提交线上代码

.idea/deployment.xml

 <?xml version="1.0" encoding="UTF-8"?>
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+  <component name="PublishConfigData" autoUpload="Always" remoteFilesAllowedToDisappearOnAutoupload="false">
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         <serverdata>
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+            <mapping deploy="/home/DATA/prod/algSch" local="$PROJECT_DIR$" web="/" />
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.idea/runConfigurations.xml

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+      <change beforePath="$PROJECT_DIR$/test/b.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/d.jpg" beforeDir="false" />
+      <change beforePath="$PROJECT_DIR$/test/互信息.py" beforeDir="false" afterPath="$PROJECT_DIR$/test/水印/互信息.py" afterDir="false" />
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+      <change beforePath="$PROJECT_DIR$/test/视频添加文字水印.py" beforeDir="false" afterPath="$PROJECT_DIR$/test/水印/视频添加文字水印.py" afterDir="false" />
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concurrency/IntelligentRecognitionProcess.py

 import time
 import copy
 
-import numpy as np
-
 from common import Constant
 from multiprocessing import Process, Queue
 from loguru import logger
 from concurrency.CommonThread import Common
 from concurrency.CommonProcess import CommonProcess
 from exception.CustomerException import ServiceException
+from util.ImageUtils import PictureWaterMark
 
 
 class IntelligentRecognitionProcess(Process):
         self.msg = cfg.get("msg")
         self.imageQueue = cfg.get("imageQueue")
         self.gpu_ids = cfg.get("gpu_ids")
-        self.pic = cfg.get("pic")
+        self.pic = PictureWaterMark()
         self.type = cfg.get("type")
         # 定义原视频、AI视频保存名称
         random_time = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
             high_score_image = {}
             step = int(self.content["service"]["frame_step"])
             concurrent_frame = 1
+            service_timeout = int(self.content["service"]["timeout"])
             while True:
                 end_time = time.time()
                 create_task_time = int(end_time - start_time)
-                if create_task_time > int(self.content["service"]["timeout"]):
+                if create_task_time > service_timeout:
                     logger.error("分析超时, 超时时间：{}, requestId: {}", create_task_time, self.msg.get("request_id"))
                     raise ServiceException(ExceptionType.ANALYSE_TIMEOUT_EXCEPTION.value[0],
                                            ExceptionType.ANALYSE_TIMEOUT_EXCEPTION.value[1])
                         raise ServiceException(ExceptionType.PULLSTREAM_TIMEOUT_EXCEPTION.value[0],
                                                ExceptionType.PULLSTREAM_TIMEOUT_EXCEPTION.value[1])
                     cv2_init_num += 1
-                    time.sleep(0.5)
+                    time.sleep(1)
                     cv2tool.get_video_info()
                     cv2tool.build_pull_p()
                     continue
                 start_time_2 = time.time()
                 # time00 = time.time()
                 # 调用AI模型
-                p_result, timeOut = mod.process(copy.deepcopy(frame), cv2tool.width)
+                p_result, timeOut = mod.process(copy.deepcopy(frame), int(cv2tool.width/2))
                 # time11 = time.time()
                 # if time11 - time00 > 1:
                 #     logger.info("算法模型调度时间：{}s, requestId:{}", int(time11-time00), self.msg.get("request_id"))
                     break
                 #time00 = time.time()
                 # 调用AI模型
-                p_result, timeOut = mod.process(copy.deepcopy(frame), cv2tool.width)
+                p_result, timeOut = mod.process(copy.deepcopy(frame), int(cv2tool.width/2))
                 #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 self.content["video"]["video_add_water"]:

concurrency/MessagePollingThread.py

                             customerKafkaConsumer.commit_offset(m, topics=self.cfg["topics"])
             except Exception as e:
                 logger.exception("消息监听异常: {}", e)
+                customerKafkaConsumer = KafkaUtils.CustomerKafkaConsumer(self.cfg["content"])
             time.sleep(1)
 
     def poll(self):

dsp_application.yml

 dsp:
-  active: dev
+  active: prod12
 kafka:
   topic:
     dsp-alg-online-tasks-topic: dsp-alg-online-tasks
       auto_offset_reset: latest
       enable_auto_commit: False
       max_poll_records: 1
+  test1:
+    bootstrap_servers: ['192.168.11.242:9092']
+    dsp-alg-online-tasks:
+      partition: [1]
+    dsp-alg-offline-tasks:
+      partition: [1]
+    dsp-alg-task-results:
+      partition: [1]
+    producer:
+      acks: -1
+      retries: 3
+      linger_ms: 50
+      retry_backoff_ms: 1000
+      max_in_flight_requests_per_connection: 5
+    consumer:
+      client_id: dsp_ai_server
+      group_id: dsp-ai-test
+      auto_offset_reset: latest
+      enable_auto_commit: False
+      max_poll_records: 1
   prod12:
     bootstrap_servers: ['101.132.127.1:19092']
     dsp-alg-online-tasks:
 #  # maxusage : 单个连接的最大允许复用次数(缺省值 0 或 False 代表不限制的复用).当达到最大数时,连接会自动重新连接(关闭和重新打开)
 #  db_max_usage: 0
 #  # setsession : 一个可选的SQL命令列表用于准备每个会话，如["set datestyle to german", ...]
-#  db_set_session: None
+#  db_set_session: None

dsp_master.py

     print("(♥◠‿◠)ﾉﾞ  DSP【算法调度服务】开始启动   ლ(´ڡ`ლ)ﾞ")
     # torch.multiprocessing.set_start_method('spawn')
     Dispatcher.DispatcherService().start_service()
-    print("(♥◠‿◠)ﾉﾞ  DSP【算法调度服务】启动成功   ლ(´ڡ`ლ)ﾞ")

service/Dispatcher.py

     OfflineIntelligentRecognitionProcess
 from concurrency.MessagePollingThread import OfflineMessagePollingThread, OnlineMessagePollingThread
 from util import GPUtils
-from util.ImageUtils import PictureWaterMark
 
 '''
    分发服务
         # self.photoProcesses = {}
         self.onlineMpt = None
         self.offlineMpt = None
-        self.pic = PictureWaterMark()
+
 
     # 服务调用启动方法
     def start_service(self):
         # 启动实时，离线kafka消息拉取线程
         self.Kafka_message_listening()
+        print("(♥◠‿◠)ﾉﾞ  DSP【算法调度服务】启动成功   ლ(´ڡ`ლ)ﾞ")
         # 循环消息处理
         while True:
             time.sleep(1)
             # 检查任务进程运行情况，去除活动的任务
             self.check_process_task()
+            # 获取当前可用gpu使用数量
             gpu_ids = GPUtils.get_gpu_ids(self.content)
             if gpu_ids is not None and len(gpu_ids) > 0:
                 ################## 消息驱动实时流分析进程执行 ##################
             logger.warning("重复任务，请稍后再试！requestId:{}", msg.get("request_id"))
             return
         cfg = {"fbQueue": Queue(), "imageQueue": Queue(), "content": content, "msg": msg, "gpu_ids": gpu_ids,
-               "pic": self.pic, "type": AnalysisType.ONLINE.value}
+               "type": AnalysisType.ONLINE.value}
         # 创建在线识别进程并启动
         oirp = OnlineIntelligentRecognitionProcess(cfg)
         oirp.start()
             logger.warning("重复任务，请稍后再试！requestId:{}", msg.get("request_id"))
             return
         cfg = {"fbQueue": Queue(), "imageQueue": Queue(), "content": content, "msg": msg, "gpu_ids": gpu_ids,
-               "pic": self.pic, "type": AnalysisType.OFFLINE.value}
+               "type": AnalysisType.OFFLINE.value}
         # 创建在线识别进程并启动
         ofirp = OfflineIntelligentRecognitionProcess(cfg)
         ofirp.start()

test/ffmpeg11/ffmpeg11.py

                '-f', 'rawvideo',
                '-pix_fmt', 'bgr24',
                '-vcodec','rawvideo',
-               # '-s', "{}x{}".format(int(width), int(height)),
+               '-s', "{}x{}".format(int(width/2), int(height/2)),
                '-an',
                '-']
     p = sp.Popen(command, stdout=sp.PIPE)
     start1 = time.time()
     while True:
         start = time.time()
-        in_bytes = p.stdout.read(width * height * 3)
+        in_bytes = p.stdout.read(int(width * height * 3/4))
         if not in_bytes:
             print(in_bytes)
             ai_video_file.release()
             p.wait()
             break
         # 转成ndarray
-        in_frame = (np.frombuffer(in_bytes, np.uint8).reshape([height, width, 3]))
+        in_frame = (np.frombuffer(in_bytes, np.uint8).reshape([int(height/2), int(width/2), 3]))
+        print("拉流时间：", time.time() - start)
         # frame = cv2.resize(in_frame, (1280, 720))   # 改变图片尺寸
         # frame = cv2.cvtColor(in_frame, cv2.COLOR_RGB2BGR)  # 转成BGR
         # i += 1
-        print(round(time.time()-start, 5))
-
-        ai_video_file.write(in_frame)
-        if time.time() - start1 > 60:
-            ai_video_file.release()
-            p.stdout.close()
-            p.wait()
-            break
+        # print(round(time.time()-start, 5))
+        #
+        # ai_video_file.write(in_frame)
+        # if time.time() - start1 > 60:
+        #     ai_video_file.release()
+        #     p.stdout.close()
+        #     p.wait()
+        #     break
         # cv2.imshow('frame', frame)
         # time.sleep(1111)
     p.kill()

test/ffmpeg11/ffmpeg33.py

+import subprocess as sp
+import time
+import cv2
+import ffmpeg
+# 推流
+import numpy as np
+
+if __name__== "__main__":
+
+
+    # with open(str(cv2.__file__),"r") as f:
+    #     print (f.read())
+    # aa = {'loglevel': 'error'}
+    # process = (
+    #     ffmpeg
+    #         .input("http://cmgw-vpc.lechange.com:8888/LCO/8D0B355PAN8B3B3/0/0/20221019T130437/eabfe43d95971e0ae03de28dad4fd4ce.m3u8", **aa)
+    #         .output('pipe:', format='rawvideo', pix_fmt='bgr24', loglevel='error')# , bufsize='1000000k'
+    #         .overwrite_output()
+    #         .global_args('-an')
+    #         .run_async(pipe_stdout=True)
+    # )
+    # self.pull_p = sp.Popen(command, stdout=sp.PIPE, stderr=sp.PIPE)
+    cap = cv2.VideoCapture("http://cmgw-vpc.lechange.com:8888/LCO/8D0B355PAN8B3B3/0/0/20221019T130437/eabfe43d95971e0ae03de28dad4fd4ce.m3u8")
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
+    print(fps)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    print(width)
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    print(height)
+    fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
+    print(fourcc)
+    # print(cv2.getBuildInformation())
+    # cap.setExceptionMode(True)
+    # print(cap.getExceptionMode())
+    # cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
+    # cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
+    # cap.set(cv2.CAP_PROP_FPS, 25)
+    command = ['ffmpeg',
+               '-y', # 不经过确认，输出时直接覆盖同名文件。
+               '-f', 'rawvideo',
+               '-vcodec','rawvideo',
+               '-pix_fmt', 'bgr24',
+               # '-r', str(13),
+               '-s', "{}x{}".format(width, height),
+               # '-s', "{}x{}".format(1280, 720),
+               '-i', '-', # 指定输入文件
+               '-c:v', 'libx264', # 指定视频编码器
+               '-pix_fmt', 'yuv420p',
+               "-an",
+               # '-b:v', '3000k',
+               '-preset', 'ultrafast', # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
+               # superfast, veryfast, faster, fast, medium, slow, slower, veryslow。
+               '-f', 'flv',
+               "rtmp://live.push.t-aaron.com/live/THSAq"]
+
+    # # 管道配置
+    p = sp.Popen(command, stdin=sp.PIPE)
+    # while(cap.isOpened()):
+    while True:
+        start =time.time()
+        # in_bytes = process.stdout.read(1920 * 1080 * 3)
+        # result = (np.frombuffer(in_bytes, np.uint8).reshape([1080, 1920, 3]))
+        # time.sleep(0.04)
+        ret, frame = cap.read()
+        # print(cap.grab())
+        # print("aaaaaaaaaaaaaa", time.time()-start)
+        # start =time.time()
+        # a,b = cap.retrieve()
+        # print("bbbbbbbbbbbbbb", time.time()-start)
+        # if not ret:
+        #     print("Opening camera is failed")
+        #     break
+        # cv2.namedWindow('picture',0)
+        # cv2.resizeWindow("picture", 1980, 1080)
+        # cv2.imshow('picture', result)
+        # cv2.waitKey(1) & 0xFF == ord('q')
+        p.stdin.write(frame.tostring())
+

test/互信息.py → test/水印/互信息.py

 from PIL import Image
 from pixelmatch.contrib.PIL import pixelmatch
-img_a = Image.open("image/AI.jpg")
-img_b = Image.open("image/AI3.jpg")
+img_a = Image.open("../image/AI.jpg")
+img_b = Image.open("../image/AI3.jpg")
 img_diff = Image.new("RGBA", img_a.size)
 # note how there is no need to specify dimensions
 mismatch = pixelmatch(img_a, img_b, img_diff, includeAA=True)

test/视频添加文字水印3.py → test/水印/视频添加文字水印3.py

 
 
 if __name__ == '__main__':
-    img = Image.open("a.jpg")
+    img = Image.open("../a.jpg")
     fontcolor = 'yellow'
 
     water = Water()

util/Cv2Utils.py

 from exception.CustomerException import ServiceException
 from enums.ExceptionEnum import ExceptionType
 
-
-
 class Cv2Util():
 
     def __init__(self, pullUrl, pushUrl=None, orFilePath=None, aiFilePath=None, requestId=None):
         self.fps = None
         self.width = None
         self.height = None
+        self.wh = None
         self.all_frames = None
         self.bit_rate = None
         self.pull_p = None
     '''
         获取视频信息
     '''
+
     def get_video_info(self):
         try:
             if self.pullUrl is None:
                 self.width = int(width)
             if height:
                 self.height = int(height)
+            if width is not None and height is not None:
+                self.wh = int(width * height * 3 / 4)
             if nb_frames:
                 self.all_frames = int(nb_frames)
             if fps:
             # if duration:
             #    self.duration = float(video_stream['duration'])
             if bit_rate:
-                self.bit_rate = int(bit_rate)/1000
+                self.bit_rate = int(bit_rate) / 1000
             logger.info("视频信息, width:{}|height:{}|fps:{}|all_frames:{}|bit_rate:{}, requestId:{}", self.width,
                         self.height, self.fps, self.all_frames, self.bit_rate, self.requestId)
         except ServiceException as s:
         except Exception as e:
             logger.exception("获取视频信息异常：{}, requestId:{}", e, self.requestId)
 
+
+
     '''
         拉取视频
     '''
+
     def build_pull_p(self):
         try:
+            if self.width is None or self.height is None:
+                return
             if self.pull_p:
                 logger.info("重试, 关闭拉流管道, requestId:{}", self.requestId)
                 self.pull_p.stdout.close()
             #            # '-s', "{}x{}".format(int(width), int(height)),
             #            '-an',
             #            '-']
+            aa = {'loglevel': 'error'}
             process = (
                 ffmpeg
-                    .input(self.pullUrl)
-                    .output('pipe:', format='rawvideo', pix_fmt='bgr24')
+                    .input(self.pullUrl, **aa)
+                    .output('pipe:', format='rawvideo', pix_fmt='bgr24', loglevel='error',
+                            s="{}x{}".format(int(self.width / 2), int(self.height / 2)))
                     .overwrite_output()
                     .global_args('-an')
                     .run_async(pipe_stdout=True)
     def read(self):
         result = None
         try:
-            if self.pull_p is None:
-                logger.error("拉流管道为空, requestId:{}", self.requestId)
-                raise ServiceException(ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[0],
-                                       ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[1])
-            in_bytes = self.pull_p.stdout.read(self.width * self.height * 3)
+            # if self.pull_p is None:
+            #     logger.error("拉流管道为空, requestId:{}", self.requestId)
+            #     raise ServiceException(ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[0],
+            #                            ExceptionType.PULL_PIPELINE_INIT_EXCEPTION.value[1])
+            in_bytes = self.pull_p.stdout.read(self.wh)
             if in_bytes is not None and len(in_bytes) > 0:
-                result = (np.frombuffer(in_bytes, np.uint8).reshape([self.height, self.width, 3]))
+                result = (np.frombuffer(in_bytes, np.uint8).reshape([int(self.height / 2), int(self.width / 2), 3]))
         except ServiceException as s:
             logger.exception("读流异常: {}, requestId:{}", s, self.requestId)
         except Exception as e:
             logger.info("关闭AI视频写入流完成, requestId:{}", self.requestId)
 
     # 构建 cv2
-    def build_cv2(self):
-        try:
-            if self.cap is not None:
-                logger.info("重试, 关闭cap, requestId:{}", self.requestId)
-                self.cap.release()
-            if self.p is not None:
-                logger.info("重试, 关闭管道, requestId:{}", self.requestId)
-                self.p.stdin.close()
-                self.p.terminate()
-                self.p.wait()
-            if self.pullUrl is None:
-                logger.error("拉流地址不能为空, requestId:{}", self.requestId)
-                raise ServiceException(ExceptionType.PULL_STREAM_URL_EXCEPTION.value[0],
-                                       ExceptionType.PULL_STREAM_URL_EXCEPTION.value[1])
-            if self.pushUrl is None:
-                logger.error("推流地址不能为空, requestId:{}", self.requestId)
-                raise ServiceException(ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[0],
-                                       ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[1])
-            self.cap = cv2.VideoCapture(self.pullUrl)
-            if self.fps is None or self.fps == 0:
-                self.fps = int(self.cap.get(cv2.CAP_PROP_FPS))
-            if self.width is None or self.width == 0:
-                self.width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-            if self.height is None or self.height == 0:
-                self.height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-            command = ['/usr/bin/ffmpeg',
-                       # '-y',  # 不经过确认，输出时直接覆盖同名文件。
-                       '-f', 'rawvideo',
-                       '-vcodec', 'rawvideo',
-                       '-pix_fmt', 'bgr24',  # 显示可用的像素格式
-                       # '-s', "{}x{}".format(self.width * 2, self.height),
-                       '-s', "{}x{}".format(int(self.width), int(self.height/2)),
-                       # '-r', str(15),
-                       '-i', '-',  # 指定输入文件
-                       '-g', '25',
-                       '-b:v', '3000k',
-                       '-tune', 'zerolatency',  # 加速编码速度
-                       '-c:v', 'libx264',  # 指定视频编码器
-                       '-sc_threshold', '0',
-                       '-pix_fmt', 'yuv420p',
-                       '-an',
-                       '-preset', 'ultrafast',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
-                       # superfast, veryfast, faster, fast, medium, slow, slower, veryslow。
-                       '-f', 'flv',
-                       self.pushUrl]
-            # 管道配置
-            logger.info("fps:{}|height:{}|width:{}|requestId:{}", self.fps, self.height, self.width, self.requestId)
-            self.p = sp.Popen(command, stdin=sp.PIPE)
-        except ServiceException as s:
-            logger.exception("构建cv2异常: {}, requestId:{}", s, self.requestId)
-            raise s
-        except Exception as e:
-            logger.exception("初始化cv2异常：{}, requestId:{}", e, self.requestId)
-
+    # def build_cv2(self):
+    #     try:
+    #         if self.cap is not None:
+    #             logger.info("重试, 关闭cap, requestId:{}", self.requestId)
+    #             self.cap.release()
+    #         if self.p is not None:
+    #             logger.info("重试, 关闭管道, requestId:{}", self.requestId)
+    #             self.p.stdin.close()
+    #             self.p.terminate()
+    #             self.p.wait()
+    #         if self.pullUrl is None:
+    #             logger.error("拉流地址不能为空, requestId:{}", self.requestId)
+    #             raise ServiceException(ExceptionType.PULL_STREAM_URL_EXCEPTION.value[0],
+    #                                    ExceptionType.PULL_STREAM_URL_EXCEPTION.value[1])
+    #         if self.pushUrl is None:
+    #             logger.error("推流地址不能为空, requestId:{}", self.requestId)
+    #             raise ServiceException(ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[0],
+    #                                    ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[1])
+    #         self.cap = cv2.VideoCapture(self.pullUrl)
+    #         if self.fps is None or self.fps == 0:
+    #             self.fps = int(self.cap.get(cv2.CAP_PROP_FPS))
+    #         if self.width is None or self.width == 0:
+    #             self.width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    #         if self.height is None or self.height == 0:
+    #             self.height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    #         command = ['/usr/bin/ffmpeg',
+    #                    # '-y',  # 不经过确认，输出时直接覆盖同名文件。
+    #                    '-f', 'rawvideo',
+    #                    '-vcodec', 'rawvideo',
+    #                    '-pix_fmt', 'bgr24',  # 显示可用的像素格式
+    #                    # '-s', "{}x{}".format(self.width * 2, self.height),
+    #                    '-s', "{}x{}".format(int(self.width), int(self.height/2)),
+    #                    # '-r', str(15),
+    #                    '-i', '-',  # 指定输入文件
+    #                    '-g', '25',
+    #                    '-b:v', '3000k',
+    #                    '-tune', 'zerolatency',  # 加速编码速度
+    #                    '-c:v', 'libx264',  # 指定视频编码器
+    #                    '-sc_threshold', '0',
+    #                    '-pix_fmt', 'yuv420p',
+    #                    '-an',
+    #                    '-preset', 'ultrafast',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
+    #                    # superfast, veryfast, faster, fast, medium, slow, slower, veryslow。
+    #                    '-f', 'flv',
+    #                    self.pushUrl]
+    #         # 管道配置
+    #         logger.info("fps:{}|height:{}|width:{}|requestId:{}", self.fps, self.height, self.width, self.requestId)
+    #         self.p = sp.Popen(command, stdin=sp.PIPE)
+    #     except ServiceException as s:
+    #         logger.exception("构建cv2异常: {}, requestId:{}", s, self.requestId)
+    #         raise s
+    #     except Exception as e:
+    #         logger.exception("初始化cv2异常：{}, requestId:{}", e, self.requestId)
 
-        # 构建 cv2
+    # 构建 cv2
     def build_p(self):
         try:
             if self.p:
                 logger.info("重试, 关闭管道, requestId:{}", self.requestId)
-                self.p.stdin.close()
+                if self.p.stdin:
+                    self.p.stdin.close()
                 self.p.terminate()
                 self.p.wait()
                 # self.p.communicate()
                 raise ServiceException(ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[0],
                                        ExceptionType.PUSH_STREAM_URL_EXCEPTION.value[1])
             command = ['ffmpeg',
+                       # '-loglevel', 'debug',
                        '-y',  # 不经过确认，输出时直接覆盖同名文件。
                        '-f', 'rawvideo',
                        '-vcodec', 'rawvideo',
                        '-pix_fmt', 'bgr24',
                        # '-s', "{}x{}".format(self.width * 2, self.height),
-                       '-s', "{}x{}".format(int(self.width), int(self.height/2)),
+                       '-s', "{}x{}".format(int(self.width), int(self.height / 2)),
                        '-r', str(self.fps),
                        '-i', '-',  # 指定输入文件
                        '-g', str(self.fps),
                        # '-maxrate', '15000k',
-                       '-b:v', '6000k',
-                       # '-crf', '18',s
-                       '-bufsize', '6000k',
-                       '-tune', 'zerolatency', # 加速编码速度
+                       # '-profile:v', 'high',
+                       '-b:v', '4000k',
+                       # '-crf', '18',
+                       '-bufsize', '4000k',
                        '-c:v', 'libx264',  # 指定视频编码器
+                       '-tune', 'zerolatency',  # 加速编码速度
                        '-sc_threshold', '0',
                        '-pix_fmt', 'yuv420p',
                        "-an",
                        # '-flvflags', 'no_duration_filesize',
-                       '-preset', 'medium',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
+                       '-preset', 'veryfast',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
                        # superfast, veryfast, faster, fast, medium, slow, slower, veryslow。
                        '-f', 'flv',
                        self.pushUrl]
             #            ' -f flv ' + self.pushUrl
 
             # kwargs = {'format': 'rawvideo',
-            #           'vcodec': 'rawvideo',
+            #           # 'vcodec': 'rawvideo',
             #           'pix_fmt': 'bgr24',
             #           's': '{}x{}'.format(int(self.width), int(self.height/2))}
             # out = {
+            #     'r': str(self.fps),
             #     'g': str(self.fps),
-            #     'b:v': '8000k', # 恒定码率
-            #     'maxrate': '15000k',
+            #     'b:v': '5500k', # 恒定码率
+            #     # 'maxrate': '15000k',
             #     # 'crf': '18',
-            #     'bufsize': '3000k',
+            #     'bufsize': '5500k',
             #     'tune': 'zerolatency', # 加速编码速度
             #     'c:v': 'libx264',  # 指定视频编码器
             #     'sc_threshold': '0',
             #     'pix_fmt': 'yuv420p',
             #     # 'flvflags': 'no_duration_filesize',
-            #     'preset': 'ultrafast',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
+            #     'preset': 'medium',  # 指定输出的视频质量，会影响文件的生成速度，有以下几个可用的值 ultrafast,
             #     # superfast, veryfast, faster, fast, medium, slow, slower, veryslow。
             #     'format': 'flv'}
             # 管道配置
             #     ffmpeg
             #         .input('pipe:', **kwargs)
             #         .output(self.pushUrl, **out)
-            #         .global_args('-re', '-y', '-an')
+            #         .global_args('-y', '-an')
             #         .overwrite_output()
             #         .run_async(pipe_stdin=True)
             # )
             logger.info("fps:{}|height:{}|width:{}|requestId:{}", self.fps, self.height, self.width, self.requestId)
             self.p = sp.Popen(command, stdin=sp.PIPE, shell=False)
-
             # self.p = process2
         except ServiceException as s:
             logger.exception("构建p管道异常: {}, requestId:{}", s, self.requestId)
             current_retry_num = 0
             while True:
                 try:
-                    if self.p_push_retry_num > 500:
+                    if self.p_push_retry_num > 20:
                         logger.info("推流失败重试次数过多, 请检查相关配置信息, 当前重试次数: {}, requestId: {}",
                                     self.p_push_retry_num, self.requestId)
                         current_retry_num = 4
                         break
                     self.p_push_retry_num += 1
+                    time.sleep(10)
                     self.build_p()
                     self.p.stdin.write(frame.tostring())
                     logger.info("构建p管道重试成功, 当前重试次数: {}, requestId: {}", current_retry_num,
                         raise ServiceException(ExceptionType.SERVICE_INNER_EXCEPTION.value[0],
                                                ExceptionType.SERVICE_INNER_EXCEPTION.value[1])
 
-
     def build_write(self):
         try:
             if self.fps is None or self.width is None or self.height is None:
                                        ExceptionType.VIDEO_CONFIG_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,
-                                                     (self.width, self.height))
+                                                     (int(self.width / 2), int(self.height / 2)))
                 if self.or_video_file is None:
                     raise ServiceException(ExceptionType.OR_WRITE_OBJECT_EXCEPTION.value[0],
                                            ExceptionType.OR_WRITE_OBJECT_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.width), int(self.height/2)))
+                                                     (int(self.width), int(self.height / 2)))
                 if self.ai_video_file is None:
                     raise ServiceException(ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[0],
                                            ExceptionType.AI_WRITE_OBJECT_EXCEPTION.value[1])
             raise e
 
     def video_merge(self, frame1, frame2):
-        frameLeft = cv2.resize(frame1, (int(self.width/2), int(self.height/2)), interpolation=cv2.INTER_LINEAR)
-        frameRight = cv2.resize(frame2, (int(self.width/2), int(self.height/2)), interpolation=cv2.INTER_LINEAR)
+        frameLeft = cv2.resize(frame1, (int(self.width / 2), int(self.height / 2)), interpolation=cv2.INTER_LINEAR)
+        frameRight = cv2.resize(frame2, (int(self.width / 2), int(self.height / 2)), interpolation=cv2.INTER_LINEAR)
         frame_merge = np.hstack((frameLeft, frameRight))
         # frame_merge = np.hstack((frame1, frame2))
         return frame_merge

util/ModelUtils.py

         if self.label_arraylist is None:
             fontsize = int(width/1920*40)
             line_thickness = 1
-            if width > 1280:
-                line_thickness = int(round(width/1920*3))
-            waterLineWidth = int(round(width/1920*3) + 1)
-            numFontSize = float(format(width/1920*1.1, '.1f'))
-            self.digitFont = {'line_thickness': line_thickness, 'fontSize': numFontSize, 'waterLineColor':(0,255,255), 'waterLineWidth': waterLineWidth}
+            boxLine_thickness = 1
+            waterLineWidth = 1
+            if width >= 960:
+                line_thickness = int(round(width/1920*3) - 1)
+                boxLine_thickness = int(round(width/1920*3))
+                waterLineWidth = int(round(width/1920*3))
+            numFontSize = float(format(width/1920*1.1, '.1f')) # 文字大小
+            self.digitFont = {'line_thickness': line_thickness,
+                              'boxLine_thickness': boxLine_thickness,
+                              'fontSize': numFontSize,
+                              'waterLineColor': (0, 255, 255),
+                              'waterLineWidth': waterLineWidth}
             self.label_arraylist = get_label_arrays(self.names, self.rainbows, outfontsize=fontsize,
                                                     fontpath="../AIlib/conf/platech.ttf")
         return AI_process([frame], self.model, self.segmodel, self.names, self.label_arraylist,
         if self.label_arraylist is None:
             fontsize = int(width/1920*40)
             line_thickness = 1
-            if width > 1280:
-                line_thickness = int(round(width/1920*3))
-            waterLineWidth = int(round(width/1920*3) + 1)
-            numFontSize = float(format(width/1920*1.1, '.1f'))
-            self.digitFont = {'line_thickness': line_thickness, 'fontSize': numFontSize, 'waterLineColor':(0,255,255), 'waterLineWidth': waterLineWidth}  ###数字显示的线宽度，大小; 如果都是None，则采用默认大小
+            boxLine_thickness = 1
+            waterLineWidth = 1
+            if width >= 960:
+                line_thickness = int(round(width/1920*3) - 1)
+                boxLine_thickness = int(round(width/1920*3))
+                waterLineWidth = int(round(width/1920*3))
+            numFontSize = float(format(width/1920*1.1, '.1f')) # 文字大小
+            self.digitFont = {'line_thickness': line_thickness,
+                              'boxLine_thickness': boxLine_thickness,
+                              'fontSize': numFontSize,
+                              'waterLineColor': (0, 255, 255),
+                              'waterLineWidth': waterLineWidth}
             self.label_arraylist = get_label_arrays(self.names, self.rainbows, outfontsize=fontsize, fontpath="../AIlib/conf/platech.ttf")
         return AI_process_forest([frame], self.model, self.segmodel, self.names, self.label_arraylist,
                                  self.rainbows, self.half, self.device, self.conf_thres, self.iou_thres,
         if self.label_arraylist is None:
             fontsize = int(width/1920*40)
             line_thickness = 1
-            if width > 1280:
-                line_thickness = int(round(width/1920*3))
-            waterLineWidth = int(round(width/1920*3) + 1)
+            boxLine_thickness = 1
+            waterLineWidth = 1
+            if width >= 960:
+                line_thickness = int(round(width/1920*3) - 1)
+                boxLine_thickness = int(round(width/1920*2))
+                waterLineWidth = int(round(width/1920*3))
             numFontSize = float(format(width/1920*1.1, '.1f'))
-            self.digitFont = {'line_thickness': line_thickness, 'fontSize': numFontSize, 'waterLineColor':(0,255,255), 'waterLineWidth': waterLineWidth}  ###数字显示的线宽度，大小; 如果都是None，则采用默认大小
+
+            self.digitFont = {'line_thickness': line_thickness,
+                              'boxLine_thickness': boxLine_thickness,
+                              'fontSize': numFontSize,
+                              'waterLineColor': (0, 255, 255),
+                              'waterLineWidth': waterLineWidth}
             self.label_arraylist = get_label_arrays(self.names, self.rainbows, outfontsize=fontsize, fontpath="../AIlib/conf/platech.ttf")
         return AI_process_forest([frame], self.model, self.segmodel, self.names, self.label_arraylist,
                                  self.rainbows, self.half, self.device, self.conf_thres, self.iou_thres,