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- # -*- coding: utf-8 -*-
- from concurrent.futures import ThreadPoolExecutor
- from os.path import join
- from threading import Thread
- from traceback import format_exc
-
- import cv2
- import numpy as np
- from loguru import logger
- from util.Cv2Utils import write_or_video, write_ai_video, push_video_stream, close_all_p, video_conjuncing
- from util.ImageUtils import url2Array, add_water_pic
- from util.PlotsUtils import draw_painting_joint
- from util.QueUtil import put_queue
-
-
- class OnPushStreamThread(Thread):
- __slots__ = ('_msg', '_push_queue', '_context', 'ex', '_logo', '_image_queue')
-
- def __init__(self, *args):
- super().__init__()
- # 传参
- self._msg, self._push_queue, self._image_queue, self._context = args
- # 自带参数
- self.ex = None
- self._logo = None
- if self._context["video"]["video_add_water"]:
- self._logo = self._msg.get("logo_url")
- if self._logo:
- self._logo = url2Array(self._logo, enable_ex=False)
- if not self._logo:
- self._logo = cv2.imread(join(self._context['base_dir'], "image/logo.png"), -1)
-
- def run(self):
- request_id, push_queue, image_queue = self._msg.get("request_id"), self._push_queue, self._image_queue
- orFilePath, aiFilePath, logo = self._context.get("orFilePath"), self._context.get("aiFilePath"), self._logo
- or_video_file, ai_video_file, push_p = None, None, None
- push_url = self._msg.get("push_url")
- try:
- logger.info("开始启动推流线程！requestId:{}", request_id)
- with ThreadPoolExecutor(max_workers=2) as t:
- p_push_status, or_write_status, ai_write_status = [0, 0], [0, 0], [0, 0]
- while True:
- push_parm = push_queue.get()
- if push_parm is not None:
- # [(1, 原视频帧, 分析视频帧)]
- # # [视频帧、当前帧数、 总帧数、 [(问题数组、code、allowedList、label_arraylist、rainbows)]]
- # res = (1, (pull_frame[1], pull_frame[2], pull_frame[3], []))
- # [(2, 操作指令)]
- if push_parm[0] == 1: # 视频帧操作
- frame, current_frame, all_frames, ques_list = push_parm[1]
- copy_frame = frame.copy()
- det_xywh = {}
- if len(ques_list) > 0:
- for qs in ques_list:
- det_xywh[qs[1]] = {}
- detect_targets_code = int(qs[0][0])
- score = qs[0][-1]
- label_array = qs[3][detect_targets_code]
- color = qs[4][detect_targets_code]
- if not isinstance(qs[0][1], (list, tuple, np.ndarray)):
- xc, yc, x2, y2 = int(qs[0][1]), int(qs[0][2]), int(qs[0][3]), int(qs[0][4])
- box = [(xc, yc), (x2, yc), (x2, y2), (xc, y2)]
- else:
- box = qs[0][1]
- draw_painting_joint(box, copy_frame, label_array, score, color, "leftTop")
- cd = det_xywh[qs[1]].get(detect_targets_code)
- if cd is None:
- det_xywh[qs[1]][detect_targets_code] = [
- [detect_targets_code, box, score, label_array, color]]
- else:
- det_xywh[qs[1]][detect_targets_code].append(
- [detect_targets_code, box, score, label_array, color])
- if logo:
- frame = add_water_pic(frame, logo, request_id)
- copy_frame = add_water_pic(copy_frame, logo, request_id)
- frame_merge = video_conjuncing(frame, copy_frame)
- # 写原视频到本地
- write_or_video_result = t.submit(write_or_video, frame, orFilePath, or_video_file,
- or_write_status, request_id)
- # 写识别视频到本地
- write_ai_video_result = t.submit(write_ai_video, frame_merge, aiFilePath, ai_video_file,
- ai_write_status, request_id)
- if len(det_xywh) > 0:
- put_queue(image_queue, (1, (det_xywh, frame, current_frame, all_frames)))
- push_p = push_video_stream(frame_merge, push_p, push_url, p_push_status, request_id)
- ai_video_file = write_ai_video_result.result()
- or_video_file = write_or_video_result.result()
- if push_parm[0] == 2:
- if 'stop' == push_parm[1]:
- logger.info("停止推流线程, requestId: {}", request_id)
- close_all_p(push_p, or_video_file, ai_video_file, request_id)
- or_video_file, ai_video_file, push_p = None, None, None
- break
- except Exception as e:
- logger.error("推流线程异常:{}, requestId:{}", format_exc(), request_id)
- self.ex = e
- finally:
- close_all_p(push_p, or_video_file, ai_video_file, request_id)
- logger.info("推流线程停止完成！requestId:{}", request_id)
-
-
- class OffPushStreamThread(Thread):
- __slots__ = ('_msg', '_push_queue', '_context', 'ex', '_logo', '_image_queue')
-
- def __init__(self, *args):
- super().__init__()
- # 传参
- self._msg, self._push_queue, self._image_queue, self._context = args
- # 自带参数
- self.ex = None
- self._logo = None
- if self._context["video"]["video_add_water"]:
- self._logo = self._msg.get("logo_url")
- if self._logo:
- self._logo = url2Array(self._logo, enable_ex=False)
- if not self._logo:
- self._logo = cv2.imread(join(self._context['base_dir'], "image/logo.png"), -1)
-
- def run(self):
- request_id, push_queue, image_queue = self._msg.get("request_id"), self._push_queue, self._image_queue
- aiFilePath, logo = self._context.get("aiFilePath"), self._logo
- ai_video_file, push_p = None, None
- push_url = self._msg.get("push_url")
- try:
- logger.info("开始启动推流线程！requestId:{}", request_id)
- with ThreadPoolExecutor(max_workers=1) as t:
- p_push_status, or_write_status, ai_write_status = [0, 0], [0, 0], [0, 0]
- while True:
- push_parm = push_queue.get()
- if push_parm is not None:
- # [(1, 原视频帧, 分析视频帧)]
- # # [视频帧、当前帧数、 总帧数、 [(问题数组、code、allowedList、label_arraylist、rainbows)]]
- # res = (1, (pull_frame[1], pull_frame[2], pull_frame[3], []))
- # [(2, 操作指令)]
- if push_parm[0] == 1: # 视频帧操作
- frame, current_frame, all_frames, ques_list = push_parm[1]
- copy_frame = frame.copy()
- det_xywh = {}
- if len(ques_list) > 0:
- for qs in ques_list:
- det_xywh[qs[1]] = {}
- detect_targets_code = int(qs[0][0])
- score = qs[0][-1]
- label_array = qs[3][detect_targets_code]
- color = qs[4][detect_targets_code]
- if not isinstance(qs[0][1], (list, tuple, np.ndarray)):
- xc, yc, x2, y2 = int(qs[0][1]), int(qs[0][2]), int(qs[0][3]), int(qs[0][4])
- box = [(xc, yc), (x2, yc), (x2, y2), (xc, y2)]
- else:
- box = qs[0][1]
- draw_painting_joint(box, copy_frame, label_array, score, color, "leftTop")
- cd = det_xywh[qs[1]].get(detect_targets_code)
- if cd is None:
- det_xywh[qs[1]][detect_targets_code] = [
- [detect_targets_code, box, score, label_array, color]]
- else:
- det_xywh[qs[1]][detect_targets_code].append(
- [detect_targets_code, box, score, label_array, color])
- if logo:
- frame = add_water_pic(frame, logo, request_id)
- copy_frame = add_water_pic(copy_frame, logo, request_id)
- frame_merge = video_conjuncing(frame, copy_frame)
- # 写识别视频到本地
- write_ai_video_result = t.submit(write_ai_video, frame_merge, aiFilePath, ai_video_file,
- ai_write_status, request_id)
- if len(det_xywh) > 0:
- put_queue(image_queue, (1, (det_xywh, frame, current_frame, all_frames)))
- push_p = push_video_stream(frame_merge, push_p, push_url, p_push_status, request_id)
- ai_video_file = write_ai_video_result.result()
- if push_parm[0] == 2:
- if 'stop' == push_parm[1]:
- logger.info("停止推流线程, requestId: {}", request_id)
- close_all_p(push_p, None, ai_video_file, request_id)
- ai_video_file, push_p = None, None
- break
- except Exception as e:
- logger.error("推流线程异常:{}, requestId:{}", format_exc(), request_id)
- self.ex = e
- finally:
- close_all_p(push_p, None, ai_video_file, request_id)
- logger.info("推流线程停止完成！requestId:{}", request_id)
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