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Datasets:
Varsha0105
/
HEp2

Tasks:
Image Classification
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
biology
medical
License:
Dataset card Files
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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 HEp2@c40d829f50cc907634fb36e77c6e39840c09c463
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2092, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2197, in cast_table_to_features
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1995, in cast_array_to_feature
                  return feature.cast_storage(array)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1169, in cast_storage
                  [self._strval2int(label) if label is not None else None for label in storage.to_pylist()]
                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1098, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label HEp2@c40d829f50cc907634fb36e77c6e39840c09c463

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Dataset card for HEp2

The HEp-2 (Human Epithelial type 2) dataset is a widely used benchmark in the field of medical image analysis, especially for the task of antinuclear antibody (ANA) pattern classification. The dataset contains microscopic images of HEp-2 cells stained with fluorescence, demonstrating multiple patterns of autoantibody binding associated with various autoimmune diseases. The HEp-2 dataset is utilized by researchers and practitioners to develop and evaluate algorithms for automated ANA pattern recognition to aid in the diagnosis of autoimmune diseases. The intricate patterns in this dataset test the robustness of computational models, making it a valuable resource for advancing the understanding of autoimmune diseases and the development of advanced medical image analysis techniques.

Usage 

from datasets import load_dataset

ds = load_dataset("Genius-Society/HEp2", split="train")
labels = ds.features["label"].names
for item in ds:
    print("image: ", item["image"])
    print("label name: " + labels[item["label"]])

Maintenance 

GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/Genius-Society/HEp2
cd HEp2

Mirror

https://www.modelscope.cn/datasets/Genius-Society/HEp2

Thanks

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Paper for Varsha0105/HEp2