인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
생산성 및 협업 · SKILL.md

scene-generation

scene-generation

Generate WorldGen 3D scenes from text, images, or equirectangular panoramas, choose splat or mesh output, and explore results in a local Viser viewer.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: scene-generation description: "Generate WorldGen 3D scenes from text, images, or equirectangular panoramas, choose splat or mesh output, and explore results in a local Viser viewer." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Scene generation

Use this route when the task asks for a WorldGen scene from a text prompt, source image, or 360 panorama; wants a Gaussian splat or Open3D mesh; needs low-VRAM or experimental Sharp/inpainting options; or wants to explore and export novel views in a browser.

Choose the input path

  • Text-to-scene: construct WorldGen(mode="t2s", ...) and call generate_world(prompt).
  • Image-to-scene: construct WorldGen(mode="i2s", ...), load an RGB PIL image, and call generate_world(prompt, image=image).
  • Panorama-to-scene: load a 2:1 equirectangular PIL image and call _generate_world(pano_image, return_mesh=...) to skip panorama diffusion.
  • Interactive viewer: run the bundled scripts/worldgen_demo.py; it starts Viser at http://localhost:8080, renders the scene, and exposes camera path and novel-view export controls.

Read references/workflows.md for concrete code and command recipes. Read references/troubleshooting.md for workflow-specific failures after the package-level checks in the root references/troubleshooting.md.

Select the output

  • Leave return_mesh=False for the default SplatFile Gaussian scene. Save it with scene.save("scene.ply").
  • Set return_mesh=True for an Open3D triangle mesh and save it with open3d.io.write_triangle_mesh("scene.glb", mesh).
  • Do not combine return_mesh=True and inpaint_bg=True in the bundled demo. The inpainting implementation merges foreground/background splats.

Select runtime options

  • Use low_vram=True when the GPU has limited memory or when model loading causes an OOM. The bundled launcher auto-enables it below 24 GB.
  • Use use_sharp=True only after the base pipeline works and the optional Sharp package/checkpoint is available.
  • Use inpaint_bg=True only for an explicitly experimental background repair; it adds segmentation and LaMa model dependencies and extra downloads.
  • Use resolution to trade panorama detail against memory and latency. Start lower when debugging an environment or an input contract.

Safe preflight

Before a long model download or generation run:

python scripts/check_worldgen_env.py --demo-help

This confirms the installed public API and a tiny CUDA allocation without loading FLUX, DA-2, Sharp, or LaMa weights. For the full flag surface, run:

python scripts/worldgen_demo.py --help

Boundaries

This sub-skill owns user-facing generation, output conversion, the bundled viewer helper, and optional generation modes. It does not own package installation diagnosis, upstream DA-2/PyTorch3D development, model training, release engineering, or repository maintenance. Route those questions to the root references or a more appropriate skill.

저장한 Skills