Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    FileNotFoundError
Message:      [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f6e87558770>'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/xml/xml.py", line 67, in _generate_tables
                  with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
                       ~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
                  return function(*args, download_config=download_config, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 967, in xopen
                  return open(main_hop, mode, *args, **kwargs)
              FileNotFoundError: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f6e87558770>'

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Asset Library

中文说明

Unified robotics and simulation asset library.

This repository stores normalized reusable assets from RoboCasa, Discoverse, TinyForge, Hunter, and third-party asset sites. It is designed to be hosted as a Hugging Face Dataset.

Layout

Raw source-preserved asset layout:

assets/<source>/raw/<asset_type>/<category>/<asset_id>/

Example:

assets/robocasa/raw/fixtures/dishwashers/Dishwasher031/

Derived asset layout:

assets/<source>/derived/<asset_type>/<category>/<asset_id>/

Use derived/ for generated or transformed outputs such as convex decomposition, collision meshes, cleaned meshes, and conversions.

For convex decomposition scaffolding:

python scripts/scaffold_convex_decomposition.py assets/robocasa/raw/fixtures/dishwashers/Dishwasher031

Collection-level imports are allowed when an upstream repository has many internal relative references. They still use the same layout under raw/:

assets/<source>/raw/<asset_type>/<category>/<asset_id>/

Current example:

assets/discoverse/raw/collections/models/discoverse_models/

Top-level repository structure:

.
├── AGENTS.md
├── README.md
├── assets/
│   ├── discoverse/
│   ├── hunter/
│   ├── robocasa/
│   ├── third_party/
│   └── tinyforge/
├── templates/
├── docs/
│   ├── asset_readiness_classification.md
│   ├── convex_decomposition_spec.md
│   ├── external_source_catalog.md
│   ├── naming_spec.md
│   ├── placement_asset_notes.md
│   ├── primitive_collision_proxy_spec.md
│   ├── structure_mapping.md
│   ├── source_notes/
│   └── storage_spec.md
├── manifest/
│   ├── assets.jsonl
│   ├── licenses.yaml
│   └── sources.yaml
└── scripts/
    ├── run_convex_decomposition.py
    ├── run_primitive_collision_proxy.py
    ├── scaffold_convex_decomposition.py
    ├── download_from_hf.sh
    ├── upload_to_hf.sh
    └── validate_asset.py

Naming rule:

<source>.<asset_type>.<category>.<upstream_id>

Example:

robocasa.fixtures.dishwashers.Dishwasher031

Current seed assets

  • RoboCasa dishwasher fixtures: 25 MJCF assets under assets/robocasa/raw/fixtures/dishwashers/
  • RoboCasa dishwasher support files:
    • fixture registry: assets/robocasa/raw/fixtures/fixture_registry/dishwasher.yaml
    • implementation reference: docs/source_notes/robocasa/dishwasher_fixture.py
  • DISCOVERSE models collection: upstream models/ tree under assets/discoverse/raw/collections/models/discoverse_models/
    • stored as a collection-level asset to preserve internal relative references
    • includes MJCF, URDF, mesh, and reference image files

Placement-related notes and candidate external links are tracked in:

docs/asset_readiness_classification.md
docs/convex_decomposition_spec.md
docs/external_source_catalog.md
docs/placement_asset_notes.md
docs/primitive_collision_proxy_spec.md
docs/structure_mapping.md
docs/source_notes/third_party.md

Readiness is tracked separately from storage. A downloaded asset is not automatically production-ready:

  • L0: validated for the target task, robot, policy, verifier, and replay pipeline
  • L1: complete simulation asset in its original simulator
  • L2: articulated structure exists but physics/task information is incomplete
  • L3: movable parts are separated but joints are not reliable
  • L4: complete static object
  • L5: raw or incomplete static mesh

See docs/asset_readiness_classification.md for the full standard.

Index

The global asset index is:

manifest/assets.jsonl

Each asset directory also contains a local metadata.yaml.

Validate

python scripts/validate_asset.py assets/robocasa/raw/fixtures/dishwashers/Dishwasher031
python scripts/validate_asset.py --all

Current expected result:

validated_assets=26

Upload to Hugging Face

Login first:

export HF_ENDPOINT=https://hf-mirror.com
hf auth login

Create the dataset repo if needed:

hf repo create <namespace>/<dataset_repo> --type dataset --private

Upload:

cd /path/to/asset-library
scripts/upload_to_hf.sh <namespace>/<dataset_repo>

Download from Hugging Face

export HF_ENDPOINT=https://hf-mirror.com

scripts/download_from_hf.sh <namespace>/<dataset_repo> ./asset-library
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