{"data":{"slug":"maximeraafat-blendernerf","name":"BlenderNeRF","tagline":"Easy NeRF synthetic dataset creation within Blender","github_url":"https://github.com/maximeraafat/BlenderNeRF","owner":"maximeraafat","repo":"BlenderNeRF","owner_avatar_url":"https://avatars.githubusercontent.com/u/51931580?v=4","primary_language":"Python","stars":1009,"forks":76,"topics":["addons","ai","blender","computer-graphics","computer-vision","gaussian-splatting","instant-ngp","nerf","neural-rendering","python"],"archived":false,"github_pushed_at":"2024-12-16T22:12:27+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/maximeraafat-blendernerf","markdown_url":"https://www.graphcanon.com/tools/maximeraafat-blendernerf.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/maximeraafat-blendernerf","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=maximeraafat-blendernerf","description":"Easy NeRF synthetic dataset creation within Blender","homepage_url":null,"license":"MIT","open_issues":11,"watchers":19,"ai_summary":"A Python-based add-on for Blender that simplifies the process of creating Neural Radiance Fields (NeRF) datasets, tailored for tasks related to computer vision and neural rendering.","readme_excerpt":"## Installation\n\n1. Download this repository as a **ZIP** file\n2. Open Blender (4.0.0 or above)\n3. In Blender, head to **Edit > Preferences > Add-ons**, and select **Install From Disk** under the drop icon\n4. Select the downloaded **ZIP** file\n\nAlthough release versions of **BlenderNeRF** are available for download, they are primarily intended for tracking major code changes and for citation purposes. I recommend downloading the current repository directly, since minor changes or bug fixes might not be included in a release right away.","github_created_at":"2022-07-11T21:09:11+00:00","created_at":"2026-07-11T12:26:55.220872+00:00","updated_at":"2026-07-31T12:00:35.010461+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"}],"tags":[{"slug":"addons","name":"addons"},{"slug":"ai","name":"ai"},{"slug":"blender","name":"blender"},{"slug":"computer-graphics","name":"computer-graphics"},{"slug":"gaussian-splatting","name":"gaussian-splatting"},{"slug":"instant-ngp","name":"instant-ngp"},{"slug":"nerf","name":"nerf"},{"slug":"neural-rendering","name":"neural-rendering"}],"trust":{"provenance":{"is_fork":false,"github_id":512909393,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-31T12:00:34.269Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":591,"last_release_at":"2024-08-06T23:38:43Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T12:26:56.757Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-31T12:00:34.724Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-31T12:00:34.724Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-31T12:00:34.724Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium"},"requirements":{"notes":[],"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"when_to_use":["Use if you are familiar with Blender and want to create customized NeRF datasets quickly and efficiently within the Blender environment.","If your project demands precise control over the synthetic data generation process, which can be finely tuned through BlenderNeRF's capabilities."],"when_not_to_use":["Avoid using BlenderNeRF if you lack proficiency with Blender as its interface might pose a significant learning curve for beginners.","Not recommended if real-world dataset acquisition is prioritized over synthetic data creation, as NeRF datasets created here are limited to the digital environments of Blender."],"source":"enrich:decision_facts","observed_at":"2026-07-17T00:11:12.915Z"},"constraint_facets":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium"},{"label":"Requirements","value":"Min 8 GB RAM"},{"label":"Adopt for","value":"BlenderNeRF streamlines synthetic NeRF dataset creation for users with experience in Blender"}]}}