[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-70955":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":15,"compositeScore":18,"rankGlobal":9,"rankLanguage":9,"license":19,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":22,"hasPages":20,"topics":23,"createdAt":9,"pushedAt":9,"updatedAt":24,"readmeContent":25,"aiSummary":26,"trendingCount":15,"starSnapshotCount":15,"syncStatus":16,"lastSyncTime":27,"discoverSource":28},70955,"shap-e","openai\u002Fshap-e","openai","Generate 3D objects conditioned on text or images",null,"Python",12244,1072,233,93,0,2,6,70.69,"MIT License",false,"main",true,[],"2026-06-12 04:00:58","# Shap-E\n\nThis is the official code and model release for [Shap-E: Generating Conditional 3D Implicit Functions](https:\u002F\u002Farxiv.org\u002Fabs\u002F2305.02463).\n\n * See [Usage](#usage) for guidance on how to use this repository.\n * See [Samples](#samples) for examples of what our text-conditional model can generate.\n\n# Samples\n\nHere are some highlighted samples from our text-conditional model. For random samples on selected prompts, see [samples.md](samples.md).\n\n\u003Ctable>\n    \u003Ctbody>\n        \u003Ctr>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_chair_that_looks_like_an_avocado\u002F2.gif\" alt=\"A chair that looks like an avocado\">\n            \u003C\u002Ftd>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fan_airplane_that_looks_like_a_banana\u002F3.gif\" alt=\"An airplane that looks like a banana\">\n            \u003C\u002Ftd align=\"center\">\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_spaceship\u002F0.gif\" alt=\"A spaceship\">\n            \u003C\u002Ftd>\n        \u003C\u002Ftr>\n        \u003Ctr>\n            \u003Ctd align=\"center\">A chair that looks\u003Cbr>like an avocado\u003C\u002Ftd>\n            \u003Ctd align=\"center\">An airplane that looks\u003Cbr>like a banana\u003C\u002Ftd>\n            \u003Ctd align=\"center\">A spaceship\u003C\u002Ftd>\n        \u003C\u002Ftr>\n        \u003Ctr>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_birthday_cupcake\u002F3.gif\" alt=\"A birthday cupcake\">\n            \u003C\u002Ftd>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_chair_that_looks_like_a_tree\u002F2.gif\" alt=\"A chair that looks like a tree\">\n            \u003C\u002Ftd>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_green_boot\u002F3.gif\" alt=\"A green boot\">\n            \u003C\u002Ftd>\n        \u003C\u002Ftr>\n        \u003Ctr>\n            \u003Ctd align=\"center\">A birthday cupcake\u003C\u002Ftd>\n            \u003Ctd align=\"center\">A chair that looks\u003Cbr>like a tree\u003C\u002Ftd>\n            \u003Ctd align=\"center\">A green boot\u003C\u002Ftd>\n        \u003C\u002Ftr>\n        \u003Ctr>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_penguin\u002F1.gif\" alt=\"A penguin\">\n            \u003C\u002Ftd>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fube_ice_cream_cone\u002F3.gif\" alt=\"Ube ice cream cone\">\n            \u003C\u002Ftd>\n            \u003Ctd align=\"center\">\n                \u003Cimg src=\"samples\u002Fa_bowl_of_vegetables\u002F2.gif\" alt=\"A bowl of vegetables\">\n            \u003C\u002Ftd>\n        \u003C\u002Ftr>\n        \u003Ctr>\n            \u003Ctd align=\"center\">A penguin\u003C\u002Ftd>\n            \u003Ctd align=\"center\">Ube ice cream cone\u003C\u002Ftd>\n            \u003Ctd align=\"center\">A bowl of vegetables\u003C\u002Ftd>\n        \u003C\u002Ftr>\n    \u003C\u002Ftbody>\n\u003Ctable>\n\n# Usage\n\nInstall with `pip install -e .`.\n\nTo get started with examples, see the following notebooks:\n\n* [sample_text_to_3d.ipynb](shap_e\u002Fexamples\u002Fsample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text prompt.\n* [sample_image_to_3d.ipynb](shap_e\u002Fexamples\u002Fsample_image_to_3d.ipynb) - sample a 3D model, conditioned on a synthetic view image. To get the best result, you should remove background from the input image.\n* [encode_model.ipynb](shap_e\u002Fexamples\u002Fencode_model.ipynb) - loads a 3D model or a trimesh, creates a batch of multiview renders and a point cloud, encodes them into a latent, and renders it back. For this to work, install Blender version 3.3.1 or higher, and set the environment variable `BLENDER_PATH` to the path of the Blender executable.\n","Shap-E 是一个基于文本或图像生成3D对象的项目。其核心功能是利用条件生成技术，将输入的文本描述或2D图像转换为相应的3D模型，支持从简单的日常用品到复杂的创意设计等多种类型。该项目采用Python语言开发，并通过隐式函数来定义3D形状，使得生成的模型具有较高的细节度与灵活性。适合于需要快速原型制作、概念验证或是探索性设计的场景中使用，如产品设计、游戏开发以及艺术创作等领域。","2026-06-11 03:35:08","high_star"]