diff --git a/__pycache__/Send_tranfer_oss.cpython-38.pyc b/__pycache__/Send_tranfer_oss.cpython-38.pyc index 93fc83b..2dbddd4 100644 Binary files a/__pycache__/Send_tranfer_oss.cpython-38.pyc and b/__pycache__/Send_tranfer_oss.cpython-38.pyc differ diff --git a/__pycache__/queRiver.cpython-38.pyc b/__pycache__/queRiver.cpython-38.pyc index 856fbea..48609a5 100644 Binary files a/__pycache__/queRiver.cpython-38.pyc and b/__pycache__/queRiver.cpython-38.pyc differ diff --git a/debut.txt b/debut.txt new file mode 100644 index 0000000..e69de29 diff --git a/logs/master/detector.log b/logs/master/detector.log index bb1a8a3..52fe27e 100644 --- a/logs/master/detector.log +++ b/logs/master/detector.log @@ -39,3 +39,5 @@ 2022-07-12 22:55:55.595 [INFO][master:readingKafka][401][logs.master.detector.log]- read msgs from kafka online task and response to kafka, taskId:XJRW20211129170353 msgId:bbCLSkaZXRrWQTbMUwjEYIfOAlsGxudV send:{"msg_id": "bbCLSkaZXRrWQTbMUwjEYIfOAlsGxudV", "biz_id": "hehuzhang", "mod_id": "ai", "status": "waiting", "type": "2", "error": "9999", "progressbar": "None", "results": [{"original_url": "", "sign_url": ""}]} 2022-07-12 22:55:56.323 [INFO][master:detector][467][logs.master.detector.log]- start to process onLine taskId:XJRW20211129170353 msgId:bbCLSkaZXRrWQTbMUwjEYIfOAlsGxudV 2022-07-12 22:57:16.753 [INFO][master:detector][544][logs.master.detector.log]- ********************sleep ******************** +2022-07-13 00:17:00.509 [INFO][master:detector][434][logs.master.detector.log]- detector process starts +2022-07-13 00:17:00.667 [INFO][master:readingKafka][375][logs.master.detector.log]- reading kafka process starts diff --git a/logs/send/SendPics.log b/logs/send/SendPics.log index c30fe8d..b0dee41 100644 --- a/logs/send/SendPics.log +++ b/logs/send/SendPics.log @@ -133,3 +133,6 @@ UnboundLocalError: local variable 'e' referenced before assignment 2022-07-12 22:58:08.525 [INFO][Send-tranfer-oss:mintor-offline-ending][101][logs.send.SendPics.log]- child processs starts 2022-07-12 22:58:20.693 [INFO][Send-tranfer-oss:main][261][logs.send.SendPics.log]- fecc085bb03c4aec9224f6f9b5a4e71f,935ec5b554a24392895cf27aefbe36c7 2022-07-12 22:58:20.741 [INFO][Send-tranfer-oss:main][310][logs.send.SendPics.log]- kafka send:live msg:{"msg_id": "bbCLSkaZXRrWQTbMUwjEYIfOAlsGxudV", "biz_id": "hehuzhang", "mod_id": "ai", "status": "success", "type": "2", "error": "9999", "progressbar": "None", "results": [{"original_url": "fecc085bb03c4aec9224f6f9b5a4e71f", "sign_url": "935ec5b554a24392895cf27aefbe36c7"}]} producer status:False +2022-07-13 00:17:43.825 [INFO][Send-tranfer-oss:main][154][logs.send.SendPics.log]- Send_tranfer_oss process starts +2022-07-13 00:17:43.962 [INFO][Send-tranfer-oss:main][185][logs.send.SendPics.log]- Load Parameter over +2022-07-13 00:17:43.969 [INFO][Send-tranfer-oss:mintor-offline-ending][101][logs.send.SendPics.log]- child processs starts diff --git a/master.py b/master.py index 9eb57bc..3ff15c2 100644 --- a/master.py +++ b/master.py @@ -1,583 +1,3 @@ -<<<<<<< HEAD -import numpy as np -import time,ast,copy -#from flask import request, Flask,jsonify -import base64,cv2,os,sys,json -#sys.path.extend(['../yolov5']) -#from Send_tranfer import b64encode_function,JsonSend,name_dic,nameID_dic,getLogFileFp -from segutils.segmodel import SegModel,get_largest_contours -from models.experimental import attempt_load -from utils.datasets import LoadStreams, LoadImages -from utils.torch_utils import select_device, load_classifier, time_synchronized -from queRiver import get_labelnames,get_label_arrays,post_process_,save_problem_images,time_str -import subprocess as sp -import matplotlib.pyplot as plt -import torch,random,string -import multiprocessing -from multiprocessing import Process,Queue -import traceback -from kafka import KafkaProducer, KafkaConsumer,TopicPartition -from kafka.errors import kafka_errors - -#torch.multiprocessing.set_start_method('spawn') -import utilsK -from utilsK.GPUtils import * -from utilsK.masterUtils import * -from utilsK.sendUtils import create_status_msg,update_json - -#from utilsK.modelEval import onlineModelProcsss -import random,string -from Send_tranfer_oss import msg_dict_on,msg_dict_off - -process_id=0 - -def onlineModelProcess(parIn ): - DEBUG=False - streamName = parIn['streamName'] - childCallback=parIn['callback'] - outStrList={} - channelIndex=parIn['channelIndex'] - #try: - for wan in ['test']: - jsonfile=parIn['modelJson'] - with open(jsonfile,'r') as fp: - parAll = json.load(fp) - - Detweights=parAll['gpu_process']['det_weights'] - seg_nclass = parAll['gpu_process']['seg_nclass'] - Segweights = parAll['gpu_process']['seg_weights'] - StreamRecoveringTime=int(parAll['StreamRecoveringTime']) - videoSave = parAll['AI_video_save'] - imageTxtFile = parAll['imageTxtFile'] - taskId,msgId = streamName.split('-')[1:3] - - inSource,outSource=parIn['inSource'],parIn['outSource'] - - ##构建日志文件 - if outSource != 'NO': - logdir = parAll['logChildProcessOnline'] - waitingTime=parAll['StreamWaitingTime'] - else: - logdir = parAll['logChildProcessOffline'] - waitingTime=5 - logname='gpuprocess.log' - fp_log=create_logFile(logdir=logdir,name=logname) - logger=logdir.replace('/','.')+'.'+logname - kafka_par=parIn['kafka_par'] - producer = KafkaProducer(bootstrap_servers=kafka_par['server'],value_serializer=lambda v: v.encode('utf-8'),metadata_max_age_ms=120000) - - ####要先检查视频的有效性 - ###开始的时候,如果在线任务没有流，要发送的心跳消息，msg_h, - msg_h= copy.deepcopy(msg_dict_off); - msg_h['status']='waiting';msg_h['msg_id']=msgId - - - thread='master:gpuprocess-%s'%(msgId) - if outSource == 'NO': - msg_h['type']=1 - Stream_ok,_= get_fps_rtmp(inSource,video=True) - else: - msg_h['type']=2 - msg_h_d = json.dumps(msg_h, ensure_ascii=False) - outStrList=get_infos(taskId, msgId,msg_h_d,key_str='waiting stream or video, send heartbeat') - Stream_ok=check_stream(inSource,producer,kafka_par,msg_h_d,outStrList,fp_log,logger,line=sys._getframe().f_lineno,thread=thread ,timeMs=waitingTime) - - if Stream_ok:###发送开始信号 - msg_h['status']='running' - msg_h_d = json.dumps(msg_h, ensure_ascii=False) - outStrList= get_infos(taskId, msgId,msg_h_d,key_str='informing stream/video is ok') - send_kafka(producer,kafka_par,msg_h_d,outStrList,fp_log,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - - else: - ####检测离线视频是否有效,无效要报错 - outstr='offline vedio or live stream Error:%s '%(inSource) - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,level='ERROR',line=sys._getframe().f_lineno,logger=logger) - - msg_h['error']='Stream or video ERROR';msg_h['status']='failed'; - msg_h_d = json.dumps(msg_h, ensure_ascii=False); - outStrList= get_infos(taskId, msgId,msg_h_d,key_str='informing invaid video or stream success') - send_kafka(producer,kafka_par,msg_h_d,outStrList,fp_log ,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - childCallback.send(' offline vedio or live stream Error') - continue - - - - if (inSource.endswith('.MP4')) or (inSource.endswith('.mp4')): - fps,outW,outH,totalcnt=get_fps_rtmp(inSource,video=True)[1][0:4]; - else: - fps,outW,outH,totalcnt=get_fps_rtmp(inSource,video=False)[1][0:4] - fps = int(fps+0.5) - if fps>30: fps=25 ###线下测试时候，有时候读帧率是9000，明显不符合实际，所以加这个判断。 - if outSource != 'NO': - command=['/usr/bin/ffmpeg','-y','-f', 'rawvideo','-vcodec','rawvideo','-pix_fmt', 'bgr24', - '-s', "{}x{}".format(outW,outH),# 图片分辨率 - '-r', str(fps),# 视频帧率 - '-i', '-','-c:v', - 'libx264', - '-pix_fmt', 'yuv420p', - '-f', 'flv',outSource - ] - - - video_flag = videoSave['onLine'] - logdir = parAll['logChildProcessOnline'] - waitingTime=parAll['StreamWaitingTime'] - else: - video_flag = videoSave['offLine'] ;logdir = parAll['logChildProcessOffline'] - waitingTime=5 - - device = select_device(parIn['device']) - half = device.type != 'cpu' # half precision only supported on CUDA - model = attempt_load(Detweights, map_location=device) # load FP32 model - if half: model.half() - - segmodel = SegModel(nclass=seg_nclass,weights=Segweights,device=device) - - - - - ##后处理参数 - par=parAll['post_process'] - conf_thres,iou_thres,classes=par['conf_thres'],par['iou_thres'],par['classes'] - outImaDir = par['outImaDir'] - outVideoDir = par['outVideoDir'] - labelnames=par['labelnames'] - rainbows=par['rainbows'] - fpsample = par['fpsample'] - names=get_labelnames(labelnames) - label_arraylist = get_label_arrays(names,rainbows,outfontsize=40) - - #dataset = LoadStreams(inSource, img_size=640, stride=32) - - - childCallback.send('####model load success####') - print('#####line153:',outVideoDir,video_flag) - if (outVideoDir!='NO') : ####2022.06.27新增在线任务也要传AI视频和原始视频 - if video_flag: - msg_id = streamName.split('-')[2] - save_path = os.path.join(outVideoDir,msg_id+'.MP4') - vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (outW,outH)) - if vid_writer.isOpened(): outstr='touch video success:%s'%(save_path);level='INFO' - else:outstr='touch video failed:%s'%(save_path);level='ERROR' - writeELK_log(msg=outstr,fp=fp_log,level=level,line=sys._getframe().f_lineno,logger=logger) - else: - msg_id = streamName.split('-')[2] - save_path_OR = os.path.join(outVideoDir,msg_id+'_OR.MP4') - vid_writer_OR = cv2.VideoWriter(save_path_OR, cv2.VideoWriter_fourcc(*'mp4v'), fps, (outW,outH)) - save_path_AI = os.path.join(outVideoDir,msg_id+'_AI.MP4') - vid_writer_AI = cv2.VideoWriter(save_path_AI, cv2.VideoWriter_fourcc(*'mp4v'), fps, (outW,outH)) - if vid_writer_AI.isOpened() and vid_writer_OR.isOpened() :outstr='touch video success:%s,%s'%(save_path_OR,save_path_AI);level='INFO' - else:outstr='touch video failed:%s,%s, fps:%d ,%d , %d'%(save_path_OR,save_path_AI,fps,outW,outH);level='ERROR' - writeELK_log(msg=outstr,fp=fp_log,level=level,line=sys._getframe().f_lineno,logger=logger) - - iframe = 0;post_results=[];time_beg=time.time() - - t00=time.time() - time_kafka0=time.time() - - Pushed_Flag=False - while True: - try: - dataset = LoadStreams(inSource, img_size=640, stride=32) - # 管道配置，其中用到管道 - if outSource !='NO' and (not Pushed_Flag): - ppipe = sp.Popen(command, stdin=sp.PIPE);Pushed_Flag = True - for path, img, im0s, vid_cap in dataset: - t0= time_synchronized() - if outSource == 'NO':###如果不推流，则显示进度条。离线不推流 - view_bar(iframe,totalcnt,time_beg ,parIn['process_uid'] ) - streamCheckCnt=0 - ###直播和离线都是1分钟发一次消息 - time_kafka1 = time.time() - if time_kafka1 - time_kafka0 >60: - time_kafka0 = time_kafka1 - ###发送状态信息waiting - msg = copy.deepcopy(msg_dict_off); - msg['msg_id']= msgId; - if outSource == 'NO': - msg['progressbar']= '%.4f'%(iframe*1.0/totalcnt) - msg['type']=1 - else: - msg['progressbarOn']= str(iframe) - msg['type']=2 - - msg = json.dumps(msg, ensure_ascii=False) - outStrList= get_infos(taskId, msgId,msg,key_str='processing send progressbar or online heartbeat') - send_kafka(producer,kafka_par,msg,outStrList,fp_log,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - - time0=time.time() - iframe +=1 - time1=time.time() - img = torch.from_numpy(img).to(device) - img = img.half() if half else img.float() # uint8 to fp16/32 - - img /= 255.0 # 0 - 255 to 0.0 - 1.0 - - timeseg0 = time.time() - seg_pred,segstr = segmodel.eval(im0s[0] ) - timeseg1 = time.time() - - t1= time_synchronized() - - pred = model(img,augment=False)[0] - - time4 = time.time() - datas = [path, img, im0s, vid_cap,pred,seg_pred,iframe] - - p_result,timeOut = post_process_(datas,conf_thres, iou_thres,names,label_arraylist,rainbows,iframe) - t2= time_synchronized() - - #print('###line138:',timeOut,outSource,outVideoDir) - ##每隔 fpsample帧处理一次，如果有问题就保存图片 - if (iframe % fpsample == 0) and (len(post_results)>0) : - parImage=save_problem_images(post_results,iframe,names,streamName=streamName,outImaDir='problems/images_tmp',imageTxtFile=imageTxtFile) - post_results=[] - - if len(p_result[2] )>0: ## - post_results.append(p_result) - t3= time_synchronized() - image_array = p_result[1] - if outSource!='NO': - ppipe.stdin.write(image_array.tobytes()) - - if (outVideoDir!='NO'): - if video_flag: ret = vid_writer.write(image_array) - else: - time_w0=time.time() - ret = vid_writer_AI.write(image_array) - ret = vid_writer_OR.write(im0s[0]) - time_w1=time.time() - #if not ret: - # print('\n write two videos time:%f ms'%(time_w1-time_w0)*1000,ret) - t4= time_synchronized() - - timestr2 = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) - if iframe%100==0: - outstr='%s,,read:%.1f ms,copy:%.1f, infer:%.1f ms, detinfer:%.1f ms,draw:%.1f ms, save:%.1f ms total:%.1f ms \n'%(timestr2,(t0 - t00)*1000,(timeseg0-t0)*1000, (t1 - timeseg0)*1000,(t2-t1)*1000, (t3 - t2)*1000,(t4-t3)*1000, (t4-t00)*1000) - #wrtiteLog(fp_log,outstr); - writeELK_log(msg=outstr,fp=fp_log,line=sys._getframe().f_lineno,logger=logger,printFlag=False) - #print(outstr) - t00 = t4; - - except Exception as e: - #if outSource:###推流才有如下 - streamCheckCnt+=1;taskEnd=False - if streamCheckCnt==1:timeBreak0=time.time();time_kafka0 = time.time() - timeBreak1=time.time(); - if timeBreak1-timeBreak0 >5 and Pushed_Flag:###流断开5秒后，要关闭推流 - ppipe.kill();Pushed_Flag=False - writeELK_log(msg='stream pip is killed ',fp=fp_log,line=sys._getframe().f_lineno,logger=logger) - - ###读接口，看看任务有没有结束 - ChanellInfos,taskEnd=query_channel_status(channelIndex) - ####taskEnd######################DEBUG - #taskEnd=False - - if timeBreak1-timeBreak0 >StreamRecoveringTime : ##默认30分钟内，流没有恢复的话，就断开。 - taskEnd=True - - outstr_channel='%s ,taskEnd:%s'%(ChanellInfos,taskEnd) - writeELK_log(msg=outstr_channel,fp=fp_log,line=sys._getframe().f_lineno,logger=logger) - if outSource == 'NO':#离线没有推流 - taskEnd=True - if taskEnd: - if timeBreak1-timeBreak0 > 60:###超时结束 - writeTxtEndFlag(outImaDir,streamName,imageTxtFile,endFlag='超时结束') - else: - writeTxtEndFlag(outImaDir,streamName,imageTxtFile,endFlag='结束') - if (outVideoDir!='NO'): - if video_flag:vid_writer.release() - else: - vid_writer_OR.release(); - vid_writer_AI.release(); - outstr='Task ends:%.1f , msgid:%s,taskID:%s '%(timeBreak1-timeBreak0,taskId,msgId) - writeELK_log(msg=outstr,fp=fp_log,line=sys._getframe().f_lineno,logger=logger) - break - - ##执行到这里的一定是在线任务，在等待流的过程中要发送waiting - time_kafka1 = time.time() - if time_kafka1-time_kafka0>60: - msg_res = copy.deepcopy(msg_dict_off); - msg_res['msg_id']= msgId; msg_res['type']=2 - msg_res = json.dumps(msg_res, ensure_ascii=False) - outStrList= get_infos(taskId, msgId,msg_res,key_str='Waiting stream restoring heartbeat') - send_kafka(producer,kafka_par,msg_res,outStrList,fp_log,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - - outstr='Waiting stream recovering:%.1f s'%(timeBreak1-timeBreak0) - writeELK_log(msg=outstr,fp=fp_log,line=sys._getframe().f_lineno,logger=logger) - writeELK_log(msg=outstr_channel,fp=fp_log,line=sys._getframe().f_lineno,logger=logger) - time_kafka0 = time_kafka1 - - #break###断流或者到终点 - - time.sleep(5) - print('Waiting stream for ',e) -def lauch_process(gpuid,inSource,outSource,taskId,msgId,modelJson,kafka_par,channelIndex='LC001'): - - if outSource=='NO': - streamName='off-%s-%s'%(taskId,msgId) - else: - streamName='live-%s-%s'%(taskId,msgId) - dataPar ={ - 'imgData':'', - 'imgName':'testW', - 'streamName':streamName, - 'taskId':taskId, - 'msgId':msgId, - 'channelIndex':channelIndex, - 'device':str(gpuid), - 'modelJson':modelJson, - 'kafka_par':kafka_par, - - } - #dataPar['inSource'] = 'http://images.5gai.taauav.com/video/8bc32984dd893930dabb2856eb92b4d1.mp4';dataPar['outSource'] = None - dataPar['inSource'] = inSource;dataPar['outSource'] = outSource - process_uid=''.join(random.sample(string.ascii_letters + string.digits, 16));dataPar['process_uid']=process_uid - parent_conn, child_conn = multiprocessing.Pipe();dataPar['callback']=child_conn - gpuProcess=Process(target=onlineModelProcess,name='process:%s'%( process_uid ),args=(dataPar,)) - gpuProcess.start() - #print(dir(gpuProcess)) - #child_return = parent_conn.recv() - #timestr2=time.strftime("%Y-%m-%d %H:%M:%S ", time.localtime()) - #print(timestr2,'-'*20,'progress:%s ,msgId:%s , taskId:%s return:'%(process_uid,msgId,taskId),child_return) - - return gpuProcess - - -msg_dict_offline = { - - "biz_id":"hehuzhang", - "mod_id":"ai", - "msg_id":'bb'+''.join(random.sample(string.ascii_letters ,30) ) , - "offering_id":"http://vod.play.t-aaron.com/customerTrans/c49a2c620795d124f2ae4b10197b8d0e/303b7a58-17f3ef4494e-0004-f90c-f2c-7ec68.mp4", - "offering_type":"mp4", - "results_base_dir": "XJRW202203171535"+str(random.randint(10,99)), - - 'outSource':'NO' - - - } - - -taskStatus={} -taskStatus['onLine'] = Queue(100) -taskStatus['offLine']= Queue(100) -taskStatus['pidInfos']= {} - -def get_msg_from_kafka(par): - thread='master:readingKafka' - outStrList={} - fp_log = par['fp_log'] - logger=par['logger'] - consumer = KafkaConsumer(bootstrap_servers=par['server'],client_id='AI_server',group_id=par['group_id'],auto_offset_reset='latest') - consumer.subscribe( par['topic'][0:2]) - outstr='reading kafka process starts' - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - kafka_par ={ 'server':par['server'],'topic':par['topic'][2] } - producer = KafkaProducer( - bootstrap_servers=par['server'],#tencent yun - value_serializer=lambda v: v.encode('utf-8'), - metadata_max_age_ms=120000) - - - for ii,msg in enumerate(consumer): - ##读取消息 - try: - taskInfos = eval(msg.value.decode('utf-8') ) - except: - outstr='%s msg format error,value:%s,offset:%d partition:%s topic:%s'%('#'*20,msg.value,msg.offset,msg.topic,msg.topic) - continue - - if msg.topic == par['topic'][0]: ## - taskInfos['inSource']= taskInfos['pull_channel']; - taskInfos['outSource']= get_push_address(taskInfos['push_channel']) ; - - taskStatus['onLine'].put( taskInfos ) - save_message(par['kafka'],taskInfos) - - ###发送状态信息waiting - msg = create_status_msg(msg_dict_on,taskInfos,sts='waiting') - outStrList=get_infos(taskInfos['results_base_dir'], taskInfos['msg_id'],msg,key_str='read msgs from kafka online task and response to kafka') - send_kafka(producer,kafka_par,msg,outStrList,fp_log,line=sys._getframe().f_lineno,logger=logger,thread=thread); - - else: - try: - taskInfos['inSource']= taskInfos['offering_id']; - taskInfos['outSource']= 'NO' - - taskStatus['offLine'].put( taskInfos ) - save_message(par['kafka'],taskInfos) - - ###发送状态信息waiting - msg = create_status_msg(msg_dict_off,taskInfos,sts='waiting') - outStrList=get_infos(taskInfos['results_base_dir'], taskInfos['msg_id'],msg,key_str='read msgs from kafka offline task and response to kafka') - send_kafka(producer,kafka_par,msg,outStrList,fp_log ,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - except Exception as e: - print('######msg Error######',msg,e) - - -def detector(par): - - ####初始化信息列表 - kafka_par ={ 'server':par['server'],'topic':par['topic'][2] } - producer = KafkaProducer( - bootstrap_servers=par['server'],#tencent yun - value_serializer=lambda v: v.encode('utf-8'), - metadata_max_age_ms=120000) - time_interval=par['logPrintInterval'] - logname='detector.log';thread='master:detector' - fp_log=create_logFile(logdir=par['logDir'],name=logname) - ##准备日志函数所需参数 - logger=par['logDir'].replace('/','.')+'.'+logname - #wrtiteLog(fp_log,'########### detector process starts ######\n'); - outstr='detector process starts';sys._getframe().f_lineno - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - - ###开启kafka consumer 进程## - parIn=copy.deepcopy(par);parIn['fp_log']=fp_log ;parIn['logger']=logger - HeartProcess=Process(target=get_msg_from_kafka,name='process-consumer-kafka',args=(parIn,)) - HeartProcess.start() - - - timeSleep=1 - - time0=time.time() - time0_kafQuery=time.time() - time0_taskQuery=time.time() - time0_sleep=time.time() - outStrList={} - while True:###每隔timeSleep秒，轮询一次 - - time0_taskQuery,printFlag = check_time_interval(time0_taskQuery,time_interval) - outstr_task= ' task queue onLine cnt:%d offLine:%d'%(taskStatus['onLine'].qsize(), taskStatus['offLine'].qsize()) - if (taskStatus['onLine'].qsize()>0) or (taskStatus['offLine'].qsize()>0): - #outstr_task=wrtiteLog(fp_log,outstr_task);print( outstr_task); - writeELK_log(msg=outstr_task,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - ##2-更新显卡信息 - gpuStatus = getGPUInfos() - - ##3-优先考虑在线任务 - if not taskStatus['onLine'].empty(): - ###3.1-先判断有没有空闲显卡： - cuda = get_available_gpu(gpuStatus) - ###获取在线任务信息，并执行,lauch process - taskInfos = taskStatus['onLine'].get() - outstr='start to process onLine taskId:%s msgId:%s'%( taskInfos['results_base_dir'],taskInfos['msg_id'] ) - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - if cuda: ###3.1.1 -有空余显卡 - #lauch process - msg= copy.deepcopy(msg_dict_on); - gpuProcess=lauch_process(cuda,taskInfos['inSource'],taskInfos['outSource'],taskInfos['results_base_dir'],taskInfos['msg_id'],par['modelJson'],kafka_par,taskInfos['channel_code']) - taskStatus['pidInfos'][gpuProcess.pid] = {'gpuProcess':gpuProcess,'type':'onLine','taskInfos':taskInfos} - - else:###3.1.2-没有显卡 - ##判断有没有显卡上面都是离线进程的 - cuda_pid = get_potential_gpu(gpuStatus,taskStatus['pidInfos']) - - if cuda_pid:#3.1.2.1 - ##如果有可以杀死的进程 - cuda = cuda_pid['cuda'] - pids = cuda_pid['pids'] - ##kill 离线进程，并更新离线任务表 - cnt_off_0 = taskStatus['offLine'].qsize() - for pid in pids: - ##kill 离线进程 - taskStatus['pidInfos'][pid]['gpuProcess'].kill() - ##更新离线任务表 - taskStatus['offLine'].put( taskStatus['pidInfos'][pid]['taskInfos'] ) - taskInfos_off=taskStatus['pidInfos'][pid]['taskInfos'] - - ##发送离线数据，说明状态变成waiting - msg= msg_dict_off; - msg=update_json(taskInfos_off,msg,offkeys=["msg_id","biz_id" ,"mod_id"] ) - msg['results'][0]['original_url']=taskInfos_off['inSource'] - msg['results'][0]['sign_url']=get_boradcast_address(taskInfos_off['outSource']) - msg['status']='waiting' - msg = json.dumps(msg, ensure_ascii=False) - - - outStrList=get_infos(taskInfos_off['results_base_dir'], taskInfos_off['msg_id'],msg,key_str='start online task after kill offline tasks') - - send_kafka(producer,kafka_par,msg,outStrList,fp_log ,line=sys._getframe().f_lineno,logger=logger,thread=thread ); - - - cnt_off_1 = taskStatus['offLine'].qsize() - outstr='before killing process, offtask cnt:%d ,after killing, offtask cnt:%d '%(cnt_off_0,cnt_off_1) - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - gpuProcess=lauch_process(cuda,taskInfos['inSource'],taskInfos['outSource'],taskInfos['results_base_dir'],taskInfos['msg_id'],par['modelJson'],kafka_par,taskInfos['channel_code']) - - ###更新pidinfos，update pidInfos - taskStatus['pidInfos'][gpuProcess.pid] = {'gpuProcess':gpuProcess,'type':'onLine','taskInfos':taskInfos} - else: - outstr='No available GPUs for onLine task' - #outstr=wrtiteLog(fp_log,outstr);print(outstr); - writeELK_log(msg=outstr,fp=fp_log,level='ERROR',thread=thread,line=sys._getframe().f_lineno,logger=logger) - - ##4-更新显卡信息 - gpuStatus = getGPUInfos() - ##5-考虑离线任务 - if not taskStatus['offLine'].empty(): - cudaArrange= arrange_offlineProcess(gpuStatus,taskStatus['pidInfos'],modelMemory=1500) - outstr='IN OFF LINE TASKS available cudas:%s'%(cudaArrange) - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - - for cuda in cudaArrange: - if not taskStatus['offLine'].empty(): - taskInfos = taskStatus['offLine'].get() - outstr='start to process offLine taskId:%s msgId:%s'%( taskInfos['results_base_dir'],taskInfos['msg_id'] ) - taskInfos['channel_code']='LC999'###离线消息没有这个参数 - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - gpuProcess=lauch_process(cuda,taskInfos['inSource'],taskInfos['outSource'],taskInfos['results_base_dir'],taskInfos['msg_id'],par['modelJson'],kafka_par,taskInfos['channel_code']) - taskStatus['pidInfos'][gpuProcess.pid] = {'gpuProcess':gpuProcess,'type':'offLine','taskInfos':taskInfos} - - - - - if get_whether_gpuProcess(): - time0_sleep,printFlag = check_time_interval(time0_sleep,time_interval) - if printFlag: - outstr= '*'*20 +'sleep '+'*'*20; - #outstr=wrtiteLog(fp_log,outstr);print( outstr); - writeELK_log(msg=outstr,fp=fp_log,thread=thread,line=sys._getframe().f_lineno,logger=logger) - - time.sleep(timeSleep) - - print('########Program End#####') - - - -if __name__ == '__main__': - par={}; - ###topic0--在线，topic1--离线 - - #par['server']='212.129.223.66:9092';par['topic']=('thsw','thsw2','testReturn');par['group_id']='test'; - #101.132.127.1:19092 - - ''' - par['server']='101.132.127.1:19092 ';par['topic']=('alg-online-tasks','alg-offline-tasks','alg-task-results');par['group_id']='test'; - - par['kafka']='mintors/kafka' - par['modelJson']='conf/model.json' - ''' - masterFile="conf/master.json" - assert os.path.exists(masterFile) - with open(masterFile,'r') as fp: - data=json.load(fp) - par=data['par'] - print(par) - detector(par) - - - - - - - -======= import numpy as np import time,ast,copy #from flask import request, Flask,jsonify @@ -1156,4 +576,3 @@ if __name__ == '__main__': ->>>>>>> thsw diff --git a/models/__pycache__/__init__.cpython-38.pyc b/models/__pycache__/__init__.cpython-38.pyc index e294e1f..5b43ca1 100644 Binary files a/models/__pycache__/__init__.cpython-38.pyc and b/models/__pycache__/__init__.cpython-38.pyc differ diff --git a/models/__pycache__/common.cpython-38.pyc b/models/__pycache__/common.cpython-38.pyc index 35d1669..7075d4a 100644 Binary files a/models/__pycache__/common.cpython-38.pyc and 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