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MTools_Windows_amd64：体积最小，并且支持nvidia、amd、intel显卡加速，但不支持手动管理显存\n  - MTools_Windows_amd64_CUDA：体积中等，使用CUDA进行加速，但需要手动安装CUDA 12.x + cuDNN 9.x\n  - MTools_Windows_amd64_CUDA_FULL：体积最大，内置完整的CUDA加速环境，无需手动安装CUDA和cuDNN\n\n- ⚠️ macOS (实验性支持)\n  - MTools_Darwin_arm64：只支M系列芯片，支持Core ML加速\n\n- ⚠️ Linux (实验性支持)\n  - MTools_Linux_amd64：体积最小，不支持GPU加速\n  - MTools_Linux_amd64_CUDA：体积中等，使用CUDA进行加速，但需要手动安装CUDA 12.x + cuDNN 9.x\n  - MTools_Linux_amd64_CUDA_FULL：体积最大，内置完整的CUDA加速环境，无需手动安装CUDA和cuDNN\n\n下载后解压即可使用！\n\n### 方式二：从源码运行\n\n#### 环境要求\n- **操作系统**: Windows 10/11、macOS 或 Linux\n- **Python**: 3.11+\n- **包管理器**: [uv](https://github.com/astral-sh/uv) - 推荐使用的 Python 包管理器\n\n#### 一键安装依赖\n\n```bash\n# 1. 克隆仓库\ngit clone https://github.com/HG-ha/MTools.git\ncd MTools\n\n# 2. 一键同步依赖（自动创建虚拟环境）\nuv sync\n\n# 3. 运行程序\nuv run flet run\n```\n\n启用 CUDA GPU 加速（默认已启用平台通用加速）：\n\n```bash\n# 使用此方式可完全榨干NVIDIA GPU性能\n# 替换为 GPU 版本（需要 NVIDIA GPU 和 CUDA 环境）\nuv remove onnxruntime-directml onnxruntime\nuv add onnxruntime-gpu==1.22.0\n# 需要免去配置cuda和cudnn环境的话请更改为此依赖\n# 会导致体积增大数倍\n# uv add onnxruntime-gpu[cuda,cudnn]==1.22.0\n```\n\n\u003e 📘 **版本说明**：\n\u003e - **普通版本**：支持NVIDIA、AMD、Intel显卡加速，支持coreml加速，对 NVIDIA GPU 的性能释放可能不如CUDA系列\n\u003e - **CUDA 版本**：使用系统安装的 CUDA 和 cuDNN，体积小但需要预先配置 CUDA 环境（CUDA 12.x + cuDNN 9.x）\n\u003e - **CUDA_FULL 版本**：内置完整的 CUDA 和 cuDNN 运行时库，无需额外配置，开箱即用，但体积较大（+2GB）\n\n\u003e 💡 **编译和版本说明**：如需将项目编译为独立可执行文件，请参考 📘 **[完整编译指南](./docs/build_guide.md)**\n\n---\n\n## 性能优化\n\n### GPU 加速支持\n\n本项目的 AI 功能支持 GPU 加速，可大幅提升处理速度，并且提供 `CUDA` 以及 `CUDA_FULL` 编译版本\n\n### 平台特定说明\n\n#### AI 功能（ONNX Runtime）\n\n| 平台 | 默认版本 | GPU 支持 | 说明 |\n|------|---------|---------|------|\n| **Windows** | `onnxruntime-directml==1.22.0` | ✅ DirectML | 自动支持 Intel/AMD/NVIDIA GPU |\n| **macOS (Apple Silicon)** | `onnxruntime==1.22.0` | ✅ CoreML | 内置硬件加速 |\n| **macOS (Intel)** | `onnxruntime==1.22.0` | ⚠️ CPU | 无 GPU 加速 |\n| **Linux** | `onnxruntime==1.22.0` | ⚠️ CPU | 可选 `onnxruntime-gpu` (CUDA) |\n\n\u003e 💡 **提示**：DirectML 版本不支持限制显存，只有CUDA可限制显存大小\n\n---\n\n\n## 致谢\n\n### 代码参考\n\n本项目在开发过程中参考和使用了以下开源项目的代码：\n\n- **[sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx)** - 语音识别与合成框架，提供高性能的离线语音处理能力\n- **[PPOCR_v5](https://github.com/Nnow2024/PPOCR_v5)** - 高精度OCR识别引擎\n- **[FunASR](https://github.com/modelscope/FunASR)** - 语音识别工具包\n- **[ICP_Query](https://github.com/HG-ha/ICP_Query)** - ICP备案查询功能实现\n- **[HivisionIDPhotos](https://github.com/Zeyi-Lin/HivisionIDPhotos)** - AI证件照\n- **[video-subtitle-remover](https://github.com/YaoFANGUK/video-subtitle-remover)** - AI去水印\n\n\n### 外部服务\n\n本项目使用了以下外部服务：\n\n- **[ModelScope](https://www.modelscope.cn/)** - AI模型托管与分享平台\n- **[imagetourl.net](https://imagetourl.net/)** - 图片转URL服务\n- **[catbox.moe](https://catbox.moe/)** - 文件上传服务\n- **[gh-proxy.com](https://gh-proxy.com/)** - GitHub加速代理\n\n### 服务器赞助\n\n感谢以下赞助商为本项目提供服务器支持：\n\n- **[林枫云 www.dkdun.cn](https://www.dkdun.cn/)** - 提供稳定的云服务器资源\n\n---\n\n\u003cdiv align=\"center\"\u003e\n\n## Star History\n\n[![Star History Chart](https://api.star-history.com/svg?repos=HG-ha/MTools\u0026type=Date)](https://star-history.com/#HG-ha/MTools\u0026Date)\n\n---\n\n## 支持项目\n\n如果这个项目对你有帮助，欢迎通过以下方式支持：\n\n- 给项目一个 ⭐ Star\n- 分享给更多需要的人\n- 提交 Issue 和 Pull Request\n- 请作者喝杯咖啡 ☕\n\n\u003cdetails\u003e\n\u003csummary\u003e打赏支持\u003c/summary\u003e\n\n\u003cbr/\u003e\n\n你的支持是项目持续维护的动力！\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"./assets/wechat_reward.jpg\" alt=\"微信赞赏码\" width=\"300\"/\u003e\n  \u003cp\u003e\u003cb\u003e微信赞赏\u003c/b\u003e\u003c/p\u003e\n\u003c/div\u003e\n\n\u003c/details\u003e\n\n---\n\n**Made with ❤️ using Python \u0026 Flet**\n\n👨‍💻 **作者**：[HG-ha](https://github.com/HG-ha) · [加入Q群 1029212047](https://qm.qq.com/q/gHf7f0R3zy)\n\n**如果这个项目对你有帮助，请给个 ⭐ Star 支持一下！**\n\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhg-ha%2Fmtools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhg-ha%2Fmtools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhg-ha%2Fmtools/lists"}