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Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 298, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 78, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 52, in _get_pipeline_from_tar
current_example[field_name] = cls.DECODERS[data_extension](current_example[field_name])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 299, in npy_loads
return numpy.lib.format.read_array(stream, allow_pickle=False)
File "/src/services/worker/.venv/lib/python3.9/site-packages/numpy/lib/format.py", line 795, in read_array
raise ValueError("Object arrays cannot be loaded when "
ValueError: Object arrays cannot be loaded when allow_pickle=False
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 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 352, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 303, 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.
Kubric Dataset for CoTracker 3
Overview
This dataset was specifically created for training CoTracker 3, a state-of-the-art point tracking model. The dataset was generated using the Kubric engine.
Dataset Specifications
- Size: ~6,000 sequences
- Resolution: 512×512 pixels
- Sequence Length: 120 frames per sequence
- Camera Movement: Carefully rendered with subtle camera motion to simulate realistic scenarios
- Format: Generated using Kubric engine
Usage
The dataset can be parsed using the official CoTracker implementation. For detailed parsing instructions, refer to:
Citation
If you use this dataset in your research, please cite the following papers:
@inproceedings{karaev24cotracker3,
title = {CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos},
author = {Nikita Karaev and Iurii Makarov and Jianyuan Wang and Natalia Neverova and Andrea Vedaldi and Christian Rupprecht},
booktitle = {Proc. {arXiv:2410.11831}},
year = {2024}
}
@article{greff2021kubric,
title = {Kubric: a scalable dataset generator},
author = {Klaus Greff and Francois Belletti and Lucas Beyer and Carl Doersch and
Yilun Du and Daniel Duckworth and David J Fleet and Dan Gnanapragasam and
Florian Golemo and Charles Herrmann and Thomas Kipf and Abhijit Kundu and
Dmitry Lagun and Issam Laradji and Hsueh-Ti (Derek) Liu and Henning Meyer and
Yishu Miao and Derek Nowrouzezahrai and Cengiz Oztireli and Etienne Pot and
Noha Radwan and Daniel Rebain and Sara Sabour and Mehdi S. M. Sajjadi and Matan Sela and
Vincent Sitzmann and Austin Stone and Deqing Sun and Suhani Vora and Ziyu Wang and
Tianhao Wu and Kwang Moo Yi and Fangcheng Zhong and Andrea Tagliasacchi},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}
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