{"id":13448944,"url":"https://github.com/openai/shap-e","last_synced_at":"2025-04-29T18:34:38.809Z","repository":{"id":161869636,"uuid":"630141866","full_name":"openai/shap-e","owner":"openai","description":"Generate 3D objects conditioned on text or images","archived":false,"fork":false,"pushed_at":"2024-06-22T19:19:14.000Z","size":11987,"stargazers_count":11864,"open_issues_count":99,"forks_count":991,"subscribers_count":236,"default_branch":"main","last_synced_at":"2025-04-09T01:22:38.177Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/openai.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-04-19T18:54:32.000Z","updated_at":"2025-04-08T18:03:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"ebbc0215-308f-4c98-b17a-354128295146","html_url":"https://github.com/openai/shap-e","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openai%2Fshap-e","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openai%2Fshap-e/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openai%2Fshap-e/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openai%2Fshap-e/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/openai","download_url":"https://codeload.github.com/openai/shap-e/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251560780,"owners_count":21609262,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T06:00:25.784Z","updated_at":"2025-04-29T18:34:38.784Z","avatar_url":"https://github.com/openai.png","language":"Python","funding_links":[],"categories":["Python","Uncategorized","\u003cspan id=\"model\"\u003e3D Model\u003c/span\u003e","三维化","Repos","3D视觉生成重建","排行榜 [2025-03-18]","Tools / Software"],"sub_categories":["Uncategorized","\u003cspan id=\"tool\"\u003eLLM (LLM \u0026 Tool)\u003c/span\u003e","资源传输下载","Generative Art"],"readme":"# Shap-E\n\nThis is the official code and model release for [Shap-E: Generating Conditional 3D Implicit Functions](https://arxiv.org/abs/2305.02463).\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\u003e\n    \u003ctbody\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_chair_that_looks_like_an_avocado/2.gif\" alt=\"A chair that looks like an avocado\"\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/an_airplane_that_looks_like_a_banana/3.gif\" alt=\"An airplane that looks like a banana\"\u003e\n            \u003c/td align=\"center\"\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_spaceship/0.gif\" alt=\"A spaceship\"\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003eA chair that looks\u003cbr\u003elike an avocado\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eAn airplane that looks\u003cbr\u003elike a banana\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eA spaceship\u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_birthday_cupcake/3.gif\" alt=\"A birthday cupcake\"\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_chair_that_looks_like_a_tree/2.gif\" alt=\"A chair that looks like a tree\"\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_green_boot/3.gif\" alt=\"A green boot\"\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003eA birthday cupcake\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eA chair that looks\u003cbr\u003elike a tree\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eA green boot\u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_penguin/1.gif\" alt=\"A penguin\"\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/ube_ice_cream_cone/3.gif\" alt=\"Ube ice cream cone\"\u003e\n            \u003c/td\u003e\n            \u003ctd align=\"center\"\u003e\n                \u003cimg src=\"samples/a_bowl_of_vegetables/2.gif\" alt=\"A bowl of vegetables\"\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd align=\"center\"\u003eA penguin\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eUbe ice cream cone\u003c/td\u003e\n            \u003ctd align=\"center\"\u003eA bowl of vegetables\u003c/td\u003e\n        \u003c/tr\u003e\n    \u003c/tbody\u003e\n\u003ctable\u003e\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/examples/sample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text prompt.\n* [sample_image_to_3d.ipynb](shap_e/examples/sample_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/examples/encode_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","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenai%2Fshap-e","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenai%2Fshap-e","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenai%2Fshap-e/lists"}