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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "VoiceChangerDemo",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyN+8irLJYUFlwMPzvHMSJof",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU",
"gpuClass": "standard"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/w-okada/voice-changer/blob/dev/VoiceChangerDemo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"source": [],
"metadata": {
"id": "57p7pA1Qb5wa"
}
},
{
"cell_type": "code",
"source": [
"!nvidia-smi"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "vV1t7PBRm-o6",
"outputId": "60fc80b2-a39e-4840-88c1-0d8d483a36ca"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Wed Aug 31 06:14:56 2022 \n",
"+-----------------------------------------------------------------------------+\n",
"| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\n",
"|-------------------------------+----------------------+----------------------+\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
"| | | MIG M. |\n",
"|===============================+======================+======================|\n",
"| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
"| N/A 72C P8 12W / 70W | 0MiB / 15109MiB | 0% Default |\n",
"| | | N/A |\n",
"+-------------------------------+----------------------+----------------------+\n",
" \n",
"+-----------------------------------------------------------------------------+\n",
"| Processes: |\n",
"| GPU GI CI PID Type Process name GPU Memory |\n",
"| ID ID Usage |\n",
"|=============================================================================|\n",
"| No running processes found |\n",
"+-----------------------------------------------------------------------------+\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"CONFIG=\"/content/drive/MyDrive/VoiceChanger/config.json\"\n",
"MODEL=\"/content/drive/MyDrive/VoiceChanger/G_326000.pth\""
],
"metadata": {
"id": "nSXATMWYb4Ik"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "2wxD-gRSMU5R",
"outputId": "83bb80fa-9ced-43e2-a304-d53a3501b142"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Mounted at /content/drive\n"
]
}
],
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
]
},
{
"cell_type": "code",
"source": [
"!git clone https://github.com/w-okada/voice-changer.git\n",
"%cd voice-changer/demo/\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "86wTFmqsNMnD",
"outputId": "3fc68f14-b6b7-48bb-e285-5bed78e74f26"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'voice-changer'...\n",
"remote: Enumerating objects: 266, done.\u001b[K\n",
"remote: Counting objects: 100% (266/266), done.\u001b[K\n",
"remote: Compressing objects: 100% (189/189), done.\u001b[K\n",
"remote: Total 266 (delta 123), reused 194 (delta 65), pack-reused 0\u001b[K\n",
"Receiving objects: 100% (266/266), 19.11 MiB | 35.44 MiB/s, done.\n",
"Resolving deltas: 100% (123/123), done.\n",
"/content/voice-changer/demo\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!git checkout dev\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "CBsogR-zWH4r",
"outputId": "f4c9737b-831d-4938-d387-caf07693030e"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Branch 'dev' set up to track remote branch 'dev' from 'origin'.\n",
"Switched to a new branch 'dev'\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!mkdir -p ../frontend/dist\n",
"!cp -r ../docs/* ../frontend/dist/\n",
"!ls ../frontend/dist\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "uCEKf3_JNoyq",
"outputId": "746e1946-5c3a-49af-df26-d86149f8adb1"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"assets\t coffee.png index.html index.js.LICENSE.txt\n",
"audiolet favicon.ico index.js\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!cp ../template/setting_colab.json ../frontend/dist/assets/setting.json"
],
"metadata": {
"id": "Bn4kV8TgXp8i"
},
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!cat ../frontend/dist/assets/setting.json"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pjxPsOOaXXTj",
"outputId": "1bf85102-87ed-462c-e732-cffb878d95f3"
},
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{\n",
" \"app_title\": \"voice-changer\",\n",
" \"majar_mode\": \"colab\",\n",
" \"voice_changer_server_url\": \"http://localhost:8080/test\",\n",
" \"sample_rate\": 48000,\n",
" \"buffer_size\": 1024,\n",
" \"prefix_chunk_size\": 24,\n",
" \"chunk_size\": 24,\n",
" \"speaker_ids\": [100, 107, 101, 102, 103],\n",
" \"speaker_names\": [\"ずんだもん\", \"user\", \"そら\", \"めたん\", \"つぐみ\"],\n",
" \"src_id\": 107,\n",
" \"dst_id\": 100,\n",
" \"vf_enable\": true,\n",
" \"voice_changer_mode\": \"realtime\",\n",
" \"gpu\": 0,\n",
" \"available_gpus\": [-1, 0, 1, 2, 3, 4],\n",
" \"avatar\": {\n",
" \"motion_capture_face\": true,\n",
" \"motion_capture_upperbody\": true,\n",
" \"lip_overwrite_with_voice\": true,\n",
" \"avatar_url\": \"./assets/vrm/zundamon/zundamon.vrm\",\n",
" \"backgournd_image_url\": \"./assets/images/bg_natural_sougen.jpg\",\n",
" \"background_color\": \"#0000dd\",\n",
" \"chroma_key\": \"#0000dd\",\n",
" \"avatar_canvas_size\": [1280, 720],\n",
" \"screen_canvas_size\": [1280, 720]\n",
" },\n",
" \"advance\": {\n",
" \"avatar_draw_skip_rate\": 3,\n",
" \"screen_draw_skip_rate\": 3,\n",
" \"visualizer_draw_skip_rate\": 3,\n",
" \"cross_fade_lower_value\": 0.1,\n",
" \"cross_fade_overlap_rate\": 0.03\n",
" }\n",
"}\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"# 手作業\n",
"\n",
"・configとモデルをdemoフォルダにコピー\n",
"\n",
"・docsをfrontendに変更\n",
"\n",
"・setting.jsonをfrontendにコピー\n"
],
"metadata": {
"id": "8Na2PbLZSWgZ"
}
},
{
"cell_type": "code",
"source": [
"!apt-get install -y espeak libsndfile1-dev\n",
"!pip install flask\n",
"!pip install python-socketio\n",
"!pip install eventlet\n",
"!pip install unidecode\n",
"!pip install phonemizer\n",
"!pip install retry\n",
"!pip install flask\n",
"!pip install flask_cors\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LwZAAuqxX7yY",
"outputId": "c67b2741-7a1e-448d-abf9-7b8d8f5e3d15"
},
"execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Reading package lists... Done\n",
"Building dependency tree \n",
"Reading state information... Done\n",
"libsndfile1-dev is already the newest version (1.0.28-4ubuntu0.18.04.2).\n",
"The following package was automatically installed and is no longer required:\n",
" libnvidia-common-460\n",
"Use 'apt autoremove' to remove it.\n",
"The following additional packages will be installed:\n",
" espeak-data libespeak1 libportaudio2 libsonic0\n",
"The following NEW packages will be installed:\n",
" espeak espeak-data libespeak1 libportaudio2 libsonic0\n",
"0 upgraded, 5 newly installed, 0 to remove and 20 not upgraded.\n",
"Need to get 1,219 kB of archives.\n",
"After this operation, 3,031 kB of additional disk space will be used.\n",
"Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libportaudio2 amd64 19.6.0-1 [64.6 kB]\n",
"Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libsonic0 amd64 0.2.0-6 [13.4 kB]\n",
"Get:3 http://archive.ubuntu.com/ubuntu bionic/universe amd64 espeak-data amd64 1.48.04+dfsg-5 [934 kB]\n",
"Get:4 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libespeak1 amd64 1.48.04+dfsg-5 [145 kB]\n",
"Get:5 http://archive.ubuntu.com/ubuntu bionic/universe amd64 espeak amd64 1.48.04+dfsg-5 [61.6 kB]\n",
"Fetched 1,219 kB in 1s (1,636 kB/s)\n",
"Selecting previously unselected package libportaudio2:amd64.\n",
"(Reading database ... 155676 files and directories currently installed.)\n",
"Preparing to unpack .../libportaudio2_19.6.0-1_amd64.deb ...\n",
"Unpacking libportaudio2:amd64 (19.6.0-1) ...\n",
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"Preparing to unpack .../libsonic0_0.2.0-6_amd64.deb ...\n",
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"Setting up libportaudio2:amd64 (19.6.0-1) ...\n",
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"Setting up libsonic0:amd64 (0.2.0-6) ...\n",
"Setting up libespeak1:amd64 (1.48.04+dfsg-5) ...\n",
"Setting up espeak (1.48.04+dfsg-5) ...\n",
"Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n",
"Processing triggers for libc-bin (2.27-3ubuntu1.5) ...\n",
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"\u001b[K |████████████████████████████████| 56 kB 5.0 MB/s \n",
"\u001b[?25hCollecting bidict>=0.21.0\n",
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"\u001b[?25hInstalling collected packages: python-engineio, bidict, python-socketio\n",
"Successfully installed bidict-0.22.0 python-engineio-4.3.4 python-socketio-5.7.1\n",
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"\u001b[K |████████████████████████████████| 226 kB 33.3 MB/s \n",
"\u001b[?25hCollecting dnspython>=1.15.0\n",
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"\u001b[?25hInstalling collected packages: unidecode\n",
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"\u001b[K |████████████████████████████████| 90 kB 9.5 MB/s \n",
"\u001b[?25hCollecting segments\n",
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"Installing collected packages: isodate, rfc3986, rdflib, language-tags, colorama, csvw, colorlog, clldutils, segments, dlinfo, phonemizer\n",
"Successfully installed clldutils-3.12.0 colorama-0.4.5 colorlog-6.7.0 csvw-3.1.1 dlinfo-1.2.1 isodate-0.6.1 language-tags-1.1.0 phonemizer-3.2.1 rdflib-6.2.0 rfc3986-1.5.0 segments-2.2.1\n",
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Requirement already satisfied: flask in /usr/local/lib/python3.7/dist-packages (1.1.4)\n",
"Requirement already satisfied: itsdangerous<2.0,>=0.24 in /usr/local/lib/python3.7/dist-packages (from flask) (1.1.0)\n",
"Requirement already satisfied: Jinja2<3.0,>=2.10.1 in /usr/local/lib/python3.7/dist-packages (from flask) (2.11.3)\n",
"Requirement already satisfied: Werkzeug<2.0,>=0.15 in /usr/local/lib/python3.7/dist-packages (from flask) (1.0.1)\n",
"Requirement already satisfied: click<8.0,>=5.1 in /usr/local/lib/python3.7/dist-packages (from flask) (7.1.2)\n",
"Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from Jinja2<3.0,>=2.10.1->flask) (2.0.1)\n",
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Collecting flask_cors\n",
" Downloading Flask_Cors-3.0.10-py2.py3-none-any.whl (14 kB)\n",
"Requirement already satisfied: Flask>=0.9 in /usr/local/lib/python3.7/dist-packages (from flask_cors) (1.1.4)\n",
"Requirement already satisfied: Six in /usr/local/lib/python3.7/dist-packages (from flask_cors) (1.15.0)\n",
"Requirement already satisfied: itsdangerous<2.0,>=0.24 in /usr/local/lib/python3.7/dist-packages (from Flask>=0.9->flask_cors) (1.1.0)\n",
"Requirement already satisfied: Jinja2<3.0,>=2.10.1 in /usr/local/lib/python3.7/dist-packages (from Flask>=0.9->flask_cors) (2.11.3)\n",
"Requirement already satisfied: Werkzeug<2.0,>=0.15 in /usr/local/lib/python3.7/dist-packages (from Flask>=0.9->flask_cors) (1.0.1)\n",
"Requirement already satisfied: click<8.0,>=5.1 in /usr/local/lib/python3.7/dist-packages (from Flask>=0.9->flask_cors) (7.1.2)\n",
"Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from Jinja2<3.0,>=2.10.1->Flask>=0.9->flask_cors) (2.0.1)\n",
"Installing collected packages: flask-cors\n",
"Successfully installed flask-cors-3.0.10\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"get_ipython().system_raw(f'python3 serverFlask.py 8082 {CONFIG} {MODEL} >foo 2>&1 &')"
],
"metadata": {
"id": "iNOAB7zISI6J"
},
"execution_count": 14,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!cat foo"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "chu06KpAjEK6",
"outputId": "887c2d50-c49f-4a22-f0d0-8a3667511466"
},
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[2022-08-31 06:17:58,669] INFO in serverFlask: INITIALIZE MODEL\n",
"[2022-08-31 06:18:08,764] INFO in utils: Loaded checkpoint '/content/drive/MyDrive/VoiceChanger/G_326000.pth' (iteration 1136)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from google.colab import output\n",
"\n",
"output.serve_kernel_port_as_window(8082)"
],
"metadata": {
"id": "nkRjZm95l87C",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "abf57f92-5cb6-4325-b64a-095d42f561d5"
},
"execution_count": 27,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"(async (port, path, text, element) => {\n",
" if (!google.colab.kernel.accessAllowed) {\n",
" return;\n",
" }\n",
" element.appendChild(document.createTextNode(''));\n",
" const url = await google.colab.kernel.proxyPort(port);\n",
" const anchor = document.createElement('a');\n",
" anchor.href = new URL(path, url).toString();\n",
" anchor.target = '_blank';\n",
" anchor.setAttribute('data-href', url + path);\n",
" anchor.textContent = text;\n",
" element.appendChild(anchor);\n",
" })(8082, \"/\", \"https://localhost:8082/\", window.element)"
]
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"! ls ../frontend/dist/index.html"
],
"metadata": {
"id": "DKWni4moSyzO",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "b5635a1e-6ac6-41db-a706-dc3e5fb866a5"
},
"execution_count": 23,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"../frontend/dist/index.html\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "3hwJmseXZhJY"
},
"execution_count": null,
"outputs": []
}
]
}

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136
demo/serverFlask.py Executable file
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@ -0,0 +1,136 @@
from flask import Flask, request, Markup, abort, jsonify
from flask_cors import CORS
import logging
from logging.config import dictConfig
import sys
import base64
import torch
import numpy as np
from scipy.io.wavfile import write, read
from datetime import datetime
import traceback
import struct
sys.path.append("mod")
sys.path.append("mod/text")
import utils
from data_utils import TextAudioSpeakerLoader, TextAudioSpeakerCollate
from models import SynthesizerTrn
from text.symbols import symbols
dictConfig({
'version': 1,
'formatters': {'default': {
'format': '[%(asctime)s] %(levelname)s in %(module)s: %(message)s',
}},
'handlers': {'wsgi': {
'class': 'logging.StreamHandler',
'stream': 'ext://flask.logging.wsgi_errors_stream',
'formatter': 'default'
}},
'root': {
'level': 'INFO',
'handlers': ['wsgi']
}
})
app = Flask(__name__, static_folder="../frontend/dist", static_url_path='/')
CORS(app, resources={r"/*": {"origins": "*"}})
class VoiceChanger():
def __init__(self, config, model):
self.hps =utils.get_hparams_from_file(config)
self.net_g = SynthesizerTrn(
len(symbols),
self.hps.data.filter_length // 2 + 1,
self.hps.train.segment_size // self.hps.data.hop_length,
n_speakers=self.hps.data.n_speakers,
**self.hps.model)
self.net_g.eval()
self.gpu_num = torch.cuda.device_count()
print("GPU_NUM:",self.gpu_num)
utils.load_checkpoint( model, self.net_g, None)
def on_request(self, gpu, srcId, dstId, timestamp, wav):
if wav==0:
samplerate, data=read("dummy.wav")
unpackedData = data
else:
unpackedData = np.array(struct.unpack('<%sh'%(len(wav) // struct.calcsize('<h') ), wav))
write("logs/received_data.wav", 24000, unpackedData.astype(np.int16))
try:
if gpu<0 or self.gpu_num==0 :
with torch.no_grad():
dataset = TextAudioSpeakerLoader("dummy.txt", self.hps.data, no_use_textfile=True)
data = dataset.get_audio_text_speaker_pair([ unpackedData, srcId, "a"])
data = TextAudioSpeakerCollate()([data])
x, x_lengths, spec, spec_lengths, y, y_lengths, sid_src = [x.cpu() for x in data]
sid_tgt1 = torch.LongTensor([dstId]).cpu()
audio1 = (self.net_g.cpu().voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt1)[0][0,0].data * self.hps.data.max_wav_value).cpu().float().numpy()
else:
with torch.no_grad():
dataset = TextAudioSpeakerLoader("dummy.txt", self.hps.data, no_use_textfile=True)
data = dataset.get_audio_text_speaker_pair([ unpackedData, srcId, "a"])
data = TextAudioSpeakerCollate()([data])
x, x_lengths, spec, spec_lengths, y, y_lengths, sid_src = [x.cuda(gpu) for x in data]
sid_tgt1 = torch.LongTensor([dstId]).cuda(gpu)
audio1 = (self.net_g.cuda(gpu).voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt1)[0][0,0].data * self.hps.data.max_wav_value).cpu().float().numpy()
except Exception as e:
print("VC PROCESSING!!!! EXCEPTION!!!", e)
print(traceback.format_exc())
audio1 = audio1.astype(np.int16)
return audio1
@app.route('/test', methods=['GET', 'POST'])
def test():
try:
if request.method == 'GET':
return request.args.get('query', '')
elif request.method == 'POST':
print("POST REQUEST PROCESSING....")
gpu = int(request.json['gpu'])
srcId = int(request.json['srcId'])
dstId = int(request.json['dstId'])
timestamp = int(request.json['timestamp'])
buffer = request.json['buffer']
wav = base64.b64decode(buffer)
# print(wav)
# print(base64.b64encode(wav))
changedVoice = voiceChanger.on_request(gpu, srcId, dstId, timestamp, wav)
changedVoiceBase64 = base64.b64encode(changedVoice).decode('utf-8')
# print("changedVoice",changedVoice)
# print("CV64",changedVoiceBase64)
data = {
"gpu":gpu,
"srcId":srcId,
"dstId":dstId,
"timestamp":timestamp,
"changedVoiceBase64":changedVoiceBase64
}
return jsonify(data)
else:
return abort(400)
except Exception as e:
print("REQUEST PROCESSING!!!! EXCEPTION!!!", e)
print(traceback.format_exc())
return str(e)
if __name__ == '__main__':
args = sys.argv
PORT = args[1]
CONFIG = args[2]
MODEL = args[3]
app.logger.info('INITIALIZE MODEL')
voiceChanger = VoiceChanger(CONFIG, MODEL)
voiceChanger.on_request(0,0,0,0,0)
app.logger.info('START APP')
app.run(debug=True, host='0.0.0.0',port=PORT)

10
demo/serverSIO.py
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@ -17,7 +17,7 @@ from text.symbols import symbols
class MyCustomNamespace(socketio.Namespace): # 名前空間を設定するクラス class MyCustomNamespace(socketio.Namespace):
def __init__(self, namespace, config, model): def __init__(self, namespace, config, model):
super().__init__(namespace) super().__init__(namespace)
self.hps =utils.get_hparams_from_file(config) self.hps =utils.get_hparams_from_file(config)
@ -36,7 +36,7 @@ class MyCustomNamespace(socketio.Namespace): # 名前空間を設定するクラ
print('[{}] connet sid : {}'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S') , sid)) print('[{}] connet sid : {}'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S') , sid))
# print('[{}] connet env : {}'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S') , environ)) # print('[{}] connet env : {}'.format(datetime.now().strftime('%Y-%m-%d %H:%M:%S') , environ))
def on_request_message(self, sid, msg): # 送信してきたクライアントだけにメッセージを送る関数 def on_request_message(self, sid, msg):
# print("MESSGaa", msg) # print("MESSGaa", msg)
gpu = int(msg[0]) gpu = int(msg[0])
srcId = int(msg[1]) srcId = int(msg[1])
@ -88,9 +88,9 @@ if __name__ == '__main__':
print(f"start... PORT:{PORT}, CONFIG:{CONFIG}, MODEL:{MODEL}") print(f"start... PORT:{PORT}, CONFIG:{CONFIG}, MODEL:{MODEL}")
# sio = socketio.Server(cors_allowed_origins='http://localhost:8080') # sio = socketio.Server(cors_allowed_origins='http://localhost:8080')
sio = socketio.Server(cors_allowed_origins='*') sio = socketio.Server(cors_allowed_origins='*')
sio.register_namespace(MyCustomNamespace('/test', CONFIG, MODEL)) # 名前空間を設定 sio.register_namespace(MyCustomNamespace('/test', CONFIG, MODEL))
app = socketio.WSGIApp(sio,static_files={ app = socketio.WSGIApp(sio,static_files={
'': '../frontend/dist', '': '../frontend/dist',
}) # wsgiサーバーミドルウェア生成 })
eventlet.wsgi.server(eventlet.listen(('0.0.0.0',int(PORT))), app) # wsgiサーバー起動 eventlet.wsgi.server(eventlet.listen(('0.0.0.0',int(PORT))), app)

14
demo/setupFlask.sh Executable file
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@ -0,0 +1,14 @@
#!/bin/bash
echo config: $1
echo model: $2
cp -r /resources/* .
if [[ -e ./setting.json ]]; then
cp ./setting.json ../frontend/dist/assets/setting.json
fi
pip install flask
pip install flask_cors
python3 serverFlask.py 8080 $1 $2

2
docs/assets/setting.json
View File

@ -1,8 +1,10 @@
{ {
"app_title": "voice-changer", "app_title": "voice-changer",
"majar_mode": "docker",
"voice_changer_server_url": "http://localhost:8080/test", "voice_changer_server_url": "http://localhost:8080/test",
"sample_rate": 48000, "sample_rate": 48000,
"buffer_size": 1024, "buffer_size": 1024,
"prefix_chunk_size": 24,
"chunk_size": 24, "chunk_size": 24,
"speaker_ids": [100, 107, 101, 102, 103], "speaker_ids": [100, 107, 101, 102, 103],
"speaker_names": ["ずんだもん", "user", "そら", "めたん", "つぐみ"], "speaker_names": ["ずんだもん", "user", "そら", "めたん", "つぐみ"],

1
docs/audiolet/index.js Executable file
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@ -0,0 +1 @@
(()=>{"use strict";class e extends AudioWorkletProcessor{initialized=!1;playBuffer=[];deltaChunkSize=24;bufferSize=1024;constructor(){super(),this.initialized=!0,this.port.onmessage=this.handleMessage.bind(this)}prevF32Data=null;handleMessage(e){if(e.data.deltaSize)return void(this.deltaChunkSize=e.data.deltaSize);const t=e.data.data,l=new Int16Array(t),n=new Float32Array(l.length);l.forEach(((e,t)=>{const l=e>=32768?-(65536-e)/32768:e/32767;n[t]=l}));let s=this.prevF32Data?this.prevF32Data.slice(this.prevF32Data.length-this.deltaChunkSize*this.bufferSize/2):null;const h=n.slice(n.length-this.deltaChunkSize*this.bufferSize*2/2,n.length-this.deltaChunkSize*this.bufferSize/2);if(s?.length!==h.length&&(s=null),s)for(let e=0;e<s.length;e++){let t=0;if(e<s.length/3)t=0;else if(e>s.length/3*2)t=1;else{const l=e-s.length/3;t=Math.min(l/(s.length/3),1)}const l=s[e]*(1-t),n=h[e]*t;h[e]=l+n}if(this.playBuffer.length>50)for(console.log("Buffer truncated");this.playBuffer.length>2;)this.playBuffer.shift();let i;for(let e=0;e<h.length;e++){const t=2*e%128;0===t&&(i=new Float32Array(128));const l=h[e],n=e+1<h.length?h[e+1]:h[e];i[t]=l,i[t+1]=(l+n)/2,i.length===t+2&&this.playBuffer.push(i)}this.prevF32Data=n}handleMessage_(e){const t=e.data.data,l=new Int16Array(t),n=new Float32Array(l.length);l.forEach(((e,t)=>{const l=e>=32768?-(65536-e)/32768:e/32767;n[t]=l}));let s=this.prevF32Data?this.prevF32Data.slice(this.prevF32Data.length/2):null;const h=n.slice(0,n.length/2);if(s?.length!==h.length&&(s=null),s)for(let e=0;e<s.length;e++){let t=0;if(e<s.length/3)t=0;else if(e>s.length/3*2)t=1;else{const l=e-s.length/3;t=Math.min(l/(s.length/100),1)}const l=s[e]*(1-t),n=h[e]*t;h[e]=l+n}if(this.playBuffer.length>100)for(console.log("Buffer truncated");this.playBuffer.length>2;)this.playBuffer.shift();let i;for(let e=0;e<h.length;e++){const t=2*e%128;0===t&&(i=new Float32Array(128));const l=h[e],n=e+1<h.length?h[e+1]:h[e];i[t]=l,i[t+1]=(l+n)/2,i.length===t+2&&this.playBuffer.push(i)}this.prevF32Data=n}process(e,t,l){if(!this.initialized)return console.log("worklet_process not ready"),!0;if(0===this.playBuffer.length)return console.log("no play buffer"),!0;const n=this.playBuffer.shift();return t[0][0].set(n),!0}}registerProcessor("voice-player-worklet-processor",e)})();

2
docs/index.js
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File diff suppressed because one or more lines are too long

2
start2.sh
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@ -2,7 +2,7 @@
# 参考:https://programwiz.org/2022/03/22/how-to-write-shell-script-for-option-parsing/ # 参考:https://programwiz.org/2022/03/22/how-to-write-shell-script-for-option-parsing/
DOCKER_IMAGE=dannadori/voice-changer:20220829_110113 DOCKER_IMAGE=dannadori/voice-changer:20220831_151141
TENSORBOARD_PORT=6006 TENSORBOARD_PORT=6006
VOICE_CHANGER_PORT=8080 VOICE_CHANGER_PORT=8080

8
template/setting.json
View File

@ -1,8 +1,10 @@
{ {
"app_title": "voice-changer", "app_title": "voice-changer",
"majar_mode": "docker",
"voice_changer_server_url": "http://localhost:8080/test", "voice_changer_server_url": "http://localhost:8080/test",
"sample_rate": 48000, "sample_rate": 48000,
"buffer_size": 1024, "buffer_size": 1024,
"prefix_chunk_size": 24,
"chunk_size": 24, "chunk_size": 24,
"speaker_ids": [100, 107, 101, 102, 103], "speaker_ids": [100, 107, 101, 102, 103],
"speaker_names": ["ずんだもん", "user", "そら", "めたん", "つぐみ"], "speaker_names": ["ずんだもん", "user", "そら", "めたん", "つぐみ"],
@ -11,7 +13,7 @@
"vf_enable": true, "vf_enable": true,
"voice_changer_mode": "realtime", "voice_changer_mode": "realtime",
"gpu": 0, "gpu": 0,
"available_gpus": [-1, 0, 1, 2, 3, 4, 5, 100, 200], "available_gpus": [-1, 0, 1, 2, 3, 4],
"avatar": { "avatar": {
"motion_capture_face": true, "motion_capture_face": true,
"motion_capture_upperbody": true, "motion_capture_upperbody": true,
@ -26,6 +28,8 @@
"advance": { "advance": {
"avatar_draw_skip_rate": 3, "avatar_draw_skip_rate": 3,
"screen_draw_skip_rate": 3, "screen_draw_skip_rate": 3,
"visualizer_draw_skip_rate": 3 "visualizer_draw_skip_rate": 3,
"cross_fade_lower_value": 0.1,
"cross_fade_overlap_rate": 0.03
} }
} }

35
template/setting_colab.json Normal file
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@ -0,0 +1,35 @@
{
"app_title": "voice-changer",
"majar_mode": "colab",
"voice_changer_server_url": "http://localhost:8080/test",
"sample_rate": 48000,
"buffer_size": 1024,
"prefix_chunk_size": 24,
"chunk_size": 24,
"speaker_ids": [100, 107, 101, 102, 103],
"speaker_names": ["ずんだもん", "user", "そら", "めたん", "つぐみ"],
"src_id": 107,
"dst_id": 100,
"vf_enable": true,
"voice_changer_mode": "realtime",
"gpu": 0,
"available_gpus": [-1, 0, 1, 2, 3, 4],
"avatar": {
"motion_capture_face": true,
"motion_capture_upperbody": true,
"lip_overwrite_with_voice": true,
"avatar_url": "./assets/vrm/zundamon/zundamon.vrm",
"backgournd_image_url": "./assets/images/bg_natural_sougen.jpg",
"background_color": "#0000dd",
"chroma_key": "#0000dd",
"avatar_canvas_size": [1280, 720],
"screen_canvas_size": [1280, 720]
},
"advance": {
"avatar_draw_skip_rate": 3,
"screen_draw_skip_rate": 3,
"visualizer_draw_skip_rate": 3,
"cross_fade_lower_value": 0.1,
"cross_fade_overlap_rate": 0.03
}
}

2
trainer/Dockerfile
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@ -1,4 +1,4 @@
FROM dannadori/voice-changer-internal:20220829_105932 as front FROM dannadori/voice-changer-internal:20220831_150941 as front
FROM debian:bullseye-slim as base FROM debian:bullseye-slim as base
ARG DEBIAN_FRONTEND=noninteractive ARG DEBIAN_FRONTEND=noninteractive