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# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import copy
from concurrent.futures import ThreadPoolExecutor, Future
from dataclasses import dataclass, fields
from contextlib import ExitStack
import gzip
import json
import logging
import os
from pathlib import Path
import random
import sys
import typing as tp
import torch
import torch.nn.functional as F
from .audio import audio_read, audio_info
from .audio_utils import convert_audio
from .zip import PathInZip
try:
import dora
except ImportError:
dora = None # type: ignore
@dataclass(order=True)
class BaseInfo:
@classmethod
def _dict2fields(cls, dictionary: dict):
return {
field.name: dictionary[field.name]
for field in fields(cls) if field.name in dictionary
}
@classmethod
def from_dict(cls, dictionary: dict):
_dictionary = cls._dict2fields(dictionary)
return cls(**_dictionary)
def to_dict(self):
return {
field.name: self.__getattribute__(field.name)
for field in fields(self)
}
@dataclass(order=True)
class AudioMeta(BaseInfo):
path: str
duration: float
sample_rate: int
amplitude: tp.Optional[float] = None
weight: tp.Optional[float] = None
# info_path is used to load additional information about the audio file that is stored in zip files.
info_path: tp.Optional[PathInZip] = None
@classmethod
def from_dict(cls, dictionary: dict):
base = cls._dict2fields(dictionary)
if 'info_path' in base and base['info_path'] is not None:
base['info_path'] = PathInZip(base['info_path'])
return cls(**base)
def to_dict(self):
d = super().to_dict()
if d['info_path'] is not None:
d['info_path'] = str(d['info_path'])
return d
@dataclass(order=True)
class SegmentInfo(BaseInfo):
meta: AudioMeta
seek_time: float
n_frames: int # actual number of frames without padding
total_frames: int # total number of frames, padding included
sample_rate: int # actual sample rate
DEFAULT_EXTS = ['.wav', '.mp3', '.flac', '.ogg', '.m4a']
logger = logging.getLogger(__name__)
def _get_audio_meta(file_path: str, minimal: bool = True) -> AudioMeta:
"""AudioMeta from a path to an audio file.
Args:
file_path (str): Resolved path of valid audio file.
minimal (bool): Whether to only load the minimal set of metadata (takes longer if not).
Returns:
AudioMeta: Audio file path and its metadata.
"""
info = audio_info(file_path)
amplitude: tp.Optional[float] = None
if not minimal:
wav, sr = audio_read(file_path)
amplitude = wav.abs().max().item()
return AudioMeta(file_path, info.duration, info.sample_rate, amplitude)
def _resolve_audio_meta(m: AudioMeta, fast: bool = True) -> AudioMeta:
"""If Dora is available as a dependency, try to resolve potential relative paths
in list of AudioMeta. This method is expected to be used when loading meta from file.
Args:
m (AudioMeta): Audio meta to resolve.
fast (bool): If True, uses a really fast check for determining if a file is already absolute or not.
Only valid on Linux/Mac.
Returns:
AudioMeta: Audio meta with resolved path.
"""
def is_abs(m):
if fast:
return str(m)[0] == '/'
else:
os.path.isabs(str(m))
if not dora:
return m
if not is_abs(m.path):
m.path = dora.git_save.to_absolute_path(m.path)
if m.info_path is not None and not is_abs(m.info_path.zip_path):
m.info_path.zip_path = dora.git_save.to_absolute_path(m.path)
return m
def find_audio_files(path: tp.Union[Path, str],
exts: tp.List[str] = DEFAULT_EXTS,
resolve: bool = True,
minimal: bool = True,
progress: bool = False,
workers: int = 0) -> tp.List[AudioMeta]:
"""Build a list of AudioMeta from a given path,
collecting relevant audio files and fetching meta info.
Args:
path (str or Path): Path to folder containing audio files.
exts (list of str): List of file extensions to consider for audio files.
minimal (bool): Whether to only load the minimal set of metadata (takes longer if not).
progress (bool): Whether to log progress on audio files collection.
workers (int): number of parallel workers, if 0, use only the current thread.
Returns:
List[AudioMeta]: List of audio file path and its metadata.
"""
audio_files = []
futures: tp.List[Future] = []
pool: tp.Optional[ThreadPoolExecutor] = None
with ExitStack() as stack:
if workers > 0:
pool = ThreadPoolExecutor(workers)
stack.enter_context(pool)
if progress:
print("Finding audio files...")
for root, folders, files in os.walk(path, followlinks=True):
for file in files:
full_path = Path(root) / file
if full_path.suffix.lower() in exts:
audio_files.append(full_path)
if pool is not None:
futures.append(pool.submit(_get_audio_meta, str(audio_files[-1]), minimal))
if progress:
print(format(len(audio_files), " 8d"), end='\r', file=sys.stderr)
if progress:
print("Getting audio metadata...")
meta: tp.List[AudioMeta] = []
for idx, file_path in enumerate(audio_files):
try:
if pool is None:
m = _get_audio_meta(str(file_path), minimal)
else:
m = futures[idx].result()
if resolve:
m = _resolve_audio_meta(m)
except Exception as err:
print("Error with", str(file_path), err, file=sys.stderr)
continue
meta.append(m)
if progress:
print(format((1 + idx) / len(audio_files), " 3.1%"), end='\r', file=sys.stderr)
meta.sort()
return meta
def load_audio_meta(path: tp.Union[str, Path],
resolve: bool = True, fast: bool = True) -> tp.List[AudioMeta]:
"""Load list of AudioMeta from an optionally compressed json file.
Args:
path (str or Path): Path to JSON file.
resolve (bool): Whether to resolve the path from AudioMeta (default=True).
fast (bool): activates some tricks to make things faster.
Returns:
List[AudioMeta]: List of audio file path and its total duration.
"""
open_fn = gzip.open if str(path).lower().endswith('.gz') else open
with open_fn(path, 'rb') as fp: # type: ignore
lines = fp.readlines()
meta = []
for line in lines:
d = json.loads(line)
m = AudioMeta.from_dict(d)
if resolve:
m = _resolve_audio_meta(m, fast=fast)
meta.append(m)
return meta
def save_audio_meta(path: tp.Union[str, Path], meta: tp.List[AudioMeta]):
"""Save the audio metadata to the file pointer as json.
Args:
path (str or Path): Path to JSON file.
metadata (list of BaseAudioMeta): List of audio meta to save.
"""
Path(path).parent.mkdir(exist_ok=True, parents=True)
open_fn = gzip.open if str(path).lower().endswith('.gz') else open
with open_fn(path, 'wb') as fp: # type: ignore
for m in meta:
json_str = json.dumps(m.to_dict()) + '\n'
json_bytes = json_str.encode('utf-8')
fp.write(json_bytes)
def main():
logging.basicConfig(stream=sys.stderr, level=logging.INFO)
parser = argparse.ArgumentParser(
prog='audio_dataset',
description='Generate .jsonl files by scanning a folder.')
parser.add_argument('root', help='Root folder with all the audio files')
parser.add_argument('output_meta_file',
help='Output file to store the metadata, ')
parser.add_argument('--complete',
action='store_false', dest='minimal', default=True,
help='Retrieve all metadata, even the one that are expansive '
'to compute (e.g. normalization).')
parser.add_argument('--resolve',
action='store_true', default=False,
help='Resolve the paths to be absolute and with no symlinks.')
parser.add_argument('--workers',
default=10, type=int,
help='Number of workers.')
args = parser.parse_args()
meta = find_audio_files(args.root, DEFAULT_EXTS, progress=True,
resolve=args.resolve, minimal=args.minimal, workers=args.workers)
save_audio_meta(args.output_meta_file, meta)
if __name__ == '__main__':
main()
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