From d61146f244819d204dd8d9d484beaa642d60579b Mon Sep 17 00:00:00 2001 From: jiangchaoqing Date: Mon, 11 Aug 2025 09:46:44 +0800 Subject: [PATCH] Fileupload --- concurrency/FileUploadThread.py | 112 ++++++++++++++++++++++---------- 1 file changed, 76 insertions(+), 36 deletions(-) diff --git a/concurrency/FileUploadThread.py b/concurrency/FileUploadThread.py index 8ee9a61..2be418a 100644 --- a/concurrency/FileUploadThread.py +++ b/concurrency/FileUploadThread.py @@ -21,8 +21,7 @@ from util.QueUtil import put_queue, get_no_block_queue, clear_queue import io from util.LocationUtils import locate_byMqtt -# -from common.YmlConstant import service_yml_path + class FileUpload(Thread): __slots__ = ('_fb_queue', '_context', '_image_queue', '_analyse_type', '_msg', '_mqtt_list') @@ -35,8 +34,18 @@ class FileUpload(Thread): # self._algStatus = True # 默认关闭 self._algSwitch = self._context['service']['algSwitch'] - self.is_use_llm = True - self.cnt = 0 + + + + + self.server_ip = self._context['llm']['server_ip'] + self.server_port = self._context['llm']['server_port'] + self.is_use_llm = self._context['llm']['is_use_llm'] + self.cnt = self._context['llm']['cnt'] + + + + #0521: default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true" @@ -64,9 +73,14 @@ class ImageFileUpload(FileUpload): answers.append(line) return answers - def get_llm_res(self, image, prompt): - SERVER_IP = "192.168.10.11" - API_URL = f"http://{SERVER_IP}:8000/generate" + def get_llm_res(self, image, prompt,SERVER_IP,API_PORT): + + # SERVER_IP = "192.168.10.11" + # API_URL = f"http://{SERVER_IP}:8000/generate" + + SERVER_IP = SERVER_IP + + API_URL = f"http://{SERVER_IP}:{API_PORT}/generate" # _, buffer = cv2.imencode('.jpg', image) # is_success, buffer = cv2.imencode('.png', image) @@ -99,6 +113,11 @@ class ImageFileUpload(FileUpload): logger.info(f"无法解析服务器返回的响应: {response.text}") new_result = self.extract_answers(result) + print("###line116",new_result) + + + + new_result = new_result[1] # 获取第二点内容 # 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 flag = "不存在" in new_result or ("没" in new_result and "没错" not in new_result) or ( @@ -202,41 +221,60 @@ class ImageFileUpload(FileUpload): model_info_list = image_result["model_info"] llm_flag_list = [] msg_list = [] + + for model_info in model_info_list: - aFrame = model_info["aFrame"] - # aFrame_rgb = cv2.cvtColor(aFrame, cv2.COLOR_BGR2RGB) + + fire_flag = model_info.get("modelCode") + print("###line229",fire_flag) + + if fire_flag == "008": + + aFrame = model_info["aFrame"] + # aFrame_rgb = cv2.cvtColor(aFrame, cv2.COLOR_BGR2RGB) - tar_cls = model_info["detectTargetCode"] - logger.info("目标类别：{}", tar_cls) + tar_cls = model_info["detectTargetCode"] + logger.info("目标类别：{}", tar_cls) - # is_use_llm = True - if tar_cls == '0': - # tar = "明火" - 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]" - elif tar_cls == '1': - # tar = "某种物质燃烧产生的烟雾" - 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]" - else: - self.is_use_llm = False - llm_flag = True - if self.is_use_llm: - # prompt = f"我看到图中有{tar}，请你判断是否正确。简要回答。" - prompt = f"分点进行输出：1. 简短描述图像中的场景。{tar}" - logger.info("检测到目标，大模型提示词：{}", prompt) - llm_flag, llm_res = self.get_llm_res(aFrame, prompt) - llm_flag_list.append(llm_flag) - 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) - - if llm_flag: - logger.info("经大模型筛查，小模型识别正确!!!") - # cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_1.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80]) - # self.cnt = self.cnt + 1 + # 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 + + # is_use_llm = True + if tar_cls == '0': + # tar = "明火" + 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]" + elif tar_cls == '1': + # tar = "某种物质燃烧产生的烟雾" + 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]" else: - logger.info("经大模型筛查，小模型识别错误!!!") - # cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_0.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80]) - # self.cnt = self.cnt + 1 + self.is_use_llm = False + + llm_flag = True + if self.is_use_llm: + # prompt = f"我看到图中有{tar}，请你判断是否正确。简要回答。" + prompt = f"分点进行输出：1. 简短描述图像中的场景。{tar}" + logger.info("检测到目标，大模型提示词：{}", prompt) + + + # llm_flag, llm_res = self.get_llm_res(aFrame, prompt) + + + llm_flag, llm_res = self.get_llm_res(aFrame, prompt,self.server_ip,self.server_port) + + llm_flag_list.append(llm_flag) + 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) + + if llm_flag: + logger.info("经大模型筛查，小模型识别正确!!!") + # cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_1.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80]) + # self.cnt = self.cnt + 1 + else: + logger.info("经大模型筛查，小模型识别错误!!!") + # cv2.imwrite(f"/home/thsw2/wei/image_res/{self.cnt}_{tar_cls}_0.jpg", aFrame, [cv2.IMWRITE_JPEG_QUALITY, 80]) + # self.cnt = self.cnt + 1 else: llm_flag_list.append(llm_flag) + + ai_image = cv2.imencode(".jpg", aFrame)[1] ai_image_name = build_image_name(image_result["current_frame"], @@ -271,6 +309,7 @@ class ImageFileUpload(FileUpload): remote_image_list.append( tk.result() ) for ii, model_info in enumerate(model_info_list): + if llm_flag_list[ii]: msg_list.append( message_feedback(request_id, AnalysisStatus.RUNNING.value, @@ -282,6 +321,7 @@ class ImageFileUpload(FileUpload): longitude=model_info['gps'][0], latitude=model_info['gps'][1], ) ) + if (not self._algSwitch) or ( self._algStatus and self._algSwitch): for msg in msg_list: