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import os |
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import sys |
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from dotenv import load_dotenv |
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import shutil |
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|
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load_dotenv() |
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|
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os.environ["OMP_NUM_THREADS"] = "4" |
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if sys.platform == "darwin": |
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1" |
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|
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now_dir = os.getcwd() |
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sys.path.append(now_dir) |
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import multiprocessing |
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flag_vc = False |
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|
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def printt(strr, *args): |
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if len(args) == 0: |
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print(strr) |
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else: |
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print(strr % args) |
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|
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def phase_vocoder(a, b, fade_out, fade_in): |
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window = torch.sqrt(fade_out * fade_in) |
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fa = torch.fft.rfft(a * window) |
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fb = torch.fft.rfft(b * window) |
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absab = torch.abs(fa) + torch.abs(fb) |
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n = a.shape[0] |
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if n % 2 == 0: |
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absab[1:-1] *= 2 |
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else: |
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absab[1:] *= 2 |
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phia = torch.angle(fa) |
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phib = torch.angle(fb) |
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deltaphase = phib - phia |
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deltaphase = deltaphase - 2 * np.pi * torch.floor(deltaphase / 2 / np.pi + 0.5) |
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w = 2 * np.pi * torch.arange(n // 2 + 1).to(a) + deltaphase |
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t = torch.arange(n).unsqueeze(-1).to(a) / n |
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result = ( |
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a * (fade_out**2) |
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+ b * (fade_in**2) |
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+ torch.sum(absab * torch.cos(w * t + phia), -1) * window / n |
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) |
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return result |
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class Harvest(multiprocessing.Process): |
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def __init__(self, inp_q, opt_q): |
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multiprocessing.Process.__init__(self) |
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self.inp_q = inp_q |
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self.opt_q = opt_q |
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|
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def run(self): |
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import numpy as np |
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import pyworld |
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|
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while 1: |
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idx, x, res_f0, n_cpu, ts = self.inp_q.get() |
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f0, t = pyworld.harvest( |
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x.astype(np.double), |
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fs=16000, |
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f0_ceil=1100, |
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f0_floor=50, |
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frame_period=10, |
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) |
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res_f0[idx] = f0 |
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if len(res_f0.keys()) >= n_cpu: |
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self.opt_q.put(ts) |
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|
|
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if __name__ == "__main__": |
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import json |
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import multiprocessing |
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import re |
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import threading |
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import time |
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import traceback |
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from multiprocessing import Queue, cpu_count |
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from queue import Empty |
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|
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import librosa |
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from tools.torchgate import TorchGate |
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import numpy as np |
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import PySimpleGUI as sg |
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import sounddevice as sd |
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import torch |
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import torch.nn.functional as F |
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import torchaudio.transforms as tat |
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|
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import tools.rvc_for_realtime as rvc_for_realtime |
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from i18n.i18n import I18nAuto |
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from configs.config import Config |
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|
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i18n = I18nAuto() |
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|
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current_dir = os.getcwd() |
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inp_q = Queue() |
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opt_q = Queue() |
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n_cpu = min(cpu_count(), 8) |
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for _ in range(n_cpu): |
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Harvest(inp_q, opt_q).start() |
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|
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class GUIConfig: |
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def __init__(self) -> None: |
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self.pth_path: str = "" |
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self.index_path: str = "" |
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self.pitch: int = 0 |
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self.sr_type: str = "sr_model" |
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self.block_time: float = 0.25 |
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self.threhold: int = -60 |
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self.crossfade_time: float = 0.05 |
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self.extra_time: float = 2.5 |
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self.I_noise_reduce: bool = False |
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self.O_noise_reduce: bool = False |
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self.use_pv: bool = False |
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self.rms_mix_rate: float = 0.0 |
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self.index_rate: float = 0.0 |
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self.n_cpu: int = min(n_cpu, 4) |
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self.f0method: str = "fcpe" |
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self.sg_hostapi: str = "" |
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self.wasapi_exclusive: bool = False |
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self.sg_input_device: str = "" |
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self.sg_output_device: str = "" |
|
|
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class GUI: |
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def __init__(self) -> None: |
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self.gui_config = GUIConfig() |
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self.config = Config() |
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self.function = "vc" |
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self.delay_time = 0 |
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self.hostapis = None |
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self.input_devices = None |
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self.output_devices = None |
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self.input_devices_indices = None |
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self.output_devices_indices = None |
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self.stream = None |
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self.update_devices() |
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self.launcher() |
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|
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def load(self): |
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try: |
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if not os.path.exists("configs/inuse/config.json"): |
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shutil.copy("configs/config.json", "configs/inuse/config.json") |
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with open("configs/inuse/config.json", "r") as j: |
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data = json.load(j) |
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data["sr_model"] = data["sr_type"] == "sr_model" |
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data["sr_device"] = data["sr_type"] == "sr_device" |
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data["pm"] = data["f0method"] == "pm" |
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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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data["fcpe"] = data["f0method"] == "fcpe" |
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if data["sg_hostapi"] in self.hostapis: |
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self.update_devices(hostapi_name=data["sg_hostapi"]) |
|
if ( |
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data["sg_input_device"] not in self.input_devices |
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or data["sg_output_device"] not in self.output_devices |
|
): |
|
self.update_devices() |
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data["sg_hostapi"] = self.hostapis[0] |
|
data["sg_input_device"] = self.input_devices[ |
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self.input_devices_indices.index(sd.default.device[0]) |
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] |
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data["sg_output_device"] = self.output_devices[ |
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self.output_devices_indices.index(sd.default.device[1]) |
|
] |
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else: |
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data["sg_hostapi"] = self.hostapis[0] |
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data["sg_input_device"] = self.input_devices[ |
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self.input_devices_indices.index(sd.default.device[0]) |
|
] |
|
data["sg_output_device"] = self.output_devices[ |
|
self.output_devices_indices.index(sd.default.device[1]) |
|
] |
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except: |
|
with open("configs/inuse/config.json", "w") as j: |
|
data = { |
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"pth_path": "", |
|
"index_path": "", |
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"sg_hostapi": self.hostapis[0], |
|
"sg_wasapi_exclusive": False, |
|
"sg_input_device": self.input_devices[ |
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self.input_devices_indices.index(sd.default.device[0]) |
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], |
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"sg_output_device": self.output_devices[ |
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self.output_devices_indices.index(sd.default.device[1]) |
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], |
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"sr_type": "sr_model", |
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"threhold": -60, |
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"pitch": 0, |
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"index_rate": 0, |
|
"rms_mix_rate": 0, |
|
"block_time": 0.25, |
|
"crossfade_length": 0.05, |
|
"extra_time": 2.5, |
|
"n_cpu": 4, |
|
"f0method": "rmvpe", |
|
"use_jit": False, |
|
"use_pv": False, |
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} |
|
data["sr_model"] = data["sr_type"] == "sr_model" |
|
data["sr_device"] = data["sr_type"] == "sr_device" |
|
data["pm"] = data["f0method"] == "pm" |
|
data["harvest"] = data["f0method"] == "harvest" |
|
data["crepe"] = data["f0method"] == "crepe" |
|
data["rmvpe"] = data["f0method"] == "rmvpe" |
|
data["fcpe"] = data["f0method"] == "fcpe" |
|
return data |
|
|
|
def launcher(self): |
|
data = self.load() |
|
self.config.use_jit = False |
|
sg.theme("LightBlue3") |
|
layout = [ |
|
[ |
|
sg.Frame( |
|
title=i18n("加载模型"), |
|
layout=[ |
|
[ |
|
sg.Input( |
|
default_text=data.get("pth_path", ""), |
|
key="pth_path", |
|
), |
|
sg.FileBrowse( |
|
i18n("选择.pth文件"), |
|
initial_folder=os.path.join( |
|
os.getcwd(), "assets/weights" |
|
), |
|
file_types=((". pth"),), |
|
), |
|
], |
|
[ |
|
sg.Input( |
|
default_text=data.get("index_path", ""), |
|
key="index_path", |
|
), |
|
sg.FileBrowse( |
|
i18n("选择.index文件"), |
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initial_folder=os.path.join(os.getcwd(), "logs"), |
|
file_types=((". index"),), |
|
), |
|
], |
|
], |
|
) |
|
], |
|
[ |
|
sg.Frame( |
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layout=[ |
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[ |
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sg.Text(i18n("设备类型")), |
|
sg.Combo( |
|
self.hostapis, |
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key="sg_hostapi", |
|
default_value=data.get("sg_hostapi", ""), |
|
enable_events=True, |
|
size=(20, 1), |
|
), |
|
sg.Checkbox( |
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i18n("独占 WASAPI 设备"), |
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key="sg_wasapi_exclusive", |
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default=data.get("sg_wasapi_exclusive", False), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("输入设备")), |
|
sg.Combo( |
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self.input_devices, |
|
key="sg_input_device", |
|
default_value=data.get("sg_input_device", ""), |
|
enable_events=True, |
|
size=(45, 1), |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("输出设备")), |
|
sg.Combo( |
|
self.output_devices, |
|
key="sg_output_device", |
|
default_value=data.get("sg_output_device", ""), |
|
enable_events=True, |
|
size=(45, 1), |
|
), |
|
], |
|
[ |
|
sg.Button(i18n("重载设备列表"), key="reload_devices"), |
|
sg.Radio( |
|
i18n("使用模型采样率"), |
|
"sr_type", |
|
key="sr_model", |
|
default=data.get("sr_model", True), |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
i18n("使用设备采样率"), |
|
"sr_type", |
|
key="sr_device", |
|
default=data.get("sr_device", False), |
|
enable_events=True, |
|
), |
|
sg.Text(i18n("采样率:")), |
|
sg.Text("", key="sr_stream"), |
|
], |
|
], |
|
title=i18n("音频设备"), |
|
) |
|
], |
|
[ |
|
sg.Frame( |
|
layout=[ |
|
[ |
|
sg.Text(i18n("响应阈值")), |
|
sg.Slider( |
|
range=(-60, 0), |
|
key="threhold", |
|
resolution=1, |
|
orientation="h", |
|
default_value=data.get("threhold", -60), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("音调设置")), |
|
sg.Slider( |
|
range=(-24, 24), |
|
key="pitch", |
|
resolution=1, |
|
orientation="h", |
|
default_value=data.get("pitch", 0), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("Index Rate")), |
|
sg.Slider( |
|
range=(0.0, 1.0), |
|
key="index_rate", |
|
resolution=0.01, |
|
orientation="h", |
|
default_value=data.get("index_rate", 0), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("响度因子")), |
|
sg.Slider( |
|
range=(0.0, 1.0), |
|
key="rms_mix_rate", |
|
resolution=0.01, |
|
orientation="h", |
|
default_value=data.get("rms_mix_rate", 0), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("音高算法")), |
|
sg.Radio( |
|
"pm", |
|
"f0method", |
|
key="pm", |
|
default=data.get("pm", False), |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
"harvest", |
|
"f0method", |
|
key="harvest", |
|
default=data.get("harvest", False), |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
"crepe", |
|
"f0method", |
|
key="crepe", |
|
default=data.get("crepe", False), |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
"rmvpe", |
|
"f0method", |
|
key="rmvpe", |
|
default=data.get("rmvpe", False), |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
"fcpe", |
|
"f0method", |
|
key="fcpe", |
|
default=data.get("fcpe", True), |
|
enable_events=True, |
|
), |
|
], |
|
], |
|
title=i18n("常规设置"), |
|
), |
|
sg.Frame( |
|
layout=[ |
|
[ |
|
sg.Text(i18n("采样长度")), |
|
sg.Slider( |
|
range=(0.02, 1.5), |
|
key="block_time", |
|
resolution=0.01, |
|
orientation="h", |
|
default_value=data.get("block_time", 0.25), |
|
enable_events=True, |
|
), |
|
], |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
[ |
|
sg.Text(i18n("harvest进程数")), |
|
sg.Slider( |
|
range=(1, n_cpu), |
|
key="n_cpu", |
|
resolution=1, |
|
orientation="h", |
|
default_value=data.get( |
|
"n_cpu", min(self.gui_config.n_cpu, n_cpu) |
|
), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("淡入淡出长度")), |
|
sg.Slider( |
|
range=(0.01, 0.15), |
|
key="crossfade_length", |
|
resolution=0.01, |
|
orientation="h", |
|
default_value=data.get("crossfade_length", 0.05), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Text(i18n("额外推理时长")), |
|
sg.Slider( |
|
range=(0.05, 5.00), |
|
key="extra_time", |
|
resolution=0.01, |
|
orientation="h", |
|
default_value=data.get("extra_time", 2.5), |
|
enable_events=True, |
|
), |
|
], |
|
[ |
|
sg.Checkbox( |
|
i18n("输入降噪"), |
|
key="I_noise_reduce", |
|
enable_events=True, |
|
), |
|
sg.Checkbox( |
|
i18n("输出降噪"), |
|
key="O_noise_reduce", |
|
enable_events=True, |
|
), |
|
sg.Checkbox( |
|
i18n("启用相位声码器"), |
|
key="use_pv", |
|
default=data.get("use_pv", False), |
|
enable_events=True, |
|
), |
|
|
|
|
|
|
|
|
|
|
|
|
|
], |
|
|
|
], |
|
title=i18n("性能设置"), |
|
), |
|
], |
|
[ |
|
sg.Button(i18n("开始音频转换"), key="start_vc"), |
|
sg.Button(i18n("停止音频转换"), key="stop_vc"), |
|
sg.Radio( |
|
i18n("输入监听"), |
|
"function", |
|
key="im", |
|
default=False, |
|
enable_events=True, |
|
), |
|
sg.Radio( |
|
i18n("输出变声"), |
|
"function", |
|
key="vc", |
|
default=True, |
|
enable_events=True, |
|
), |
|
sg.Text(i18n("算法延迟(ms):")), |
|
sg.Text("0", key="delay_time"), |
|
sg.Text(i18n("推理时间(ms):")), |
|
sg.Text("0", key="infer_time"), |
|
], |
|
] |
|
self.window = sg.Window("RVC - GUI", layout=layout, finalize=True) |
|
self.event_handler() |
|
|
|
def event_handler(self): |
|
global flag_vc |
|
while True: |
|
event, values = self.window.read() |
|
if event == sg.WINDOW_CLOSED: |
|
self.stop_stream() |
|
exit() |
|
if event == "reload_devices" or event == "sg_hostapi": |
|
self.gui_config.sg_hostapi = values["sg_hostapi"] |
|
self.update_devices(hostapi_name=values["sg_hostapi"]) |
|
if self.gui_config.sg_hostapi not in self.hostapis: |
|
self.gui_config.sg_hostapi = self.hostapis[0] |
|
self.window["sg_hostapi"].Update(values=self.hostapis) |
|
self.window["sg_hostapi"].Update(value=self.gui_config.sg_hostapi) |
|
if ( |
|
self.gui_config.sg_input_device not in self.input_devices |
|
and len(self.input_devices) > 0 |
|
): |
|
self.gui_config.sg_input_device = self.input_devices[0] |
|
self.window["sg_input_device"].Update(values=self.input_devices) |
|
self.window["sg_input_device"].Update( |
|
value=self.gui_config.sg_input_device |
|
) |
|
if self.gui_config.sg_output_device not in self.output_devices: |
|
self.gui_config.sg_output_device = self.output_devices[0] |
|
self.window["sg_output_device"].Update(values=self.output_devices) |
|
self.window["sg_output_device"].Update( |
|
value=self.gui_config.sg_output_device |
|
) |
|
if event == "start_vc" and not flag_vc: |
|
if self.set_values(values) == True: |
|
printt("cuda_is_available: %s", torch.cuda.is_available()) |
|
self.start_vc() |
|
settings = { |
|
"pth_path": values["pth_path"], |
|
"index_path": values["index_path"], |
|
"sg_hostapi": values["sg_hostapi"], |
|
"sg_wasapi_exclusive": values["sg_wasapi_exclusive"], |
|
"sg_input_device": values["sg_input_device"], |
|
"sg_output_device": values["sg_output_device"], |
|
"sr_type": ["sr_model", "sr_device"][ |
|
[ |
|
values["sr_model"], |
|
values["sr_device"], |
|
].index(True) |
|
], |
|
"threhold": values["threhold"], |
|
"pitch": values["pitch"], |
|
"rms_mix_rate": values["rms_mix_rate"], |
|
"index_rate": values["index_rate"], |
|
|
|
"block_time": values["block_time"], |
|
"crossfade_length": values["crossfade_length"], |
|
"extra_time": values["extra_time"], |
|
"n_cpu": values["n_cpu"], |
|
|
|
"use_jit": False, |
|
"use_pv": values["use_pv"], |
|
"f0method": ["pm", "harvest", "crepe", "rmvpe", "fcpe"][ |
|
[ |
|
values["pm"], |
|
values["harvest"], |
|
values["crepe"], |
|
values["rmvpe"], |
|
values["fcpe"], |
|
].index(True) |
|
], |
|
} |
|
with open("configs/inuse/config.json", "w") as j: |
|
json.dump(settings, j) |
|
if self.stream is not None: |
|
self.delay_time = ( |
|
self.stream.latency[-1] |
|
+ values["block_time"] |
|
+ values["crossfade_length"] |
|
+ 0.01 |
|
) |
|
if values["I_noise_reduce"]: |
|
self.delay_time += min(values["crossfade_length"], 0.04) |
|
self.window["sr_stream"].update(self.gui_config.samplerate) |
|
self.window["delay_time"].update( |
|
int(np.round(self.delay_time * 1000)) |
|
) |
|
|
|
if event == "threhold": |
|
self.gui_config.threhold = values["threhold"] |
|
elif event == "pitch": |
|
self.gui_config.pitch = values["pitch"] |
|
if hasattr(self, "rvc"): |
|
self.rvc.change_key(values["pitch"]) |
|
elif event == "index_rate": |
|
self.gui_config.index_rate = values["index_rate"] |
|
if hasattr(self, "rvc"): |
|
self.rvc.change_index_rate(values["index_rate"]) |
|
elif event == "rms_mix_rate": |
|
self.gui_config.rms_mix_rate = values["rms_mix_rate"] |
|
elif event in ["pm", "harvest", "crepe", "rmvpe", "fcpe"]: |
|
self.gui_config.f0method = event |
|
elif event == "I_noise_reduce": |
|
self.gui_config.I_noise_reduce = values["I_noise_reduce"] |
|
if self.stream is not None: |
|
self.delay_time += ( |
|
1 if values["I_noise_reduce"] else -1 |
|
) * min(values["crossfade_length"], 0.04) |
|
self.window["delay_time"].update( |
|
int(np.round(self.delay_time * 1000)) |
|
) |
|
elif event == "O_noise_reduce": |
|
self.gui_config.O_noise_reduce = values["O_noise_reduce"] |
|
elif event == "use_pv": |
|
self.gui_config.use_pv = values["use_pv"] |
|
elif event in ["vc", "im"]: |
|
self.function = event |
|
elif event == "stop_vc" or event != "start_vc": |
|
|
|
self.stop_stream() |
|
|
|
def set_values(self, values): |
|
if len(values["pth_path"].strip()) == 0: |
|
sg.popup(i18n("请选择pth文件")) |
|
return False |
|
if len(values["index_path"].strip()) == 0: |
|
sg.popup(i18n("请选择index文件")) |
|
return False |
|
pattern = re.compile("[^\x00-\x7F]+") |
|
if pattern.findall(values["pth_path"]): |
|
sg.popup(i18n("pth文件路径不可包含中文")) |
|
return False |
|
if pattern.findall(values["index_path"]): |
|
sg.popup(i18n("index文件路径不可包含中文")) |
|
return False |
|
self.set_devices(values["sg_input_device"], values["sg_output_device"]) |
|
self.config.use_jit = False |
|
|
|
self.gui_config.sg_hostapi = values["sg_hostapi"] |
|
self.gui_config.sg_wasapi_exclusive = values["sg_wasapi_exclusive"] |
|
self.gui_config.sg_input_device = values["sg_input_device"] |
|
self.gui_config.sg_output_device = values["sg_output_device"] |
|
self.gui_config.pth_path = values["pth_path"] |
|
self.gui_config.index_path = values["index_path"] |
|
self.gui_config.sr_type = ["sr_model", "sr_device"][ |
|
[ |
|
values["sr_model"], |
|
values["sr_device"], |
|
].index(True) |
|
] |
|
self.gui_config.threhold = values["threhold"] |
|
self.gui_config.pitch = values["pitch"] |
|
self.gui_config.block_time = values["block_time"] |
|
self.gui_config.crossfade_time = values["crossfade_length"] |
|
self.gui_config.extra_time = values["extra_time"] |
|
self.gui_config.I_noise_reduce = values["I_noise_reduce"] |
|
self.gui_config.O_noise_reduce = values["O_noise_reduce"] |
|
self.gui_config.use_pv = values["use_pv"] |
|
self.gui_config.rms_mix_rate = values["rms_mix_rate"] |
|
self.gui_config.index_rate = values["index_rate"] |
|
self.gui_config.n_cpu = values["n_cpu"] |
|
self.gui_config.f0method = ["pm", "harvest", "crepe", "rmvpe", "fcpe"][ |
|
[ |
|
values["pm"], |
|
values["harvest"], |
|
values["crepe"], |
|
values["rmvpe"], |
|
values["fcpe"], |
|
].index(True) |
|
] |
|
return True |
|
|
|
def start_vc(self): |
|
torch.cuda.empty_cache() |
|
self.rvc = rvc_for_realtime.RVC( |
|
self.gui_config.pitch, |
|
self.gui_config.pth_path, |
|
self.gui_config.index_path, |
|
self.gui_config.index_rate, |
|
self.gui_config.n_cpu, |
|
inp_q, |
|
opt_q, |
|
self.config, |
|
self.rvc if hasattr(self, "rvc") else None, |
|
) |
|
self.gui_config.samplerate = ( |
|
self.rvc.tgt_sr |
|
if self.gui_config.sr_type == "sr_model" |
|
else self.get_device_samplerate() |
|
) |
|
self.gui_config.channels = self.get_device_channels() |
|
self.zc = self.gui_config.samplerate // 100 |
|
self.block_frame = ( |
|
int( |
|
np.round( |
|
self.gui_config.block_time |
|
* self.gui_config.samplerate |
|
/ self.zc |
|
) |
|
) |
|
* self.zc |
|
) |
|
self.block_frame_16k = 160 * self.block_frame // self.zc |
|
self.crossfade_frame = ( |
|
int( |
|
np.round( |
|
self.gui_config.crossfade_time |
|
* self.gui_config.samplerate |
|
/ self.zc |
|
) |
|
) |
|
* self.zc |
|
) |
|
self.sola_buffer_frame = min(self.crossfade_frame, 4 * self.zc) |
|
self.sola_search_frame = self.zc |
|
self.extra_frame = ( |
|
int( |
|
np.round( |
|
self.gui_config.extra_time |
|
* self.gui_config.samplerate |
|
/ self.zc |
|
) |
|
) |
|
* self.zc |
|
) |
|
self.input_wav: torch.Tensor = torch.zeros( |
|
self.extra_frame |
|
+ self.crossfade_frame |
|
+ self.sola_search_frame |
|
+ self.block_frame, |
|
device=self.config.device, |
|
dtype=torch.float32, |
|
) |
|
self.input_wav_denoise: torch.Tensor = self.input_wav.clone() |
|
self.input_wav_res: torch.Tensor = torch.zeros( |
|
160 * self.input_wav.shape[0] // self.zc, |
|
device=self.config.device, |
|
dtype=torch.float32, |
|
) |
|
self.rms_buffer: np.ndarray = np.zeros(4 * self.zc, dtype="float32") |
|
self.sola_buffer: torch.Tensor = torch.zeros( |
|
self.sola_buffer_frame, device=self.config.device, dtype=torch.float32 |
|
) |
|
self.nr_buffer: torch.Tensor = self.sola_buffer.clone() |
|
self.output_buffer: torch.Tensor = self.input_wav.clone() |
|
self.skip_head = self.extra_frame // self.zc |
|
self.return_length = ( |
|
self.block_frame + self.sola_buffer_frame + self.sola_search_frame |
|
) // self.zc |
|
self.fade_in_window: torch.Tensor = ( |
|
torch.sin( |
|
0.5 |
|
* np.pi |
|
* torch.linspace( |
|
0.0, |
|
1.0, |
|
steps=self.sola_buffer_frame, |
|
device=self.config.device, |
|
dtype=torch.float32, |
|
) |
|
) |
|
** 2 |
|
) |
|
self.fade_out_window: torch.Tensor = 1 - self.fade_in_window |
|
self.resampler = tat.Resample( |
|
orig_freq=self.gui_config.samplerate, |
|
new_freq=16000, |
|
dtype=torch.float32, |
|
).to(self.config.device) |
|
if self.rvc.tgt_sr != self.gui_config.samplerate: |
|
self.resampler2 = tat.Resample( |
|
orig_freq=self.rvc.tgt_sr, |
|
new_freq=self.gui_config.samplerate, |
|
dtype=torch.float32, |
|
).to(self.config.device) |
|
else: |
|
self.resampler2 = None |
|
self.tg = TorchGate( |
|
sr=self.gui_config.samplerate, n_fft=4 * self.zc, prop_decrease=0.9 |
|
).to(self.config.device) |
|
self.start_stream() |
|
|
|
def start_stream(self): |
|
global flag_vc |
|
if not flag_vc: |
|
flag_vc = True |
|
if ( |
|
"WASAPI" in self.gui_config.sg_hostapi |
|
and self.gui_config.sg_wasapi_exclusive |
|
): |
|
extra_settings = sd.WasapiSettings(exclusive=True) |
|
else: |
|
extra_settings = None |
|
self.stream = sd.Stream( |
|
callback=self.audio_callback, |
|
blocksize=self.block_frame, |
|
samplerate=self.gui_config.samplerate, |
|
channels=self.gui_config.channels, |
|
dtype="float32", |
|
extra_settings=extra_settings, |
|
) |
|
self.stream.start() |
|
|
|
def stop_stream(self): |
|
global flag_vc |
|
if flag_vc: |
|
flag_vc = False |
|
if self.stream is not None: |
|
self.stream.abort() |
|
self.stream.close() |
|
self.stream = None |
|
|
|
def audio_callback( |
|
self, indata: np.ndarray, outdata: np.ndarray, frames, times, status |
|
): |
|
""" |
|
音频处理 |
|
""" |
|
global flag_vc |
|
start_time = time.perf_counter() |
|
indata = librosa.to_mono(indata.T) |
|
if self.gui_config.threhold > -60: |
|
indata = np.append(self.rms_buffer, indata) |
|
rms = librosa.feature.rms( |
|
y=indata, frame_length=4 * self.zc, hop_length=self.zc |
|
)[:, 2:] |
|
self.rms_buffer[:] = indata[-4 * self.zc :] |
|
indata = indata[2 * self.zc - self.zc // 2 :] |
|
db_threhold = ( |
|
librosa.amplitude_to_db(rms, ref=1.0)[0] < self.gui_config.threhold |
|
) |
|
for i in range(db_threhold.shape[0]): |
|
if db_threhold[i]: |
|
indata[i * self.zc : (i + 1) * self.zc] = 0 |
|
indata = indata[self.zc // 2 :] |
|
self.input_wav[: -self.block_frame] = self.input_wav[ |
|
self.block_frame : |
|
].clone() |
|
self.input_wav[-indata.shape[0] :] = torch.from_numpy(indata).to( |
|
self.config.device |
|
) |
|
self.input_wav_res[: -self.block_frame_16k] = self.input_wav_res[ |
|
self.block_frame_16k : |
|
].clone() |
|
|
|
if self.gui_config.I_noise_reduce: |
|
self.input_wav_denoise[: -self.block_frame] = self.input_wav_denoise[ |
|
self.block_frame : |
|
].clone() |
|
input_wav = self.input_wav[-self.sola_buffer_frame - self.block_frame :] |
|
input_wav = self.tg( |
|
input_wav.unsqueeze(0), self.input_wav.unsqueeze(0) |
|
).squeeze(0) |
|
input_wav[: self.sola_buffer_frame] *= self.fade_in_window |
|
input_wav[: self.sola_buffer_frame] += ( |
|
self.nr_buffer * self.fade_out_window |
|
) |
|
self.input_wav_denoise[-self.block_frame :] = input_wav[ |
|
: self.block_frame |
|
] |
|
self.nr_buffer[:] = input_wav[self.block_frame :] |
|
self.input_wav_res[-self.block_frame_16k - 160 :] = self.resampler( |
|
self.input_wav_denoise[-self.block_frame - 2 * self.zc :] |
|
)[160:] |
|
else: |
|
self.input_wav_res[-160 * (indata.shape[0] // self.zc + 1) :] = ( |
|
self.resampler(self.input_wav[-indata.shape[0] - 2 * self.zc :])[ |
|
160: |
|
] |
|
) |
|
|
|
if self.function == "vc": |
|
infer_wav = self.rvc.infer( |
|
self.input_wav_res, |
|
self.block_frame_16k, |
|
self.skip_head, |
|
self.return_length, |
|
self.gui_config.f0method, |
|
) |
|
if self.resampler2 is not None: |
|
infer_wav = self.resampler2(infer_wav) |
|
elif self.gui_config.I_noise_reduce: |
|
infer_wav = self.input_wav_denoise[self.extra_frame :].clone() |
|
else: |
|
infer_wav = self.input_wav[self.extra_frame :].clone() |
|
|
|
if self.gui_config.O_noise_reduce and self.function == "vc": |
|
self.output_buffer[: -self.block_frame] = self.output_buffer[ |
|
self.block_frame : |
|
].clone() |
|
self.output_buffer[-self.block_frame :] = infer_wav[-self.block_frame :] |
|
infer_wav = self.tg( |
|
infer_wav.unsqueeze(0), self.output_buffer.unsqueeze(0) |
|
).squeeze(0) |
|
|
|
if self.gui_config.rms_mix_rate < 1 and self.function == "vc": |
|
if self.gui_config.I_noise_reduce: |
|
input_wav = self.input_wav_denoise[self.extra_frame :] |
|
else: |
|
input_wav = self.input_wav[self.extra_frame :] |
|
rms1 = librosa.feature.rms( |
|
y=input_wav[: infer_wav.shape[0]].cpu().numpy(), |
|
frame_length=4 * self.zc, |
|
hop_length=self.zc, |
|
) |
|
rms1 = torch.from_numpy(rms1).to(self.config.device) |
|
rms1 = F.interpolate( |
|
rms1.unsqueeze(0), |
|
size=infer_wav.shape[0] + 1, |
|
mode="linear", |
|
align_corners=True, |
|
)[0, 0, :-1] |
|
rms2 = librosa.feature.rms( |
|
y=infer_wav[:].cpu().numpy(), |
|
frame_length=4 * self.zc, |
|
hop_length=self.zc, |
|
) |
|
rms2 = torch.from_numpy(rms2).to(self.config.device) |
|
rms2 = F.interpolate( |
|
rms2.unsqueeze(0), |
|
size=infer_wav.shape[0] + 1, |
|
mode="linear", |
|
align_corners=True, |
|
)[0, 0, :-1] |
|
rms2 = torch.max(rms2, torch.zeros_like(rms2) + 1e-3) |
|
infer_wav *= torch.pow( |
|
rms1 / rms2, torch.tensor(1 - self.gui_config.rms_mix_rate) |
|
) |
|
|
|
conv_input = infer_wav[ |
|
None, None, : self.sola_buffer_frame + self.sola_search_frame |
|
] |
|
cor_nom = F.conv1d(conv_input, self.sola_buffer[None, None, :]) |
|
cor_den = torch.sqrt( |
|
F.conv1d( |
|
conv_input**2, |
|
torch.ones(1, 1, self.sola_buffer_frame, device=self.config.device), |
|
) |
|
+ 1e-8 |
|
) |
|
if sys.platform == "darwin": |
|
_, sola_offset = torch.max(cor_nom[0, 0] / cor_den[0, 0]) |
|
sola_offset = sola_offset.item() |
|
else: |
|
sola_offset = torch.argmax(cor_nom[0, 0] / cor_den[0, 0]) |
|
printt("sola_offset = %d", int(sola_offset)) |
|
infer_wav = infer_wav[sola_offset:] |
|
if "privateuseone" in str(self.config.device) or not self.gui_config.use_pv: |
|
infer_wav[: self.sola_buffer_frame] *= self.fade_in_window |
|
infer_wav[: self.sola_buffer_frame] += ( |
|
self.sola_buffer * self.fade_out_window |
|
) |
|
else: |
|
infer_wav[: self.sola_buffer_frame] = phase_vocoder( |
|
self.sola_buffer, |
|
infer_wav[: self.sola_buffer_frame], |
|
self.fade_out_window, |
|
self.fade_in_window, |
|
) |
|
self.sola_buffer[:] = infer_wav[ |
|
self.block_frame : self.block_frame + self.sola_buffer_frame |
|
] |
|
outdata[:] = ( |
|
infer_wav[: self.block_frame] |
|
.repeat(self.gui_config.channels, 1) |
|
.t() |
|
.cpu() |
|
.numpy() |
|
) |
|
total_time = time.perf_counter() - start_time |
|
if flag_vc: |
|
self.window["infer_time"].update(int(total_time * 1000)) |
|
printt("Infer time: %.2f", total_time) |
|
|
|
def update_devices(self, hostapi_name=None): |
|
"""获取设备列表""" |
|
global flag_vc |
|
flag_vc = False |
|
sd._terminate() |
|
sd._initialize() |
|
devices = sd.query_devices() |
|
hostapis = sd.query_hostapis() |
|
for hostapi in hostapis: |
|
for device_idx in hostapi["devices"]: |
|
devices[device_idx]["hostapi_name"] = hostapi["name"] |
|
self.hostapis = [hostapi["name"] for hostapi in hostapis] |
|
if hostapi_name not in self.hostapis: |
|
hostapi_name = self.hostapis[0] |
|
self.input_devices = [ |
|
d["name"] |
|
for d in devices |
|
if d["max_input_channels"] > 0 and d["hostapi_name"] == hostapi_name |
|
] |
|
self.output_devices = [ |
|
d["name"] |
|
for d in devices |
|
if d["max_output_channels"] > 0 and d["hostapi_name"] == hostapi_name |
|
] |
|
self.input_devices_indices = [ |
|
d["index"] if "index" in d else d["name"] |
|
for d in devices |
|
if d["max_input_channels"] > 0 and d["hostapi_name"] == hostapi_name |
|
] |
|
self.output_devices_indices = [ |
|
d["index"] if "index" in d else d["name"] |
|
for d in devices |
|
if d["max_output_channels"] > 0 and d["hostapi_name"] == hostapi_name |
|
] |
|
|
|
def set_devices(self, input_device, output_device): |
|
"""设置输出设备""" |
|
sd.default.device[0] = self.input_devices_indices[ |
|
self.input_devices.index(input_device) |
|
] |
|
sd.default.device[1] = self.output_devices_indices[ |
|
self.output_devices.index(output_device) |
|
] |
|
printt("Input device: %s:%s", str(sd.default.device[0]), input_device) |
|
printt("Output device: %s:%s", str(sd.default.device[1]), output_device) |
|
|
|
def get_device_samplerate(self): |
|
return int( |
|
sd.query_devices(device=sd.default.device[0])["default_samplerate"] |
|
) |
|
|
|
def get_device_channels(self): |
|
max_input_channels = sd.query_devices(device=sd.default.device[0])[ |
|
"max_input_channels" |
|
] |
|
max_output_channels = sd.query_devices(device=sd.default.device[1])[ |
|
"max_output_channels" |
|
] |
|
return min(max_input_channels, max_output_channels, 2) |
|
|
|
gui = GUI() |
|
|
