forked from mrq/DL-Art-School
69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
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"""
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Master script that processes all MP3 files found in an input directory. Performs the following operations, per-file:
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1. Splits the file on silence intervals, throwing out all clips that are too short or long.
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2.
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"""
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import argparse
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import functools
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import os
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from multiprocessing.pool import ThreadPool
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from pydub import AudioSegment
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from pydub.exceptions import CouldntDecodeError
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from pydub.silence import split_on_silence
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from tqdm import tqdm
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from data.util import find_audio_files
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def report_progress(progress_file, file):
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with open(progress_file, 'a', encoding='utf-8') as f:
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f.write(f'{file}\n')
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def process_file(file, base_path, output_path, progress_file):
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# Hyper-parameters; feel free to adjust.
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minimum_duration = 4
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maximum_duration = 20
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# Part 1 is to split a large file into chunks.
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try:
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speech = AudioSegment.from_file(file)
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except CouldntDecodeError as e:
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print(e)
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report_progress(progress_file, file)
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return
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outdir = os.path.join(output_path, f'{os.path.relpath(file, base_path)[:-4]}').replace('.', '').strip()
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os.makedirs(outdir, exist_ok=True)
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chunks = split_on_silence(speech, min_silence_len=600, silence_thresh=-40, seek_step=100, keep_silence=50)
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for i in range(0, len(chunks)):
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if chunks[i].duration_seconds < minimum_duration or chunks[i].duration_seconds > maximum_duration:
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continue
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chunks[i].export(f"{outdir}/{i:05d}.mp3", format='mp3', parameters=["-ac", "1"])
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report_progress(progress_file, file)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('-path', type=str, help='Path to search for files', default='Y:\\sources\\big_podcast')
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parser.add_argument('-progress_file', type=str, help='Place to store all files that have already been processed', default='Y:\\sources\\big_podcast\\already_processed.txt')
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parser.add_argument('-output_path', type=str, help='Path for output files', default='Y:\\split\\big_podcast')
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parser.add_argument('-num_threads', type=int, help='Number of concurrent workers processing files.', default=4)
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args = parser.parse_args()
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processed_files = set()
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if os.path.exists(args.progress_file):
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with open(args.progress_file, 'r', encoding='utf-8') as f:
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for line in f.readlines():
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processed_files.add(line.strip())
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files = set(find_audio_files(args.path, include_nonwav=True))
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orig_len = len(files)
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files = files - processed_files
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print(f"Found {len(files)} files to process. Total processing is {100*(orig_len-len(files))/orig_len}% complete.")
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with ThreadPool(args.num_threads) as pool:
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list(tqdm(pool.imap(functools.partial(process_file, output_path=args.output_path, base_path=args.path, progress_file=args.progress_file), files), total=len(files)))
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