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/hdf5/hdf5.py", line 59, in _split_generators
self.info.features = _recursive_infer_features(h5)
~~~~~~~~~~~~~~~~~~~~~~~~~^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 216, in _recursive_infer_features
features = _recursive_infer_features(obj)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 220, in _recursive_infer_features
features_dict[path] = _infer_feature(obj)
~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 229, in _infer_feature
return _create_compound_features(dset)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 175, in _create_compound_features
return _recursive_infer_features(mock_group)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 220, in _recursive_infer_features
features_dict[path] = _infer_feature(obj)
~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 229, in _infer_feature
return _create_compound_features(dset)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 175, in _create_compound_features
return _recursive_infer_features(mock_group)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 214, in _recursive_infer_features
for path, obj in _iter_with_links(h5_obj):
~~~~~~~~~~~~~~~~^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 430, in _iter_with_links
yield from h5_obj.items()
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 154, in items
for field_name in self.dset.dtype.names:
^^^^^^^^^^^^^^^^^^^^^
TypeError: 'NoneType' object is not iterable
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 68, 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.
Mouse Triplet pose re-estimated with DeepLabCut (MABe22)
Pose of three interacting mice for the videos of the MABe22 mouse triplet task, re-estimated with DeepLabCut. It is the pose used for Mouse Triplet in Learning When Visual Context Matters for Mouse Behavior Analysis (NeurIPS 2026); code: BRAINML-GT/ResiFuse.
Contents
deeplabcut_filtered/<video_id>DLC_CtdCoamW48_multi_mouse2025-11-21shuffle5_snapshot_best-180_el.h5: one file for each of 1,810 of the 1,829 videos in the MABe22 mouse submission set.
Each file is a DeepLabCut multi-animal output table (read with pandas.read_hdf) with 1,801 frames at 30 Hz and columns indexed by scorer, individuals (A0, A1, A2), bodyparts (nose, left ear, right ear, neck, center back, left forepaw, right forepaw, left hindpaw, right hindpaw, tail base, tail middle, tail tip) and coords (x, y, likelihood). Undetected keypoints are NaN.
Resolution: 448 x 448
The pose was estimated on 448 x 448 videos, and all x, y coordinates are in pixels of that resolution. The official MABe22 videos are 224 x 224; we upscaled them by 2x before running DeepLabCut. To overlay the pose on the official 224 x 224 videos, divide the coordinates by 2. The videos are not included here; the 448 x 448 versions can be made from the official ones with
ffmpeg -i <video_id>.avi -vf scale=448:448:flags=lanczos -c:v libx264 -preset medium -crf 18 -pix_fmt yuv420p <video_id>.mp4
How the pose was obtained
We use the videos of the mouse submission set of MABe22. We manually annotated a subset of videos with high-quality pose, trained a multi-animal DeepLabCut model on them, and re-estimated pose for all videos. All methods in the paper, ResiFuse and baselines, use this pose.
Use with ResiFuse
Place the folder at data/mabe2022/deeplabcut_filtered/ of the ResiFuse repository. The videos and labels come from the MABe22 release on CaltechDATA (doi:10.22002/rdsa8-rde65); the repository README describes the remaining steps.
License
MABe22 is distributed under CC BY-NC-SA. This derived pose is shared under the same terms, CC BY-NC-SA 4.0: non-commercial use, with attribution, and derivatives under the same license.
Citation
Please cite MABe22. The citation of our paper will be added once it is published.
@inproceedings{sun2023mabe22,
title = {{MABe22}: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior},
author = {Sun, Jennifer J. and Marks, Markus and Ulmer, Andrew Wesley and Chakraborty, Dipam and Geuther, Brian and Hayes, Edward and Jia, Heng and Kumar, Vivek and Oleszko, Sebastian and Partridge, Zachary and Peelman, Milan and Robie, Alice and Schretter, Catherine E and Sheppard, Keith and Sun, Chao and Uttarwar, Param and Wagner, Julian Morgan and Werner, Erik and Parker, Joseph and Perona, Pietro and Yue, Yisong and Branson, Kristin and Kennedy, Ann},
booktitle = {Proceedings of the 40th International Conference on Machine Learning},
series = {Proceedings of Machine Learning Research},
volume = {202},
pages = {32936--32990},
publisher = {PMLR},
year = {2023}
}
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