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11
README.md
11
README.md
@ -97,9 +97,9 @@ Windows 版と Mac 版を提供しています。
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| Version | OS | フレームワーク | link | サポート VC | サイズ |
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| ---------- | --- | ---------------------------------------- | ---------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | ------ |
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| v.1.5.3.4 | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1XYfdSqhrcu1Eyz0Ob5AeN7_p_l9bBgzn&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda)\*2 | [normal](https://drive.google.com/uc?id=1P7T46Iq1NTZCfs6Hsow1QYDFHQo270le&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=16Y3m3WcpYUOKvq9GTieuV4LcWkxFmbue&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| v.1.5.3.4b | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1fBuQZbAMSVFjIqjMWPVpz50tYzdI4D93&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1M2WmKnBlSH_J1fmtszxKWzA3Ci2uZ1cZ&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda)\*2 | [normal](https://drive.google.com/uc?id=17AVhvUZDOjixVZZOYkjC9i7vWIsYbhTg&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB |
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| v.1.5.3.3b | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=14_STxl6lYwhTahcgMGfsjnwpoHmN0svf&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1VpMSF5lE3VrUeb_TusWQi22_Hx8JoPhC&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, so-vits-svc 4.0v2, RVC, DDSP-SVC | 2872MB |
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@ -107,11 +107,6 @@ Windows 版と Mac 版を提供しています。
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(\*2) 開発者が AMD のグラフィックボードを持っていないので動作確認していません。onnxruntime-directml を同梱しただけのものです。
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(\*3) 解凍や起動が遅い場合、ウィルス対策ソフトのチェックが走っている可能性があります。ファイルやフォルダを対象外にして実行してみてください。（自己責任です）
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<!-- | v.1.5.3.4a | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1DTMBIWDw0v0MjwbNe22q-EK_EDTLO-4B&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=15bMpDfucOfiaiJFi6ygIvV4TbqXQ0APM&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1i5CwBkjyNsKRAPSmoqhPWcUnFhJFxnvK&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB |
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-->
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## (2) Docker や Anaconda など環境構築を行った上での利用
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本リポジトリをクローンして利用します。Windows では WSL2 の環境構築が必須になります。また、WSL2 上で Docker もしくは Anaconda などの仮想環境の構築が必要となります。Mac では Anaconda などの Python の仮想環境の構築が必要となります。事前準備が必要となりますが、多くの環境においてこの方法が一番高速で動きます。**<font color="red"> GPU が無くてもそこそこ新しい CPU であれば十分動く可能性があります </font>（下記のリアルタイム性の節を参照）**。
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14
README_en.md
14
README_en.md
@ -91,24 +91,16 @@ We offer Windows and Mac versions.
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| Version | OS | Framework | link | support VC | size |
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| ---------- | --- | ---------------------------------------- | ---------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | ------ |
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| v.1.5.3.4 | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1XYfdSqhrcu1Eyz0Ob5AeN7_p_l9bBgzn&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda)\*2 | [normal](https://drive.google.com/uc?id=1P7T46Iq1NTZCfs6Hsow1QYDFHQo270le&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=16Y3m3WcpYUOKvq9GTieuV4LcWkxFmbue&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| v.1.5.3.4b | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1fBuQZbAMSVFjIqjMWPVpz50tYzdI4D93&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1M2WmKnBlSH_J1fmtszxKWzA3Ci2uZ1cZ&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda)\*2 | [normal](https://drive.google.com/uc?id=17AVhvUZDOjixVZZOYkjC9i7vWIsYbhTg&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB |
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| v.1.5.3.3b | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=14_STxl6lYwhTahcgMGfsjnwpoHmN0svf&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1VpMSF5lE3VrUeb_TusWQi22_Hx8JoPhC&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, so-vits-svc 4.0v2, RVC, DDSP-SVC | 2872MB |
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| v.1.5.3.2 | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1K0oO6UbDUgtiZ59CUHB1VItsG_6ztSHS&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1m791W_wEx6TO135mEPNGngYBL4RLQvDO&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, so-vits-svc 4.0v2, RVC, DDSP-SVC | 2873MB |
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| v.1.5.2.9e | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1W0d7I7619PcO7kjb1SPXp6MmH5Unvd78&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 796MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1tmTMJRRggS2Sb4goU-eHlRvUBR88RZDl&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, so-vits-svc 4.0v2, RVC, DDSP-SVC | 2872MB |
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(\*1) You can alson download from [hugging_face](https://huggingface.co/wok000/vcclient000/tree/main)
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(\*2) The developer does not have an AMD graphics card, so it has not been tested. This package only includes onnxruntime-directml.
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(\*3) If unpacking or starting is slow, there is a possibility that virus checking is running on your antivirus software. Please try running it with the file or folder excluded from the target. (At your own risk)
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<!-- | v.1.5.3.4a | mac | ONNX(cpu), PyTorch(cpu,mps) | [normal](https://drive.google.com/uc?id=1DTMBIWDw0v0MjwbNe22q-EK_EDTLO-4B&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC | 797MB |
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| | win | ONNX(cpu,cuda), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=15bMpDfucOfiaiJFi6ygIvV4TbqXQ0APM&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3243MB |
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| | win | ONNX(cpu,DirectML), PyTorch(cpu,cuda) | [normal](https://drive.google.com/uc?id=1i5CwBkjyNsKRAPSmoqhPWcUnFhJFxnvK&export=download) \*1 | MMVC v.1.5.x, MMVC v.1.3.x, so-vits-svc 4.0, RVC, DDSP-SVC | 3121MB | -->
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## (2) Usage after setting up the environment such as Docker or Anaconda
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Clone this repository and use it. Setting up WSL2 is essential for Windows. Additionally, setting up virtual environments such as Docker or Anaconda on WSL2 is also required. On Mac, setting up Python virtual environments such as Anaconda is necessary. Although preparation is required, this method works the fastest in many environments. **<font color="red"> Even without a GPU, it may work well enough with a reasonably new CPU </font>(refer to the section on real-time performance below)**.
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