mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-04-05 04:08:58 +08:00
120 lines
4.2 KiB
Python
120 lines
4.2 KiB
Python
#!/usr/bin/env python3
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import os
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import subprocess
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import sys
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import requests
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from pathlib import Path
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# Part 1: Download Spark assets
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def run_command(command, error_message):
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try:
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subprocess.run(command, check=True)
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except subprocess.CalledProcessError:
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print(error_message)
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sys.exit(1)
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def clone_spark_tts():
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spark_pretrained_dir = os.path.join("spark", "pretrained_models")
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os.makedirs(spark_pretrained_dir, exist_ok=True)
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print("Running 'git lfs install'...")
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run_command(
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["git", "lfs", "install"],
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"Error: Failed to run 'git lfs install'. Make sure git-lfs is installed (https://git-lfs.com).",
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)
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clone_dir = os.path.join(spark_pretrained_dir, "Spark-TTS-0.5B")
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if not os.path.exists(clone_dir):
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print(f"Cloning Spark TTS repository into {clone_dir}...")
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run_command(
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[
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"git",
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"clone",
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"https://huggingface.co/SparkAudio/Spark-TTS-0.5B",
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clone_dir,
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],
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"Error: Failed to clone the Spark TTS repository.",
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)
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else:
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print(f"Directory '{clone_dir}' already exists. Skipping clone.")
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# Part 2: Download RVC Assets
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def dl_model(link, model_name, dir_name):
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with requests.get(f"{link}{model_name}") as r:
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r.raise_for_status()
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os.makedirs(os.path.dirname(dir_name / model_name), exist_ok=True)
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with open(dir_name / model_name, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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def download_rvc_models():
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RVC_DOWNLOAD_LINK = "https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/"
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BASE_DIR = Path(__file__).resolve().parent.parent
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def check_and_dl(link, model_name, dest_dir):
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dest_file = dest_dir / model_name
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if dest_file.exists():
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print(f"{model_name} already exists at {dest_file}. Skipping download.")
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else:
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print(f"Downloading {model_name}...")
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dl_model(link, model_name, dest_dir)
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print("Downloading hubert_base.pt...")
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check_and_dl(RVC_DOWNLOAD_LINK, "hubert_base.pt", BASE_DIR / "assets" / "hubert")
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print("Downloading rmvpe.pt...")
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check_and_dl(RVC_DOWNLOAD_LINK, "rmvpe.pt", BASE_DIR / "assets" / "rmvpe")
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print("Downloading rmvpe.onnx...")
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check_and_dl(RVC_DOWNLOAD_LINK, "rmvpe.onnx", BASE_DIR / "assets" / "rmvpe")
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print("Downloading vocals.onnx...")
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vocals_dir = BASE_DIR / "assets" / "uvr5_weights" / "onnx_dereverb_By_FoxJoy"
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check_and_dl(RVC_DOWNLOAD_LINK + "uvr5_weights/onnx_dereverb_By_FoxJoy/", "vocals.onnx", vocals_dir)
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print("Downloading ffprobe.exe...")
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check_and_dl(RVC_DOWNLOAD_LINK, "ffprobe.exe", BASE_DIR / ".")
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print("Downloading ffmpeg.exe...")
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check_and_dl(RVC_DOWNLOAD_LINK, "ffmpeg.exe", BASE_DIR / ".")
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rvc_models_dir = BASE_DIR / "assets" / "pretrained"
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print("Downloading pretrained models:")
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model_names = [
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"D32k.pth", "D40k.pth", "D48k.pth",
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"G32k.pth", "G40k.pth", "G48k.pth",
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"f0D32k.pth", "f0D40k.pth", "f0D48k.pth",
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"f0G32k.pth", "f0G40k.pth", "f0G48k.pth",
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]
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for model in model_names:
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check_and_dl(RVC_DOWNLOAD_LINK + "pretrained/", model, rvc_models_dir)
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rvc_models_dir = BASE_DIR / "assets" / "pretrained_v2"
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print("Downloading pretrained models v2:")
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for model in model_names:
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check_and_dl(RVC_DOWNLOAD_LINK + "pretrained_v2/", model, rvc_models_dir)
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print("Downloading uvr5_weights:")
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rvc_models_dir = BASE_DIR / "assets" / "uvr5_weights"
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model_names = [
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"HP2-%E4%BA%BA%E5%A3%B0vocals%2B%E9%9D%9E%E4%BA%BA%E5%A3%B0instrumentals.pth",
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"HP2_all_vocals.pth",
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"HP3_all_vocals.pth",
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"HP5-%E4%B8%BB%E6%97%8B%E5%BE%8B%E4%BA%BA%E5%A3%B0vocals%2B%E5%85%B6%E4%BB%96instrumentals.pth",
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"HP5_only_main_vocal.pth",
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"VR-DeEchoAggressive.pth",
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"VR-DeEchoDeReverb.pth",
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"VR-DeEchoNormal.pth",
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]
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for model in model_names:
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check_and_dl(RVC_DOWNLOAD_LINK + "uvr5_weights/", model, rvc_models_dir)
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print("All models downloaded!")
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def main():
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clone_spark_tts()
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download_rvc_models()
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if __name__ == "__main__":
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main()
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