mirror of
https://github.com/w-okada/voice-changer.git
synced 2025-02-02 16:23:58 +03:00
separate sio
This commit is contained in:
wataru
parent
32bd737e14
commit
86e71d05a3
5
.gitignore
vendored
5
.gitignore
vendored
@ -1,2 +1,7 @@
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dummy
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node_modules
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__pycache__
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server/upload_dir/
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server/MMVC_Trainer/
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server/key
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463
server/MMVCServerSIO.py
Executable file
463
server/MMVCServerSIO.py
Executable file
@ -0,0 +1,463 @@
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import sys, os, struct, argparse, logging, shutil, base64, traceback
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logging.getLogger('numba').setLevel(logging.WARNING)
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class UvicornSuppressFilter(logging.Filter):
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def filter(self, record):
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return False
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logger = logging.getLogger("uvicorn.error")
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logger.addFilter(UvicornSuppressFilter())
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# logger.propagate = False
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logger = logging.getLogger("multipart.multipart")
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logger.propagate = False
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from dataclasses import dataclass
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from datetime import datetime
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from distutils.util import strtobool
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import numpy as np
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from scipy.io.wavfile import write, read
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sys.path.append("MMVC_Trainer")
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sys.path.append("MMVC_Trainer/text")
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from fastapi.routing import APIRoute
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from fastapi import HTTPException, Request, Response, FastAPI, UploadFile, File, Form
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from fastapi.staticfiles import StaticFiles
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from fastapi.encoders import jsonable_encoder
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from fastapi.responses import JSONResponse
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from fastapi.middleware.cors import CORSMiddleware
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import uvicorn
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import socketio
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from pydantic import BaseModel
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from typing import Callable
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from mods.Trainer_Speakers import mod_get_speakers
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from mods.Trainer_Training import mod_post_pre_training, mod_post_start_training, mod_post_stop_training, mod_get_related_files, mod_get_tail_training_log
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from mods.Trainer_Model import mod_get_model, mod_delete_model
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from mods.Trainer_Models import mod_get_models
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from mods.Trainer_MultiSpeakerSetting import mod_get_multi_speaker_setting, mod_post_multi_speaker_setting
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from mods.Trainer_Speaker_Voice import mod_get_speaker_voice
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from mods.Trainer_Speaker_Voices import mod_get_speaker_voices
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from mods.Trainer_Speaker import mod_delete_speaker
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from mods.FileUploader import upload_file, concat_file_chunks
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from mods.VoiceChanger import VoiceChanger
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from mods.ssl import create_self_signed_cert
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from sio.MMVC_Namespace import MMVC_Namespace
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from voice_changer.VoiceChangerManager import VoiceChangerManager
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@dataclass
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class ExApplicationInfo():
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external_tensorboard_port: int
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exApplitionInfo = ExApplicationInfo(external_tensorboard_port=0)
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class VoiceModel(BaseModel):
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gpu: int
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srcId: int
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dstId: int
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timestamp: int
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prefixChunkSize: int
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buffer: str
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def setupArgParser():
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parser = argparse.ArgumentParser()
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parser.add_argument("-t", type=str, default="MMVC",
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help="Server type. MMVC|TRAIN")
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parser.add_argument("-p", type=int, default=8080, help="port")
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parser.add_argument("-c", type=str, help="path for the config.json")
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parser.add_argument("-m", type=str, help="path for the model file")
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parser.add_argument("--https", type=strtobool,
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default=False, help="use https")
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parser.add_argument("--httpsKey", type=str,
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default="ssl.key", help="path for the key of https")
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parser.add_argument("--httpsCert", type=str,
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default="ssl.cert", help="path for the cert of https")
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parser.add_argument("--httpsSelfSigned", type=strtobool,
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default=True, help="generate self-signed certificate")
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parser.add_argument("--colab", type=strtobool,
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default=False, help="run on colab")
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return parser
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def printMessage(message, level=0):
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if level == 0:
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print(f"\033[17m{message}\033[0m")
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elif level == 1:
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print(f"\033[34m {message}\033[0m")
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elif level == 2:
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print(f"\033[32m {message}\033[0m")
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else:
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print(f"\033[47m {message}\033[0m")
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global app_socketio
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global app_fastapi
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parser = setupArgParser()
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args = parser.parse_args()
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printMessage(f"Phase name:{__name__}", level=2)
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thisFilename = os.path.basename(__file__)[:-3]
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class ValidationErrorLoggingRoute(APIRoute):
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def get_route_handler(self) -> Callable:
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original_route_handler = super().get_route_handler()
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async def custom_route_handler(request: Request) -> Response:
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try:
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return await original_route_handler(request)
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except Exception as exc:
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print("Exception", request.url, str(exc))
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body = await request.body()
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detail = {"errors": exc.errors(), "body": body.decode()}
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raise HTTPException(status_code=422, detail=detail)
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return custom_route_handler
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if __name__ == thisFilename or args.colab == True:
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printMessage(f"PHASE3:{__name__}", level=2)
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TYPE = args.t
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PORT = args.p
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CONFIG = args.c
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MODEL = args.m
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if os.getenv("EX_TB_PORT"):
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EX_TB_PORT = os.environ["EX_TB_PORT"]
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exApplitionInfo.external_tensorboard_port = int(EX_TB_PORT)
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app_fastapi = FastAPI()
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app_fastapi.router.route_class = ValidationErrorLoggingRoute
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app_fastapi.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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app_fastapi.mount(
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"/front", StaticFiles(directory="../frontend/dist", html=True), name="static")
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app_fastapi.mount(
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"/trainer", StaticFiles(directory="../frontend/dist", html=True), name="static")
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app_fastapi.mount(
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"/recorder", StaticFiles(directory="../frontend/dist", html=True), name="static")
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sio = socketio.AsyncServer(
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async_mode='asgi',
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cors_allowed_origins='*'
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)
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voiceChangerManager = VoiceChangerManager.get_instance()
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namespace = MMVC_Namespace.get_instance(voiceChangerManager)
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sio.register_namespace(namespace)
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if CONFIG and MODEL:
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voiceChangerManager.loadModel(CONFIG, MODEL)
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# namespace.loadWhisperModel("base")
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app_socketio = socketio.ASGIApp(
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sio,
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other_asgi_app=app_fastapi,
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static_files={
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'/assets/icons/github.svg': {
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'filename': '../frontend/dist/assets/icons/github.svg',
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'content_type': 'image/svg+xml'
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},
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'': '../frontend/dist',
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'/': '../frontend/dist/index.html',
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}
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)
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@app_fastapi.get("/api/hello")
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async def index():
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return {"result": "Index"}
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############
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# File Uploder
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# ##########
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UPLOAD_DIR = "upload_dir"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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MODEL_DIR = "MMVC_Trainer/logs"
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os.makedirs(MODEL_DIR, exist_ok=True)
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@app_fastapi.post("/upload_file")
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async def post_upload_file(
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file: UploadFile = File(...),
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filename: str = Form(...)
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):
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return upload_file(UPLOAD_DIR, file, filename)
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@app_fastapi.post("/load_model")
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async def post_load_model(
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modelFilename: str = Form(...),
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modelFilenameChunkNum: int = Form(...),
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configFilename: str = Form(...)
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):
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modelFilePath = concat_file_chunks(
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UPLOAD_DIR, modelFilename, modelFilenameChunkNum, UPLOAD_DIR)
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print(f'File saved to: {modelFilePath}')
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configFilePath = os.path.join(UPLOAD_DIR, configFilename)
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voiceChangerManager.loadModel(configFilePath, modelFilePath)
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return {"load": f"{modelFilePath}, {configFilePath}"}
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@app_fastapi.post("/load_model_for_train")
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async def post_load_model_for_train(
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modelGFilename: str = Form(...),
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modelGFilenameChunkNum: int = Form(...),
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modelDFilename: str = Form(...),
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modelDFilenameChunkNum: int = Form(...),
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):
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modelGFilePath = concat_file_chunks(
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UPLOAD_DIR, modelGFilename, modelGFilenameChunkNum, MODEL_DIR)
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modelDFilePath = concat_file_chunks(
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UPLOAD_DIR, modelDFilename, modelDFilenameChunkNum, MODEL_DIR)
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return {"File saved": f"{modelGFilePath}, {modelDFilePath}"}
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@app_fastapi.post("/extract_voices")
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async def post_load_model(
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zipFilename: str = Form(...),
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zipFileChunkNum: int = Form(...),
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):
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zipFilePath = concat_file_chunks(
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UPLOAD_DIR, zipFilename, zipFileChunkNum, UPLOAD_DIR)
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shutil.unpack_archive(zipFilePath, "MMVC_Trainer/dataset/textful/")
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return {"Zip file unpacked": f"{zipFilePath}"}
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############
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# Voice Changer
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# ##########
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@app_fastapi.post("/test")
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async def post_test(voice: VoiceModel):
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try:
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# print("POST REQUEST PROCESSING....")
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gpu = voice.gpu
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srcId = voice.srcId
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dstId = voice.dstId
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timestamp = voice.timestamp
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prefixChunkSize = voice.prefixChunkSize
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buffer = voice.buffer
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wav = base64.b64decode(buffer)
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if wav == 0:
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samplerate, data = read("dummy.wav")
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unpackedData = data
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else:
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unpackedData = np.array(struct.unpack(
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'<%sh' % (len(wav) // struct.calcsize('<h')), wav))
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# write("logs/received_data.wav", 24000,
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# unpackedData.astype(np.int16))
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changedVoice = voiceChangerManager.changeVoice(
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gpu, srcId, dstId, timestamp, prefixChunkSize, unpackedData)
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changedVoiceBase64 = base64.b64encode(changedVoice).decode('utf-8')
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data = {
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"gpu": gpu,
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"srcId": srcId,
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"dstId": dstId,
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"timestamp": timestamp,
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"prefixChunkSize": prefixChunkSize,
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"changedVoiceBase64": changedVoiceBase64
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}
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json_compatible_item_data = jsonable_encoder(data)
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return JSONResponse(content=json_compatible_item_data)
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except Exception as e:
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print("REQUEST PROCESSING!!!! EXCEPTION!!!", e)
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print(traceback.format_exc())
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return str(e)
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# Trainer REST API ※ ColabがTop直下のパスにしかPOSTを投げれないようなので"REST風"
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@app_fastapi.get("/get_speakers")
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async def get_speakers():
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return mod_get_speakers()
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@app_fastapi.delete("/delete_speaker")
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async def delete_speaker(speaker: str = Form(...)):
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return mod_delete_speaker(speaker)
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@app_fastapi.get("/get_speaker_voices")
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async def get_speaker_voices(speaker: str):
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return mod_get_speaker_voices(speaker)
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@app_fastapi.get("/get_speaker_voice")
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async def get_speaker_voices(speaker: str, voice: str):
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return mod_get_speaker_voice(speaker, voice)
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@app_fastapi.get("/get_multi_speaker_setting")
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async def get_multi_speaker_setting():
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return mod_get_multi_speaker_setting()
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@app_fastapi.post("/post_multi_speaker_setting")
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async def post_multi_speaker_setting(setting: str = Form(...)):
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return mod_post_multi_speaker_setting(setting)
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@app_fastapi.get("/get_models")
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async def get_models():
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return mod_get_models()
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@app_fastapi.get("/get_model")
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async def get_model(model: str):
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return mod_get_model(model)
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@app_fastapi.delete("/delete_model")
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async def delete_model(model: str = Form(...)):
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return mod_delete_model(model)
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@app_fastapi.post("/post_pre_training")
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async def post_pre_training(batch: int = Form(...)):
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return mod_post_pre_training(batch)
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@app_fastapi.post("/post_start_training")
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async def post_start_training(enable_finetuning: bool = Form(...),GModel: str = Form(...),DModel: str = Form(...)):
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print("POST START TRAINING..")
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return mod_post_start_training(enable_finetuning, GModel, DModel)
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@app_fastapi.post("/post_stop_training")
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async def post_stop_training():
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print("POST STOP TRAINING..")
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return mod_post_stop_training()
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@app_fastapi.get("/get_related_files")
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async def get_related_files():
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return mod_get_related_files()
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@app_fastapi.get("/get_tail_training_log")
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async def get_tail_training_log(num: int):
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return mod_get_tail_training_log(num)
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@app_fastapi.get("/get_ex_application_info")
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async def get_ex_application_info():
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json_compatible_item_data = jsonable_encoder(exApplitionInfo)
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return JSONResponse(content=json_compatible_item_data)
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if __name__ == '__mp_main__':
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printMessage(f"PHASE2adasdfadfasd:{__name__}", level=2)
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if __name__ == '__main__':
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printMessage(f"PHASE1:{__name__}", level=2)
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TYPE = args.t
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PORT = args.p
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CONFIG = args.c
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MODEL = args.m
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if TYPE != "MMVC" and TYPE != "TRAIN":
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print("Type(-t) should be MMVC or TRAIN")
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exit(1)
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printMessage(f"Start MMVC SocketIO Server", level=0)
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printMessage(f"CONFIG:{CONFIG}, MODEL:{MODEL}", level=1)
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if args.colab == False:
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if os.getenv("EX_PORT"):
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EX_PORT = os.environ["EX_PORT"]
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printMessage(
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f"External_Port:{EX_PORT} Internal_Port:{PORT}", level=1)
|
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else:
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printMessage(f"Internal_Port:{PORT}", level=1)
|
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|
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if os.getenv("EX_TB_PORT"):
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EX_TB_PORT = os.environ["EX_TB_PORT"]
|
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printMessage(f"External_TeonsorBord_Port:{EX_TB_PORT}", level=1)
|
||||
|
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if os.getenv("EX_IP"):
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EX_IP = os.environ["EX_IP"]
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printMessage(f"External_IP:{EX_IP}", level=1)
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# HTTPS key/cert作成
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if args.https and args.httpsSelfSigned == 1:
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# HTTPS(おれおれ証明書生成)
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os.makedirs("./key", exist_ok=True)
|
||||
key_base_name = f"{datetime.now().strftime('%Y%m%d_%H%M%S')}"
|
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keyname = f"{key_base_name}.key"
|
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certname = f"{key_base_name}.cert"
|
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create_self_signed_cert(certname, keyname, certargs={"Country": "JP",
|
||||
"State": "Tokyo",
|
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"City": "Chuo-ku",
|
||||
"Organization": "F",
|
||||
"Org. Unit": "F"}, cert_dir="./key")
|
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key_path = os.path.join("./key", keyname)
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cert_path = os.path.join("./key", certname)
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||||
printMessage(
|
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f"protocol: HTTPS(self-signed), key:{key_path}, cert:{cert_path}", level=1)
|
||||
elif args.https and args.httpsSelfSigned == 0:
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# HTTPS
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||||
key_path = args.httpsKey
|
||||
cert_path = args.httpsCert
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printMessage(
|
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f"protocol: HTTPS, key:{key_path}, cert:{cert_path}", level=1)
|
||||
else:
|
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# HTTP
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||||
printMessage(f"protocol: HTTP", level=1)
|
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|
||||
# アドレス表示
|
||||
if args.https == 1:
|
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printMessage(
|
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f"open https://<IP>:<PORT>/ with your browser.", level=0)
|
||||
else:
|
||||
printMessage(
|
||||
f"open http://<IP>:<PORT>/ with your browser.", level=0)
|
||||
|
||||
if TYPE == "MMVC":
|
||||
path = ""
|
||||
else:
|
||||
path = "trainer"
|
||||
if "EX_PORT" in locals() and "EX_IP" in locals() and args.https == 1:
|
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printMessage(f"In many cases it is one of the following", level=1)
|
||||
printMessage(f"https://localhost:{EX_PORT}/{path}", level=1)
|
||||
for ip in EX_IP.strip().split(" "):
|
||||
printMessage(f"https://{ip}:{EX_PORT}/{path}", level=1)
|
||||
elif "EX_PORT" in locals() and "EX_IP" in locals() and args.https == 0:
|
||||
printMessage(f"In many cases it is one of the following", level=1)
|
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printMessage(f"http://localhost:{EX_PORT}/{path}", level=1)
|
||||
|
||||
# サーバ起動
|
||||
if args.https:
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# HTTPS サーバ起動
|
||||
uvicorn.run(
|
||||
f"{os.path.basename(__file__)[:-3]}:app_socketio",
|
||||
host="0.0.0.0",
|
||||
port=int(PORT),
|
||||
reload=True,
|
||||
ssl_keyfile=key_path,
|
||||
ssl_certfile=cert_path,
|
||||
log_level="critical"
|
||||
)
|
||||
else:
|
||||
# HTTP サーバ起動
|
||||
if args.colab == True:
|
||||
uvicorn.run(
|
||||
f"{os.path.basename(__file__)[:-3]}:app_fastapi",
|
||||
host="0.0.0.0",
|
||||
port=int(PORT),
|
||||
log_level="critical"
|
||||
)
|
||||
else:
|
||||
uvicorn.run(
|
||||
f"{os.path.basename(__file__)[:-3]}:app_socketio",
|
||||
host="0.0.0.0",
|
||||
port=int(PORT),
|
||||
reload=True,
|
||||
log_level="critical"
|
||||
)
|
||||
|
||||
43
server/sio/MMVC_Namespace.py
Normal file
43
server/sio/MMVC_Namespace.py
Normal file
@ -0,0 +1,43 @@
|
||||
import struct
|
||||
from datetime import datetime
|
||||
import numpy as np
|
||||
import socketio
|
||||
from voice_changer.VoiceChangerManager import VoiceChangerManager
|
||||
|
||||
|
||||
class MMVC_Namespace(socketio.AsyncNamespace):
|
||||
def __init__(self, namespace:str, voiceChangerManager:VoiceChangerManager):
|
||||
super().__init__(namespace)
|
||||
self.voiceChangerManager = voiceChangerManager
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls, voiceChangerManager:VoiceChangerManager):
|
||||
if not hasattr(cls, "_instance"):
|
||||
cls._instance = cls("/test", voiceChangerManager)
|
||||
return cls._instance
|
||||
|
||||
def on_connect(self, sid, environ):
|
||||
# print('[{}] connet sid : {}'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S') , sid))
|
||||
pass
|
||||
|
||||
async def on_request_message(self, sid, msg):
|
||||
# print("on_request_message", torch.cuda.memory_allocated())
|
||||
gpu = int(msg[0])
|
||||
srcId = int(msg[1])
|
||||
dstId = int(msg[2])
|
||||
timestamp = int(msg[3])
|
||||
prefixChunkSize = int(msg[4])
|
||||
data = msg[5]
|
||||
# print(srcId, dstId, timestamp)
|
||||
unpackedData = np.array(struct.unpack(
|
||||
'<%sh' % (len(data) // struct.calcsize('<h')), data))
|
||||
audio1 = self.voiceChangerManager.changeVoice(
|
||||
gpu, srcId, dstId, timestamp, prefixChunkSize, unpackedData)
|
||||
|
||||
bin = struct.pack('<%sh' % len(audio1), *audio1)
|
||||
await self.emit('response', [timestamp, bin])
|
||||
|
||||
def on_disconnect(self, sid):
|
||||
# print('[{}] disconnect'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
pass
|
||||
|
||||
21
server/voice_changer/VoiceChangerManager.py
Normal file
21
server/voice_changer/VoiceChangerManager.py
Normal file
@ -0,0 +1,21 @@
|
||||
import numpy as np
|
||||
from mods.VoiceChanger import VoiceChanger
|
||||
|
||||
class VoiceChangerManager():
|
||||
@classmethod
|
||||
def get_instance(cls):
|
||||
if not hasattr(cls, "_instance"):
|
||||
cls._instance = cls()
|
||||
return cls._instance
|
||||
|
||||
def loadModel(self, config, model):
|
||||
if hasattr(self, 'voiceChanger') == True:
|
||||
self.voiceChanger.destroy()
|
||||
self.voiceChanger = VoiceChanger(config, model)
|
||||
|
||||
def changeVoice(self, gpu, srcId, dstId, timestamp, prefixChunkSize, unpackedData):
|
||||
if hasattr(self, 'voiceChanger') == True:
|
||||
return self.voiceChanger.on_request(gpu, srcId, dstId, timestamp, prefixChunkSize, unpackedData)
|
||||
else:
|
||||
print("Voice Change is not loaded. Did you load a correct model?")
|
||||
return np.zeros(1).astype(np.int16)
|
||||
Loading…
Reference in New Issue
Block a user