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# Copyright (c) Facebook, Inc. and its affiliates.
# 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 os
from collections import defaultdict, namedtuple
from pathlib import Path
import musdb
import numpy as np
import torch as th
import tqdm
from torch.utils.data import DataLoader
from .audio import AudioFile
ChunkInfo = namedtuple("ChunkInfo", ["file_index", "offset", "local_index"])
class Rawset:
"""
Dataset of raw, normalized, float32 audio files
"""
def __init__(self, path, samples=None, stride=None, channels=2, streams=None):
self.path = Path(path)
self.channels = channels
self.samples = samples
if stride is None:
stride = samples if samples is not None else 0
self.stride = stride
entries = defaultdict(list)
for root, folders, files in os.walk(self.path, followlinks=True):
folders.sort()
files.sort()
for file in files:
if file.endswith(".raw"):
path = Path(root) / file
name, stream = path.stem.rsplit('.', 1)
entries[(path.parent.relative_to(self.path), name)].append(int(stream))
self._entries = list(entries.keys())
sizes = []
self._lengths = []
ref_streams = sorted(entries[self._entries[0]])
assert ref_streams == list(range(len(ref_streams)))
if streams is None:
self.streams = ref_streams
else:
self.streams = streams
for entry in sorted(entries.keys()):
streams = entries[entry]
assert sorted(streams) == ref_streams
file = self._path(*entry)
length = file.stat().st_size // (4 * channels)
if samples is None:
sizes.append(1)
else:
if length < samples:
self._entries.remove(entry)
continue
sizes.append((length - samples) // stride + 1)
self._lengths.append(length)
if not sizes:
raise ValueError(f"Empty dataset {self.path}")
self._cumulative_sizes = np.cumsum(sizes)
self._sizes = sizes
def __len__(self):
return self._cumulative_sizes[-1]
@property
def total_length(self):
return sum(self._lengths)
def chunk_info(self, index):
file_index = np.searchsorted(self._cumulative_sizes, index, side='right')
if file_index == 0:
local_index = index
else:
local_index = index - self._cumulative_sizes[file_index - 1]
return ChunkInfo(offset=local_index * self.stride,
file_index=file_index,
local_index=local_index)
def _path(self, folder, name, stream=0):
return self.path / folder / (name + f'.{stream}.raw')
def __getitem__(self, index):
chunk = self.chunk_info(index)
entry = self._entries[chunk.file_index]
length = self.samples or self._lengths[chunk.file_index]
streams = []
to_read = length * self.channels * 4
for stream_index, stream in enumerate(self.streams):
offset = chunk.offset * 4 * self.channels
file = open(self._path(*entry, stream=stream), 'rb')
file.seek(offset)
content = file.read(to_read)
assert len(content) == to_read
content = np.frombuffer(content, dtype=np.float32)
content = content.copy() # make writable
streams.append(th.from_numpy(content).view(length, self.channels).t())
return th.stack(streams, dim=0)
def name(self, index):
chunk = self.chunk_info(index)
folder, name = self._entries[chunk.file_index]
return folder / name
class MusDBSet:
def __init__(self, mus, streams=slice(None), samplerate=44100, channels=2):
self.mus = mus
self.streams = streams
self.samplerate = samplerate
self.channels = channels
def __len__(self):
return len(self.mus.tracks)
def __getitem__(self, index):
track = self.mus.tracks[index]
return (track.name, AudioFile(track.path).read(channels=self.channels,
seek_time=0,
streams=self.streams,
samplerate=self.samplerate))
def build_raw(mus, destination, normalize, workers, samplerate, channels):
destination.mkdir(parents=True, exist_ok=True)
loader = DataLoader(MusDBSet(mus, channels=channels, samplerate=samplerate),
batch_size=1,
num_workers=workers,
collate_fn=lambda x: x[0])
for name, streams in tqdm.tqdm(loader):
if normalize:
ref = streams[0].mean(dim=0) # use mono mixture as reference
streams = (streams - ref.mean()) / ref.std()
for index, stream in enumerate(streams):
open(destination / (name + f'.{index}.raw'), "wb").write(stream.t().numpy().tobytes())
def main():
parser = argparse.ArgumentParser('rawset')
parser.add_argument('--workers', type=int, default=10)
parser.add_argument('--samplerate', type=int, default=44100)
parser.add_argument('--channels', type=int, default=2)
parser.add_argument('musdb', type=Path)
parser.add_argument('destination', type=Path)
args = parser.parse_args()
build_raw(musdb.DB(root=args.musdb, subsets=["train"], split="train"),
args.destination / "train",
normalize=True,
channels=args.channels,
samplerate=args.samplerate,
workers=args.workers)
build_raw(musdb.DB(root=args.musdb, subsets=["train"], split="valid"),
args.destination / "valid",
normalize=True,
samplerate=args.samplerate,
channels=args.channels,
workers=args.workers)
if __name__ == "__main__":
main()
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