add input wav and delay time monitor (#1295)
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a47aad5a3c
commit
ac1397f3f9
85
gui_v1.py
85
gui_v1.py
@ -14,7 +14,7 @@ sys.path.append(now_dir)
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import multiprocessing
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logger = logging.getLogger(__name__)
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stream_latency = -1
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class Harvest(multiprocessing.Process):
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def __init__(self, inp_q, opt_q):
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@ -100,7 +100,8 @@ if __name__ == "__main__":
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def __init__(self) -> None:
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self.config = GUIConfig()
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self.flag_vc = False
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self.function = 'vc'
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self.delay_time = 0
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self.launcher()
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def load(self):
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@ -112,6 +113,10 @@ if __name__ == "__main__":
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data["harvest"] = data["f0method"] == "harvest"
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data["crepe"] = data["f0method"] == "crepe"
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data["rmvpe"] = data["f0method"] == "rmvpe"
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if data["sg_input_device"] not in input_devices:
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data["sg_input_device"] = input_devices[sd.default.device[0]]
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if data["sg_output_device"] not in output_devices:
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data["sg_output_device"] = output_devices[sd.default.device[1]]
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except:
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with open("configs/config.json", "w") as j:
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data = {
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@ -342,6 +347,22 @@ if __name__ == "__main__":
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[
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sg.Button(i18n("开始音频转换"), key="start_vc"),
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sg.Button(i18n("停止音频转换"), key="stop_vc"),
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sg.Radio(
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i18n("输入监听"),
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"function",
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key="im",
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default=False,
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enable_events=True,
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),
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sg.Radio(
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i18n("输出变声"),
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"function",
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key="vc",
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default=True,
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enable_events=True,
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),
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sg.Text(i18n("算法延迟(ms):")),
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sg.Text("0", key="delay_time"),
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sg.Text(i18n("推理时间(ms):")),
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sg.Text("0", key="infer_time"),
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],
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@ -403,9 +424,16 @@ if __name__ == "__main__":
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}
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with open("configs/config.json", "w") as j:
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json.dump(settings, j)
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global stream_latency
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while stream_latency < 0:
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time.sleep(0.01)
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self.delay_time = stream_latency + values["block_time"] + values["crossfade_length"] + 0.01
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if values["I_noise_reduce"]:
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self.delay_time += values["crossfade_length"]
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self.window["delay_time"].update(int(self.delay_time * 1000))
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if event == "stop_vc" and self.flag_vc == True:
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self.flag_vc = False
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stream_latency = -1
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# Parameter hot update
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if event == "threhold":
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self.config.threhold = values["threhold"]
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@ -423,11 +451,17 @@ if __name__ == "__main__":
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self.config.f0method = event
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elif event == "I_noise_reduce":
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self.config.I_noise_reduce = values["I_noise_reduce"]
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if stream_latency > 0:
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self.delay_time += (1 if values["I_noise_reduce"] else -1) * values["crossfade_length"]
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self.window["delay_time"].update(int(self.delay_time * 1000))
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elif event == "O_noise_reduce":
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self.config.O_noise_reduce = values["O_noise_reduce"]
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elif event in ["vc", "im"]:
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self.function = event
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elif event != "start_vc" and self.flag_vc == True:
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# Other parameters do not support hot update
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self.flag_vc = False
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stream_latency = -1
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def set_values(self, values):
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if len(values["pth_path"].strip()) == 0:
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@ -565,7 +599,9 @@ if __name__ == "__main__":
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blocksize=self.block_frame,
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samplerate=self.config.samplerate,
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dtype="float32",
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):
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) as stream:
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global stream_latency
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stream_latency = stream.latency[-1]
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while self.flag_vc:
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time.sleep(self.config.block_time)
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logger.debug("Audio block passed.")
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@ -597,7 +633,7 @@ if __name__ == "__main__":
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self.block_frame_16k :
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].clone()
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# input noise reduction and resampling
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if self.config.I_noise_reduce:
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if self.config.I_noise_reduce and self.function == 'vc':
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input_wav = self.input_wav[
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-self.crossfade_frame - self.block_frame - 2 * self.zc :
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]
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@ -621,23 +657,28 @@ if __name__ == "__main__":
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self.input_wav[-self.block_frame - 2 * self.zc :]
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)[160:]
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# infer
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f0_extractor_frame = self.block_frame_16k + 800
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if self.config.f0method == "rmvpe":
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f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1) - 160
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infer_wav = self.rvc.infer(
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self.input_wav_res,
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self.input_wav_res[-f0_extractor_frame:].cpu().numpy(),
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self.block_frame_16k,
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self.valid_rate,
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self.pitch,
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self.pitchf,
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self.config.f0method,
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)
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infer_wav = infer_wav[
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-self.crossfade_frame - self.sola_search_frame - self.block_frame :
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]
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if self.function == 'vc':
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f0_extractor_frame = self.block_frame_16k + 800
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if self.config.f0method == "rmvpe":
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f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1) - 160
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infer_wav = self.rvc.infer(
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self.input_wav_res,
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self.input_wav_res[-f0_extractor_frame:].cpu().numpy(),
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self.block_frame_16k,
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self.valid_rate,
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self.pitch,
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self.pitchf,
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self.config.f0method,
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)
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infer_wav = infer_wav[
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-self.crossfade_frame - self.sola_search_frame - self.block_frame :
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]
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else:
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infer_wav = self.input_wav[
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-self.crossfade_frame - self.sola_search_frame - self.block_frame :
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].clone()
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# output noise reduction
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if self.config.O_noise_reduce:
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if (self.config.O_noise_reduce and self.function == 'vc') or (self.config.I_noise_reduce and self.function == 'im'):
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self.output_buffer[: -self.block_frame] = self.output_buffer[
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self.block_frame :
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].clone()
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@ -646,7 +687,7 @@ if __name__ == "__main__":
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infer_wav.unsqueeze(0), self.output_buffer.unsqueeze(0)
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).squeeze(0)
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# volume envelop mixing
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if self.config.rms_mix_rate < 1:
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if self.config.rms_mix_rate < 1 and self.function == 'vc':
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rms1 = librosa.feature.rms(
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y=self.input_wav_res[-160 * infer_wav.shape[0] // self.zc :]
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.cpu()
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@ -211,13 +211,6 @@ class TorchGate(torch.nn.Module):
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Returns:
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torch.Tensor: The denoised audio signal, with the same shape as the input signal.
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"""
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assert x.ndim == 2
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if x.shape[-1] < self.win_length * 2:
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raise Exception(f"x must be bigger than {self.win_length * 2}")
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assert xn is None or xn.ndim == 1 or xn.ndim == 2
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if xn is not None and xn.shape[-1] < self.win_length * 2:
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raise Exception(f"xn must be bigger than {self.win_length * 2}")
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# Compute short-time Fourier transform (STFT)
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X = torch.stft(
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