support sola

client/demo/dist/assets/gui_settings/RVC.json

@@ -168,6 +168,10 @@
             {
                 "name": "rvcQuality",
                 "options": {}
+            },
+            {
+                "name": "solaEnable",
+                "options": {}
             }
         ]
     },

client/demo/public/assets/gui_settings/RVC.json

@@ -168,6 +168,10 @@
             {
                 "name": "rvcQuality",
                 "options": {}
+            },
+            {
+                "name": "solaEnable",
+                "options": {}
             }
         ]
     },

client/demo/src/components/demo/002_ComponentGenerator.tsx

@@ -34,9 +34,10 @@ import { CrossFadeEndRateRow, CrossFadeEndRateRowProps } from "./components/807_
 import { DownSamplingModeRow, DownSamplingModeRowProps } from "./components/808_DownSamplingModeRow"
 import { TrancateNumTresholdRow, TrancateNumTresholdRowProps } from "./components/809_TrancateNumTresholdRow"
 import { IndexRatioRow, IndexRatioRowProps } from "./components/609_IndexRatioRow"
-import { RVCQualityRow, RVCQualityRowProps } from "./components/810_RVCQuality"
+import { RVCQualityRow, RVCQualityRowProps } from "./components/810_RVCQualityRow"
 import { ModelSamplingRateRow, ModelSamplingRateRowProps } from "./components/303_ModelSamplingRateRow"
 import { OnnxExportRow, OnnxExportRowProps } from "./components/304_OnnxExportRow"
+import { SolaEnableRow, SolaEnableRowProps } from "./components/811_SolaEnableRow"
 
 export const catalog: { [key: string]: (props: any) => JSX.Element } = {}
 
@@ -101,6 +102,7 @@ const initialize = () => {
     addToCatalog("downSamplingMode", (props: DownSamplingModeRowProps) => { return <DownSamplingModeRow {...props} /> })
     addToCatalog("trancateNumThreshold", (props: TrancateNumTresholdRowProps) => { return <TrancateNumTresholdRow {...props} /> })
     addToCatalog("rvcQuality", (props: RVCQualityRowProps) => { return <RVCQualityRow {...props} /> })
+    addToCatalog("solaEnable", (props: SolaEnableRowProps) => { return <SolaEnableRow {...props} /> })
 
 
 

client/demo/src/components/demo/components/701_InputChunkNumRow.tsx

@@ -15,7 +15,7 @@ export const InputChunkNumRow = (_props: InputChunkNumRowProps) => {
                         appState.workletNodeSetting.trancateBuffer()
                     }}>
                         {
-                            [16, 32, 64, 128, 192, 256, 320, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024, 2048].map(x => {
+                            [8, 16, 24, 32, 40, 48, 64, 128, 192, 256, 320, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024, 2048].map(x => {
                                 return <option key={x} value={x}>{x}</option>
                             })
                         }

client/demo/src/components/demo/components/811_SolaEnableRow.tsx

@@ -0,0 +1,31 @@
+import React, { useMemo } from "react"
+import { useAppState } from "../../../001_provider/001_AppStateProvider"
+
+export type SolaEnableRowProps = {
+}
+
+export const SolaEnableRow = (_props: SolaEnableRowProps) => {
+    const appState = useAppState()
+
+    const trancateNumTresholdRow = useMemo(() => {
+        const onSolaEnableChanged = (val: number) => {
+            appState.serverSetting.updateServerSettings({
+                ...appState.serverSetting.serverSetting,
+                solaEnabled: val
+            })
+        }
+        return (
+            <div className="body-row split-3-7 left-padding-1 guided">
+                <div className="body-item-title left-padding-1">Sola enable</div>
+                <div className="body-input-container">
+                    <select value={appState.serverSetting.serverSetting.solaEnabled} onChange={(e) => { onSolaEnableChanged(Number(e.target.value)) }}>
+                        <option value="0" >disable</option>
+                        <option value="1" >enable</option>
+                    </select>
+                </div>
+            </div>
+        )
+    }, [appState.serverSetting.serverSetting, appState.serverSetting.updateServerSettings])
+
+    return trancateNumTresholdRow
+}

client/lib/src/const.ts

@@ -71,6 +71,7 @@ export const ServerSettingKey = {
     "crossFadeOffsetRate": "crossFadeOffsetRate",
     "crossFadeEndRate": "crossFadeEndRate",
     "crossFadeOverlapSize": "crossFadeOverlapSize",
+    "solaEnabled": "solaEnabled",
 
     "framework": "framework",
     "onnxExecutionProvider": "onnxExecutionProvider",
@@ -104,6 +105,7 @@ export type VoiceChangerServerSetting = {
     crossFadeOffsetRate: number,
     crossFadeEndRate: number,
     crossFadeOverlapSize: CrossFadeOverlapSize,
+    solaEnabled: number,
 
     framework: Framework
     onnxExecutionProvider: OnnxExecutionProvider,
@@ -145,6 +147,7 @@ export const DefaultServerSetting_MMVCv15: ServerInfo = {
     crossFadeOffsetRate: 0.0,
     crossFadeEndRate: 1.0,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 0,
 
     framework: Framework.PyTorch,
     f0Factor: 1.0,
@@ -181,6 +184,7 @@ export const DefaultServerSetting_MMVCv13: ServerInfo = {
     crossFadeOffsetRate: 0.0,
     crossFadeEndRate: 1.0,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 0,
 
     framework: Framework.ONNX,
     f0Factor: 1.0,
@@ -218,6 +222,7 @@ export const DefaultServerSetting_so_vits_svc_40: ServerInfo = {
     crossFadeOffsetRate: 0.0,
     crossFadeEndRate: 1.0,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 0,
 
     framework: Framework.PyTorch,
     f0Factor: 1.0,
@@ -259,6 +264,7 @@ export const DefaultServerSetting_so_vits_svc_40_c: ServerInfo = {
     crossFadeOffsetRate: 0.0,
     crossFadeEndRate: 1.0,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 0,
 
     framework: Framework.ONNX,
     f0Factor: 1.0,
@@ -299,6 +305,7 @@ export const DefaultServerSetting_so_vits_svc_40v2: ServerInfo = {
     crossFadeOffsetRate: 0.0,
     crossFadeEndRate: 1.0,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 0,
 
     framework: Framework.PyTorch,
     f0Factor: 1.0,
@@ -341,6 +348,7 @@ export const DefaultServerSetting_RVC: ServerInfo = {
     crossFadeOffsetRate: 0.1,
     crossFadeEndRate: 0.8,
     crossFadeOverlapSize: CrossFadeOverlapSize[1024],
+    solaEnabled: 1,
 
     framework: Framework.PyTorch,
     f0Factor: 1.0,

server/restapi/MMVC_Rest_Fileuploader.py

@@ -34,8 +34,10 @@ class MMVC_Rest_Fileuploader:
         json_compatible_item_data = jsonable_encoder(res)
         return JSONResponse(content=json_compatible_item_data)
 
+    # def post_concat_uploaded_file(self, slot: int = Form(...), filename: str = Form(...), filenameChunkNum: int = Form(...)):
     def post_concat_uploaded_file(self, filename: str = Form(...), filenameChunkNum: int = Form(...)):
-        res = concat_file_chunks(UPLOAD_DIR, filename, filenameChunkNum, UPLOAD_DIR)
+        slot = 0
+        res = concat_file_chunks(slot, UPLOAD_DIR, filename, filenameChunkNum, UPLOAD_DIR)
         json_compatible_item_data = jsonable_encoder(res)
         return JSONResponse(content=json_compatible_item_data)
 
@@ -52,6 +54,7 @@ class MMVC_Rest_Fileuploader:
 
     def post_load_model(
         self,
+        # slot: int = Form(...),
         pyTorchModelFilename: str = Form(...),
         onnxModelFilename: str = Form(...),
         configFilename: str = Form(...),

server/restapi/mods/FileUploader.py

@@ -16,8 +16,11 @@ def upload_file(upload_dirname: str, file: UploadFile, filename: str):
     return {"status": "ERROR", "msg": "uploaded file is not found."}
 
 
-def concat_file_chunks(upload_dirname: str, filename: str, chunkNum: int, dest_dirname: str):
-    target_file_name = os.path.join(dest_dirname, filename)
+def concat_file_chunks(slot: int, upload_dirname: str, filename: str, chunkNum: int, dest_dirname: str):
+    # target_dir = os.path.join(dest_dirname, f"{slot}")
+    target_dir = os.path.join(dest_dirname)
+    os.makedirs(target_dir, exist_ok=True)
+    target_file_name = os.path.join(target_dir, filename)
     if os.path.exists(target_file_name):
         os.remove(target_file_name)
     with open(target_file_name, "ab") as target_file:

server/voice_changer/RVC/RVC.py

@@ -165,7 +165,32 @@ class RVC:
     def get_processing_sampling_rate(self):
         return self.settings.modelSamplingRate
 
-    def generate_input(self, newData: any, inputSize: int, crossfadeSize: int):
+    def generate_input(self, newData: any, inputSize: int, crossfadeSize: int, solaEnabled: bool = False, solaSearchFrame: int = 0):
+        newData = newData.astype(np.float32) / 32768.0
+
+        if hasattr(self, "audio_buffer"):
+            self.audio_buffer = np.concatenate([self.audio_buffer, newData], 0)  # 過去のデータに連結
+        else:
+            self.audio_buffer = newData
+
+        if solaEnabled:
+            convertSize = inputSize + crossfadeSize + solaSearchFrame + self.settings.extraConvertSize
+        else:
+            convertSize = inputSize + crossfadeSize + self.settings.extraConvertSize
+
+        if convertSize % 128 != 0:  # モデルの出力のホップサイズで切り捨てが発生するので補う。
+            convertSize = convertSize + (128 - (convertSize % 128))
+
+        self.audio_buffer = self.audio_buffer[-1 * convertSize:]  # 変換対象の部分だけ抽出
+
+        crop = self.audio_buffer[-1 * (inputSize + crossfadeSize):-1 * (crossfadeSize)]  # 出力部分だけ切り出して音量を確認。(solaとの関係性について、現状は無考慮)
+        rms = np.sqrt(np.square(crop).mean(axis=0))
+        vol = max(rms, self.prevVol * 0.0)
+        self.prevVol = vol
+
+        return (self.audio_buffer, convertSize, vol, solaEnabled)
+
+    def generate_input_old(self, newData: any, inputSize: int, crossfadeSize: int):
         newData = newData.astype(np.float32) / 32768.0
 
         if hasattr(self, "audio_buffer"):
@@ -276,7 +301,13 @@ class RVC:
             audio = self._onnx_inference(data)
         else:
             audio = self._pyTorch_inference(data)
-        return audio
+
+        sola_enabled = data[3]
+        if sola_enabled:
+            return audio
+            # return audio[self.settings.extraConvertSize:]
+        else:
+            return audio
 
     def __del__(self):
         del self.net_g

server/voice_changer/VoiceChanger.py

@@ -13,7 +13,6 @@ from voice_changer.IORecorder import IORecorder
 
 from voice_changer.utils.Timer import Timer
 from voice_changer.utils.VoiceChangerModel import VoiceChangerModel, AudioInOut
-
 import time
 
 
@@ -32,12 +31,13 @@ class VoiceChangerSettings():
     crossFadeOffsetRate: float = 0.1
     crossFadeEndRate: float = 0.9
     crossFadeOverlapSize: int = 4096
+    solaEnabled: int = 1  # 0:off, 1:on
 
     recordIO: int = 0  # 0:off, 1:on
 
     # ↓mutableな物だけ列挙
     intData: list[str] = field(
-        default_factory=lambda: ["inputSampleRate", "crossFadeOverlapSize", "recordIO"]
+        default_factory=lambda: ["inputSampleRate", "crossFadeOverlapSize", "recordIO", "solaEnabled"]
     )
     floatData: list[str] = field(
         default_factory=lambda: ["crossFadeOffsetRate", "crossFadeEndRate"]
@@ -199,10 +199,102 @@ class VoiceChanger():
             if hasattr(self, 'np_prev_audio1') == True:
                 delattr(self, "np_prev_audio1")
 
+            del self.sola_buffer
+
     #  receivedData: tuple of short
     def on_request(self, receivedData: AudioInOut) -> tuple[AudioInOut, list[Union[int, float]]]:
+        if self.settings.solaEnabled and self.modelType == "RVC":
+            return self.on_request_sola(receivedData)
+        else:
+            return self.on_request_legacy(receivedData)
+
+    def on_request_sola(self, receivedData: AudioInOut) -> tuple[AudioInOut, list[Union[int, float]]]:
+        # print("processing with sola")
         processing_sampling_rate = self.voiceChanger.get_processing_sampling_rate()
 
+        # 前処理
+        with Timer("pre-process") as t:
+            if self.settings.inputSampleRate != processing_sampling_rate:
+                newData = cast(AudioInOut, resampy.resample(receivedData, self.settings.inputSampleRate, processing_sampling_rate))
+            else:
+                newData = receivedData
+
+            sola_search_frame = int(0.012 * processing_sampling_rate)
+            # sola_search_frame = 0
+            block_frame = newData.shape[0]
+            crossfade_frame = min(self.settings.crossFadeOverlapSize, block_frame)
+            self._generate_strength(crossfade_frame)
+
+            data = self.voiceChanger.generate_input(newData, block_frame, crossfade_frame, True, sola_search_frame)
+        preprocess_time = t.secs
+
+        # 変換処理
+        with Timer("main-process") as t:
+            try:
+                # Inference
+                audio = self.voiceChanger.inference(data)
+
+                if hasattr(self, 'sola_buffer') == True:
+                    np.set_printoptions(threshold=10000)
+                    audio = audio[-sola_search_frame - crossfade_frame - block_frame:]
+                    # SOLA algorithm from https://github.com/yxlllc/DDSP-SVC, https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI
+                    cor_nom = np.convolve(audio[: crossfade_frame + sola_search_frame], np.flip(self.sola_buffer), 'valid')
+                    cor_den = np.sqrt(np.convolve(audio[: crossfade_frame + sola_search_frame] ** 2, np.ones(crossfade_frame), 'valid') + 1e-3)
+                    sola_offset = np.argmax(cor_nom / cor_den)
+                    print("sola_offset", sola_offset, sola_search_frame)
+
+                    output_wav = audio[sola_offset: sola_offset + block_frame].astype(np.float64)
+                    output_wav[:crossfade_frame] *= self.np_cur_strength
+                    output_wav[:crossfade_frame] += self.sola_buffer[:]
+
+                    result = output_wav
+                else:
+                    print("no sola buffer")
+                    result = np.zeros(4096).astype(np.int16)
+
+                if hasattr(self, 'sola_buffer') == True and sola_offset < sola_search_frame:
+                    sola_buf_org = audio[- sola_search_frame - crossfade_frame + sola_offset: -sola_search_frame + sola_offset]
+                    self.sola_buffer = sola_buf_org * self.np_prev_strength
+                else:
+                    self.sola_buffer = audio[- crossfade_frame:] * self.np_prev_strength
+                    # self.sola_buffer = audio[- crossfade_frame:]
+
+            except Exception as e:
+                print("VC PROCESSING!!!! EXCEPTION!!!", e)
+                print(traceback.format_exc())
+                return np.zeros(1).astype(np.int16), [0, 0, 0]
+        mainprocess_time = t.secs
+
+        # 後処理
+        with Timer("post-process") as t:
+            result = result.astype(np.int16)
+            if self.settings.inputSampleRate != processing_sampling_rate:
+                outputData = cast(AudioInOut, resampy.resample(result, processing_sampling_rate, self.settings.inputSampleRate).astype(np.int16))
+            else:
+                outputData = result
+
+            print_convert_processing(
+                f" Output data size of {result.shape[0]}/{processing_sampling_rate}hz {outputData.shape[0]}/{self.settings.inputSampleRate}hz")
+
+            if self.settings.recordIO == 1:
+                self.ioRecorder.writeInput(receivedData)
+                self.ioRecorder.writeOutput(outputData.tobytes())
+
+            # if receivedData.shape[0] != outputData.shape[0]:
+            #     print(f"Padding, in:{receivedData.shape[0]} out:{outputData.shape[0]}")
+            #     outputData = pad_array(outputData, receivedData.shape[0])
+            #     # print_convert_processing(
+            #     #     f" Padded!, Output data size of {result.shape[0]}/{processing_sampling_rate}hz {outputData.shape[0]}/{self.settings.inputSampleRate}hz")
+        postprocess_time = t.secs
+
+        print_convert_processing(f" [fin] Input/Output size:{receivedData.shape[0]},{outputData.shape[0]}")
+        perf = [preprocess_time, mainprocess_time, postprocess_time]
+        return outputData, perf
+
+    def on_request_legacy(self, receivedData: AudioInOut) -> tuple[AudioInOut, list[Union[int, float]]]:
+        # print("processing with legacy")
+
+        processing_sampling_rate = self.voiceChanger.get_processing_sampling_rate()
         print_convert_processing(f"------------ Convert processing.... ------------")
         # 前処理
         with Timer("pre-process") as t: