread_ai.get_result()
         return or_url
+
     '''    
     @staticmethod
     def upload_video(base_dir, env, request_id, orFilePath):

concurrency/PullMqttThread.py

@@ -16,18 +16,22 @@ from multiprocessing import Process, Queue
 import paho.mqtt.client as mqtt  
 import json,os
 class PullMqtt(Thread):
-    __slots__ = ('__fb_queue', '__mqtt_list', '__request_id', '__analyse_type', "_context")
+    __slots__ = ('__fb_queue', '__mqtt_list', '__request_id', '__analyse_type', "_context" ,'__business')
 
     def __init__(self, *args):
         super().__init__()
-        self.__fb_queue, self.__mqtt_list, self.__request_id, self.__analyse_type, self._context = args
+        self.__fb_queue, self.__mqtt_list, self.__request_id, self.__analyse_type, self._context, self.__business = args
         
         base_dir, env = self._context["base_dir"], self._context["env"]
         self.__config = getConfigs(os.path.join(base_dir, mqtt_yml_path % env))
-        
+        if self.__business == 0:
-        self.__broker = self.__config["broker"]
+            self.__broker = self.__config['location']["broker"]
-        self.__port = self.__config["port"]
+            self.__port = self.__config['location']["port"]
-        self.__topic = self.__config["topic"]
+            self.__topic = self.__config['location']["topic"]
+        elif self.__business == 1:
+            self.__broker = self.__config['invade']["broker"]
+            self.__port = self.__config['invade']["port"]
+            self.__topic = self.__config['invade']["topic"]
         self.__lengthMqttList = self.__config["length"]
         
     
@@ -41,13 +45,11 @@ class PullMqtt(Thread):
 
 
     # 当接收到MQTT消息时，回调函数
-    def on_message(self,client, userdata, msg):
+    def on_location(self,client, userdata, msg):
         # 将消息解码为JSON格式
         payload = msg.payload.decode('utf-8')
         data = json.loads(payload)
         #logger.info(str(data))
-        
-
         # 解析位姿信息
         lon = data.get("lon")
         lat = data.get("lat")
@@ -58,18 +60,37 @@ class PullMqtt(Thread):
         
         if len(self.__mqtt_list) == self.__lengthMqttList:
             self.__mqtt_list.pop(0)
-        self.__mqtt_list.append(data)   
+        self.__mqtt_list.append([self.__business,data])
     
        
         # 打印无人机的位姿信息
         #print(f"Longitude: {lon}, Latitude: {lat}, Altitude: {alt}, sat:{data.get('satcount')} , list length:{len(self.__mqtt_list)}")
 
+    def on_invade(self, client, userdata, msg):
+        # 将消息解码为JSON格式
+        payload = msg.payload.decode('utf-8')
+        data = json.loads(payload)
+        # logger.info(str(data))
+        # 解析位姿信息
+        points = data.get("points")
+
+        if len(self.__mqtt_list) == self.__lengthMqttList:
+            self.__mqtt_list.pop(0)
+        self.__mqtt_list.append([self.__business,points])
+
+        # 打印无人机的位姿信息
+        # print(f"Longitude: {lon}, Latitude: {lat}, Altitude: {alt}, sat:{data.get('satcount')} , list length:{len(self.__mqtt_list)}")
+       
     def mqtt_connect(self):
         # 创建客户端  
         self.client = mqtt.Client()
         self.client.on_connect = self.on_connect
+        if self.__business == 0:
             # 设置回调函数
-        self.client.on_message = self.on_message  
+            self.client.on_message = self.on_location
+        elif self.__business == 1:
+            # 设置回调函数
+            self.client.on_message = self.on_invade
 
         # 连接到 Broker  
         self.client.connect(self.__broker, self.__port)  

concurrency/PullVideoStreamProcess.py

@@ -35,15 +35,15 @@ class PullVideoStreamProcess(Process):
         put_queue(self._command_queue, result, timeout=2, is_ex=True)
 
     @staticmethod
-    def start_File_upload(fb_queue, context, msg, image_queue, analyse_type,mqtt_list):
+    def start_File_upload(fb_queue, context, msg, image_queue, analyse_type):
-        image_thread = ImageFileUpload(fb_queue, context, msg, image_queue, analyse_type,mqtt_list)
+        image_thread = ImageFileUpload(fb_queue, context, msg, image_queue, analyse_type)
         image_thread.setDaemon(True)
         image_thread.start()
         return image_thread
         
     @staticmethod
-    def start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context):
+    def start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context,business):
-        mqtt_thread = PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
+        mqtt_thread = PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context,business)
         mqtt_thread.setDaemon(True)
         mqtt_thread.start()
         return mqtt_thread
@@ -82,12 +82,13 @@ class OnlinePullVideoStreamProcess(PullVideoStreamProcess):
             init_log(base_dir, env)
             logger.info("开启启动实时视频拉流进程, requestId:{},pid:{},ppid:{}", request_id,os.getpid(),os.getppid())
 
-            #开启mqtt
+            # 开启mqtt
-            if service["mqtt_flag"]==1:
+            if service['mqtt']["flag"] == 1:
-                mqtt_thread = self.start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
+                business = service['mqtt']["business"]
+                mqtt_thread = self.start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context, business)
 
             # 开启图片上传线程
-            image_thread = self.start_File_upload(fb_queue, context, msg, image_queue, analyse_type,mqtt_list)
+            image_thread = self.start_File_upload(fb_queue, context, msg, image_queue, analyse_type)
             cv2_init_num, init_pull_num, concurrent_frame = 0, 1, 1
             start_time, pull_stream_start_time, read_start_time, full_timeout = time(), None, None, None
             while True:
@@ -171,7 +172,7 @@ class OnlinePullVideoStreamProcess(PullVideoStreamProcess):
                     sleep(1)
                     continue
                 init_pull_num, read_start_time = 1, None
-                frame_list.append(frame)
+                frame_list.append([frame, mqtt_list])
                 frame_index_list.append(concurrent_frame)
                 if len(frame_list) >= frame_num:
                     put_queue(pull_queue, (4, (frame_list, frame_index_list, all_frames)), timeout=1, is_ex=True)
@@ -222,10 +223,11 @@ class OfflinePullVideoStreamProcess(PullVideoStreamProcess):
 
     def run(self):
         msg, context, frame_num, analyse_type = self._msg, self._context, self._frame_num, self._analyse_type
-        request_id, base_dir, env, pull_url = msg["request_id"], context['base_dir'], context['env'], msg["pull_url"]
+        request_id, base_dir, env, pull_url, service = msg["request_id"], context['base_dir'], context['env'], msg["pull_url"], context["service"]
         ex, service_timeout, full_timeout = None, int(context["service"]["timeout"]) + 120, None
-        command_queue, pull_queue, image_queue, fb_queue = self._command_queue, self._pull_queue, self._image_queue, \
+
-            self._fb_queue
+        command_queue, pull_queue, image_queue, fb_queue, mqtt_list = self._command_queue, self._pull_queue, self._image_queue, \
+            self._fb_queue, self._mqtt_list
         image_thread, pull_p = None, None
         width, height, width_height_3, all_frames, w_2, h_2 = None, None, None, 0, None, None
         frame_list, frame_index_list = [], []
@@ -235,8 +237,12 @@ class OfflinePullVideoStreamProcess(PullVideoStreamProcess):
             init_log(base_dir, env)
             logger.info("开启离线视频拉流进程, requestId:{}", request_id)
 
+            #开启mqtt
+            if service['mqtt']["flag"]==1:
+                business = service['mqtt']["business"]
+                mqtt_thread = self.start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context, business)
             # 开启图片上传线程
-            image_thread = self.start_File_upload(fb_queue, context, msg, image_queue, analyse_type,[])
+            image_thread = self.start_File_upload(fb_queue, context, msg, image_queue, analyse_type)
 
             # 初始化拉流工具类
             cv2_init_num, concurrent_frame = 0, 1
@@ -306,7 +312,7 @@ class OfflinePullVideoStreamProcess(PullVideoStreamProcess):
                                                ExceptionType.READSTREAM_TIMEOUT_EXCEPTION.value[1])
                     logger.info("离线拉流线程结束, requestId: {}", request_id)
                     break
-                frame_list.append(frame)
+                frame_list.append([frame,mqtt_list])
                 frame_index_list.append(concurrent_frame)
                 if len(frame_list) >= frame_num:
                     put_queue(pull_queue, (4, (frame_list, frame_index_list, all_frames)), timeout=1, is_ex=True)

concurrency/PushVideoStreamProcess.py

@@ -23,7 +23,7 @@ from util.Cv2Utils import video_conjuncing, write_or_video, write_ai_video, push
 from util.ImageUtils import url2Array, add_water_pic
 from util.LogUtils import init_log
 
-from util.PlotsUtils import draw_painting_joint, filterBox, xywh2xyxy2, xy2xyxy, draw_name_joint, plot_one_box_auto, draw_name_ocr,draw_name_crowd
+from util.PlotsUtils import draw_painting_joint, filterBox, xywh2xyxy2, xy2xyxy, draw_name_joint, plot_one_box_auto, draw_name_ocr,draw_name_crowd,draw_transparent_red_polygon
 
 from util.QueUtil import get_no_block_queue, put_queue, clear_queue
 
@@ -130,12 +130,22 @@ class OnPushStreamProcess(PushStreamProcess):
                     if push_r is not None:
                         if push_r[0] == 1:
                             frame_list, frame_index_list, all_frames, draw_config, push_objs = push_r[1]
-                            for i, frame in enumerate(frame_list):
+                            # 处理每1帧
+                            for i, [frame,mqtt_list] in enumerate(frame_list):
+                                # mqtt传参
+                                border = None
+                                mqttPares = None
+                                if len(mqtt_list) >= 1:
+                                    mqttPares = mqtt_list[0]
+                                    if mqttPares[0] == 1:
+                                        border = mqttPares[1]
                                 pix_dis = int((frame.shape[0]//10)*1.2)
                                 # 复制帧用来画图
                                 copy_frame = frame.copy()
+                                if border is not None:
+                                    copy_frame = draw_transparent_red_polygon(copy_frame, np.array(border, np.int32),alpha=0.25)
                                 det_xywh, thread_p = {}, []
-                                det_xywh2 = {}
+                                det_xywh2 = {'mqttPares':mqttPares}
                                 # 所有问题的矩阵集合
                                 qs_np = None
                                 qs_reurn = []
@@ -181,8 +191,8 @@ class OnPushStreamProcess(PushStreamProcess):
                                                                   draw_config[code]["label_dict"], score, color,
                                                                   font_config, qs[6])
                                                 else:
-                                                    rr = t.submit(draw_painting_joint, box, copy_frame, label_array,
+                                                    rr = t.submit(draw_painting_joint, box, copy_frame, label_array, score, color, font_config, border=border)
-                                                                  score, color, font_config)
+
 
                                             thread_p.append(rr)
                                             if det_xywh.get(code) is None:
@@ -384,17 +394,27 @@ class OffPushStreamProcess(PushStreamProcess):
                         # [(2, 操作指令)] 指令操作
                         if push_r[0] == 1:
                             frame_list, frame_index_list, all_frames, draw_config, push_objs = push_r[1]
+
                             # 处理每一帧图片
-                            for i, frame in enumerate(frame_list):
+                            for i, [frame,mqtt_list] in enumerate(frame_list):
+                                # mqtt传参
+                                border = None
+                                mqttPares = None
+                                if len(mqtt_list) >= 1:
+                                    mqttPares = mqtt_list[0]
+                                    if mqttPares[0] == 1:
+                                        border = mqttPares[1]
                                 pix_dis = int((frame.shape[0]//10)*1.2)
                                 if frame_index_list[i] % 300 == 0 and frame_index_list[i] <= all_frames:
                                     task_process = "%.2f" % (float(frame_index_list[i]) / float(all_frames))
                                     put_queue(hb_queue, {"hb_value": task_process}, timeout=2)
                                 # 复制帧用来画图
                                 copy_frame = frame.copy()
+                                if border is not None:
+                                    copy_frame = draw_transparent_red_polygon(copy_frame, np.array(border, np.int32),alpha=0.25)
                                 # 所有问题记录字典
                                 det_xywh, thread_p = {}, []
-                                det_xywh2 = {}
+                                det_xywh2 = {'mqttPares':mqttPares}
                                 # 所有问题的矩阵集合
                                 qs_np = None
                                 qs_reurn = []
@@ -437,7 +457,7 @@ class OffPushStreamProcess(PushStreamProcess):
                                                 if ModelType.CHANNEL2_MODEL.value[1] == str(code) and cls == 2:
                                                     rr = t.submit(draw_name_joint, box, copy_frame, draw_config[code]["label_dict"], score, color, font_config, qs[6])
                                                 else:
-                                                    rr = t.submit(draw_painting_joint, box, copy_frame, label_array, score, color, font_config)
+                                                    rr = t.submit(draw_painting_joint, box, copy_frame, label_array, score, color, font_config, border=border)
 
                                             thread_p.append(rr)
                                             if det_xywh.get(code) is None:
@@ -540,7 +560,7 @@ class OffPushStreamProcess(PushStreamProcess):
                                             else:
                                                 det_xywh2[code][cls].append(
                                                     [cls, box, score, label_array, color, is_new])
-                                    if len(det_xywh2) > 0:
+                                    if len(det_xywh2) > 1:
                                         put_queue(image_queue, (1, [det_xywh2, frame, frame_index_list[i], all_frames, draw_config["font_config"]]))
                                 push_p = push_stream_result.result(timeout=60)
                                 ai_video_file = write_ai_video_result.result(timeout=60)

config/mqtt/dsp_test_mqtt.yml

@@ -1,10 +1,21 @@
 mqtt_flag: true
-broker : "58.213.148.44"
+# 业务0为经纬度定位，业务1为入侵算法开关
-port : 1883
+business: 1
-username: "admin"
+# 经纬度定位
-password: "admin##123"
+location:
-#topic: "/topic/v1/airportFly/%s/aiDroneData"
+  broker : "58.213.148.44"
-topic: "/topic/v1/airportDrone/THJSQ03B2309TPCTD5QV/realTime/data"
+  port : 1883
-# 存储多少条消息到list里
+  username: "admin"
-length: 10
+  password: "admin##123"
+  #topic: "/topic/v1/airportFly/%s/aiDroneData"
+  topic: "/topic/v1/airportDrone/THJSQ03B2309TPCTD5QV/realTime/data"
 
+# 入侵
+invade:
+  broker : "192.168.11.8"
+  port : 2883
+  #topic: "/topic/v1/airportFly/%s/aiDroneData"
+  topic: "test000/topic"
+# 存储多少条消息到list里
+
+length: 30

config/service/dsp_test_service.yml

@@ -33,7 +33,8 @@ service:
   #storage source,0--aliyun,1--minio    
   storage_source: 0
   #是否启用mqtt，0--不用，1--启用
-  mqtt_flag: 0
+  mqtt:
+    flag: 1
+    business: 1
   #是否启用alg控制功能
   algSwitch: False
-

util/PlotsUtils.py

@@ -24,7 +24,6 @@ def get_label_array(color=None, label=None, font=None, fontSize=40, unify=False)
     im_array = cv2.resize(im_array, (0, 0), fx=scale, fy=scale)
     return im_array
 
-
 def get_label_arrays(labelNames, colors, fontSize=40, fontPath="platech.ttf"):
     font = ImageFont.truetype(fontPath, fontSize, encoding='utf-8')
     label_arraylist = [get_label_array(colors[i % 20], label_name, font, fontSize) for i, label_name in
@@ -117,38 +116,18 @@ def xy2xyxy(box):
         box = [(x1, y1), (x2, y1), (x2, y2), (x1, y2)]
     return box
 
-def draw_painting_joint(box, img, label_array, score=0.5, color=None, config=None, isNew=False):
+def draw_painting_joint(box, img, label_array, score=0.5, color=None, config=None, isNew=False, border=None):
     # 识别问题描述图片的高、宽
     # 图片的长度和宽度
+    if border is not None:
+        border = np.array(border,np.int32)
+        color,label_array=draw_name_border(box,color,label_array,border)
+        #img = draw_transparent_red_polygon(img,border,'',alpha=0.1)
+
     lh, lw = label_array.shape[0:2]
     tl = config[0]
     if isinstance(box[-1], np.ndarray):
-        font = ImageFont.truetype(FONT_PATH, 10, encoding='utf-8')
+        return draw_name_points(img,box,color)
-        points = box[-1]
-        arrea = cv2.contourArea(points)
-        label = '火焰'
-        #arealabel = '面积:%s'%f"{arrea:.1e}"
-        arealabel = '面积:%s'%arrea
-        label_array_area = get_label_array(color, arealabel, font, 10)
-        label_array = get_label_array(color, label, font, 10)
-        lh_area, lw_area = label_array_area.shape[0:2]
-        box = box[:4]
-        # 框框左上的位置
-        x0, y1 = box[0][0], max(box[0][1]-lh_area-3,0)
-        x1, y0 = box[1][0], box[1][1]
-        x0_label,y0_label,x1_label,y1_label = get_label_left(x0, y1,label_array,img)
-        x0_area, y0_area, x1_area, y1_area = get_label_right(x1, y0, label_array_area)
-        img[y0_label:y1_label, x0_label:x1_label, :] = label_array
-        img[y0_area:y1_area, x0_area:x1_area, :] = label_array_area
-        #cv2.drawContours(img, points, -1, color, tl)
-        cv2.polylines(img, [points], False, color, 1)
-        if lw_area < box[1][0]-box[0][0]:
-            box = [(x0, y1), (x1, y1),(x1, box[2][1]),(x0, box[2][1])]
-        else:
-            box = [(x0_label, y1), (x1, y1), (x1, box[2][1]), (x0_label, box[2][1])]
-        box = np.asarray(box, np.int32)
-        cv2.polylines(img, [box], True, color, 1)
-        return img, box
 
     label = ' %.2f' % score
     box = xywh2xyxy(box)
@@ -358,7 +337,6 @@ def plot_one_box_auto(box, img, color=None, line_thickness=2, label_array=None):
 
     return img, box
 
-
 def draw_name_crowd(dets, img, color, outfontsize=20):
     font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
     if len(dets) == 2:
@@ -410,3 +388,89 @@ def draw_name_crowd(dets, img, color, outfontsize=20):
 
 
     return img, dets
+
+def draw_name_points(img,box,color):
+    font = ImageFont.truetype(FONT_PATH, 6, encoding='utf-8')
+    points = box[-1]
+    arrea = cv2.contourArea(points)
+    label = '火焰'
+    arealabel = '面积:%s' % f"{arrea:.1e}"
+    label_array_area = get_label_array(color, arealabel, font, 10)
+    label_array = get_label_array(color, label, font, 10)
+    lh_area, lw_area = label_array_area.shape[0:2]
+    box = box[:4]
+    # 框框左上的位置
+    x0, y1 = box[0][0], max(box[0][1] - lh_area - 3, 0)
+    x1, y0 = box[1][0], box[1][1]
+    x0_label, y0_label, x1_label, y1_label = get_label_left(x0, y1, label_array, img)
+    x0_area, y0_area, x1_area, y1_area = get_label_right(x1, y0, label_array_area)
+    img[y0_label:y1_label, x0_label:x1_label, :] = label_array
+    img[y0_area:y1_area, x0_area:x1_area, :] = label_array_area
+    # cv2.drawContours(img, points, -1, color, tl)
+    cv2.polylines(img, [points], False, color, 2)
+    if lw_area < box[1][0] - box[0][0]:
+        box = [(x0, y1), (x1, y1), (x1, box[2][1]), (x0, box[2][1])]
+    else:
+        box = [(x0_label, y1), (x1, y1), (x1, box[2][1]), (x0_label, box[2][1])]
+    box = np.asarray(box, np.int32)
+    cv2.polylines(img, [box], True, color, 2)
+    return img, box
+
+def draw_name_border(box,color,label_array,border):
+    box = xywh2xyxy(box[:4])
+    cx, cy = int((box[0][0] + box[2][0]) / 2), int((box[0][1] + box[2][1]) / 2)
+    flag = cv2.pointPolygonTest(border, (int(cx), int(cy)),
+                                False)  # 若为False，会找点是否在内，外，或轮廓上
+    if flag == 1:
+        color = [0, 0, 255]
+        # 纯白色是(255, 255, 255)，根据容差定义白色范围
+        lower_white = np.array([255 - 30] * 3, dtype=np.uint8)
+        upper_white = np.array([255, 255, 255], dtype=np.uint8)
+        # 创建白色区域的掩码（白色区域为True，非白色为False）
+        white_mask = cv2.inRange(label_array, lower_white, upper_white)
+        # 创建与原图相同大小的目标颜色图像
+        target_img = np.full_like(label_array, color, dtype=np.uint8)
+        # 先将非白色区域设为目标颜色，再将白色区域覆盖回原图颜色
+        label_array = np.where(white_mask[..., None], label_array, target_img)
+    return color,label_array
+
+def draw_transparent_red_polygon(img, points, alpha=0.5):
+    """
+    在图像中指定的多边形区域绘制半透明红色
+
+    参数:
+        image_path: 原始图像路径
+        points: 多边形顶点坐标列表，格式为[(x1,y1), (x2,y2), ..., (xn,yn)]
+        output_path: 输出图像路径
+        alpha: 透明度系数，0-1之间，值越小透明度越高
+    """
+    # 读取原始图像
+    if img is None:
+        raise ValueError(f"无法读取图像")
+
+    # 创建与原图大小相同的透明图层（RGBA格式）
+    overlay = np.zeros((img.shape[0], img.shape[1], 4), dtype=np.uint8)
+
+    # 将点列表转换为适合cv2.fillPoly的格式
+    #pts = np.array(points, np.int32)
+    pts = points.reshape((-1, 1, 2))
+
+    # 在透明图层上绘制红色多边形（BGR为0,0,255）
+    # 最后一个通道是Alpha值，控制透明度，黄色rgb
+    cv2.fillPoly(overlay, [pts], (255, 0, 0, int(alpha * 255)))
+
+    # 将透明图层转换为BGR格式（用于与原图混合）
+    overlay_bgr = cv2.cvtColor(overlay, cv2.COLOR_RGBA2BGR)
+
+    # 创建掩码，用于提取红色区域
+    mask = overlay[:, :, 3] / 255.0
+    mask = np.stack([mask] * 3, axis=-1)  # 转换为3通道
+
+    # 混合原图和透明红色区域
+    img = img * (1 - mask) + overlay_bgr * mask
+    img = img.astype(np.uint8)
+
+    # # 保存结果
+    # cv2.imwrite(output_path, result)
+
+    return img