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import json
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import os
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import os.path as osp
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data_file = '../../../data/ActivityNet'
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video_list = f'{data_file}/video_info_new.csv'
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anno_file = f'{data_file}/anet_anno_action.json'
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rawframe_dir = f'{data_file}/rawframes'
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action_name_list = 'action_name.csv'
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train_rawframe_dir = rawframe_dir
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val_rawframe_dir = rawframe_dir
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json_file = f'{data_file}/activity_net.v1-3.min.json'
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def generate_rawframes_filelist():
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load_dict = json.load(open(json_file))
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anet_labels = open(action_name_list).readlines()
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anet_labels = [x.strip() for x in anet_labels[1:]]
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train_dir_list = [
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osp.join(train_rawframe_dir, x) for x in os.listdir(train_rawframe_dir)
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]
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val_dir_list = [
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osp.join(val_rawframe_dir, x) for x in os.listdir(val_rawframe_dir)
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]
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def simple_label(anno):
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label = anno[0]['label']
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return anet_labels.index(label)
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def count_frames(dir_list, video):
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for dir_name in dir_list:
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if video in dir_name:
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return osp.basename(dir_name), len(os.listdir(dir_name))
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return None, None
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database = load_dict['database']
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training = {}
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validation = {}
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key_dict = {}
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for k in database:
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data = database[k]
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subset = data['subset']
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if subset in ['training', 'validation']:
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annotations = data['annotations']
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label = simple_label(annotations)
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if subset == 'training':
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dir_list = train_dir_list
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data_dict = training
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else:
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dir_list = val_dir_list
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data_dict = validation
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else:
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continue
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gt_dir_name, num_frames = count_frames(dir_list, k)
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if gt_dir_name is None:
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continue
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data_dict[gt_dir_name] = [num_frames, label]
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key_dict[gt_dir_name] = k
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train_lines = [
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k + ' ' + str(training[k][0]) + ' ' + str(training[k][1])
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for k in training
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]
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val_lines = [
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k + ' ' + str(validation[k][0]) + ' ' + str(validation[k][1])
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for k in validation
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]
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with open(osp.join(data_file, 'anet_train_video.txt'), 'w') as fout:
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fout.write('\n'.join(train_lines))
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with open(osp.join(data_file, 'anet_val_video.txt'), 'w') as fout:
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fout.write('\n'.join(val_lines))
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def clip_list(k, anno, video_anno):
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duration = anno['duration']
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num_frames = video_anno[0]
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fps = num_frames / duration
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segs = anno['annotations']
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lines = []
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for seg in segs:
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segment = seg['segment']
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label = seg['label']
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label = anet_labels.index(label)
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start, end = int(segment[0] * fps), int(segment[1] * fps)
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if end > num_frames - 1:
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end = num_frames - 1
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newline = f'{k} {start} {end - start + 1} {label}'
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lines.append(newline)
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return lines
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train_clips, val_clips = [], []
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for k in training:
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train_clips.extend(clip_list(k, database[key_dict[k]], training[k]))
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for k in validation:
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val_clips.extend(clip_list(k, database[key_dict[k]], validation[k]))
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with open(osp.join(data_file, 'anet_train_clip.txt'), 'w') as fout:
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fout.write('\n'.join(train_clips))
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with open(osp.join(data_file, 'anet_val_clip.txt'), 'w') as fout:
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fout.write('\n'.join(val_clips))
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if __name__ == '__main__':
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generate_rawframes_filelist()
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