From 2c8597d7420c94ea3d406974b91aba1d6d3f81ac Mon Sep 17 00:00:00 2001
From: w-okada <you@example.com>
Date: Sat, 4 Nov 2023 04:22:24 +0900
Subject: [PATCH] update
---
server/voice_changer/Beatrice/Beatrice.py | 154 ++--------------------
1 file changed, 9 insertions(+), 145 deletions(-)
diff --git a/server/voice_changer/Beatrice/Beatrice.py b/server/voice_changer/Beatrice/Beatrice.py
index 512e0879..44658c7f 100644
--- a/server/voice_changer/Beatrice/Beatrice.py
+++ b/server/voice_changer/Beatrice/Beatrice.py
@@ -1,120 +1,31 @@
-"""
-
-"""
-
-
-from dataclasses import asdict
-from typing import Union
-import os
-import numpy as np
-from const import MODEL_DIR_STATIC
from data.ModelSlot import BeatriceModelSlot
from mods.log_control import VoiceChangaerLogger
-from voice_changer.Beatrice.BeatriceSettings import BeatriceSettings
from voice_changer.utils.VoiceChangerModel import AudioInOut, VoiceChangerModel
from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
-from beatrice_internal_api import BeatriceInternalAPI
logger = VoiceChangaerLogger.get_instance().getLogger()
-class BeatriceAPI(BeatriceInternalAPI):
- def __init__(self, sample_rate: float = 48000.0):
- if sample_rate < 1000.0:
- raise ValueError(sample_rate)
- super().__init__(float(sample_rate))
-
- def get_n_speakers(self):
- return 500
-
- def get_target_speaker_names(self):
- names = []
- for i in range(1, 101):
- names.append(f"[商用不可] jvs{i:03d}")
- names.append(f"[商用不可] jvs{i:03d} -1")
- names.append(f"[商用不可] jvs{i:03d} -2")
- names.append(f"[商用不可] jvs{i:03d} +1")
- names.append(f"[商用不可] jvs{i:03d} +2")
- return names
-
- def set_sample_rate(self, sample_rate: float):
- if sample_rate < 1000.0:
- raise ValueError(sample_rate)
- super().set_sample_rate(float(sample_rate))
-
- def set_target_speaker_id(self, target_speaker_id: int):
- if not 0 <= target_speaker_id < self.get_n_speakers():
- raise ValueError(target_speaker_id)
- super().set_target_speaker_id(int(target_speaker_id))
-
- def read_parameters(self, filename: Union[str, bytes, os.PathLike]):
- super().read_parameters(filename)
-
- def convert(self, in_wav: np.ndarray) -> np.ndarray:
- if in_wav.ndim != 1:
- raise ValueError(in_wav.ndim)
- if in_wav.dtype != np.float32:
- raise ValueError(in_wav.dtype)
- out_wav = super().convert(in_wav)
- assert in_wav.shape == out_wav.shape
- return out_wav
-
-
class Beatrice(VoiceChangerModel):
- def __init__(self, params: VoiceChangerParams, slotInfo: BeatriceModelSlot, static: bool = False):
- logger.info("[Voice Changer] [Beatrice] Creating instance ")
- self.settings = BeatriceSettings()
- self.params = params
-
- self.prevVol = 0.0
- self.slotInfo = slotInfo
- self.audio_buffer: AudioInOut | None = None
-
- self.static = static
+ def __init__(self, params: VoiceChangerParams, slotInfo: BeatriceModelSlot):
+ raise RuntimeError("not implemented")
def initialize(self):
- logger.info("[Voice Changer] [Beatrice] Initializing... ")
-
- self.beatrice_api = BeatriceAPI()
- if self.static:
- modelPath = os.path.join(MODEL_DIR_STATIC, str(self.slotInfo.slotIndex), os.path.basename(self.slotInfo.modelFile))
- else:
- modelPath = os.path.join(self.params.model_dir, str(self.slotInfo.slotIndex), os.path.basename(self.slotInfo.modelFile))
- self.beatrice_api.read_parameters(modelPath)
- self.beatrice_api.set_sample_rate(self.inputSampleRate)
-
- # その他の設定
- self.settings.dstId = self.slotInfo.dstId
- logger.info("[Voice Changer] [Beatrice] Initializing... done")
+ raise RuntimeError("not implemented")
def setSamplingRate(self, inputSampleRate, outputSampleRate):
- if inputSampleRate == outputSampleRate:
- self.inputSampleRate = inputSampleRate
- self.outputSampleRate = outputSampleRate
- self.initialize()
- else:
- print("inputSampleRate, outputSampleRate", inputSampleRate, outputSampleRate)
+ raise RuntimeError("not implemented")
def update_settings(self, key: str, val: int | float | str):
- logger.info(f"[Voice Changer][Beatrice]: update_settings {key}:{val}")
- if key in self.settings.intData:
- setattr(self.settings, key, int(val))
- elif key in self.settings.floatData:
- setattr(self.settings, key, float(val))
- elif key in self.settings.strData:
- setattr(self.settings, key, str(val))
- else:
- return False
- return True
+ raise RuntimeError("not implemented")
def get_info(self):
- data = asdict(self.settings)
- return data
+ raise RuntimeError("not implemented")
def get_processing_sampling_rate(self):
- return self.inputSampleRate
+ raise RuntimeError("not implemented")
def generate_input(
self,
@@ -122,61 +33,14 @@ class Beatrice(VoiceChangerModel):
crossfadeSize: int,
solaSearchFrame: int = 0,
):
- newData = newData.astype(np.float32) / 32768.0
- # 過去のデータに連結
- if self.audio_buffer is not None:
- self.audio_buffer = np.concatenate([self.audio_buffer, newData], 0)
- else:
- self.audio_buffer = newData
-
- convertSize = newData.shape[0] + crossfadeSize + solaSearchFrame
-
- # バッファがたまっていない場合はzeroで補う
- if self.audio_buffer.shape[0] < convertSize:
- self.audio_buffer = np.concatenate([np.zeros([convertSize]), self.audio_buffer])
-
- # 変換対象の部分だけ抽出
- convertOffset = -1 * convertSize
- self.audio_buffer = self.audio_buffer[convertOffset:]
-
- return (self.audio_buffer,)
+ raise RuntimeError("not implemented")
def inference(self, receivedData: AudioInOut, crossfade_frame: int, sola_search_frame: int):
- data = self.generate_input(receivedData, crossfade_frame, sola_search_frame)
- audio = (data[0]).astype(np.float32)
-
- self.beatrice_api.set_target_speaker_id(self.settings.dstId)
-
- block_size = 500
- out_wav_blocks = []
- head = 0
- while head < len(audio):
- in_wav_block = audio[head : head + block_size]
- out_wav_block = self.beatrice_api.convert(in_wav_block)
- out_wav_blocks.append(out_wav_block)
- head += block_size
- out_wav = np.concatenate(out_wav_blocks)
- assert audio.shape == out_wav.shape
-
- return (out_wav * 32767.0).astype(np.int16)
+ raise RuntimeError("not implemented")
def __del__(self):
del self.pipeline
- # def export2onnx(self):
- # modelSlot = self.slotInfo
-
- # if modelSlot.isONNX:
- # print("[Voice Changer] export2onnx, No pyTorch filepath.")
- # return {"status": "ng", "path": ""}
-
- # output_file_simple = export2onnx(self.settings.gpu, modelSlot)
- # return {
- # "status": "ok",
- # "path": f"/tmp/{output_file_simple}",
- # "filename": output_file_simple,
- # }
-
def get_model_current(self):
return [
{