1)新增M027:建筑物下行人检测及计数 2)密集人群计数模型及自研车牌模型优化 3)分类模型支持pt模型加载（巴中水利）

concurrency/FileUploadThread.py

@@ -27,7 +27,6 @@ class FileUpload(Thread):
         super().__init__()
         self._fb_queue, self._context, self._msg, self._image_queue, self._analyse_type, self._mqtt_list = args
         self._storage_source = self._context['service']['storage_source']
-<<<<<<< HEAD
         self._algStatus = False  # 默认关闭
 
         # self._algStatus = True # 默认关闭
@@ -35,17 +34,6 @@ class FileUpload(Thread):
 
         # 0521:
         default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true"
-=======
-        self._algStatus = False # 默认关闭
-        
-        # self._algStatus = True # 默认关闭
-        self._algSwitch = self._context['service']['algSwitch']  
-        
-        
-        
-        #0521:
-        default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true"    
->>>>>>> origin/zsl
         if default_enabled:
             print("执行默认程序（defaultEnabled=True）")
             self._algSwitch = True
@@ -55,17 +43,10 @@ class FileUpload(Thread):
             # 这里放非默认逻辑的代码
             self._algSwitch = False
 
-<<<<<<< HEAD
         print("---line46 :FileUploadThread.py---", self._algSwitch)
 
 
 # 如果任务是在线、离线处理，则用此类
-=======
-        print("---line46 :FileUploadThread.py---",self._algSwitch)
-
-
-#如果任务是在线、离线处理，则用此类
->>>>>>> origin/zsl
 class ImageFileUpload(FileUpload):
     __slots__ = ()
 
@@ -85,10 +66,6 @@ class ImageFileUpload(FileUpload):
         '''
         print('*' * 100, ' mqtt_list:', len(self._mqtt_list))
 
-<<<<<<< HEAD
-=======
-
->>>>>>> origin/zsl
         model_info = []
         # 更加模型编码解析数据
         for code, det_list in det_xywh.items():
@@ -99,19 +76,10 @@ class ImageFileUpload(FileUpload):
                         for target in target_list:
                             # 自研车牌模型判断
                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
-<<<<<<< HEAD
                                 draw_name_ocr(target[1], aFrame, target[4])
                             elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                 draw_name_crowd(target[1], aFrame, target[4])
-=======
-                                box = [target[1][0][0], target[1][0][1], target[1][3][0], target[1][3][1]]
-                                draw_name_ocr(box, aFrame, target[4], target[0])
-                                cls = 0
-                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                draw_name_crowd(target[3], aFrame, target[4], cls)
-                                cls = 0
->>>>>>> origin/zsl
                             else:
                                 draw_painting_joint(target[1], aFrame, target[3], target[2], target[4], font_config,
                                                     target[5])
@@ -171,15 +139,10 @@ class ImageFileUpload(FileUpload):
                                 if 'stop' == image_msg[1]:
                                     logger.info("开始停止图片上传线程, requestId:{}", request_id)
                                     break
-<<<<<<< HEAD
                                 if 'algStart' == image_msg[1]: self._algStatus = True; logger.info(
                                     "图片上传线程,执行算法开启命令, requestId:{}", request_id)
                                 if 'algStop' == image_msg[1]:  self._algStatus = False; logger.info(
                                     "图片上传线程,执行算法关闭命令, requestId:{}", request_id)
-=======
-                                if 'algStart' == image_msg[1]: self._algStatus = True; logger.info("图片上传线程,执行算法开启命令, requestId:{}", request_id)
-                                if 'algStop' == image_msg[1]:  self._algStatus = False; logger.info("图片上传线程,执行算法关闭命令, requestId:{}", request_id) 
->>>>>>> origin/zsl
 
                             if image_msg[0] == 1:
                                 image_result = self.handle_image(image_msg[1], frame_step)
@@ -190,13 +153,8 @@ class ImageFileUpload(FileUpload):
                                                                      image_result["last_frame"],
                                                                      analyse_type,
                                                                      "OR", "0", "0", request_id)
-<<<<<<< HEAD
                                     if self._storage_source == 1:
                                         or_future = t.submit(minioSdk.put_object, or_image, or_image_name)
-=======
-                                    if self._storage_source==1: 
-                                        or_future = t.submit(minioSdk.put_object, or_image,or_image_name)    
->>>>>>> origin/zsl
                                     else:
                                         or_future = t.submit(aliyunOssSdk.put_object, or_image_name, or_image.tobytes())
                                     task.append(or_future)
@@ -211,20 +169,12 @@ class ImageFileUpload(FileUpload):
                                                                          model_info["modelCode"],
                                                                          model_info["detectTargetCode"],
                                                                          request_id)
-<<<<<<< HEAD
                                         if self._storage_source == 1:
-=======
-                                        if self._storage_source==1:
->>>>>>> origin/zsl
                                             ai_future = t.submit(minioSdk.put_object, ai_image,
                                                                  ai_image_name)
                                         else:
                                             ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
-<<<<<<< HEAD
                                                                  ai_image.tobytes())
-=======
-                                                             ai_image.tobytes())
->>>>>>> origin/zsl
 
                                         task.append(ai_future)
                                         # msg_list.append(message_feedback(request_id,
@@ -248,15 +198,9 @@ class ImageFileUpload(FileUpload):
                                                                          model_info['detectTargetCode'],
                                                                          longitude=model_info['gps'][0],
                                                                          latitude=model_info['gps'][1],
-<<<<<<< HEAD
                                                                          ))
 
                                     if (not self._algSwitch) or (self._algStatus and self._algSwitch):
-=======
-                                                                         )  )
-
-                                    if (not self._algSwitch)  or  ( self._algStatus and  self._algSwitch):
->>>>>>> origin/zsl
                                         for msg in msg_list:
                                             put_queue(fb_queue, msg, timeout=2, is_ex=False)
                                     del task, msg_list
@@ -281,10 +225,6 @@ def build_image_name(*args):
     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)
-<<<<<<< HEAD
-=======
-
->>>>>>> origin/zsl
 
 
 # 如果任务是图像处理，则用此类
@@ -317,16 +257,10 @@ class ImageTypeImageFileUpload(Thread):
                         for target in target_list:
                             # 自研车牌模型判断
                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
-<<<<<<< HEAD
                                 draw_name_ocr(target, aiFrame, font_config[cls])
                             elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or \
                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                 draw_name_crowd(target, aiFrame, font_config[cls])
-=======
-                                draw_name_ocr(target[1], aiFrame, font_config[cls], target[0])
-                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                draw_name_crowd(target[1],aiFrame,font_config[cls],target[0])
->>>>>>> origin/zsl
                             else:
                                 draw_painting_joint(target[1], aiFrame, target[3], target[2], target[4], font_config)
 
@@ -381,13 +315,8 @@ class ImageTypeImageFileUpload(Thread):
                                     ai_image_name = build_image_name(0, 0, analyse_type, "AI", result.get("modelCode"),
                                                                      result.get("type"), request_id)
 
-<<<<<<< HEAD
                                     if self._storage_source == 1:
                                         ai_future = t.submit(minioSdk.put_object, copy_frame, ai_image_name)
-=======
-                                    if self._storage_source==1:
-                                        ai_future = t.submit(minioSdk.put_object, copy_frame,ai_image_name)    
->>>>>>> origin/zsl
                                     else:
                                         ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name, copy_frame)
 
@@ -409,21 +338,12 @@ class ImageTypeImageFileUpload(Thread):
                                         if image_url is None:
                                             or_result, or_image = cv2.imencode(".jpg", image_result.get("or_frame"))
                                             image_url_0 = build_image_name(image_result.get("current_frame"),
-<<<<<<< HEAD
                                                                            image_result.get("last_frame"),
                                                                            analyse_type,
                                                                            "OR", "0", "O", request_id)
 
                                             if self._storage_source == 1:
                                                 or_future = t.submit(minioSdk.put_object, or_image, image_url_0)
-=======
-                                                                         image_result.get("last_frame"),
-                                                                         analyse_type,
-                                                                         "OR", "0", "O", request_id)
-
-                                            if self._storage_source==1: 
-                                                or_future = t.submit(minioSdk.put_object, or_image,image_url_0)    
->>>>>>> origin/zsl
                                             else:
                                                 or_future = t.submit(aliyunOssSdk.put_object, image_url_0,
                                                                      or_image.tobytes())
@@ -439,13 +359,8 @@ class ImageTypeImageFileUpload(Thread):
                                                                              model_info.get("modelCode"),
                                                                              model_info.get("detectTargetCode"),
                                                                              request_id)
-<<<<<<< HEAD
                                             if self._storage_source == 1:
                                                 ai_future = t.submit(minioSdk.put_object, ai_image, ai_image_name)
-=======
-                                            if self._storage_source==1: 
-                                                ai_future = t.submit(minioSdk.put_object, ai_image, ai_image_name)    
->>>>>>> origin/zsl
                                             else:
                                                 ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
                                                                      ai_image.tobytes())

concurrency/IntelligentRecognitionProcess.py

@@ -91,11 +91,6 @@ class IntelligentRecognitionProcess(Process):
         hb_thread.start()
         return hb_thread
 
-<<<<<<< HEAD
-=======
-
->>>>>>> origin/zsl
-
 
 class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
     __slots__ = ()
@@ -300,12 +295,8 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                     for i, model in enumerate(model_array):
                                         model_conf, code = model
                                         if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
-<<<<<<< HEAD
                                            ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                 ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
-=======
-                                           ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
->>>>>>> origin/zsl
                                             if draw_config.get(code) is None:
                                                 draw_config[code] = {}
                                                 draw_config["font_config"] = model_conf[4]
@@ -452,12 +443,12 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
 class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
     __slots__ = ()
 
-    def upload_video(self,base_dir, env, request_id, aiFilePath):
+    def upload_video(self, base_dir, env, request_id, aiFilePath):
         aliyunVodSdk = ThAliyunVodSdk(base_dir, env, request_id)
         upload_video_thread_ai = Common(aliyunVodSdk.get_play_url, aiFilePath, "ai_online_%s" % request_id)
 
-        if self._storage_source==1:
+        if self._storage_source == 1:
-            minioSdk = MinioSdk(base_dir, env, request_id )
+            minioSdk = MinioSdk(base_dir, env, request_id)
             upload_video_thread_ai = Common(minioSdk.put_object, aiFilePath, "ai_online_%s.mp4" % request_id)
         else:
             aliyunVodSdk = ThAliyunVodSdk(base_dir, env, request_id)
@@ -631,12 +622,8 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
                                     for i, model in enumerate(model_array):
                                         model_conf, code = model
                                         if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
-<<<<<<< HEAD
                                            ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                 ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
-=======
-                                           ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
->>>>>>> origin/zsl
                                             if draw_config.get(code) is None:
                                                 draw_config[code] = {}
                                                 draw_config["font_config"] = model_conf[4]
@@ -953,11 +940,7 @@ class PhotosIntelligentRecognitionProcess(Process):
             logger.error("模型分析异常: {}, requestId: {}", format_exc(), request_id)
             raise e
 
-<<<<<<< HEAD
+    # 自研究车牌模型
-    #自研车牌模型
-=======
-    #自研究车牌模型
->>>>>>> origin/zsl
     def carplate_rec(self, imageUrl, mod, image_queue, request_id):
         try:
             # model_conf： modeType, allowedList, detpar, ocrmodel, rainbows
@@ -996,10 +979,6 @@ class PhotosIntelligentRecognitionProcess(Process):
             # param = [image, new_device, model, par, img_type, request_id]
             # model_conf, frame, device, requestId
             dataBack = MODEL_CONFIG[code][3]([[modeType, device, model, postPar], image, request_id])[0][2]
-<<<<<<< HEAD
-=======
-            logger.info("当前人数：{}", dataBack[0][0])
->>>>>>> origin/zsl
             dets[code][0] = dataBack
             if not dataBack:
                 logger.info("当前页面无人")
@@ -1288,12 +1267,8 @@ class PhotosIntelligentRecognitionProcess(Process):
                         result = t.submit(self.carpalteRec, imageUrls, model, image_queue, request_id)
                         task_list.append(result)
                     # 人群计数模型
-<<<<<<< HEAD
                     elif model[1] == ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] or \
                             model[1] == ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1]:
-=======
-                    elif model[1] == ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1]:
->>>>>>> origin/zsl
                         result = t.submit(self.denscrowdcountRec, imageUrls, model, image_queue, request_id)
                         task_list.append(result)
                     else:
@@ -1508,15 +1483,9 @@ class ScreenRecordingProcess(Process):
         clear_queue(self._hb_queue)
         clear_queue(self._pull_queue)
 
-<<<<<<< HEAD
     def upload_video(self, base_dir, env, request_id, orFilePath):
         if self._storage_source == 1:
             minioSdk = MinioSdk(base_dir, env, request_id)
-=======
-    def upload_video(self,base_dir, env, request_id, orFilePath):
-        if self._storage_source==1:
-            minioSdk = MinioSdk(base_dir, env, request_id )
->>>>>>> origin/zsl
             upload_video_thread_ai = Common(minioSdk.put_object, aiFilePath, "%s/ai_online.mp4" % request_id)
         else:
             aliyunVodSdk = ThAliyunVodSdk(base_dir, env, request_id)

concurrency/PushVideoStreamProcess.py

@@ -151,7 +151,6 @@ class OnPushStreamProcess(PushStreamProcess):
                                             # 自研车牌模型处理
                                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
                                                 cls = 0
-<<<<<<< HEAD
                                                 box = xy2xyxy(qs[1])
                                                 score = None
                                                 color = rainbows[cls]
@@ -160,22 +159,11 @@ class OnPushStreamProcess(PushStreamProcess):
                                             elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                                 cls = 0
-=======
+                                                # crowdlabel, points = qs
-                                                ocrlabel, xybox = qs
-                                                box = xy2xyxy(xybox)
-                                                score = None
-                                                color = rainbows[cls]
-                                                label_array = None
-                                                rr = t.submit(draw_name_ocr, xybox, copy_frame, color, ocrlabel)
-                                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                                cls = 0
-                                                crowdlabel, points = qs
->>>>>>> origin/zsl
                                                 box = [(0, 0), (0, 0), (0, 0), (0, 0)]
                                                 score = None
                                                 color = rainbows[cls]
                                                 label_array = None
-<<<<<<< HEAD
                                                 rr = t.submit(draw_name_crowd, qs, copy_frame, color)
                                             else:
                                                 try:  # 应对NaN情况
@@ -192,24 +180,6 @@ class OnPushStreamProcess(PushStreamProcess):
                                                 else:
                                                     rr = t.submit(draw_painting_joint, box, copy_frame, label_array,
                                                                   score, color, font_config)
-=======
-                                                rr = t.submit(draw_name_crowd, points, copy_frame, color, crowdlabel)
-                                            else:
-                                                 try:  # 应对NaN情况
-                                                     box, score, cls = xywh2xyxy2(qs)
-                                                 except:
-                                                     continue
-                                                 if cls not in allowedList or score < frame_score:
-                                                     continue
-                                                 label_array, color = label_arrays[cls], rainbows[cls]
-                                                 if ModelType.CHANNEL2_MODEL.value[1] == str(code) and cls == 2:
-                                                     rr = t.submit(draw_name_joint, box, copy_frame,
-                                                                   draw_config[code]["label_dict"], score, color,
-                                                                   font_config, qs[6])
-                                                 else:
-                                                     rr = t.submit(draw_painting_joint, box, copy_frame, label_array,
-                                                                   score, color, font_config)
->>>>>>> origin/zsl
 
                                             thread_p.append(rr)
                                             if det_xywh.get(code) is None:
@@ -291,24 +261,18 @@ class OnPushStreamProcess(PushStreamProcess):
                                             is_new = False
                                             if q[11] == 1:
                                                 is_new = True
-<<<<<<< HEAD
                                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
                                                 ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                                 box = qs
-=======
-                                            if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
-                                                cls = ocrlabel
-                                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                                cls = crowdlabel
-                                                label_array = points                                            
->>>>>>> origin/zsl
                                             if cd is None:
                                                 det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]]
                                             else:
-                                                det_xywh2[code][cls].append([cls, box, score, label_array, color, is_new])
+                                                det_xywh2[code][cls].append(
+                                                    [cls, box, score, label_array, color, is_new])
                                     if len(det_xywh2) > 0:
-                                        put_queue(image_queue, (1, [det_xywh2, frame, frame_index_list[i], all_frames, draw_config["font_config"]]))
+                                        put_queue(image_queue, (1, [det_xywh2, frame, frame_index_list[i], all_frames,
+                                                                    draw_config["font_config"]]))
 
                                 push_p = push_stream_result.result(timeout=60)
                                 ai_video_file = write_ai_video_result.result(timeout=60)
@@ -430,38 +394,21 @@ class OffPushStreamProcess(PushStreamProcess):
                                             # 自研车牌模型处理
                                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
                                                 cls = 0
-<<<<<<< HEAD
                                                 box = xy2xyxy(qs[1])
-=======
-                                                ocrlabel, xybox = qs
-                                                box = xy2xyxy(xybox)
->>>>>>> origin/zsl
                                                 score = None
                                                 color = rainbows[cls]
                                                 label_array = None
                                                 label_arrays = [None]
-<<<<<<< HEAD
                                                 rr = t.submit(draw_name_ocr, qs, copy_frame, color)
 
                                             elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                                 cls = 0
-=======
-                                                rr = t.submit(draw_name_ocr,xybox,copy_frame,color,ocrlabel)
-
-                                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                                cls = 0
-                                                crowdlabel, points = qs
->>>>>>> origin/zsl
                                                 box = [(0,0),(0,0),(0,0),(0,0)]
                                                 score = None
                                                 color = rainbows[cls]
                                                 label_array = None
-<<<<<<< HEAD
                                                 rr = t.submit(draw_name_crowd, qs, copy_frame, color)
-=======
-                                                rr = t.submit(draw_name_crowd, points, copy_frame, color, crowdlabel)
->>>>>>> origin/zsl
 
                                             else:
                                                 box, score, cls = xywh2xyxy2(qs)
@@ -553,23 +500,15 @@ class OffPushStreamProcess(PushStreamProcess):
                                             if q[11] == 1:
                                                 is_new = True
 
-<<<<<<< HEAD
                                             if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
                                                 ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
                                                     ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
                                                 box = qs
-=======
-                                            if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
-                                                cls = ocrlabel
-                                            elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
-                                                cls = crowdlabel
-                                                label_array = points
-
->>>>>>> origin/zsl
                                             if cd is None:
-                                                det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]] 
+                                                det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]]
                                             else:
-                                                det_xywh2[code][cls].append([cls, box, score, label_array, color, is_new])
+                                                det_xywh2[code][cls].append(
+                                                    [cls, box, score, label_array, color, is_new])
                                     if len(det_xywh2) > 0:
                                         put_queue(image_queue, (1, [det_xywh2, frame, frame_index_list[i], all_frames, draw_config["font_config"]]))
                                 push_p = push_stream_result.result(timeout=60)

enums/ModelTypeEnum.py

@@ -374,13 +374,8 @@ class ModelType(Enum):
                     },
         'models':[
             {
-<<<<<<< HEAD
                  'weight':'../weights/trt/AIlib2/cityMangement3/yolov5_%s_fp16.engine'%(gpuName),
                  'name':'yolov5',
-=======
-                'weight':'../weights/trt/AIlib2/cityMangement3/yolov5_%s_fp16.engine'%(gpuName),
-                'name':'yolov5',
->>>>>>> origin/zsl
                 'model':yolov5Model,
                 'par':{ 'half':True,'device':'cuda:0' ,'conf_thres':0.25,'iou_thres':0.45,'allowedList':[0,1,2,3,4,5,6,7],'segRegionCnt':1, 'trtFlag_det':True,'trtFlag_seg':True, "score_byClass":{"0":0.8,"1":0.4,"2":0.5,"3":0.5  } }
             },
@@ -979,11 +974,7 @@ class ModelType(Enum):
                     'row': 2,
                     'line': 2,
                     'point_loss_coef': 0.45,
-<<<<<<< HEAD
+                    'conf': 0.65,
-                    'conf': 0.50,
-=======
-                    'conf': 0.25,
->>>>>>> origin/zsl
                     'gpu_id': 0,
                     'eos_coef': '0.5',
                     'set_cost_class': 1,
@@ -1011,7 +1002,6 @@ class ModelType(Enum):
             "rainbows": COLOR
         },
 
-<<<<<<< HEAD
     })
 
     CITY_UNDERBUILDCOUNT_MODEL = ("30", "306", "建筑物下人群计数", 'perUnderBuild', lambda device, gpuName: {
@@ -1046,8 +1036,6 @@ class ModelType(Enum):
                     'backbone': 'vgg16_bn'
                 },
             }],
-=======
->>>>>>> origin/zsl
     })
 
     @staticmethod

util/PlotsUtils.py

@@ -225,19 +225,11 @@ def draw_name_joint(box, img, label_array_dict, score=0.5, color=None, config=No
     cv2.putText(img, label, p3, 0, config[3], [225, 255, 255], thickness=config[4], lineType=cv2.LINE_AA)
     return img, box
 
-<<<<<<< HEAD
 def draw_name_ocr(box, img, color, line_thickness=2, outfontsize=40):
     font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
     # (color=None, label=None, font=None, fontSize=40, unify=False)
     label_zh = get_label_array(color, box[0], font, outfontsize)
     return plot_one_box_auto(box[1], img, color, line_thickness, label_zh)
-=======
-def draw_name_ocr(box, img, color, label, line_thickness=2, outfontsize=40):
-    font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
-    #(color=None, label=None, font=None, fontSize=40, unify=False)
-    label_zh = get_label_array(color, label, font, outfontsize)
-    return plot_one_box_auto(box, img, color, line_thickness, label_zh)
->>>>>>> origin/zsl
 
 def filterBox(det0, det1, pix_dis):
     # det0为 (m1, 11) 矩阵
@@ -325,7 +317,6 @@ def plot_one_box_auto(box, img, color=None, line_thickness=2, label_array=None):
     return img, box
 
 
-<<<<<<< HEAD
 def draw_name_crowd(dets, img, color, line_thickness=2, outfontsize=20):
     font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
     if len(dets) == 1:
@@ -372,23 +363,6 @@ def draw_name_crowd(dets, img, color, line_thickness=2, outfontsize=20):
 
             cv2.polylines(img, [np.asarray(xy2xyxy(b), np.int32)], True, (0, 128, 255), 2)
             img[y0:y1, x0:x1, :] = label_arr
-=======
-def draw_name_crowd(dets, img, color, label, line_thickness=2, outfontsize=20):
-    font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
-    H,W = img.shape[:2]
-    # img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    # img = Image.fromarray(img)
-    # width, height = img.size
-    Wrate = W // 128 * 128/W
-    Hrate = H // 128 * 128/H
 
-    # img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
-
-    for p in dets:
-        img = cv2.circle(img, (int(p[0]/Wrate), int(p[1]/Hrate)), line_thickness, color, -1)
-    Calc_label_arr = get_label_array(color, label, font, outfontsize)
-    lh, lw = Calc_label_arr.shape[0:2]
-    img[0:lh, 0:lw, :] = Calc_label_arr
->>>>>>> origin/zsl
 
     return img, dets