64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
import pickle
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from collections import defaultdict
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from pathlib import Path
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import librosa as librosa
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from torch.utils.data import Dataset
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import torch
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import variables as V
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from ml_lib.modules.utils import F_x
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class BinaryMasksDataset(Dataset):
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_to_label = defaultdict(lambda: -1)
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_to_label.update(dict(clear=V.CLEAR, mask=V.MASK))
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@property
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def sample_shape(self):
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return self[0][0].shape
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def __init__(self, data_root, setting, transforms=None):
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assert isinstance(setting, str), f'Setting has to be a string, but was: {type(setting)}.'
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assert setting in V.DATA_OPTIONS, f'Setting must match one of: {V.DATA_OPTIONS}.'
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assert callable(transforms) or None, f'Transforms has to be callable, but was: {type(transforms)}'
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super(BinaryMasksDataset, self).__init__()
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self.data_root = Path(data_root)
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self.setting = setting
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self._transforms = transforms or F_x()
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self._labels = self._build_labels()
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self._wav_folder = self.data_root / 'wav'
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self._wav_files = list(sorted(self._labels.keys()))
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self._mel_folder = self.data_root / 'raw_mel'
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def _build_labels(self):
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with open(Path(self.data_root) / 'lab' / 'labels.csv', mode='r') as f:
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# Exclude the header
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_ = next(f)
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labeldict = dict()
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for row in f:
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if self.setting not in row:
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continue
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filename, label = row.strip().split(',')
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labeldict[filename] = self._to_label[label.lower()]
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return labeldict
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def __len__(self):
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return len(self._labels)
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def __getitem__(self, item):
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key = self._wav_files[item]
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filename = key[:-4] + '.pik'
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if not (self._mel_folder / filename).exists():
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raw_sample, sr = librosa.core.load(self._wav_folder / self._wav_files[item])
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transformed_sample = self._transforms(raw_sample)
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self._mel_folder.mkdir(exist_ok=True, parents=True)
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with (self._mel_folder / filename).open(mode='wb') as f:
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pickle.dump(transformed_sample, f, protocol=pickle.HIGHEST_PROTOCOL)
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with (self._mel_folder / filename).open(mode='rb') as f:
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sample = pickle.load(f, fix_imports=True)
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label = torch.as_tensor(self._labels[key], dtype=torch.float)
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return sample, label
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