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import numpy as np | |
import argparse | |
import csv | |
import os | |
import glob | |
import datetime | |
import time | |
import logging | |
import h5py | |
import librosa | |
from utilities import create_folder, get_sub_filepaths | |
import config | |
def create_indexes(args): | |
"""Create indexes a for dataloader to read for training. When users have | |
a new task and their own data, they need to create similar indexes. The | |
indexes contain meta information of "where to find the data for training". | |
""" | |
# Arguments & parameters | |
waveforms_hdf5_path = args.waveforms_hdf5_path | |
indexes_hdf5_path = args.indexes_hdf5_path | |
# Paths | |
create_folder(os.path.dirname(indexes_hdf5_path)) | |
with h5py.File(waveforms_hdf5_path, 'r') as hr: | |
with h5py.File(indexes_hdf5_path, 'w') as hw: | |
audios_num = len(hr['audio_name']) | |
hw.create_dataset('audio_name', data=hr['audio_name'][:], dtype='S20') | |
hw.create_dataset('target', data=hr['target'][:], dtype=np.bool) | |
hw.create_dataset('hdf5_path', data=[waveforms_hdf5_path.encode()] * audios_num, dtype='S200') | |
hw.create_dataset('index_in_hdf5', data=np.arange(audios_num), dtype=np.int32) | |
print('Write to {}'.format(indexes_hdf5_path)) | |
def combine_full_indexes(args): | |
"""Combine all balanced and unbalanced indexes hdf5s to a single hdf5. This | |
combined indexes hdf5 is used for training with full data (~20k balanced | |
audio clips + ~1.9m unbalanced audio clips). | |
""" | |
# Arguments & parameters | |
indexes_hdf5s_dir = args.indexes_hdf5s_dir | |
full_indexes_hdf5_path = args.full_indexes_hdf5_path | |
classes_num = config.classes_num | |
# Paths | |
paths = get_sub_filepaths(indexes_hdf5s_dir) | |
paths = [path for path in paths if ( | |
'train' in path and 'full_train' not in path and 'mini' not in path)] | |
print('Total {} hdf5 to combine.'.format(len(paths))) | |
with h5py.File(full_indexes_hdf5_path, 'w') as full_hf: | |
full_hf.create_dataset( | |
name='audio_name', | |
shape=(0,), | |
maxshape=(None,), | |
dtype='S20') | |
full_hf.create_dataset( | |
name='target', | |
shape=(0, classes_num), | |
maxshape=(None, classes_num), | |
dtype=np.bool) | |
full_hf.create_dataset( | |
name='hdf5_path', | |
shape=(0,), | |
maxshape=(None,), | |
dtype='S200') | |
full_hf.create_dataset( | |
name='index_in_hdf5', | |
shape=(0,), | |
maxshape=(None,), | |
dtype=np.int32) | |
for path in paths: | |
with h5py.File(path, 'r') as part_hf: | |
print(path) | |
n = len(full_hf['audio_name'][:]) | |
new_n = n + len(part_hf['audio_name'][:]) | |
full_hf['audio_name'].resize((new_n,)) | |
full_hf['audio_name'][n : new_n] = part_hf['audio_name'][:] | |
full_hf['target'].resize((new_n, classes_num)) | |
full_hf['target'][n : new_n] = part_hf['target'][:] | |
full_hf['hdf5_path'].resize((new_n,)) | |
full_hf['hdf5_path'][n : new_n] = part_hf['hdf5_path'][:] | |
full_hf['index_in_hdf5'].resize((new_n,)) | |
full_hf['index_in_hdf5'][n : new_n] = part_hf['index_in_hdf5'][:] | |
print('Write combined full hdf5 to {}'.format(full_indexes_hdf5_path)) | |
if __name__ == '__main__': | |
parser = argparse.ArgumentParser() | |
subparsers = parser.add_subparsers(dest='mode') | |
parser_create_indexes = subparsers.add_parser('create_indexes') | |
parser_create_indexes.add_argument('--waveforms_hdf5_path', type=str, required=True, help='Path of packed waveforms hdf5.') | |
parser_create_indexes.add_argument('--indexes_hdf5_path', type=str, required=True, help='Path to write out indexes hdf5.') | |
parser_combine_full_indexes = subparsers.add_parser('combine_full_indexes') | |
parser_combine_full_indexes.add_argument('--indexes_hdf5s_dir', type=str, required=True, help='Directory containing indexes hdf5s to be combined.') | |
parser_combine_full_indexes.add_argument('--full_indexes_hdf5_path', type=str, required=True, help='Path to write out full indexes hdf5 file.') | |
args = parser.parse_args() | |
if args.mode == 'create_indexes': | |
create_indexes(args) | |
elif args.mode == 'combine_full_indexes': | |
combine_full_indexes(args) | |
else: | |
raise Exception('Incorrect arguments!') |