README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - robotics
  - image-segmentation
  - depth-estimation
tags:
  - simready
  - openusd
  - usd
  - usdz
  - isaac-sim
  - omniverse
  - robotics
  - embodied-ai
  - synthetic-data
  - home
  - apartment
  - floorplan
  - multi-room
  - indoor-navigation
  - scene-graph
  - digital-twin
pretty_name: 'PhysicalAI SimReady Homes: Multi-Room Interiors'
size_categories:
  - 1K<n<10K
gated: manual
extra_gated_prompt: >-
  Access to this dataset is granted for non-commercial research and evaluation.
  Please tell us who you are and what you plan to evaluate. Commercial training,
  fine-tuning, product development, or production use requires a separate
  written license from Imagine.
extra_gated_fields:
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  Intended use:
    type: select
    options:
      - Academic / non-commercial research
      - Education
      - Commercial internal evaluation
      - Commercial model training
      - Commercial model evaluation / benchmarking
      - Simulation pipeline evaluation
      - Dataset vendor / platform evaluation
      - Other
  Please describe what you want to evaluate: text
  I acknowledge that public access is for non-commercial research only unless Imagine grants separate evaluation or commercial rights: checkbox
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  I agree not to use the dataset for commercial training, fine-tuning, product development, or production systems without a separate written license: checkbox
extra_gated_button_content: Request access
configs:
  - config_name: default
    data_files:
      - split: train
        path: scenes.parquet

PhysicalAI SimReady Homes: Multi-Room Interiors

1,000 simulation-ready multi-room home interiors in OpenUSD, each with physics, PBR materials, HDRI lighting, an editable scene graph, and a SimReady metadata sidecar.

Built by Imagine.io with simreadyfloorplans. Companion to PhysicalAI SimReady Assets, which holds the object, material and HDRI library these scenes draw from.

Scenes	1,000
Floorplans	4 (scandinavian_1br, scandinavian_2br, scandinavian_3bed, scandinavian_4br)
Seeds per floorplan	250
Total size	1.55 GB (mean 1.55 MB per scene)
Objects per scene	~322
Distinct assets used	513
HDRI environments	6
Floor material packs	25

Read this first — three things that will surprise you

1. A scene needs network access to open. The bundle holds the USD, not the geometry. Every mesh, PBR texture and the HDRI resolves by https:// URL from the public, ungated imagineio/PhysicalAI-SimReady-Assets at load time. That is why a scene is under a megabyte instead of about a gigabyte, and it means you need a resolver that speaks HTTPS — Isaac Sim's OmniUsdResolver does, the PyPI usd-core build does not (it opens the stage and shows an empty room). Access here is enough; the assets repo needs no separate grant.

If assets come up missing after a network blip, Omniverse caches the failed fetch. Clear %LOCALAPPDATA%\ov\cache (Windows) or ~/.cache/ov (Linux) before retrying.

2. There are 4 floorplans, not 1,000. Each is furnished 250 times. A seed is a genuine re-furnish, not a re-skin: measured between two seeds of one floorplan, 73 of 98 shared objects move, the object count rises 112 → 139, the kitchen re-tiles, and every material pack and asset pick changes. But the walls do not move — room polygons, door positions and the footprint are identical across all seeds of a floorplan. If you need architectural diversity, this is 4 architectures.

3. A scene is one archive, and it nests. Download <scene_digest>.zip, unpack it, then open model.usdz — you cannot point a viewer at the download. There is no text-readable USD layer at any level; the root inside the package is a binary crate (model.usdc).

What's in each scene

scenes/<style>/<scene_digest>.zip        ~1.55 MB
    model.usdz          the scene: geometry, physics, materials, lighting, cameras
    metadata.json       SimReady sidecar — rooms, objects, physics index, design choices
    topdown.png         plan sheet (imperial drafting sheet)
    scene_graph.json    editable room/object graph with poses and asset refs
    floorplan.json      the source floorplan the scene was built from

The archive is named by a digest of its scene graph, so identical scenes are identical files. layouts/<style>/ carries each floorplan's authored inputs once.

Browse the index

scenes.parquet is the index — and because nothing inside a bundle has its own URL, it is the only index. Every variation axis is a column, so you filter here and download only what you want. The preview column embeds a 256 px thumbnail, so the Data Studio viewer above shows a plan sheet for every row.

import pandas as pd
df = pd.read_parquet("hf://datasets/imagineio/PhysicalAI-SimReady-Homes/scenes.parquet")

hits = df[(df.bedrooms == 3) & (df.interior_run == "island") & (df.tv_mount == "wall")]
print(hits[["style", "seed", "scene_id", "zip_url"]])

Variation axes you can filter on

Group	Columns
Identity	scene_id (= scene_digest), style, seed, zip_url, hf_path
Plan shape	room_count, bedrooms, bathrooms, room_types, room_areas_m2, floor_area_m2, footprint_w_m, footprint_d_m
Typology	circulation, open_kitchen, has_courtyard, veranda_depth
Surfaces	floor_pack_living, floor_pack_kitchen, floor_pack_bathroom, floor_pack_balcony, wall_pack_exterior, wall_pack_interior, ceiling_pack, wall_tile_pack, wall_tile_m, rug_packs, mat_packs
Kitchen design	kitchen_shape, kitchen_run_count, cabinet_door_style, cabinet_handle_variant, countertop_finish, cook_mode, oven_housing, interior_run
Living design	sofa_shape, tv_mount
Lighting	hdri, lighting_mode, sun_azimuth, color_temp, light_count
Assets	asset_ids, asset_names, assets_by_class, door_assets, window_assets, balcony_door_assets, object_variants
Composition	object_count, referenced_count, placeholder_count, class_histogram
Physics	rigid_body_count, static_body_count, collider_count, joint_count, articulation_root_count, material_count, camera_count
Quality	dropped_required, dropped_bathroom_core, scale_up_factor, scale_up_capped, bath_openings_clamped
Provenance	code_rev, asset_index_sha256, generated_at, remote_assets_remote, remote_assets_local, build_s, stage_timings_s

Quick start

pip install huggingface_hub pandas pyarrow
huggingface-cli login                    # gated: request access first

python dataset_tools/download_scene.py --style scandinavian_3bed --seed 7 --out ./scenes --extract
python dataset_tools/validate_scene.py ./scenes/scandinavian_3bed_s7
<isaac>/python.sh dataset_tools/load_isaac.py ./scenes/scandinavian_3bed_s7/model.usdz

dataset_tools/ in this repo holds download_scene.py, extract_scene.py, validate_scene.py and load_isaac.py.

Physics and SimReady

Every scene is authored for direct use in Isaac Sim: rigid bodies with mass and inertia, collision approximations per object class, PhysX materials with real friction/restitution/ density, articulated openings (doors, cabinet doors, drawers) with joints, and per-object semantic labels. metadata.json carries a physics_index naming every rigid body, static body, collider, joint, articulation root, material, light and camera by prim path.

The design block in metadata.json records the seeded per-room choices — the door style a kitchen's casework wears, the countertop stone, the sofa shape — at the point each was drawn. These are not derivable from the geometry and are mirrored into the index columns above.

Metadata schema

metadata.json is simready_scene_metadata_v2: schema, schema_version, scene_id, units, coordinate_system, usd_export, packaging, variation_config, source_floorplan, functional_layout, dropped_furniture, design, rooms, objects, physics_index, build_stats.

Reproducibility

Each row carries code_rev, asset_index_sha256, seed and the build flags, which together name the exact inputs a scene came from.

One caveat, stated plainly: asset URLs point at resolve/main/ of the assets repo rather than a pinned commit. Scenes therefore track that repo's main branch — asset fixes reach already-published scenes for free, but a restructuring there would affect every scene here at once.

Known limits

• 4 floorplans. See point 2 above.
• Ceiling material is constant. The library ships exactly one ceiling pack, so every scene shares it.
• Wall materials are thin — 7 packs across the corpus.
• HDRI is keyed on the seed alone, from a pool of 6, so all floorplans at a given seed share their lighting.
• Scenes are not SimReady-validated per scene in this release. The rules exist in the generator and pass on spot-checked scenes, but the corpus run did not gate on them.

License

CC BY-NC 4.0 — non-commercial research and evaluation. Commercial training, fine-tuning, product development or production use requires a separate written license from Imagine. See the access form above.

Citation

@misc{imagineio_physicalai_simready_homes,
  title  = {PhysicalAI SimReady Homes: Multi-Room Interiors},
  author = {Imagine.io},
  year   = {2026},
  url    = {https://huggingface.co/datasets/imagineio/PhysicalAI-SimReady-Homes}
}

About Imagine.io

Imagine.io builds 3D content and simulation pipelines for retail, furniture and robotics. We generate SimReady environments at scale — get in touch if you need a corpus shaped to your task.