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voice-changer/Hina_Modified_Realtime_Voice_Changer_on_Colab.ipynb

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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/hinabl/voice-changer/blob/master/Hina_Modified_Realtime_Voice_Changer_on_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "Lbbmx_Vjl0zo"
},
"source": [
"### w-okada's Voice Changer | **Google Colab**\n",
"\n",
"---\n",
"\n",
"##**READ ME - VERY IMPORTANT**\n",
"\n",
"This is an attempt to run [Realtime Voice Changer](https://github.com/w-okada/voice-changer) on Google Colab, still not perfect but is totally usable, you can use the following settings for better results:\n",
"\n",
"If you're using a index: `f0: RMVPE_ONNX | Chunk: 112 or higher | Extra: 8192`\\\n",
"If you're not using a index: `f0: RMVPE_ONNX | Chunk: 96 or higher | Extra: 16384`\\\n",
"**Don't forget to select your Colab GPU in the GPU field (<b>Tesla T4</b>, for free users)*\n",
"> Seems that PTH models performance better than ONNX for now, you can still try ONNX models and see if it satisfies you\n",
"\n",
"\n",
"*You can always [click here](https://github.com/YunaOneeChan/Voice-Changer-Settings) to check if these settings are up-to-date*\n",
"<br><br>\n",
"\n",
"---\n",
"\n",
"###Always use Colab GPU (**VERY VERY VERY IMPORTANT!**)\n",
"You need to use a Colab GPU so the Voice Changer can work faster and better\\\n",
"Use the menu above and click on **Runtime** » **Change runtime** » **Hardware acceleration** to select a GPU (**T4 is the free one**)\n",
"\n",
"---\n",
"\n",
"<br>\n",
"\n",
"# **Credits and Support**\n",
"Realtime Voice Changer by [w-okada](https://github.com/w-okada)\\\n",
"Colab files updated by [rafacasari](https://github.com/Rafacasari)\\\n",
"Recommended settings by [YunaOneeChan](https://github.com/YunaOneeChan)\\\n",
"Modified again by [Hina](https://huggingface.co/HinaBl)\n",
"\n",
"Need help? [AI Hub Discord](https://discord.gg/aihub) » ***#help-realtime-vc***\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cellView": "form",
"id": "RhdqDSt-LfGr"
},
"outputs": [],
"source": [
"# @title **[Optional]** Connect to Google Drive\n",
"# @markdown Using Google Drive can improve load times a bit and your models will be stored, so you don't need to re-upload every time that you use.\n",
"import os\n",
"from google.colab import drive\n",
"\n",
"if not os.path.exists('/content/drive'):\n",
" drive.mount('/content/drive')\n",
"\n",
"%cd /content/drive/MyDrive"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "86wTFmqsNMnD",
"cellView": "form"
},
"outputs": [],
"source": [
"# @title **[1]** Clone repository and install dependencies\n",
"# @markdown This first step will download the latest version of Voice Changer and install the dependencies. **It will take around 2 minutes to complete.**\n",
"import os\n",
"import time\n",
"import subprocess\n",
"import threading\n",
"import shutil\n",
"import base64\n",
"import codecs\n",
"\n",
"from IPython.display import clear_output, Javascript\n",
"\n",
"externalgit=codecs.decode('uggcf://tvguho.pbz/j-bxnqn/ibvpr-punatre.tvg','rot_13')\n",
"rvctimer=codecs.decode('uggcf://tvguho.pbz/uvanoy/eipgvzre.tvg','rot_13')\n",
"pathloc=codecs.decode('ibvpr-punatre','rot_13')\n",
"!git clone --depth 1 $externalgit &> /dev/null\n",
"\n",
"def update_timer_and_print():\n",
" global timer\n",
" while True:\n",
" hours, remainder = divmod(timer, 3600)\n",
" minutes, seconds = divmod(remainder, 60)\n",
" timer_str = f'{hours:02}:{minutes:02}:{seconds:02}'\n",
" print(f'\\rTimer: {timer_str}', end='', flush=True) # Print without a newline\n",
" time.sleep(1)\n",
" timer += 1\n",
"timer = 0\n",
"threading.Thread(target=update_timer_and_print, daemon=True).start()\n",
"\n",
"# os.system('cls')\n",
"clear_output()\n",
"!rm -rf rvctimer\n",
"!git clone --depth 1 $rvctimer\n",
"!cp -f rvctimer/index.html $pathloc/client/demo/dist/\n",
"\n",
"\n",
"%cd $pathloc/server/\n",
"\n",
"print(\"\\033[92mSuccessfully cloned the repository\")\n",
"\n",
"\n",
"\n",
"!apt-get install libportaudio2 &> /dev/null --quiet\n",
"!pip install pyworld onnxruntime-gpu uvicorn faiss-gpu fairseq jedi google-colab moviepy decorator==4.4.2 sounddevice numpy==1.23.5 pyngrok --quiet\n",
"print(\"\\033[92mInstalling Requirements!\")\n",
"clear_output()\n",
"!pip install -r requirements.txt --no-build-isolation --quiet\n",
"# Maybe install Tensor packages?\n",
"#!pip install torch-tensorrt\n",
"#!pip install TensorRT\n",
"print(\"\\033[92mSuccessfully installed all packages!\")\n",
"# os.system('cls')\n",
"clear_output()\n",
"print(\"\\033[92mFinished, please continue to the next cell\")"
]
},
{
"cell_type": "code",
"source": [
"\n",
"#@title #**[Optional]** Upload a voice model (Run this before running the Voice Changer)**[Currently Under Construction]**\n",
"#@markdown ---\n",
"import os\n",
"import json\n",
"\n",
"\n",
"#@markdown #Model Number `(Default is 0)` you can add multiple models as long as you change the number!\n",
"model_number = \"0\" #@param ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120', '121', '122', '123', '124', '125', '126', '127', '128', '129', '130', '131', '132', '133', '134', '135', '136', '137', '138', '139', '140', '141', '142', '143', '144', '145', '146', '147', '148', '149', '150', '151', '152', '153', '154', '155', '156', '157', '158', '159', '160', '161', '162', '163', '164', '165', '166', '167', '168', '169', '170', '171', '172', '173', '174', '175', '176', '177', '178', '179', '180', '181', '182', '183', '184', '185', '186', '187', '188', '189', '190', '191', '192', '193', '194', '195', '196', '197', '198', '199']\n",
"\n",
"!rm -rf model_dir/$model_number\n",
"#@markdown ---\n",
"#@markdown #**[Optional]** Add an icon to the model `(can be any image/leave empty for no image)`\n",
"icon_link = \"https://cdn.donmai.us/original/8a/92/8a924397e9aac922e94bdc1f28ff978a.jpg\" #@param {type:\"string\"}\n",
"#@markdown ---\n",
"icon_link = '\"'+icon_link+'\"'\n",
"!mkdir model_dir\n",
"!mkdir model_dir/$model_number\n",
"#@markdown #Put your model's download link here `(must be a zip file)`\n",
"model_link = \"https://huggingface.co/HinaBl/Akatsuki/resolve/main/akatsuki_200epoch.zip\" #@param {type:\"string\"}\n",
"model_link = '\"'+model_link+'\"'\n",
"!curl -L $model_link > model.zip\n",
"\n",
"\n",
"# Conditionally set the iconFile based on whether icon_link is empty\n",
"if icon_link:\n",
" iconFile = \"icon.png\"\n",
" !curl -L $icon_link > model_dir/$model_number/icon.png\n",
"else:\n",
" print(\"icon_link is empty, so no icon file will be downloaded.\")\n",
"#@markdown ---\n",
"\n",
"\n",
"!unzip model.zip -d model_dir/$model_number\n",
"\n",
"# Checks all the files in model_number and puts it outside of it\n",
"\n",
"!mv model_dir/$model_number/*/* model_dir/$model_number/\n",
"!rm -rf model_dir/$model_number/*/\n",
"\n",
"# if theres a folder in the number,\n",
"# take all the files in the folder and put it outside of that folder\n",
"\n",
"\n",
"#@markdown #**Model Voice Convertion Setting**\n",
"Tune = 12 #@param {type:\"slider\",min:-50,max:50,step:1}\n",
"Index = 0 #@param {type:\"slider\",min:0,max:1,step:0.1}\n",
"#@markdown ---\n",
"#@markdown #Parameter Option `(Ignore if theres a Parameter File)`\n",
"Slot_Index = -1 #@param [-1,0,1] {type:\"raw\"}\n",
"Sampling_Rate = 48000 #@param [32000,40000,48000] {type:\"raw\"}\n",
"\n",
"# @markdown #**[Optional]** Parameter file for your voice model\n",
"#@markdown _(must be named params.json)_ (Leave Empty for Default)\n",
"param_link = \"\" #@param {type:\"string\"}\n",
"if param_link == \"\":\n",
" model_dir = \"model_dir/\"+model_number+\"/\"\n",
"\n",
" # Find the .pth and .index files in the model_dir/0 directory\n",
" pth_files = [f for f in os.listdir(model_dir) if f.endswith(\".pth\")]\n",
" index_files = [f for f in os.listdir(model_dir) if f.endswith(\".index\")]\n",
"\n",
" if pth_files and index_files:\n",
" # Take the first .pth and .index file as model and index names\n",
" model_name = pth_files[0].replace(\".pth\", \"\")\n",
" index_name = index_files[0].replace(\".index\", \"\")\n",
" else:\n",
" # Set default values if no .pth and .index files are found\n",
" model_name = \"Null\"\n",
" index_name = \"Null\"\n",
"\n",
" # Define the content for params.json\n",
" params_content = {\n",
" \"slotIndex\": Slot_Index,\n",
" \"voiceChangerType\": \"RVC\",\n",
" \"name\": model_name,\n",
" \"description\": \"\",\n",
" \"credit\": \"\",\n",
" \"termsOfUseUrl\": \"\",\n",
" \"iconFile\": iconFile,\n",
" \"speakers\": {\n",
" \"0\": \"target\"\n",
" },\n",
" \"modelFile\": f\"{model_name}.pth\",\n",
" \"indexFile\": f\"{index_name}.index\",\n",
" \"defaultTune\": Tune,\n",
" \"defaultIndexRatio\": Index,\n",
" \"defaultProtect\": 0.5,\n",
" \"isONNX\": False,\n",
" \"modelType\": \"pyTorchRVCv2\",\n",
" \"samplingRate\": Sampling_Rate,\n",
" \"f0\": True,\n",
" \"embChannels\": 768,\n",
" \"embOutputLayer\": 12,\n",
" \"useFinalProj\": False,\n",
" \"deprecated\": False,\n",
" \"embedder\": \"hubert_base\",\n",
" \"sampleId\": \"\"\n",
" }\n",
"\n",
" # Write the content to params.json\n",
" with open(f\"{model_dir}/params.json\", \"w\") as param_file:\n",
" json.dump(params_content, param_file)\n",
"\n",
"# !unzip model.zip -d model_dir/0/\n",
"clear_output()\n",
"print(\"\\033[92mModel with the name of \"+model_name+\" has been Imported!\")\n"
],
"metadata": {
"cellView": "form",
"id": "_ZtbKUVUgN3G"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#@title Delete a model\n",
"#@markdown ---\n",
"#@markdown Select which slot you want to delete\n",
"Delete_Slot = \"0\" #@param ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '100', '101', '102', '103', '104', '105', '106', '107', '108', '109', '110', '111', '112', '113', '114', '115', '116', '117', '118', '119', '120', '121', '122', '123', '124', '125', '126', '127', '128', '129', '130', '131', '132', '133', '134', '135', '136', '137', '138', '139', '140', '141', '142', '143', '144', '145', '146', '147', '148', '149', '150', '151', '152', '153', '154', '155', '156', '157', '158', '159', '160', '161', '162', '163', '164', '165', '166', '167', '168', '169', '170', '171', '172', '173', '174', '175', '176', '177', '178', '179', '180', '181', '182', '183', '184', '185', '186', '187', '188', '189', '190', '191', '192', '193', '194', '195', '196', '197', '198', '199']\n",
"{type:\"slider\",min:0,max:1,step:0.1}\n",
"\n",
"!rm -rf model_dir/$Model_Number\n",
"print(\"\\033[92mSuccessfully removed Model is slot \"+Delete_Slot)\n"
],
"metadata": {
"id": "P9g6rG1-KUwt"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "lLWQuUd7WW9U"
},
"outputs": [],
"source": [
"# @title **[2]** Start Server **using ngrok** (Recommended | **need a ngrok account**)\n",
"# @markdown This cell will start the server, the first time that you run it will download the models, so it can take a while (~1-2 minutes)\n",
"\n",
"# @markdown ---\n",
"# @markdown You'll need a ngrok account, but **it's free**!\n",
"# @markdown ---\n",
"# @markdown **1** - Create a **free** account at [ngrok](https://dashboard.ngrok.com/signup)\\\n",
"# @markdown **2** - If you didn't logged in with Google or Github, you will need to **verify your e-mail**!\\\n",
"# @markdown **3** - Click [this link](https://dashboard.ngrok.com/get-started/your-authtoken) to get your auth token, copy it and place it here:\n",
"from pyngrok import conf, ngrok\n",
"\n",
"f0_det= \"rmvpe_onnx\" #@param [\"rmvpe_onnx\",\"rvc\"]\n",
"Token = 'YOUR_TOKEN_HERE' # @param {type:\"string\"}\n",
"# @markdown **4** - Still need further tests, but maybe region can help a bit on latency?\\\n",
"# @markdown `Default Region: us - United States (Ohio)`\n",
"Region = \"ap - Asia/Pacific (Singapore)\" # @param [\"ap - Asia/Pacific (Singapore)\", \"au - Australia (Sydney)\",\"eu - Europe (Frankfurt)\", \"in - India (Mumbai)\",\"jp - Japan (Tokyo)\",\"sa - South America (Sao Paulo)\", \"us - United States (Ohio)\"]\n",
"MyConfig = conf.PyngrokConfig()\n",
"\n",
"MyConfig.auth_token = Token\n",
"MyConfig.region = Region[0:2]\n",
"\n",
"conf.get_default().authtoken = Token\n",
"conf.get_default().region = Region[0:2]\n",
"\n",
"conf.set_default(MyConfig);\n",
"\n",
"# @markdown ---\n",
"# @markdown If you want to automatically clear the output when the server loads, check this option.\n",
"Clear_Output = True # @param {type:\"boolean\"}\n",
"\n",
"mainpy=codecs.decode('ZZIPFreireFVB.cl','rot_13')\n",
"\n",
"import portpicker, socket, urllib.request\n",
"PORT = portpicker.pick_unused_port()\n",
"\n",
"from pyngrok import ngrok\n",
"# Edited ⏬⏬\n",
"ngrokConnection = ngrok.connect(PORT)\n",
"public_url = ngrokConnection.public_url\n",
"\n",
"def iframe_thread(port):\n",
" while True:\n",
" time.sleep(0.5)\n",
" sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
" result = sock.connect_ex(('127.0.0.1', port))\n",
" if result == 0:\n",
" break\n",
" sock.close()\n",
" clear_output()\n",
" print(\"------- SERVER READY! -------\")\n",
" print(\"Your server is available at:\")\n",
" print(public_url)\n",
" print(\"-----------------------------\")\n",
" # display(Javascript('window.open(\"{url}\", \\'_blank\\');'.format(url=public_url)))\n",
"\n",
"print(PORT)\n",
"\n",
"\n",
"\n",
"threading.Thread(target=iframe_thread, daemon=True, args=(PORT,)).start()\n",
"\n",
"\n",
"!python3 $mainpy \\\n",
" -p {PORT} \\\n",
" --https False \\\n",
" --content_vec_500 pretrain/checkpoint_best_legacy_500.pt \\\n",
" --content_vec_500_onnx pretrain/content_vec_500.onnx \\\n",
" --content_vec_500_onnx_on true \\\n",
" --hubert_base pretrain/hubert_base.pt \\\n",
" --hubert_base_jp pretrain/rinna_hubert_base_jp.pt \\\n",
" --hubert_soft pretrain/hubert/hubert-soft-0d54a1f4.pt \\\n",
" --nsf_hifigan pretrain/nsf_hifigan/model \\\n",
" --crepe_onnx_full pretrain/crepe_onnx_full.onnx \\\n",
" --crepe_onnx_tiny pretrain/crepe_onnx_tiny.onnx \\\n",
" --rmvpe pretrain/rmvpe.pt \\\n",
" --model_dir model_dir \\\n",
" --samples samples.json\n",
"\n"
]
},
{
"cell_type": "code",
"source": [
"# @title **[Optional]** Start Server **using localtunnel** (ngrok alternative | no account needed)\n",
"# @markdown This cell will start the server, the first time that you run it will download the models, so it can take a while (~1-2 minutes)\n",
"\n",
"# @markdown ---\n",
"!npm config set update-notifier false\n",
"!npm install -g localtunnel\n",
"print(\"\\033[92mLocalTunnel installed!\")\n",
"# @markdown If you want to automatically clear the output when the server loads, check this option.\n",
"Clear_Output = True # @param {type:\"boolean\"}\n",
"\n",
"import portpicker, subprocess, threading, time, socket, urllib.request\n",
"PORT = portpicker.pick_unused_port()\n",
"\n",
"from IPython.display import clear_output, Javascript\n",
"\n",
"def iframe_thread(port):\n",
" while True:\n",
" time.sleep(0.5)\n",
" sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n",
" result = sock.connect_ex(('127.0.0.1', port))\n",
" if result == 0:\n",
" break\n",
" sock.close()\n",
" clear_output()\n",
" print(\"Use the following endpoint to connect to localtunnel:\", urllib.request.urlopen('https://ipv4.icanhazip.com').read().decode('utf8').strip(\"\\n\"))\n",
" p = subprocess.Popen([\"lt\", \"--port\", \"{}\".format(port)], stdout=subprocess.PIPE)\n",
" for line in p.stdout:\n",
" print(line.decode(), end='')\n",
"\n",
"threading.Thread(target=iframe_thread, daemon=True, args=(PORT,)).start()\n",
"\n",
"\n",
"!python3 MMVCServerSIO.py \\\n",
" -p {PORT} \\\n",
" --https False \\\n",
" --content_vec_500 pretrain/checkpoint_best_legacy_500.pt \\\n",
" --content_vec_500_onnx pretrain/content_vec_500.onnx \\\n",
" --content_vec_500_onnx_on true \\\n",
" --hubert_base pretrain/hubert_base.pt \\\n",
" --hubert_base_jp pretrain/rinna_hubert_base_jp.pt \\\n",
" --hubert_soft pretrain/hubert/hubert-soft-0d54a1f4.pt \\\n",
" --nsf_hifigan pretrain/nsf_hifigan/model \\\n",
" --crepe_onnx_full pretrain/crepe_onnx_full.onnx \\\n",
" --crepe_onnx_tiny pretrain/crepe_onnx_tiny.onnx \\\n",
" --rmvpe pretrain/rmvpe.pt \\\n",
" --model_dir model_dir \\\n",
" --samples samples.json \\\n",
" --colab True"
],
"metadata": {
"cellView": "form",
"id": "ZwZaCf4BeZi2"
},
"execution_count": null,
"outputs": []
}
],
"metadata": {
"colab": {
"provenance": [],
"private_outputs": true,
"gpuType": "T4"
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"nbformat": 4,
"nbformat_minor": 0
}
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