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cdcc62ae22* fix: Configure "uv" build system to use CUDA on supported platforms
- Linux builds of PyTorch always have CUDA acceleration built-in, but Windows only has it if we request a CUDA build.
- The built-in CUDA on Linux uses old libraries and can be slow.
- We now request PyTorch built for the most modern CUDA Toolkit on Linux + Windows, to solve both problems.
- Mac uses PyTorch without CUDA support, since it doesn't exist on that platform.
- Other dependencies have received new releases and are included in this fix too:
* click was downgraded because the author revoked 8.2.2 due to a bug.
* wetext received a new release now.
* fix: Use PyPI as the hashing reference in "uv" lockfile
- PyPI is the most trustworthy source for package hashes. We need to remove the custom mirror from the config, otherwise that mirror always becomes the default lockfile/package source, which leads to user trust issues and package impersonation risks.
- Regional mirrors should be added by users during installation instead, via the `uv sync --default-index` flag. Documented with example for Chinese mirror.
- When users add `--default-index`, "uv" will try to discover the exact same packages via the mirror to improve download speeds, but automatically uses PyPI if the mirror didn't have the files or if the mirror's file hashes were incorrect. Thus ensuring that users always have the correct package files.
* docs: Improve README for IndexTTS2 release!
- "Abstract" separated into paragraphs for easier readability.
- Clearer document structure and many grammatical improvements.
- More emojis, to make it easier to find sections when scrolling through the page!
- Added missing instructions:
* Needing `git-lfs` to clone the code.
* Needing CUDA Toolkit to install the dependencies.
* How to install the `hf` or `modelscope` CLI tools to download the models.
- Made our web demo the first section within "quickstart", to give users a quick, fun demo to start experimenting with.
- Fixed a bug in the "PYTHONPATH" recommendation. It must be enclosed in quotes `""`, otherwise the new path would break on systems that had spaces in their original path.
- Improved all Python code-example descriptions to make them much easier to understand.
- Clearly marked the IndexTTS1 legacy section as "legacy" to avoid confusion.
- Removed outdated Windows "conda/pip" instruction which is no longer relevant since we use "uv" now.
* refactor(webui): Remove unused imports
The old IndexTTS1 module and ModelScope were being loaded even though we don't need them. They also have a lot of dependencies, which slowed down loading and could even cause some conflicts.
* feat!: Remove obsolete build system (setup.py)
BREAKING CHANGE: The `setup.py` file has been removed.
Users should now use the new `pyproject.toml` based "uv" build system for installing and developing the project.
* feat: Add support for installing IndexTTS as a CLI tool
- We now support installing as a CLI tool via "uv".
- Uses the modern "hatchling" as the package / CLI build system.
- The `cli.py` code is currently outdated (doesn't support IndexTTS2). Marking as a TODO.
* chore: Add authors and classifiers metadata to pyproject.toml
* feat: Faster installs by making WebUI dependencies optional
* refactor!: Rename "sentences" to "segments" for clarity
- When we are splitting text into generation chunks, we are *not* creating "sentences". We are creating "segments". Because a *sentence* must always end with punctuation (".!?" etc). A *segment* can be a small fragment of a sentence, without any punctuation, so it's not accurate (and was very misleading) to use the word "sentences".
- All variables, function calls and strings have been carefully analyzed and renamed.
- This change will be part of user-facing code via a new feature, which is why the change was applied to the entire codebase.
- This change also helps future code contributors understand the code.
- All affected features are fully tested and work correctly after this refactoring.
- The `is_fp16` parameter has also been renamed to `use_fp16` since the previous name could confuse people ("is" implies an automatic check, "use" implies a user decision to enable/disable FP16).
- `cli.py`'s "--fp16" default value has been set to False, exactly like the web UI.
- `webui.py`'s "--is_fp16" flag has been changed to "--fp16" for easier usage and consistency with the CLI program, and the help-description has been improved.
* feat(webui): Set "max tokens per generation segment" via CLI flag
- The "Max tokens per generation segment" is a critical setting, as it directly impacts VRAM usage. Since the optimal value varies significantly based on a user's GPU, it is a frequent point of adjustment to prevent out-of-memory issues.
- This change allows the default value to be set via a CLI flag. Users can now conveniently start the web UI with the correct setting for their system, eliminating the need to manually reconfigure the value on every restart.
- The `webui.py -h` help text has also been enhanced to automatically display the default values for all CLI settings.
* refactor(i18n): Improve clarity of all web UI translation strings
* feat(webui): Use main text as emotion guidance when description is empty
If the user selects "text-to-emotion" control, but leaves the emotion description empty, we now automatically use the main text prompt instead.
This ensures that web users can enjoy every feature of IndexTTS2, including the ability to automatically guess the emotion from the main text prompt.
* feat: Add PyTorch GPU acceleration diagnostic tool
* chore: Use NVIDIA CUDA Toolkit v12.8
Downgrade from CUDA 12.9 to 12.8 to simplify user installation, since version 12.8 is very popular.
* docs: Simplify "uv run" command examples
The "uv run" command can take a `.py` file as direct argument and automatically understands that it should run via python.
42 lines
3.6 KiB
Python
42 lines
3.6 KiB
Python
from indextts.infer import IndexTTS
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if __name__ == "__main__":
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prompt_wav="tests/sample_prompt.wav"
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tts = IndexTTS(cfg_path="checkpoints/config.yaml", model_dir="checkpoints", use_fp16=True, use_cuda_kernel=False)
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# 单音频推理测试
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text="晕 XUAN4 是 一 种 GAN3 觉"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text='大家好，我现在正在bilibili 体验 ai 科技，说实话，来之前我绝对想不到！AI技术已经发展到这样匪夷所思的地步了！'
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text="There is a vehicle arriving in dock number 7?"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text = "“我爱你！”的英语是“I love you!”"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text = "Joseph Gordon-Levitt is an American actor"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text = "约瑟夫·高登-莱维特是美国演员"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text = "蒂莫西·唐纳德·库克（英文名：Timothy Donald Cook），通称蒂姆·库克（Tim Cook），现任苹果公司首席执行官。"
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tts.infer(audio_prompt=prompt_wav, text=text, output_path="outputs/蒂莫西·唐纳德·库克.wav", verbose=True)
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# 并行推理测试
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text="亲爱的伙伴们，大家好！每一次的努力都是为了更好的未来，要善于从失败中汲取经验，让我们一起勇敢前行,迈向更加美好的明天！"
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tts.infer_fast(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text="The weather is really nice today, perfect for studying at home.Thank you!"
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tts.infer_fast(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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text='''叶远随口答应一声，一定帮忙云云。
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教授看叶远的样子也知道，这事情多半是黄了。
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谁得到这样的东西也不会轻易贡献出来，这是很大的一笔财富。
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叶远回来后，又自己做了几次试验，发现空间湖水对一些外伤也有很大的帮助。
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找来一只断了腿的兔子，喝下空间湖水，一天时间，兔子就完全好了。
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还想多做几次试验，可是身边没有试验的对象，就先放到一边，了解空间湖水可以饮用，而且对人有利，这些就足够了。
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感谢您的收听，下期再见！
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'''.replace("\n", "")
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tts.infer_fast(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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# 长文本推理测试
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text = """《盗梦空间》是由美国华纳兄弟影片公司出品的电影，由克里斯托弗·诺兰执导并编剧，
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莱昂纳多·迪卡普里奥、玛丽昂·歌迪亚、约瑟夫·高登-莱维特、艾利奥特·佩吉、汤姆·哈迪等联袂主演，
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2010年7月16日在美国上映，2010年9月1日在中国内地上映，2020年8月28日在中国内地重映。
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影片剧情游走于梦境与现实之间，被定义为“发生在意识结构内的当代动作科幻片”，
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讲述了由莱昂纳多·迪卡普里奥扮演的造梦师，带领特工团队进入他人梦境，从他人的潜意识中盗取机密，并重塑他人梦境的故事。
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""".replace("\n", "")
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tts.infer_fast(audio_prompt=prompt_wav, text=text, output_path=f"outputs/{text[:20]}.wav", verbose=True)
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