forked from PulseFocusPlatform/PulseFocusPlatform
824 lines
20 KiB
Python
824 lines
20 KiB
Python
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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from ppdet.data.source.voc import pascalvoc_label
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from ppdet.data.source.widerface import widerface_label
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from ppdet.utils.logger import setup_logger
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logger = setup_logger(__name__)
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__all__ = ['get_categories']
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def get_categories(metric_type, anno_file=None, arch=None):
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"""
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Get class id to category id map and category id
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to category name map from annotation file.
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Args:
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metric_type (str): metric type, currently support 'coco', 'voc', 'oid'
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and 'widerface'.
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anno_file (str): annotation file path
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"""
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if arch == 'keypoint_arch':
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return (None, {'id': 'keypoint'})
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if metric_type.lower() == 'coco':
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if anno_file and os.path.isfile(anno_file):
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# lazy import pycocotools here
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from pycocotools.coco import COCO
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coco = COCO(anno_file)
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cats = coco.loadCats(coco.getCatIds())
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clsid2catid = {i: cat['id'] for i, cat in enumerate(cats)}
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catid2name = {cat['id']: cat['name'] for cat in cats}
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return clsid2catid, catid2name
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# anno file not exist, load default categories of COCO17
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else:
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return _coco17_category()
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elif metric_type.lower() == 'voc':
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if anno_file and os.path.isfile(anno_file):
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cats = []
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with open(anno_file) as f:
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for line in f.readlines():
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cats.append(line.strip())
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if cats[0] == 'background':
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cats = cats[1:]
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clsid2catid = {i: i for i in range(len(cats))}
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catid2name = {i: name for i, name in enumerate(cats)}
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return clsid2catid, catid2name
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# anno file not exist, load default categories of
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# VOC all 20 categories
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else:
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return _vocall_category()
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elif metric_type.lower() == 'oid':
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if anno_file and os.path.isfile(anno_file):
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logger.warning("only default categories support for OID19")
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return _oid19_category()
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elif metric_type.lower() == 'widerface':
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return _widerface_category()
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elif metric_type.lower() == 'keypointtopdowncocoeval':
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return (None, {'id': 'keypoint'})
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elif metric_type.lower() in ['mot', 'motdet', 'reid']:
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return _mot_category()
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else:
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raise ValueError("unknown metric type {}".format(metric_type))
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def _mot_category():
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"""
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Get class id to category id map and category id
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to category name map of mot dataset
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"""
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label_map = {'person': 0}
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label_map = sorted(label_map.items(), key=lambda x: x[1])
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cats = [l[0] for l in label_map]
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clsid2catid = {i: i for i in range(len(cats))}
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catid2name = {i: name for i, name in enumerate(cats)}
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return clsid2catid, catid2name
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def _coco17_category():
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"""
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Get class id to category id map and category id
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to category name map of COCO2017 dataset
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"""
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clsid2catid = {
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1: 1,
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2: 2,
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3: 3,
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4: 4,
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5: 5,
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6: 6,
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7: 7,
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8: 8,
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9: 9,
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10: 10,
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11: 11,
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12: 13,
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13: 14,
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14: 15,
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15: 16,
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16: 17,
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17: 18,
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18: 19,
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19: 20,
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20: 21,
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21: 22,
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22: 23,
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23: 24,
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24: 25,
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25: 27,
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26: 28,
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27: 31,
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28: 32,
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29: 33,
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30: 34,
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31: 35,
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32: 36,
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33: 37,
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34: 38,
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35: 39,
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36: 40,
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37: 41,
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38: 42,
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39: 43,
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40: 44,
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41: 46,
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42: 47,
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43: 48,
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44: 49,
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45: 50,
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46: 51,
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47: 52,
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48: 53,
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49: 54,
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50: 55,
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51: 56,
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52: 57,
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53: 58,
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54: 59,
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55: 60,
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56: 61,
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57: 62,
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58: 63,
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59: 64,
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60: 65,
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61: 67,
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62: 70,
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63: 72,
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64: 73,
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65: 74,
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66: 75,
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67: 76,
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68: 77,
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69: 78,
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70: 79,
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71: 80,
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72: 81,
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73: 82,
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74: 84,
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75: 85,
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76: 86,
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77: 87,
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78: 88,
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79: 89,
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80: 90
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}
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catid2name = {
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0: 'background',
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1: 'person',
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2: 'bicycle',
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3: 'car',
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4: 'motorcycle',
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5: 'airplane',
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6: 'bus',
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7: 'train',
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8: 'truck',
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9: 'boat',
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10: 'traffic light',
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11: 'fire hydrant',
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13: 'stop sign',
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14: 'parking meter',
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15: 'bench',
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16: 'bird',
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17: 'cat',
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18: 'dog',
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19: 'horse',
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20: 'sheep',
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21: 'cow',
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22: 'elephant',
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23: 'bear',
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24: 'zebra',
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25: 'giraffe',
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27: 'backpack',
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28: 'umbrella',
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31: 'handbag',
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32: 'tie',
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33: 'suitcase',
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34: 'frisbee',
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35: 'skis',
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36: 'snowboard',
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37: 'sports ball',
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38: 'kite',
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39: 'baseball bat',
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40: 'baseball glove',
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41: 'skateboard',
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42: 'surfboard',
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43: 'tennis racket',
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44: 'bottle',
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46: 'wine glass',
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47: 'cup',
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48: 'fork',
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49: 'knife',
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50: 'spoon',
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51: 'bowl',
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52: 'banana',
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53: 'apple',
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54: 'sandwich',
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55: 'orange',
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56: 'broccoli',
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57: 'carrot',
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58: 'hot dog',
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59: 'pizza',
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60: 'donut',
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61: 'cake',
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62: 'chair',
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63: 'couch',
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64: 'potted plant',
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65: 'bed',
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67: 'dining table',
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70: 'toilet',
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72: 'tv',
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73: 'laptop',
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74: 'mouse',
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75: 'remote',
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76: 'keyboard',
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77: 'cell phone',
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78: 'microwave',
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79: 'oven',
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80: 'toaster',
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81: 'sink',
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82: 'refrigerator',
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84: 'book',
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85: 'clock',
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86: 'vase',
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87: 'scissors',
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88: 'teddy bear',
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89: 'hair drier',
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90: 'toothbrush'
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}
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clsid2catid = {k - 1: v for k, v in clsid2catid.items()}
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catid2name.pop(0)
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return clsid2catid, catid2name
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def _vocall_category():
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"""
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Get class id to category id map and category id
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to category name map of mixup voc dataset
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"""
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label_map = pascalvoc_label()
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label_map = sorted(label_map.items(), key=lambda x: x[1])
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cats = [l[0] for l in label_map]
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clsid2catid = {i: i for i in range(len(cats))}
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catid2name = {i: name for i, name in enumerate(cats)}
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return clsid2catid, catid2name
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def _widerface_category():
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label_map = widerface_label()
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label_map = sorted(label_map.items(), key=lambda x: x[1])
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cats = [l[0] for l in label_map]
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clsid2catid = {i: i for i in range(len(cats))}
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catid2name = {i: name for i, name in enumerate(cats)}
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return clsid2catid, catid2name
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def _oid19_category():
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clsid2catid = {k: k + 1 for k in range(500)}
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catid2name = {
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0: "background",
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1: "Infant bed",
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2: "Rose",
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3: "Flag",
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4: "Flashlight",
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5: "Sea turtle",
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6: "Camera",
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7: "Animal",
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8: "Glove",
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9: "Crocodile",
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10: "Cattle",
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11: "House",
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12: "Guacamole",
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13: "Penguin",
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14: "Vehicle registration plate",
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15: "Bench",
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16: "Ladybug",
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17: "Human nose",
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18: "Watermelon",
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19: "Flute",
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20: "Butterfly",
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21: "Washing machine",
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22: "Raccoon",
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23: "Segway",
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24: "Taco",
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25: "Jellyfish",
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26: "Cake",
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27: "Pen",
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28: "Cannon",
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29: "Bread",
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30: "Tree",
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31: "Shellfish",
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32: "Bed",
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33: "Hamster",
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34: "Hat",
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35: "Toaster",
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36: "Sombrero",
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37: "Tiara",
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38: "Bowl",
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39: "Dragonfly",
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40: "Moths and butterflies",
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41: "Antelope",
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42: "Vegetable",
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43: "Torch",
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44: "Building",
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45: "Power plugs and sockets",
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46: "Blender",
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47: "Billiard table",
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48: "Cutting board",
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49: "Bronze sculpture",
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50: "Turtle",
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51: "Broccoli",
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52: "Tiger",
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53: "Mirror",
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54: "Bear",
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55: "Zucchini",
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56: "Dress",
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57: "Volleyball",
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58: "Guitar",
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59: "Reptile",
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60: "Golf cart",
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61: "Tart",
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62: "Fedora",
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63: "Carnivore",
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64: "Car",
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65: "Lighthouse",
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66: "Coffeemaker",
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67: "Food processor",
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68: "Truck",
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69: "Bookcase",
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70: "Surfboard",
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71: "Footwear",
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72: "Bench",
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73: "Necklace",
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74: "Flower",
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75: "Radish",
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76: "Marine mammal",
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77: "Frying pan",
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78: "Tap",
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79: "Peach",
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80: "Knife",
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81: "Handbag",
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82: "Laptop",
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83: "Tent",
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84: "Ambulance",
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85: "Christmas tree",
|
||
|
|
86: "Eagle",
|
||
|
|
87: "Limousine",
|
||
|
|
88: "Kitchen & dining room table",
|
||
|
|
89: "Polar bear",
|
||
|
|
90: "Tower",
|
||
|
|
91: "Football",
|
||
|
|
92: "Willow",
|
||
|
|
93: "Human head",
|
||
|
|
94: "Stop sign",
|
||
|
|
95: "Banana",
|
||
|
|
96: "Mixer",
|
||
|
|
97: "Binoculars",
|
||
|
|
98: "Dessert",
|
||
|
|
99: "Bee",
|
||
|
|
100: "Chair",
|
||
|
|
101: "Wood-burning stove",
|
||
|
|
102: "Flowerpot",
|
||
|
|
103: "Beaker",
|
||
|
|
104: "Oyster",
|
||
|
|
105: "Woodpecker",
|
||
|
|
106: "Harp",
|
||
|
|
107: "Bathtub",
|
||
|
|
108: "Wall clock",
|
||
|
|
109: "Sports uniform",
|
||
|
|
110: "Rhinoceros",
|
||
|
|
111: "Beehive",
|
||
|
|
112: "Cupboard",
|
||
|
|
113: "Chicken",
|
||
|
|
114: "Man",
|
||
|
|
115: "Blue jay",
|
||
|
|
116: "Cucumber",
|
||
|
|
117: "Balloon",
|
||
|
|
118: "Kite",
|
||
|
|
119: "Fireplace",
|
||
|
|
120: "Lantern",
|
||
|
|
121: "Missile",
|
||
|
|
122: "Book",
|
||
|
|
123: "Spoon",
|
||
|
|
124: "Grapefruit",
|
||
|
|
125: "Squirrel",
|
||
|
|
126: "Orange",
|
||
|
|
127: "Coat",
|
||
|
|
128: "Punching bag",
|
||
|
|
129: "Zebra",
|
||
|
|
130: "Billboard",
|
||
|
|
131: "Bicycle",
|
||
|
|
132: "Door handle",
|
||
|
|
133: "Mechanical fan",
|
||
|
|
134: "Ring binder",
|
||
|
|
135: "Table",
|
||
|
|
136: "Parrot",
|
||
|
|
137: "Sock",
|
||
|
|
138: "Vase",
|
||
|
|
139: "Weapon",
|
||
|
|
140: "Shotgun",
|
||
|
|
141: "Glasses",
|
||
|
|
142: "Seahorse",
|
||
|
|
143: "Belt",
|
||
|
|
144: "Watercraft",
|
||
|
|
145: "Window",
|
||
|
|
146: "Giraffe",
|
||
|
|
147: "Lion",
|
||
|
|
148: "Tire",
|
||
|
|
149: "Vehicle",
|
||
|
|
150: "Canoe",
|
||
|
|
151: "Tie",
|
||
|
|
152: "Shelf",
|
||
|
|
153: "Picture frame",
|
||
|
|
154: "Printer",
|
||
|
|
155: "Human leg",
|
||
|
|
156: "Boat",
|
||
|
|
157: "Slow cooker",
|
||
|
|
158: "Croissant",
|
||
|
|
159: "Candle",
|
||
|
|
160: "Pancake",
|
||
|
|
161: "Pillow",
|
||
|
|
162: "Coin",
|
||
|
|
163: "Stretcher",
|
||
|
|
164: "Sandal",
|
||
|
|
165: "Woman",
|
||
|
|
166: "Stairs",
|
||
|
|
167: "Harpsichord",
|
||
|
|
168: "Stool",
|
||
|
|
169: "Bus",
|
||
|
|
170: "Suitcase",
|
||
|
|
171: "Human mouth",
|
||
|
|
172: "Juice",
|
||
|
|
173: "Skull",
|
||
|
|
174: "Door",
|
||
|
|
175: "Violin",
|
||
|
|
176: "Chopsticks",
|
||
|
|
177: "Digital clock",
|
||
|
|
178: "Sunflower",
|
||
|
|
179: "Leopard",
|
||
|
|
180: "Bell pepper",
|
||
|
|
181: "Harbor seal",
|
||
|
|
182: "Snake",
|
||
|
|
183: "Sewing machine",
|
||
|
|
184: "Goose",
|
||
|
|
185: "Helicopter",
|
||
|
|
186: "Seat belt",
|
||
|
|
187: "Coffee cup",
|
||
|
|
188: "Microwave oven",
|
||
|
|
189: "Hot dog",
|
||
|
|
190: "Countertop",
|
||
|
|
191: "Serving tray",
|
||
|
|
192: "Dog bed",
|
||
|
|
193: "Beer",
|
||
|
|
194: "Sunglasses",
|
||
|
|
195: "Golf ball",
|
||
|
|
196: "Waffle",
|
||
|
|
197: "Palm tree",
|
||
|
|
198: "Trumpet",
|
||
|
|
199: "Ruler",
|
||
|
|
200: "Helmet",
|
||
|
|
201: "Ladder",
|
||
|
|
202: "Office building",
|
||
|
|
203: "Tablet computer",
|
||
|
|
204: "Toilet paper",
|
||
|
|
205: "Pomegranate",
|
||
|
|
206: "Skirt",
|
||
|
|
207: "Gas stove",
|
||
|
|
208: "Cookie",
|
||
|
|
209: "Cart",
|
||
|
|
210: "Raven",
|
||
|
|
211: "Egg",
|
||
|
|
212: "Burrito",
|
||
|
|
213: "Goat",
|
||
|
|
214: "Kitchen knife",
|
||
|
|
215: "Skateboard",
|
||
|
|
216: "Salt and pepper shakers",
|
||
|
|
217: "Lynx",
|
||
|
|
218: "Boot",
|
||
|
|
219: "Platter",
|
||
|
|
220: "Ski",
|
||
|
|
221: "Swimwear",
|
||
|
|
222: "Swimming pool",
|
||
|
|
223: "Drinking straw",
|
||
|
|
224: "Wrench",
|
||
|
|
225: "Drum",
|
||
|
|
226: "Ant",
|
||
|
|
227: "Human ear",
|
||
|
|
228: "Headphones",
|
||
|
|
229: "Fountain",
|
||
|
|
230: "Bird",
|
||
|
|
231: "Jeans",
|
||
|
|
232: "Television",
|
||
|
|
233: "Crab",
|
||
|
|
234: "Microphone",
|
||
|
|
235: "Home appliance",
|
||
|
|
236: "Snowplow",
|
||
|
|
237: "Beetle",
|
||
|
|
238: "Artichoke",
|
||
|
|
239: "Jet ski",
|
||
|
|
240: "Stationary bicycle",
|
||
|
|
241: "Human hair",
|
||
|
|
242: "Brown bear",
|
||
|
|
243: "Starfish",
|
||
|
|
244: "Fork",
|
||
|
|
245: "Lobster",
|
||
|
|
246: "Corded phone",
|
||
|
|
247: "Drink",
|
||
|
|
248: "Saucer",
|
||
|
|
249: "Carrot",
|
||
|
|
250: "Insect",
|
||
|
|
251: "Clock",
|
||
|
|
252: "Castle",
|
||
|
|
253: "Tennis racket",
|
||
|
|
254: "Ceiling fan",
|
||
|
|
255: "Asparagus",
|
||
|
|
256: "Jaguar",
|
||
|
|
257: "Musical instrument",
|
||
|
|
258: "Train",
|
||
|
|
259: "Cat",
|
||
|
|
260: "Rifle",
|
||
|
|
261: "Dumbbell",
|
||
|
|
262: "Mobile phone",
|
||
|
|
263: "Taxi",
|
||
|
|
264: "Shower",
|
||
|
|
265: "Pitcher",
|
||
|
|
266: "Lemon",
|
||
|
|
267: "Invertebrate",
|
||
|
|
268: "Turkey",
|
||
|
|
269: "High heels",
|
||
|
|
270: "Bust",
|
||
|
|
271: "Elephant",
|
||
|
|
272: "Scarf",
|
||
|
|
273: "Barrel",
|
||
|
|
274: "Trombone",
|
||
|
|
275: "Pumpkin",
|
||
|
|
276: "Box",
|
||
|
|
277: "Tomato",
|
||
|
|
278: "Frog",
|
||
|
|
279: "Bidet",
|
||
|
|
280: "Human face",
|
||
|
|
281: "Houseplant",
|
||
|
|
282: "Van",
|
||
|
|
283: "Shark",
|
||
|
|
284: "Ice cream",
|
||
|
|
285: "Swim cap",
|
||
|
|
286: "Falcon",
|
||
|
|
287: "Ostrich",
|
||
|
|
288: "Handgun",
|
||
|
|
289: "Whiteboard",
|
||
|
|
290: "Lizard",
|
||
|
|
291: "Pasta",
|
||
|
|
292: "Snowmobile",
|
||
|
|
293: "Light bulb",
|
||
|
|
294: "Window blind",
|
||
|
|
295: "Muffin",
|
||
|
|
296: "Pretzel",
|
||
|
|
297: "Computer monitor",
|
||
|
|
298: "Horn",
|
||
|
|
299: "Furniture",
|
||
|
|
300: "Sandwich",
|
||
|
|
301: "Fox",
|
||
|
|
302: "Convenience store",
|
||
|
|
303: "Fish",
|
||
|
|
304: "Fruit",
|
||
|
|
305: "Earrings",
|
||
|
|
306: "Curtain",
|
||
|
|
307: "Grape",
|
||
|
|
308: "Sofa bed",
|
||
|
|
309: "Horse",
|
||
|
|
310: "Luggage and bags",
|
||
|
|
311: "Desk",
|
||
|
|
312: "Crutch",
|
||
|
|
313: "Bicycle helmet",
|
||
|
|
314: "Tick",
|
||
|
|
315: "Airplane",
|
||
|
|
316: "Canary",
|
||
|
|
317: "Spatula",
|
||
|
|
318: "Watch",
|
||
|
|
319: "Lily",
|
||
|
|
320: "Kitchen appliance",
|
||
|
|
321: "Filing cabinet",
|
||
|
|
322: "Aircraft",
|
||
|
|
323: "Cake stand",
|
||
|
|
324: "Candy",
|
||
|
|
325: "Sink",
|
||
|
|
326: "Mouse",
|
||
|
|
327: "Wine",
|
||
|
|
328: "Wheelchair",
|
||
|
|
329: "Goldfish",
|
||
|
|
330: "Refrigerator",
|
||
|
|
331: "French fries",
|
||
|
|
332: "Drawer",
|
||
|
|
333: "Treadmill",
|
||
|
|
334: "Picnic basket",
|
||
|
|
335: "Dice",
|
||
|
|
336: "Cabbage",
|
||
|
|
337: "Football helmet",
|
||
|
|
338: "Pig",
|
||
|
|
339: "Person",
|
||
|
|
340: "Shorts",
|
||
|
|
341: "Gondola",
|
||
|
|
342: "Honeycomb",
|
||
|
|
343: "Doughnut",
|
||
|
|
344: "Chest of drawers",
|
||
|
|
345: "Land vehicle",
|
||
|
|
346: "Bat",
|
||
|
|
347: "Monkey",
|
||
|
|
348: "Dagger",
|
||
|
|
349: "Tableware",
|
||
|
|
350: "Human foot",
|
||
|
|
351: "Mug",
|
||
|
|
352: "Alarm clock",
|
||
|
|
353: "Pressure cooker",
|
||
|
|
354: "Human hand",
|
||
|
|
355: "Tortoise",
|
||
|
|
356: "Baseball glove",
|
||
|
|
357: "Sword",
|
||
|
|
358: "Pear",
|
||
|
|
359: "Miniskirt",
|
||
|
|
360: "Traffic sign",
|
||
|
|
361: "Girl",
|
||
|
|
362: "Roller skates",
|
||
|
|
363: "Dinosaur",
|
||
|
|
364: "Porch",
|
||
|
|
365: "Human beard",
|
||
|
|
366: "Submarine sandwich",
|
||
|
|
367: "Screwdriver",
|
||
|
|
368: "Strawberry",
|
||
|
|
369: "Wine glass",
|
||
|
|
370: "Seafood",
|
||
|
|
371: "Racket",
|
||
|
|
372: "Wheel",
|
||
|
|
373: "Sea lion",
|
||
|
|
374: "Toy",
|
||
|
|
375: "Tea",
|
||
|
|
376: "Tennis ball",
|
||
|
|
377: "Waste container",
|
||
|
|
378: "Mule",
|
||
|
|
379: "Cricket ball",
|
||
|
|
380: "Pineapple",
|
||
|
|
381: "Coconut",
|
||
|
|
382: "Doll",
|
||
|
|
383: "Coffee table",
|
||
|
|
384: "Snowman",
|
||
|
|
385: "Lavender",
|
||
|
|
386: "Shrimp",
|
||
|
|
387: "Maple",
|
||
|
|
388: "Cowboy hat",
|
||
|
|
389: "Goggles",
|
||
|
|
390: "Rugby ball",
|
||
|
|
391: "Caterpillar",
|
||
|
|
392: "Poster",
|
||
|
|
393: "Rocket",
|
||
|
|
394: "Organ",
|
||
|
|
395: "Saxophone",
|
||
|
|
396: "Traffic light",
|
||
|
|
397: "Cocktail",
|
||
|
|
398: "Plastic bag",
|
||
|
|
399: "Squash",
|
||
|
|
400: "Mushroom",
|
||
|
|
401: "Hamburger",
|
||
|
|
402: "Light switch",
|
||
|
|
403: "Parachute",
|
||
|
|
404: "Teddy bear",
|
||
|
|
405: "Winter melon",
|
||
|
|
406: "Deer",
|
||
|
|
407: "Musical keyboard",
|
||
|
|
408: "Plumbing fixture",
|
||
|
|
409: "Scoreboard",
|
||
|
|
410: "Baseball bat",
|
||
|
|
411: "Envelope",
|
||
|
|
412: "Adhesive tape",
|
||
|
|
413: "Briefcase",
|
||
|
|
414: "Paddle",
|
||
|
|
415: "Bow and arrow",
|
||
|
|
416: "Telephone",
|
||
|
|
417: "Sheep",
|
||
|
|
418: "Jacket",
|
||
|
|
419: "Boy",
|
||
|
|
420: "Pizza",
|
||
|
|
421: "Otter",
|
||
|
|
422: "Office supplies",
|
||
|
|
423: "Couch",
|
||
|
|
424: "Cello",
|
||
|
|
425: "Bull",
|
||
|
|
426: "Camel",
|
||
|
|
427: "Ball",
|
||
|
|
428: "Duck",
|
||
|
|
429: "Whale",
|
||
|
|
430: "Shirt",
|
||
|
|
431: "Tank",
|
||
|
|
432: "Motorcycle",
|
||
|
|
433: "Accordion",
|
||
|
|
434: "Owl",
|
||
|
|
435: "Porcupine",
|
||
|
|
436: "Sun hat",
|
||
|
|
437: "Nail",
|
||
|
|
438: "Scissors",
|
||
|
|
439: "Swan",
|
||
|
|
440: "Lamp",
|
||
|
|
441: "Crown",
|
||
|
|
442: "Piano",
|
||
|
|
443: "Sculpture",
|
||
|
|
444: "Cheetah",
|
||
|
|
445: "Oboe",
|
||
|
|
446: "Tin can",
|
||
|
|
447: "Mango",
|
||
|
|
448: "Tripod",
|
||
|
|
449: "Oven",
|
||
|
|
450: "Mouse",
|
||
|
|
451: "Barge",
|
||
|
|
452: "Coffee",
|
||
|
|
453: "Snowboard",
|
||
|
|
454: "Common fig",
|
||
|
|
455: "Salad",
|
||
|
|
456: "Marine invertebrates",
|
||
|
|
457: "Umbrella",
|
||
|
|
458: "Kangaroo",
|
||
|
|
459: "Human arm",
|
||
|
|
460: "Measuring cup",
|
||
|
|
461: "Snail",
|
||
|
|
462: "Loveseat",
|
||
|
|
463: "Suit",
|
||
|
|
464: "Teapot",
|
||
|
|
465: "Bottle",
|
||
|
|
466: "Alpaca",
|
||
|
|
467: "Kettle",
|
||
|
|
468: "Trousers",
|
||
|
|
469: "Popcorn",
|
||
|
|
470: "Centipede",
|
||
|
|
471: "Spider",
|
||
|
|
472: "Sparrow",
|
||
|
|
473: "Plate",
|
||
|
|
474: "Bagel",
|
||
|
|
475: "Personal care",
|
||
|
|
476: "Apple",
|
||
|
|
477: "Brassiere",
|
||
|
|
478: "Bathroom cabinet",
|
||
|
|
479: "studio couch",
|
||
|
|
480: "Computer keyboard",
|
||
|
|
481: "Table tennis racket",
|
||
|
|
482: "Sushi",
|
||
|
|
483: "Cabinetry",
|
||
|
|
484: "Street light",
|
||
|
|
485: "Towel",
|
||
|
|
486: "Nightstand",
|
||
|
|
487: "Rabbit",
|
||
|
|
488: "Dolphin",
|
||
|
|
489: "Dog",
|
||
|
|
490: "Jug",
|
||
|
|
491: "Wok",
|
||
|
|
492: "Fire hydrant",
|
||
|
|
493: "Human eye",
|
||
|
|
494: "Skyscraper",
|
||
|
|
495: "Backpack",
|
||
|
|
496: "Potato",
|
||
|
|
497: "Paper towel",
|
||
|
|
498: "Lifejacket",
|
||
|
|
499: "Bicycle wheel",
|
||
|
|
500: "Toilet",
|
||
|
|
}
|
||
|
|
|
||
|
|
return clsid2catid, catid2name
|