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- # -*- coding: utf-8 -*-
- from concurrent.futures import ThreadPoolExecutor
- from threading import Thread
- from time import sleep, time
- from traceback import format_exc
-
- from loguru import logger
- import cv2
-
- from entity.FeedBack import message_feedback
- from enums.ExceptionEnum import ExceptionType
- from exception.CustomerException import ServiceException
- from util.AliyunSdk import AliyunOssSdk
- from util import TimeUtils
- from enums.AnalysisStatusEnum import AnalysisStatus
- from util.PlotsUtils import draw_painting_joint
- from util.QueUtil import put_queue, get_no_block_queue, clear_queue
-
-
- class FileUpload(Thread):
- __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 = args
-
-
- class ImageFileUpload(FileUpload):
- __slots__ = ()
-
- @staticmethod
- def handle_image(frame_msg, frame_step):
- # (high_score_image["code"], all_frames, draw_config["font_config"])
- # high_score_image["code"][code][cls] = (frame, frame_index_list[i], cls_list)
- det_xywh, frame, current_frame, all_frames, font_config = frame_msg
- '''
- det_xywh:{
- 'code':{
- 1: [[detect_targets_code, box, score, label_array, color]]
- }
- }
- 模型编号：modeCode
- 检测目标：detectTargetCode
- '''
- model_info = []
- # 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:
- draw_painting_joint(target[1], aFrame, target[3], target[2], target[4], font_config, target[5])
- model_info.append({"modelCode": str(code), "detectTargetCode": str(cls), "aFrame": aFrame})
- if len(model_info) > 0:
- image_result = {
- "or_frame": frame,
- "model_info": model_info,
- "current_frame": current_frame,
- "last_frame": current_frame + frame_step
- }
- return image_result
- return None
-
- def run(self):
- msg, context = self._msg, self._context
- service = context["service"]
- base_dir, env, request_id = context["base_dir"], context["env"], msg["request_id"]
- logger.info("启动图片上传线程, requestId: {}", request_id)
- image_queue, fb_queue, analyse_type = self._image_queue, self._fb_queue, self._analyse_type
- service_timeout = int(service["timeout"])
- frame_step = int(service["filter"]["frame_step"]) + 120
- try:
- with ThreadPoolExecutor(max_workers=2) as t:
- # 初始化oss客户端
- aliyunOssSdk = AliyunOssSdk(base_dir, env, request_id)
- start_time = time()
- while True:
- try:
- if time() - start_time > service_timeout:
- logger.error("图片上线线程运行超时, requestId: {}", request_id)
- raise ServiceException(ExceptionType.TASK_EXCUTE_TIMEOUT.value[0],
- ExceptionType.TASK_EXCUTE_TIMEOUT.value[1])
- # 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:
- if 'stop' == image_msg[1]:
- logger.info("开始停止图片上传线程, requestId:{}", request_id)
- break
- if image_msg[0] == 1:
- image_result = self.handle_image(image_msg[1], frame_step)
- if image_result is not None:
- task = []
- or_image = cv2.imencode(".jpg", image_result["or_frame"])[1]
- or_image_name = build_image_name(image_result["current_frame"],
- image_result["last_frame"],
- analyse_type,
- "OR", "0", "0", request_id)
- or_future = t.submit(aliyunOssSdk.put_object, or_image_name, or_image.tobytes())
- task.append(or_future)
- model_info_list = image_result["model_info"]
- msg_list = []
- for model_info in model_info_list:
- ai_image = cv2.imencode(".jpg", model_info["aFrame"])[1]
- ai_image_name = build_image_name(image_result["current_frame"],
- image_result["last_frame"],
- analyse_type,
- "AI",
- model_info["modelCode"],
- model_info["detectTargetCode"],
- request_id)
- ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
- ai_image.tobytes())
- task.append(ai_future)
- msg_list.append(message_feedback(request_id,
- AnalysisStatus.RUNNING.value,
- analyse_type, "", "", "",
- or_image_name,
- ai_image_name,
- model_info['modelCode'],
- model_info['detectTargetCode']))
- for tk in task:
- tk.result()
- for msg in msg_list:
- put_queue(fb_queue, msg, timeout=2, is_ex=False)
- del task, msg_list
- else:
- sleep(1)
- del image_msg
- except Exception:
- logger.error("图片上传异常：{}, requestId:{}", format_exc(), request_id)
- finally:
- logger.info("停止图片上传线程0, requestId:{}", request_id)
- clear_queue(image_queue)
- logger.info("停止图片上传线程1, requestId:{}", request_id)
-
-
- def build_image_name(*args):
- """
- {requestId}/{time_now}_frame-{current_frame}-{last_frame}_type_{random_num}-{mode_type}" \
- "-{modeCode}-{target}_{image_type}.jpg
- """
- current_frame, last_frame, mode_type, image_type, modeCode, target, request_id = args
- random_num = TimeUtils.now_date_to_str(TimeUtils.YMDHMSF)
- time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
- return "%s/%s_frame-%s-%s_type_%s-%s-%s-%s_%s.jpg" % (request_id, time_now, current_frame, last_frame,
- random_num, mode_type, modeCode, target, image_type)
-
-
- class ImageTypeImageFileUpload(Thread):
- __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 = args
-
- @staticmethod
- def handle_image(det_xywh, copy_frame, font_config):
- """
- det_xywh:{
- 'code':{
- 1: [[detect_targets_code, box, score, label_array, color]]
- }
- }
- 模型编号：modeCode
- 检测目标：detectTargetCode
- """
- model_info = []
- # 更加模型编码解析数据
- for code, det_info in det_xywh.items():
- if det_info is not None and len(det_info) > 0:
- for cls, target_list in det_info.items():
- if target_list is not None and len(target_list) > 0:
- aiFrame = copy_frame.copy()
- for target in target_list:
- draw_painting_joint(target[1], aiFrame, target[3], target[2], target[4], font_config)
- model_info.append({
- "modelCode": str(code),
- "detectTargetCode": str(cls),
- "frame": aiFrame
- })
- if len(model_info) > 0:
- image_result = {
- "or_frame": copy_frame,
- "model_info": model_info,
- "current_frame": 0,
- "last_frame": 0
- }
- return image_result
- return None
-
- def run(self):
- context, msg = self._context, self._msg
- base_dir, env, request_id = context["base_dir"], context["env"], msg["request_id"]
- logger.info("启动图片识别图片上传线程, requestId: {}", request_id)
- image_queue, fb_queue, analyse_type = self._image_queue, self._fb_queue, self._analyse_type
- service_timeout = int(context["service"]["timeout"])
- with ThreadPoolExecutor(max_workers=2) as t:
- try:
- # 初始化oss客户端
- aliyunOssSdk = AliyunOssSdk(base_dir, env, request_id)
- start_time = time()
- while True:
- try:
- if time() - start_time > service_timeout:
- logger.error("拉流进程运行超时, requestId: {}", request_id)
- break
- # 获取队列中的消息
- image_msg = image_queue.get()
- if image_msg is not None:
- if image_msg[0] == 2:
- if 'stop' == image_msg[1]:
- logger.info("开始停止图片上传线程, requestId:{}", request_id)
- break
- if image_msg[0] == 1:
- task, msg_list = [], []
- det_xywh, image_url, copy_frame, font_config, result = image_msg[1]
- if det_xywh is None:
- ai_image_name = build_image_name(0, 0, analyse_type, "AI", result.get("modelCode"),
- result.get("type"), request_id)
- ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name, copy_frame)
- task.append(ai_future)
- msg_list.append(message_feedback(request_id,
- AnalysisStatus.RUNNING.value,
- analyse_type, "", "", "",
- image_url,
- ai_image_name,
- result.get("modelCode"),
- result.get("type"),
- analyse_results=result))
- else:
- image_result = self.handle_image(det_xywh, copy_frame, font_config)
- if image_result:
- # 图片帧数编码
- if image_url is None:
- or_result, or_image = cv2.imencode(".jpg", image_result.get("or_frame"))
- image_url = build_image_name(image_result.get("current_frame"),
- image_result.get("last_frame"),
- analyse_type,
- "OR", "0", "O", request_id)
- or_future = t.submit(aliyunOssSdk.put_object, image_url,
- or_image.tobytes())
- task.append(or_future)
- model_info_list = image_result.get("model_info")
- for model_info in model_info_list:
- ai_result, ai_image = cv2.imencode(".jpg", model_info.get("frame"))
- ai_image_name = build_image_name(image_result.get("current_frame"),
- image_result.get("last_frame"),
- analyse_type,
- "AI",
- model_info.get("modelCode"),
- model_info.get("detectTargetCode"),
- request_id)
- ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
- ai_image.tobytes())
- task.append(ai_future)
- msg_list.append(message_feedback(request_id,
- AnalysisStatus.RUNNING.value,
- analyse_type, "", "", "",
- image_url,
- ai_image_name,
- model_info.get('modelCode'),
- model_info.get('detectTargetCode'),
- analyse_results=result))
- for thread_result in task:
- thread_result.result()
- for msg in msg_list:
- put_queue(fb_queue, msg, timeout=2, is_ex=False)
- else:
- sleep(1)
- except Exception as e:
- logger.error("图片上传异常：{}, requestId:{}", format_exc(), request_id)
- finally:
- clear_queue(image_queue)
- logger.info("停止图片识别图片上传线程, requestId:{}", request_id)
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