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- # -*- coding: utf-8 -*-
- from concurrent.futures import ThreadPoolExecutor, wait, ALL_COMPLETED
- 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 OnPushStreamThread2(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:
- with ThreadPoolExecutor(max_workers=5) as tt:
- p_push_status, or_write_status, ai_write_status = [0, 0], [0, 0], [0, 0]
- while True:
- push_r = push_queue.get()
- if push_r is not None:
- # [(1, 原视频帧, 分析视频帧)]
- # [(code, retResults[2])]
- # [(2, 操作指令)]
- if push_r[0] == 1: # 视频帧操作
- frame_list, frame_index_list, all_frames = push_r[1]
- allowedList, rainbows, label_arrays, font_config = push_r[2]
- for i, frame in enumerate(frame_list):
- copy_frame = frame.copy()
- det_xywh = {}
- # 每帧可能存在多模型，多模型问题处理
- thread_p = []
- for det in push_r[3]:
- code, retResults = det
- det_xywh[code] = {}
- # 如果识别到了检测目标
- if len(retResults[i]) > 0:
- for qs in retResults[i]:
- detect_targets_code = int(qs[6])
- if detect_targets_code not in allowedList:
- logger.warning("当前检测目标不在检测目标中: {}, requestId: {}", detect_targets_code, request_id)
- continue
- score = qs[5]
- label_array = label_arrays[detect_targets_code]
- color = rainbows[detect_targets_code]
- if not isinstance(qs[1], (list, tuple, np.ndarray)):
- xc, yc, x2, y2 = int(qs[1]), int(qs[2]), int(qs[3]), int(qs[4])
- box = [(xc, yc), (x2, yc), (x2, y2), (xc, y2)]
- else:
- box = qs[1]
- # box, img, label_array, score=0.5, color=None, config=None
- dp = tt.submit(draw_painting_joint, box, copy_frame, label_array, score,
- color, font_config)
- thread_p.append(dp)
- cd = det_xywh[code].get(detect_targets_code)
- if cd is None:
- det_xywh[code][detect_targets_code] = [
- [detect_targets_code, box, score, label_array, color]]
- else:
- det_xywh[code][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)
- if len(thread_p) > 0:
- completed_results = wait(thread_p, timeout=60, return_when=ALL_COMPLETED)
- completed_futures = completed_results.done
- for r in completed_futures:
- if r.exception():
- raise r.exception()
- 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, frame_index_list[i], all_frames,
- font_config)))
- 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_r[0] == 2:
- if 'stop' == push_r[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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