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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label PhenoLeaf_TS@ee4c8dac44593a69c8a72e1ca09d686133161d92
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
                  example = _apply_feature_types_on_example(
                      example, self.features, token_per_repo_id=self.token_per_repo_id
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
                  return encode_nested_example(self, example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ~~~~~~~~~~~~~~~~~~~~~^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
                  example_data = self.str2int(example_data)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
                  output = [self._strval2int(value) for value in values]
                            ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label PhenoLeaf_TS@ee4c8dac44593a69c8a72e1ca09d686133161d92

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PhenoLeaf-TS

PhenoLeaf-TS is a time-series RGB image dataset associated with the dataset paper accepted at the European Conference for Computer Vision (ECCV) 2026. The dataset supports leaf instance segmentation, leaf tracking, and growth stage classification of Arabidopsis thaliana.

Download

Download PhenoLeaf-TS.zip

Project

PhenoLeaf-TS Project Website

Code

The source code and additional documentation are available in the following repository:

PhenoLeaf-TS GitHub Repository

Licence and Citation

© 2026 La Trobe University. All rights reserved.

This dataset is provided solely for non-commercial academic research and/or teaching purposes. It may be used and reproduced in non-commercial academic and research publications with mandatory citation. The dataset files must not be redistributed, republished, or publicly hosted, either in whole or in part, without prior written permission.

If you use this dataset, please cite the following paper published at the European Conference on Computer Vision (ECCV) 2026:

@inproceedings{saric2026phenoleafts,
  title     = {PhenoLeaf-TS: A Time-Series Benchmark for Leaf Instance
               Segmentation, Tracking, and Growth Stage Classification},
  author    = {Sari{\'c}, Rijad and Azam, Basim and Khan, Sarmad and
               {\v{C}}ustovi{\'c}, Edhem},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2026}
}
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