The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
ADT seq144 Subset — Projection-Assisted Segmentation Reproduction
A 300-frame slice of the Aria Digital Twin (ADT) sequence
Apartment_release_clean_seq144_M1292, packaged so that a
projection-assisted gaze-prompted segmentation pipeline can be reproduced
without downloading the ~10 GB raw ADT recording.
Companion checkpoints: tianxia2/projseg-checkpoints.
Contents
train/Apartment_release_clean_seq144_M1292/, frames 500–799 of 2852:
| File | Size | Extracts to | What |
|---|---|---|---|
rgb.tar |
790 MB | rgb/frame_%06d.png |
RGB, 1408×1408, lossless PNG |
depth.tar |
330 MB | depth/frame_%06d.npz |
Metric depth, 1408×1408 |
gaze.tar |
310 KB | gaze/frame_%06d.json |
Gaze pixel + timestamp |
segmentation.tar |
11 MB | segmentation/%06d.npz |
Instance segmentation |
semantic.tar |
11 MB | semantic/%06d.png |
Semantic labels |
aria_trajectory.csv |
920 KB | — | Device poses (tx,ty,tz,qx,qy,qz,qw) for the whole sequence |
calibration.json |
1 KB | — | RGB camera intrinsics (KB8) and T_rgb_device, extracted from the original VRS |
metadata.json |
87 KB | — | Frame index restricted to this subset |
Total ~1.2 GB. Filenames keep their original frame indices, so
frame_000500.png here is frame_000500.png in the full sequence.
The per-frame files are shipped as tar archives, one per modality. Publishing
1500 loose files instead makes a plain snapshot_download exceed the Hugging
Face API rate limit (1000 requests / 5 min) partway through. download_assets.py
in the reproduction artifact downloads and extracts them in one step.
calibration.json and aria_trajectory.csv are what make the raw ADT
recording unnecessary: upstream, the camera model was read from the 1.8 GB VRS
via projectaria_tools and the poses from the raw sequence directory.
Usage
huggingface-cli download tianxia2/projseg-adt-seq144-subset \
--repo-type dataset --local-dir data/processed_adt
cd data/processed_adt/train/Apartment_release_clean_seq144_M1292
for f in *.tar; do tar -xf "$f" && rm "$f"; done
Then follow the reproduction artifact README, which uses this as
data/processed_adt/train/Apartment_release_clean_seq144_M1292.
Provenance and license
Derived from the Aria Digital Twin dataset by Meta Platforms, Inc. The underlying data remains subject to its original license and terms of use — see the ADT dataset page. This repository redistributes a frame-limited, format-converted subset purely as a reproducibility convenience. If you use it, cite the ADT dataset and follow its terms; for full sequences or any other use, obtain the data from the official source.
@inproceedings{pan2023aria,
title = {{Aria Digital Twin}: A New Benchmark Dataset for Egocentric 3D Machine Perception},
author = {Pan, Xiaqing and Charron, Nicholas and Yang, Yongqian and Peters, Scott and
Whelan, Thomas and Kong, Chen and Parkhi, Omkar and Newcombe, Richard and Ren, Yuheng Carl},
booktitle = {ICCV},
year = {2023}
}
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