{"id":21820826,"url":"https://github.com/hrntsm/tunny","last_synced_at":"2025-04-10T00:17:13.219Z","repository":{"id":37011232,"uuid":"472376940","full_name":"hrntsm/Tunny","owner":"hrntsm","description":"🐟Tunny🐟 is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization 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align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/hrntsm/Tunny-docs/main/static/home-og.png\" /\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/hrntsm/Tunny/blob/master/LICENSE\"\u003e\u003cimg src=\"https://img.shields.io/github/license/hrntsm/Tunny\" alt=\"License\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/hrntsm/Tunny/releases\"\u003e\u003cimg src=\"https://img.shields.io/github/v/release/hrntsm/Tunny\" alt=\"Release\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/hrntsm/Tunny/releases\"\u003e\u003cimg src=\"https://img.shields.io/github/downloads/hrntsm/Tunny/total\" alt=\"download\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://www.codefactor.io/repository/github/hrntsm/tunny\"\u003e\u003cimg src=\"https://www.codefactor.io/repository/github/hrntsm/tunny/badge\" alt=\"CodeFactor\" /\u003e\u003c/a\u003e\n  \u003ca href=\"https://www.codacy.com/gh/hrntsm/Tunny/dashboard?utm_source=github.com\u0026amp;utm_medium=referral\u0026amp;utm_content=hrntsm/Tunny\u0026amp;utm_campaign=Badge_Grade\"\u003e\u003cimg src=\"https://app.codacy.com/project/badge/Grade/c7947be6770545e88153125060b41284\" alt=\"Codacy Badge\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://codeclimate.com/github/hrntsm/Tunny/maintainability\"\u003e\u003cimg src=\"https://api.codeclimate.com/v1/badges/63a5b0a923062d25ad23/maintainability\" alt=\"Maintainability\"\u003e\u003c/a\u003e\n  \u003cimg src=\"https://img.shields.io/codeclimate/tech-debt/hrntsm/Tunny\" alt=\"Code Climate technical debt\"\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/hrntsm/Tunny\"\u003e\u003cimg src=\"https://img.shields.io/github/stars/hrntsm/Tunny?style=social\" alt=\"GitHub Repo stars\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/hrntsm/Tunny/network\"\u003e\u003cimg alt=\"GitHub forks\" src=\"https://img.shields.io/github/forks/hrntsm/Tunny?style=social\"\u003e\u003c/a\u003e\n  \u003ca href=\"https://open.vscode.dev/hrntsm/Tunny\"\u003e\u003cimg src=\"https://img.shields.io/static/v1?logo=visualstudiocode\u0026amp;label=\u0026amp;message=Open in Visual Studio Code\u0026amp;labelColor=2c2c32\u0026amp;color=007acc\u0026amp;logoColor=007acc\" alt=\"Open in Visual Studio Code\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003c/p\u003e\n\n:fish:**Tunny**:fish: is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.\n\nThe following is taken from the official website\n\n\u003e Optuna™, an open-source automatic hyperparameter optimization framework, automates the trial-and-error process of optimizing the hyperparameters. It automatically finds optimal hyperparameter values based on an optimization target. Optuna is framework agnostic and can be used with most Python frameworks, including Chainer, Scikit-learn, Pytorch, etc.\n\u003e\n\u003e Optuna is used in PFN projects with good results. One example is the second place award in the [Google AI Open Images 2018 – Object Detection Track](https://www.preferred.jp/en/news/pr20180907/) competition.\n\nOptuna official site\n\n- https://optuna.org/\n\n## :tropical_fish: Install\n\nFirst, Tunny runs on Windows only.\n\n1. Download Tunny from [food4rhino](https://www.food4rhino.com/app/tunny) or [release page](https://github.com/hrntsm/tunny/releases)\n1. Right-click the file \u003e Properties \u003e make sure there is no \"blocked\" text\n1. In Grasshopper, choose File \u003e Special Folders \u003e Components folder. Move Tunny folder you downloaded there.\n1. Restart Rhino and Grasshopper\n1. In Grasshopper, Place the Tunny component and double-click the icon to start downloading the necessary libraries.\n1. Enjoy!\n\n## :sushi: Support\n\nThis software is being updated with your support.\nIf you like this software, please donation.\n\n[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/G2G5C2MIU)\n\n## :blowfish: License\n\nTunny is licensed under the [MIT](https://github.com/hrntsm/Tunny/blob/main/LICENSE) license.  \nCopyright© 2022, hrntsm\n\nTunny use TT-DesignExplorer \u0026 Python runtime \u0026 some python packages.\nThese depend on their own licenses.\nPlease see PYTHON_PACKAGE_LICENSE for more license information.\n\n## :dolphin: Usage\n\n### :speedboat: Quick usage\n\nhttps://user-images.githubusercontent.com/23289252/178105107-5e9dd9f7-5680-40d4-97b0-840a4f1f329c.mp4\n\n### :whale: More details\n\nPlease see Tunny documentation page.\n\n- https://tunny-docs.deno.dev/\n\n## :surfer: Contact information\n\n[![Twitter](https://img.shields.io/badge/Twitter-1DA1F2?style=for-the-badge\u0026logo=twitter\u0026logoColor=white)](https://twitter.com/hiron_rgkr)\n[![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white)](https://www.linkedin.com/in/hiroaki-natsume-20a22118b/)\n\n- HP : [https://hiron.dev/](https://hiron.dev/)\n- Mail : support(at)hrntsm.com\n  - change (at) to @\n- Postings to [the discussion page](https://github.com/hrntsm/Tunny/discussions) are also welcome.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhrntsm%2Ftunny","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhrntsm%2Ftunny","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhrntsm%2Ftunny/lists"}