66 lines
2.8 KiB
Python
66 lines
2.8 KiB
Python
|
|
|
|
"""
|
|
Master script that processes all MP3 files found in an input directory. Splits those files up into sub-files of a
|
|
predetermined duration.
|
|
"""
|
|
import argparse
|
|
import functools
|
|
import os
|
|
from multiprocessing.pool import ThreadPool
|
|
|
|
import torch
|
|
import torchaudio
|
|
from tqdm import tqdm
|
|
|
|
from data.util import find_audio_files, find_files_of_type
|
|
from utils.util import load_audio
|
|
|
|
|
|
def report_progress(progress_file, file):
|
|
with open(progress_file, 'a', encoding='utf-8') as f:
|
|
f.write(f'{file}\n')
|
|
|
|
|
|
def process_file(file, base_path, output_path, progress_file, duration_per_clip, sampling_rate=22050):
|
|
try:
|
|
audio = load_audio(file, sampling_rate)
|
|
except:
|
|
print(f"Error loading file {file}")
|
|
report_progress(progress_file, file)
|
|
return
|
|
|
|
outdir = os.path.join(output_path, f'{os.path.relpath(file, base_path)[:-4]}').replace('.', '').strip()
|
|
os.makedirs(outdir, exist_ok=True)
|
|
splits = torch.split(audio, duration_per_clip * sampling_rate, dim=-1)
|
|
for i, spl in enumerate(splits):
|
|
if spl.shape[-1] != duration_per_clip*sampling_rate:
|
|
continue # In general, this just means "skip the last item".
|
|
torchaudio.save(f'{outdir}/{i:05d}.wav', spl.unsqueeze(0), sampling_rate, encoding="PCM_S")
|
|
report_progress(progress_file, file)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument('-path', type=str, help='Path to search for files', default='Y:\\sources\\manual_podcasts_music')
|
|
parser.add_argument('-progress_file', type=str, help='Place to store all files that have already been processed', default='Y:\\sources\\manual_podcasts_music\\already_processed.txt')
|
|
parser.add_argument('-output_path', type=str, help='Path for output files', default='Y:\\split\\manual_podcasts_music')
|
|
parser.add_argument('-num_threads', type=int, help='Number of concurrent workers processing files.', default=4)
|
|
parser.add_argument('-duration', type=int, help='Duration per clip in seconds', default=30)
|
|
args = parser.parse_args()
|
|
|
|
processed_files = set()
|
|
if os.path.exists(args.progress_file):
|
|
with open(args.progress_file, 'r', encoding='utf-8') as f:
|
|
for line in f.readlines():
|
|
processed_files.add(line.strip())
|
|
|
|
files = set(find_audio_files(args.path, include_nonwav=True))
|
|
orig_len = len(files)
|
|
files = files - processed_files
|
|
print(f"Found {len(files)} files to process. Total processing is {100*(orig_len-len(files))/orig_len}% complete.")
|
|
|
|
with ThreadPool(args.num_threads) as pool:
|
|
list(tqdm(pool.imap(functools.partial(process_file, output_path=args.output_path, base_path=args.path,
|
|
progress_file=args.progress_file, duration_per_clip=args.duration), files), total=len(files)))
|