wehub-resource-sync
105 lines
4.1 KiB
Python
105 lines
4.1 KiB
Python
import re
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import librosa
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import numpy as np
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from scipy.io import wavfile
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def trans_f0_seq(feature_pit, transform):
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feature_pit = feature_pit * 2 ** (transform / 12)
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return round(feature_pit, 1)
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def trans_key(raw_data, key):
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warning_tag = False
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for i in raw_data:
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note_seq_list = i["note_seq"].split(" ")
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new_note_seq_list = []
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for note_seq in note_seq_list:
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if note_seq != "rest":
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new_note_seq = librosa.midi_to_note(librosa.note_to_midi(note_seq) + key, unicode=False)
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# new_note_seq = move_key(note_seq, key)
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new_note_seq_list.append(new_note_seq)
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else:
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new_note_seq_list.append(note_seq)
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i["note_seq"] = " ".join(new_note_seq_list)
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if i.get("f0_seq"):
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f0_seq_list = i["f0_seq"].split(" ")
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f0_seq_list = [float(x) for x in f0_seq_list]
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new_f0_seq_list = []
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for f0_seq in f0_seq_list:
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new_f0_seq = trans_f0_seq(f0_seq, key)
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new_f0_seq_list.append(str(new_f0_seq))
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i["f0_seq"] = " ".join(new_f0_seq_list)
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else:
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warning_tag = True
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if warning_tag:
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print("Warning: parts of f0_seq do not exist, please freeze the pitch line in the editor.\r\n")
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return raw_data
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def resample_align_curve(points: np.ndarray, original_timestep: float, target_timestep: float, align_length: int):
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t_max = (len(points) - 1) * original_timestep
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curve_interp = np.interp(
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np.arange(0, t_max, target_timestep),
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original_timestep * np.arange(len(points)),
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points
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).astype(points.dtype)
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delta_l = align_length - len(curve_interp)
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if delta_l < 0:
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curve_interp = curve_interp[:align_length]
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elif delta_l > 0:
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curve_interp = np.concatenate((curve_interp, np.full(delta_l, fill_value=curve_interp[-1])), axis=0)
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return curve_interp
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def parse_commandline_spk_mix(mix: str) -> dict:
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"""
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Parse speaker mix info from commandline
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:param mix: Input like "opencpop" or "opencpop|qixuan" or "opencpop:0.5|qixuan:0.5"
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:return: A dict whose keys are speaker names and values are proportions
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"""
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name_pattern = r'[0-9A-Za-z_-]+'
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proportion_pattern = r'\d+(\.\d+)?'
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single_pattern = rf'{name_pattern}(:{proportion_pattern})?'
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assert re.fullmatch(rf'{single_pattern}(\|{single_pattern})*', mix) is not None, f'Invalid mix pattern: {mix}'
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without_proportion = set()
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proportion_map = {}
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for component in mix.split('|'):
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# If already exists
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name_and_proportion = component.split(':')
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assert name_and_proportion[0] not in without_proportion and name_and_proportion[0] not in proportion_map, \
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f'Duplicate speaker name: {name_and_proportion[0]}'
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if ':' in component:
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proportion_map[name_and_proportion[0]] = float(name_and_proportion[1])
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else:
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without_proportion.add(name_and_proportion[0])
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sum_given_proportions = sum(proportion_map.values())
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assert sum_given_proportions < 1 or len(without_proportion) == 0, \
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'Proportion of all speakers should be specified if the sum of all given proportions are larger than 1.'
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for name in without_proportion:
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proportion_map[name] = (1 - sum_given_proportions) / len(without_proportion)
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sum_all_proportions = sum(proportion_map.values())
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assert sum_all_proportions > 0, 'Sum of all proportions should be positive.'
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for name in proportion_map:
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proportion_map[name] /= sum_all_proportions
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return proportion_map
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def cross_fade(a: np.ndarray, b: np.ndarray, idx: int):
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result = np.zeros(idx + b.shape[0])
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fade_len = a.shape[0] - idx
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np.copyto(dst=result[:idx], src=a[:idx])
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k = np.linspace(0, 1.0, num=fade_len, endpoint=True)
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result[idx: a.shape[0]] = (1 - k) * a[idx:] + k * b[: fade_len]
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np.copyto(dst=result[a.shape[0]:], src=b[fade_len:])
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return result
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def save_wav(wav, path, sr, norm=False):
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if norm:
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wav = wav / np.abs(wav).max()
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wav *= 32767
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# proposed by @dsmiller
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wavfile.write(path, sr, wav.astype(np.int16))
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