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41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
import pyworld
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import numpy as np
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from const import PitchExtractorType
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import torch
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from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
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class HarvestPitchExtractor(PitchExtractor):
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def __init__(self):
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super().__init__()
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self.pitchExtractorType: PitchExtractorType = "harvest"
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self.f0_min = 50
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self.f0_max = 1100
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self.sapmle_rate = 16000
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self.uv_interp = True
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def extract(self, audio: torch.Tensor, pitchf, f0_up_key, sr, window, silence_front=0):
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audio = audio.detach().cpu().numpy()
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start_frame = int(silence_front * self.sapmle_rate / window)
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real_silence_front = start_frame * window / self.sapmle_rate
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audio = audio[int(np.round(real_silence_front * self.sapmle_rate)):]
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f0, _ = pyworld.harvest(
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audio.astype('double'),
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16000,
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f0_floor=50,
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f0_ceil=1100,
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frame_period=(1000 * window / self.sapmle_rate))
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pitchf[-f0.shape[0]:] = f0[:pitchf.shape[0]]
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f0 = pitchf
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if self.uv_interp:
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uv = f0 == 0
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if len(f0[~uv]) > 0:
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f0[uv] = np.interp(np.where(uv)[0], np.where(~uv)[0], f0[~uv])
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f0[f0 < 50] = 50
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f0 = f0 * 2 ** (float(f0_up_key) / 12)
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return f0
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