1)新增区域入侵算法 2)火焰面积bug修复

This commit is contained in:
th 2025-08-22 11:14:08 +08:00
parent 6e89b6587b
commit 0f3a0a85b2
9 changed files with 364 additions and 231 deletions

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@ -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"

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@ -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])
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]
target[5],border)
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]:

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@ -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
@ -1241,8 +1245,7 @@ class PhotosIntelligentRecognitionProcess(Process):
ExceptionType.URL_ADDRESS_ACCESS_FAILED.value[0],
ExceptionType.URL_ADDRESS_ACCESS_FAILED.value[1]), timeout=2)
return
return
with ThreadPoolExecutor(max_workers=1) as t:
try:
@ -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):

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@ -1,142 +1,163 @@
# -*- coding: utf-8 -*-
from threading import Thread
from time import sleep, time
from traceback import format_exc
from loguru import logger
from common.YmlConstant import mqtt_yml_path
from util.RWUtils import getConfigs
from common.Constant import init_progess
from enums.AnalysisStatusEnum import AnalysisStatus
from entity.FeedBack import message_feedback
from enums.ExceptionEnum import ExceptionType
from exception.CustomerException import ServiceException
from util.QueUtil import get_no_block_queue, put_queue, clear_queue
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")
def __init__(self, *args):
super().__init__()
self.__fb_queue, self.__mqtt_list, self.__request_id, self.__analyse_type, self._context = args
base_dir, env = self._context["base_dir"], self._context["env"]
self.__config = getConfigs(os.path.join(base_dir, mqtt_yml_path % env))
self.__broker = self.__config["broker"]
self.__port = self.__config["port"]
self.__topic = self.__config["topic"]
self.__lengthMqttList = self.__config["length"]
def put_queue(self,__queue,data):
if __queue.full():
a = __queue.get()
__queue.put( data,block=True, timeout=2 )
def on_connect(self,client,userdata,flags,rc):
client.subscribe(self.__topic)
# 当接收到MQTT消息时回调函数
def on_message(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")
alt = data.get("alt")
yaw = data.get("yaw")
pitch = data.get("pitch")
roll = data.get("roll")
if len(self.__mqtt_list) == self.__lengthMqttList:
self.__mqtt_list.pop(0)
self.__mqtt_list.append(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 mqtt_connect(self):
# 创建客户端
self.client = mqtt.Client()
self.client.on_connect = self.on_connect
# 设置回调函数
self.client.on_message = self.on_message
# 连接到 Broker
self.client.connect(self.__broker, self.__port)
# 订阅主题
self.client.subscribe(self.__topic)
# 循环等待并处理网络事件
self.client.loop_forever()
def mqtt_disconnect(self):
start_time = time()
while True:
if time() - start_time > service_timeout:
logger.error("MQTT读取超时, requestId: %s,限定时间:%.1s , 已运行:%.1fs"%(request_id,service_timeout, time() - start_time))
raise ServiceException(ExceptionType.TASK_EXCUTE_TIMEOUT.value[0],
ExceptionType.TASK_EXCUTE_TIMEOUT.value[1])
client.loop_stop() # 停止循环
client.disconnect() # 断开连接
def run(self):
request_id, mqtt_list, progress = self.__request_id, self.__mqtt_list, init_progess
analyse_type, fb_queue = self.__analyse_type, self.__fb_queue
#service_timeout = int(self.__config["service"]["timeout"]) + 120
try:
logger.info("开始MQTT读取线程requestId:{}", request_id)
mqtt_init_num = 0
self.mqtt_connect()
except Exception:
logger.error("MQTT线程异常:{}, requestId:{}", format_exc(), request_id)
finally:
mqtt_list = []
logger.info("MQTT线程停止完成requestId:{}", request_id)
def start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context):
mqtt_thread = PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
mqtt_thread.setDaemon(True)
mqtt_thread.start()
return mqtt_thread
def start_PullVideo(mqtt_list):
for i in range(1000):
sleep(1)
if len(mqtt_list)>=10:
print( mqtt_list[4])
print(i,len(mqtt_list))
if __name__=="__main__":
#context = {'service':{'timeout':3600},'mqtt':{
# 'broker':"101.133.163.127",'port':1883,'topic':"test/topic","length":10}
# }
context = {
'base_dir':'/home/th/WJ/test/tuoheng_algN',
'env':'test'
}
analyse_type = '1'
request_id = '123456789'
event_queue, pull_queue, mqtt_list, image_queue, push_queue, push_ex_queue = Queue(), Queue(10), [], Queue(), Queue(), Queue()
fb_queue = Queue()
mqtt_thread = start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
start_PullVideo(mqtt_list)
print('---line117--')
#mqtt_thread.join()
# -*- coding: utf-8 -*-
from threading import Thread
from time import sleep, time
from traceback import format_exc
from loguru import logger
from common.YmlConstant import mqtt_yml_path
from util.RWUtils import getConfigs
from common.Constant import init_progess
from enums.AnalysisStatusEnum import AnalysisStatus
from entity.FeedBack import message_feedback
from enums.ExceptionEnum import ExceptionType
from exception.CustomerException import ServiceException
from util.QueUtil import get_no_block_queue, put_queue, clear_queue
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" ,'__business')
def __init__(self, *args):
super().__init__()
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['location']["broker"]
self.__port = self.__config['location']["port"]
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"]
def put_queue(self,__queue,data):
if __queue.full():
a = __queue.get()
__queue.put( data,block=True, timeout=2 )
def on_connect(self,client,userdata,flags,rc):
client.subscribe(self.__topic)
# 当接收到MQTT消息时回调函数
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")
alt = data.get("alt")
yaw = data.get("yaw")
pitch = data.get("pitch")
roll = data.get("roll")
if len(self.__mqtt_list) == self.__lengthMqttList:
self.__mqtt_list.pop(0)
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_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)
# 订阅主题
self.client.subscribe(self.__topic)
# 循环等待并处理网络事件
self.client.loop_forever()
def mqtt_disconnect(self):
start_time = time()
while True:
if time() - start_time > service_timeout:
logger.error("MQTT读取超时, requestId: %s,限定时间:%.1s , 已运行:%.1fs"%(request_id,service_timeout, time() - start_time))
raise ServiceException(ExceptionType.TASK_EXCUTE_TIMEOUT.value[0],
ExceptionType.TASK_EXCUTE_TIMEOUT.value[1])
client.loop_stop() # 停止循环
client.disconnect() # 断开连接
def run(self):
request_id, mqtt_list, progress = self.__request_id, self.__mqtt_list, init_progess
analyse_type, fb_queue = self.__analyse_type, self.__fb_queue
#service_timeout = int(self.__config["service"]["timeout"]) + 120
try:
logger.info("开始MQTT读取线程requestId:{}", request_id)
mqtt_init_num = 0
self.mqtt_connect()
except Exception:
logger.error("MQTT线程异常:{}, requestId:{}", format_exc(), request_id)
finally:
mqtt_list = []
logger.info("MQTT线程停止完成requestId:{}", request_id)
def start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context):
mqtt_thread = PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
mqtt_thread.setDaemon(True)
mqtt_thread.start()
return mqtt_thread
def start_PullVideo(mqtt_list):
for i in range(1000):
sleep(1)
if len(mqtt_list)>=10:
print( mqtt_list[4])
print(i,len(mqtt_list))
if __name__=="__main__":
#context = {'service':{'timeout':3600},'mqtt':{
# 'broker':"101.133.163.127",'port':1883,'topic':"test/topic","length":10}
# }
context = {
'base_dir':'/home/th/WJ/test/tuoheng_algN',
'env':'test'
}
analyse_type = '1'
request_id = '123456789'
event_queue, pull_queue, mqtt_list, image_queue, push_queue, push_ex_queue = Queue(), Queue(10), [], Queue(), Queue(), Queue()
fb_queue = Queue()
mqtt_thread = start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
start_PullVideo(mqtt_list)
print('---line117--')
#mqtt_thread.join()

View File

@ -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):
image_thread = ImageFileUpload(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)
image_thread.setDaemon(True)
image_thread.start()
return image_thread
@staticmethod
def start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context):
mqtt_thread = 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,business)
mqtt_thread.setDaemon(True)
mqtt_thread.start()
return mqtt_thread
@ -81,13 +81,14 @@ class OnlinePullVideoStreamProcess(PullVideoStreamProcess):
# 初始化日志
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
if service["mqtt_flag"]==1:
mqtt_thread = self.start_PullMqtt(fb_queue, mqtt_list, request_id, analyse_type, context)
# 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,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)

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@ -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,
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:
@ -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)

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

View File

@ -33,7 +33,8 @@ service:
#storage source,0--aliyun,1--minio
storage_source: 0
#是否启用mqtt0--不用1--启用
mqtt_flag: 0
mqtt:
flag: 1
business: 1
#是否启用alg控制功能
algSwitch: False
algSwitch: False

View File

@ -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')
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
return draw_name_points(img,box,color)
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:
@ -409,4 +387,90 @@ def draw_name_crowd(dets, img, color, outfontsize=20):
img[y0:y1, x0:x1, :] = label_arr
return img, dets
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