The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label Region-Aware-CGAN-based-Synthetic-Rail-Surface-Defect-Dataset@e812a84063c3d5b1d42c2adb126db1acbe20360a
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 478, 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 Region-Aware-CGAN-based-Synthetic-Rail-Surface-Defect-Dataset@e812a84063c3d5b1d42c2adb126db1acbe20360aNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Region-Aware CGAN-Based Synthetic Rail Surface Defect Dataset
Dataset Description
This dataset contains 3,000 synthetic rail surface defect image–label pairs generated for training and benchmarking deep learning-based rail surface defect segmentation models. The dataset was developed to address the limited availability of annotated rail defect images commonly encountered in railway condition monitoring applications.
The synthetic image–label pairs were generated using a Conditional Generative Adversarial Network (CGAN)-based image synthesis framework trained on the publicly available Rail Surface Discrete Defects (RSDDs) Type-I and Type-II datasets. The framework incorporates a Distance Transform (DT)-guided region-aware loss formulation that fuses geometric, structural, and perceptual information during image synthesis to improve the realism and fidelity of generated defect regions.
Dataset Statistics
- Total image–label pairs: 3,000
- Image resolution: 256 × 256 pixels
- Image format: PNG
- Number of channels: 3-channel RGB images
- Application domain: Rail surface spalling defect segmentation
Label Format
Each synthetic image is accompanied by a corresponding segmentation mask.
The mask images are stored as RGB images using the following color encoding:
| Class | RGB Color |
|---|---|
| Background | Green (0, 255, 0) |
| Defect Region | Red (255, 0, 0) |
The red regions represent rail surface spalling defects, while the green regions correspond to non-defective rail surface background.
Intended Use
The dataset is intended for:
- Semantic segmentation of rail surface defects
- Synthetic data augmentation
- Deep learning model training and benchmarking
- Railway condition monitoring research
- Computer vision research on infrastructure inspection
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