城管模型增加边界过滤参数

concurrency/PushVideoStreamProcess.py

                         if push_r[0] == 1:
                             frame_list, frame_index_list, all_frames, draw_config, push_objs = push_r[1]
                             for i, frame in enumerate(frame_list):
+                                pix_dis = int((frame.shape[0]//10)*1.2)
                                 # 复制帧用来画图
                                 copy_frame = frame.copy()
                                 det_xywh, thread_p = {}, []
                                     qs_np_tmp = np.delete(qs_np_tmp, np.where((qs_np_tmp[:, 11] >= 75))[0], axis=0)
                                 has = False
                                 for j in qs_reurn:
-                                    if j[11] == 0:
+                                    if j[11] == 1:
                                         has = True
                                         break
                                 if has:
                                     for q in qs_reurn:
-                                        if q[11] == 0:
+                                        if q[11] >= 1:
                                             cls = int(q[9])
                                             code = str(int(q[10])).zfill(3)
                                             if det_xywh2.get(code) is None:
                                             box = [(int(q[0]), int(q[1])), (int(q[2]), int(q[3])), 
                                                     (int(q[4]), int(q[5])), (int(q[6]), int(q[7]))]
                                             is_new = False
-                                            if q[11] == 0:
+                                            if q[11] == 1:
                                                 is_new = True
                                             if cd is None:
                                                 det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]] 
                             frame_list, frame_index_list, all_frames, draw_config, push_objs = push_r[1]
                             # 处理每一帧图片
                             for i, frame in enumerate(frame_list):
+                                pix_dis = int((frame.shape[0]//10)*1.2)
                                 if frame_index_list[i] % 300 == 0 and frame_index_list[i] <= all_frames:
                                     task_process = "%.2f" % (float(frame_index_list[i]) / float(all_frames))
                                     put_queue(hb_queue, {"hb_value": task_process}, timeout=2)
                                     qs_np_tmp = np.delete(qs_np_tmp, np.where((qs_np_tmp[:, 11] >= 75))[0], axis=0)
                                 has = False
                                 for j in qs_reurn:
-                                    if j[11] == 0:
+                                    if j[11] == 1:
                                         has = True
                                         break
                                 if has:
                                     for q in qs_reurn:
-                                        if q[11] == 0:
+                                        if q[11] >= 1:
                                             cls = int(q[9])
                                             code = str(int(q[10])).zfill(3)
                                             if det_xywh2.get(code) is None:
                                             box = [(int(q[0]), int(q[1])), (int(q[2]), int(q[3])), 
                                                     (int(q[4]), int(q[5])), (int(q[6]), int(q[7]))]
                                             is_new = False
-                                            if q[11] == 0:
+                                            if q[11] == 1:
                                                 is_new = True
                                             if cd is None:
                                                 det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]] 

enums/ModelTypeEnum.py

             'dmprimg_size': 640,
             'mixFunction': {
                 'function': dmpr_yolo,
-                'pars': {'carCls': 0, 'illCls': 3, 'scaleRatio': 0.5}
+                'pars': {'carCls': 0, 'illCls': 3, 'scaleRatio': 0.5, 'border':80}
             }
         },
         'postFile': {

enums/ModelTypeEnum2.py

             'dmprimg_size': 640,
             'mixFunction': {
                 'function': dmpr_yolo,
-                'pars': {'carCls': 0, 'illCls': 3, 'scaleRatio': 0.5}
+                'pars': {'carCls': 0, 'illCls': 3, 'scaleRatio': 0.5, 'border':80}
             }
         },
         'Segweights': '../AIlib2/weights/cityMangement2/dmpr_%s.engine' % gpuName,