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- """
- /**
- * Copyright 2020 Zhejiang Lab. All Rights Reserved.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * =============================================================
- */
- """
- # coding:utf-8
- import time
- import sys
- sys.path.append(r"./common")
- import predict_with_print_box as yolo_demo
- from common.log_config import setup_log
-
-
- label_log = setup_log('dev', 'label.log')
-
-
- def _init():
- print('init yolo_obj')
- global yolo_obj
- yolo_obj = yolo_demo.YoloInference(label_log)
-
-
- def _annotation(type_, image_path_list, id_list, label_list, coco_flag=0):
- """Perform automatic annotation task."""
- image_num = len(image_path_list)
- if image_num < 16:
- for i in range(16 - image_num):
- image_path_list.append(image_path_list[0])
- id_list.append(id_list[0])
- image_num = len(image_path_list)
- annotations = yolo_obj.yolo_inference(type_, id_list, image_path_list, label_list, coco_flag)
- return annotations[0:image_num]
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