Delete spec_utils.py

lib/spec_utils.py

@@ -1,136 +0,0 @@
-import os
-
-import librosa
-import numpy as np
-import soundfile as sf
-import torch
-
-
-def crop_center(h1, h2, concat=True):
-    # s_freq = (h2.shape[2] - h1.shape[2]) // 2
-    # e_freq = s_freq + h1.shape[2]
-    h1_shape = h1.size()
-    h2_shape = h2.size()
-    if h2_shape[3] < h1_shape[3]:
-        raise ValueError('h2_shape[3] must be greater than h1_shape[3]')
-    s_time = (h2_shape[3] - h1_shape[3]) // 2
-    e_time = s_time + h1_shape[3]
-    h2 = h2[:, :, :, s_time:e_time]
-    if concat:
-        return torch.cat([h1, h2], dim=1)
-    else:
-        return h2
-
-
-def calc_spec(X, hop_length):
-    n_fft = (hop_length - 1) * 2
-    audio_left = np.asfortranarray(X[0])
-    audio_right = np.asfortranarray(X[1])
-    spec_left = librosa.stft(audio_left, n_fft, hop_length=hop_length)
-    spec_right = librosa.stft(audio_right, n_fft, hop_length=hop_length)
-    spec = np.asfortranarray([spec_left, spec_right])
-
-    return spec
-
-
-def mask_uninformative(mask, ref, thres=0.3, min_range=64, fade_area=32):
-    if min_range < fade_area * 2:
-        raise ValueError('min_range must be >= fade_area * 2')
-    idx = np.where(ref.mean(axis=(0, 1)) < thres)[0]
-    starts = np.insert(idx[np.where(np.diff(idx) != 1)[0] + 1], 0, idx[0])
-    ends = np.append(idx[np.where(np.diff(idx) != 1)[0]], idx[-1])
-    uninformative = np.where(ends - starts > min_range)[0]
-    if len(uninformative) > 0:
-        starts = starts[uninformative]
-        ends = ends[uninformative]
-        old_e = None
-        for s, e in zip(starts, ends):
-            if old_e is not None and s - old_e < fade_area:
-                s = old_e - fade_area * 2
-            elif s != 0:
-                start_mask = mask[:, :, s:s + fade_area]
-                np.clip(
-                    start_mask + np.linspace(0, 1, fade_area), 0, 1,
-                    out=start_mask)
-            if e != mask.shape[2]:
-                end_mask = mask[:, :, e - fade_area:e]
-                np.clip(
-                    end_mask + np.linspace(1, 0, fade_area), 0, 1,
-                    out=end_mask)
-            mask[:, :, s + fade_area:e - fade_area] = 1
-            old_e = e
-
-    return mask
-
-
-def align_wave_head_and_tail(a, b, sr):
-    a_mono = a[:, :sr * 4].sum(axis=0)
-    b_mono = b[:, :sr * 4].sum(axis=0)
-    a_mono -= a_mono.mean()
-    b_mono -= b_mono.mean()
-    offset = len(a_mono) - 1
-    delay = np.argmax(np.correlate(a_mono, b_mono, 'full')) - offset
-
-    if delay > 0:
-        a = a[:, delay:]
-    else:
-        b = b[:, np.abs(delay):]
-    if a.shape[1] < b.shape[1]:
-        b = b[:, :a.shape[1]]
-    else:
-        a = a[:, :b.shape[1]]
-
-    return a, b
-
-
-def cache_or_load(mix_path, inst_path, sr, hop_length):
-    _, mix_ext = os.path.splitext(mix_path)
-    _, inst_ext = os.path.splitext(inst_path)
-    spec_mix_path = mix_path.replace(mix_ext, '.npy')
-    spec_inst_path = inst_path.replace(inst_ext, '.npy')
-
-    if os.path.exists(spec_mix_path) and os.path.exists(spec_inst_path):
-        X = np.load(spec_mix_path)
-        y = np.load(spec_inst_path)
-    else:
-        X, _ = librosa.load(
-            mix_path, sr, False, dtype=np.float32, res_type='kaiser_fast')
-        y, _ = librosa.load(
-            inst_path, sr, False, dtype=np.float32, res_type='kaiser_fast')
-        X, _ = librosa.effects.trim(X)
-        y, _ = librosa.effects.trim(y)
-        X, y = align_wave_head_and_tail(X, y, sr)
-
-        X = np.abs(calc_spec(X, hop_length))
-        y = np.abs(calc_spec(y, hop_length))
-
-        _, ext = os.path.splitext(mix_path)
-        np.save(spec_mix_path, X)
-        np.save(spec_inst_path, y)
-
-    return X, y
-
-
-def spec_to_wav(mag, phase, hop_length):
-    spec = mag * phase
-    spec_left = np.asfortranarray(spec[0])
-    spec_right = np.asfortranarray(spec[1])
-    wav_left = librosa.istft(spec_left, hop_length=hop_length)
-    wav_right = librosa.istft(spec_right, hop_length=hop_length)
-    wav = np.asfortranarray([wav_left, wav_right])
-
-    return wav
-
-
-if __name__ == "__main__":
-    import sys
-    X, _ = librosa.load(
-        sys.argv[1], 44100, False, dtype=np.float32, res_type='kaiser_fast')
-    y, _ = librosa.load(
-        sys.argv[2], 44100, False, dtype=np.float32, res_type='kaiser_fast')
-    X, _ = librosa.effects.trim(X)
-    y, _ = librosa.effects.trim(y)
-    X, y = align_wave_head_and_tail(X, y, 44100)
-    sf.write('test_i.wav', y.T, 44100)
-    sf.write('test_m.wav', X.T, 44100)
-    sf.write('test_v.wav', (X - y).T, 44100)