Fileupload
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jiangchaoqing
parent
8e49836d6e
commit
d61146f244
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@ -21,8 +21,7 @@ from util.QueUtil import put_queue, get_no_block_queue, clear_queue
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import io
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from util.LocationUtils import locate_byMqtt
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#
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from common.YmlConstant import service_yml_path
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class FileUpload(Thread):
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__slots__ = ('_fb_queue', '_context', '_image_queue', '_analyse_type', '_msg', '_mqtt_list')
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@ -35,8 +34,18 @@ class FileUpload(Thread):
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# self._algStatus = True # 默认关闭
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self._algSwitch = self._context['service']['algSwitch']
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self.is_use_llm = True
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self.cnt = 0
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self.server_ip = self._context['llm']['server_ip']
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self.server_port = self._context['llm']['server_port']
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self.is_use_llm = self._context['llm']['is_use_llm']
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self.cnt = self._context['llm']['cnt']
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#0521:
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default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true"
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@ -64,9 +73,14 @@ class ImageFileUpload(FileUpload):
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answers.append(line)
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return answers
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def get_llm_res(self, image, prompt):
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SERVER_IP = "192.168.10.11"
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API_URL = f"http://{SERVER_IP}:8000/generate"
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def get_llm_res(self, image, prompt,SERVER_IP,API_PORT):
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# SERVER_IP = "192.168.10.11"
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# API_URL = f"http://{SERVER_IP}:8000/generate"
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SERVER_IP = SERVER_IP
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API_URL = f"http://{SERVER_IP}:{API_PORT}/generate"
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# _, buffer = cv2.imencode('.jpg', image)
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# is_success, buffer = cv2.imencode('.png', image)
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@ -99,6 +113,11 @@ class ImageFileUpload(FileUpload):
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logger.info(f"无法解析服务器返回的响应: {response.text}")
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new_result = self.extract_answers(result)
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print("###line116",new_result)
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new_result = new_result[1] # 获取第二点内容
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# flag = "不" in result or ("没" in result and "没错" not in result) or "否" in result or "未" in result or "无" in result
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flag = "不存在" in new_result or ("没" in new_result and "没错" not in new_result) or (
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@ -202,41 +221,60 @@ class ImageFileUpload(FileUpload):
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model_info_list = image_result["model_info"]
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llm_flag_list = []
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msg_list = []
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for model_info in model_info_list:
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aFrame = model_info["aFrame"]
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# aFrame_rgb = cv2.cvtColor(aFrame, cv2.COLOR_BGR2RGB)
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fire_flag = model_info.get("modelCode")
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print("###line229",fire_flag)
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if fire_flag == "008":
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aFrame = model_info["aFrame"]
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# aFrame_rgb = cv2.cvtColor(aFrame, cv2.COLOR_BGR2RGB)
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tar_cls = model_info["detectTargetCode"]
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logger.info("目标类别：{}", tar_cls)
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tar_cls = model_info["detectTargetCode"]
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logger.info("目标类别：{}", tar_cls)
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# is_use_llm = True
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if tar_cls == '0':
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# tar = "明火"
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tar = "2. 判断图中是否有明火。3. 如果有，识别火势的大小，比如：[无情况/小/中/大]"
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elif tar_cls == '1':
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# tar = "某种物质燃烧产生的烟雾"
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tar = "2. 判断图中是否有烟雾。3. 如果有，识别烟雾的颜色，比如：[无烟雾/白/灰白/灰黑]"
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else:
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self.is_use_llm = False
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llm_flag = True
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if self.is_use_llm:
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# prompt = f"我看到图中有{tar}，请你判断是否正确。简要回答。"
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prompt = f"分点进行输出：1. 简短描述图像中的场景。{tar}"
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logger.info("检测到目标，大模型提示词：{}", prompt)
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llm_flag, llm_res = self.get_llm_res(aFrame, prompt)
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llm_flag_list.append(llm_flag)
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logger.info("检测到目标，大模型识别图中是否存在目标：{}, 大模型输出：{}", llm_flag, llm_res)
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if llm_flag:
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logger.info("经大模型筛查，小模型识别正确!!!")
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# cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_1.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80])
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# self.cnt = self.cnt + 1
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# 0715 ： 这块也不对，因为需要具体到目标才可以，否则只看0 1 ，是无法做到判断正确的火情处理，还有大量其他的部分
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# is_use_llm = True
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if tar_cls == '0':
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# tar = "明火"
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tar = "2. 判断图中是否有明火。3. 如果有，识别火势的大小，比如：[无情况/小/中/大]"
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elif tar_cls == '1':
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# tar = "某种物质燃烧产生的烟雾"
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tar = "2. 判断图中是否有烟雾。3. 如果有，识别烟雾的颜色，比如：[无烟雾/白/灰白/灰黑]"
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else:
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logger.info("经大模型筛查，小模型识别错误!!!")
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# cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_0.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80])
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# self.cnt = self.cnt + 1
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self.is_use_llm = False
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llm_flag = True
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if self.is_use_llm:
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# prompt = f"我看到图中有{tar}，请你判断是否正确。简要回答。"
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prompt = f"分点进行输出：1. 简短描述图像中的场景。{tar}"
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logger.info("检测到目标，大模型提示词：{}", prompt)
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# llm_flag, llm_res = self.get_llm_res(aFrame, prompt)
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llm_flag, llm_res = self.get_llm_res(aFrame, prompt,self.server_ip,self.server_port)
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llm_flag_list.append(llm_flag)
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logger.info("检测到目标，大模型识别图中是否存在目标：{}, 大模型输出：{}", llm_flag, llm_res)
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if llm_flag:
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logger.info("经大模型筛查，小模型识别正确!!!")
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# cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_1.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80])
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# self.cnt = self.cnt + 1
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else:
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logger.info("经大模型筛查，小模型识别错误!!!")
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# cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_0.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80])
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# self.cnt = self.cnt + 1
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else:
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llm_flag_list.append(llm_flag)
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ai_image = cv2.imencode(".jpg", aFrame)[1]
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ai_image_name = build_image_name(image_result["current_frame"],
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@ -271,6 +309,7 @@ class ImageFileUpload(FileUpload):
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remote_image_list.append( tk.result() )
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for ii, model_info in enumerate(model_info_list):
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if llm_flag_list[ii]:
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msg_list.append( message_feedback(request_id,
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AnalysisStatus.RUNNING.value,
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@ -282,6 +321,7 @@ class ImageFileUpload(FileUpload):
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longitude=model_info['gps'][0],
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latitude=model_info['gps'][1],
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) )
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if (not self._algSwitch) or ( self._algStatus and self._algSwitch):
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for msg in msg_list:
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