|
|
| """This file processes the annotation files and generates proper annotation
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| files for localizers."""
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| import json
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|
|
| import numpy as np
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|
|
|
|
| def load_json(file):
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| with open(file) as json_file:
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| data = json.load(json_file)
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| return data
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|
|
|
|
| data_file = '../../../data/ActivityNet'
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| info_file = f'{data_file}/video_info_new.csv'
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| ann_file = f'{data_file}/anet_anno_action.json'
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|
|
| anno_database = load_json(ann_file)
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|
|
| video_record = np.loadtxt(info_file, dtype=str, delimiter=',', skiprows=1)
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|
|
| video_dict_train = {}
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| video_dict_val = {}
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| video_dict_test = {}
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| video_dict_full = {}
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|
|
| for _, video_item in enumerate(video_record):
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| video_name = video_item[0]
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| video_info = anno_database[video_name]
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| video_subset = video_item[5]
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| video_info['fps'] = video_item[3].astype(np.float64)
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| video_info['rfps'] = video_item[4].astype(np.float64)
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| video_dict_full[video_name] = video_info
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| if video_subset == 'training':
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| video_dict_train[video_name] = video_info
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| elif video_subset == 'testing':
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| video_dict_test[video_name] = video_info
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| elif video_subset == 'validation':
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| video_dict_val[video_name] = video_info
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|
|
| print(f'full subset video numbers: {len(video_record)}')
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|
|
| with open(f'{data_file}/anet_anno_train.json', 'w') as result_file:
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| json.dump(video_dict_train, result_file)
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|
|
| with open(f'{data_file}/anet_anno_val.json', 'w') as result_file:
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| json.dump(video_dict_val, result_file)
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|
|
| with open(f'{data_file}/anet_anno_test.json', 'w') as result_file:
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| json.dump(video_dict_test, result_file)
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|
|
| with open(f'{data_file}/anet_anno_full.json', 'w') as result_file:
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| json.dump(video_dict_full, result_file)
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|
|
