mimic2/preprocess.py

130 lines
4.3 KiB
Python

import argparse
import os
from multiprocessing import cpu_count
from tqdm import tqdm
from datasets import amy, blizzard, ljspeech, kusal, mailabs
from datasets import mrs
from hparams import hparams, hparams_debug_string
import sys
def preprocess_blizzard(args):
in_dir = os.path.join(args.base_dir, 'Blizzard2012')
out_dir = os.path.join(args.base_dir, args.output)
os.makedirs(out_dir, exist_ok=True)
metadata = blizzard.build_from_path(
in_dir, out_dir, args.num_workers, tqdm=tqdm)
write_metadata(metadata, out_dir)
def preprocess_ljspeech(args):
in_dir = os.path.join(args.base_dir, 'LJSpeech-1.1')
out_dir = os.path.join(args.base_dir, args.output)
os.makedirs(out_dir, exist_ok=True)
metadata = ljspeech.build_from_path(
in_dir, out_dir, args.num_workers, tqdm=tqdm)
write_metadata(metadata, out_dir)
def preprocess_mrs(args):
in_dir = args.mrs_dir
out_dir = os.path.join(args.base_dir, args.output)
username = args.mrs_username
os.makedirs(out_dir, exist_ok=True)
metadata = mrs.build_from_path(
in_dir, out_dir, username, args.num_workers, tqdm=tqdm)
write_metadata(metadata, out_dir)
def preprocess_amy(args):
in_dir = os.path.join(args.base_dir, 'amy')
out_dir = os.path.join(args.base_dir, args.output)
os.makedirs(out_dir, exist_ok=True)
metadata = amy.build_from_path(in_dir, out_dir, args.num_workers, tqdm=tqdm)
write_metadata(metadata, out_dir)
def preprocess_kusal(args):
in_dir = os.path.join(args.base_dir, 'kusal')
out_dir = os.path.join(args.base_dir, args.output)
os.makedirs(out_dir, exist_ok=True)
metadata = kusal.build_from_path(
in_dir, out_dir, args.num_workers, tqdm=tqdm)
write_metadata(metadata, out_dir)
def preprocess_mailabs(args):
in_dir = os.path.join(args.mailabs_books_dir)
out_dir = os.path.join(args.base_dir, args.output)
os.makedirs(out_dir, exist_ok=True)
books = args.books
metadata = mailabs.build_from_path(
in_dir, out_dir, books, args.num_workers, tqdm)
write_metadata(metadata, out_dir)
def write_metadata(metadata, out_dir):
with open(os.path.join(out_dir, 'train.txt'), 'w', encoding='utf-8') as f:
for m in metadata:
f.write('|'.join([str(x) for x in m]) + '\n')
frames = sum([m[2] for m in metadata])
hours = frames * hparams.frame_shift_ms / (3600 * 1000)
print('Wrote %d utterances, %d frames (%.2f hours)' %
(len(metadata), frames, hours))
print('Max input length: %d' % max(len(m[3]) for m in metadata))
print('Max output length: %d' % max(m[2] for m in metadata))
with open("metadata.txt", 'w') as f:
f.write(
'''
Wrote {} utterances, {} frames, {} hours\n
Max input lengh: {} \n
Max output length: {} \n
'''.format(
len(metadata), frames, hours,
max(len(m[3]) for m in metadata), max(m[2] for m in metadata)
)
)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--base_dir', default=os.path.expanduser('~/tacotron'))
parser.add_argument('--mrs_dir', required=False)
parser.add_argument('--mrs_username', required=False)
parser.add_argument('--output', default='training')
parser.add_argument(
'--dataset', required=True, choices=['amy', 'blizzard', 'ljspeech', 'kusal', 'mailabs','mrs']
)
parser.add_argument('--mailabs_books_dir',
help='absolute directory to the books for the mlailabs')
parser.add_argument(
'--books',
help='comma-seperated and no space name of books i.e hunter_space,pink_fairy_book,etc.',
)
parser.add_argument('--num_workers', type=int, default=cpu_count())
args = parser.parse_args()
if args.dataset == 'mailabs' and args.books is None:
parser.error("--books required if mailabs is chosen for dataset.")
if args.dataset == 'mailabs' and args.mailabs_books_dir is None:
parser.error(
"--mailabs_books_dir required if mailabs is chosen for dataset.")
print(hparams_debug_string())
if args.dataset == 'amy':
preprocess_amy(args)
elif args.dataset == 'blizzard':
preprocess_blizzard(args)
elif args.dataset == 'ljspeech':
preprocess_ljspeech(args)
elif args.dataset == 'kusal':
preprocess_kusal(args)
elif args.dataset == 'mailabs':
preprocess_mailabs(args)
elif args.dataset == 'mrs':
preprocess_mrs(args)
if __name__ == "__main__":
main()