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Error code: DatasetGenerationError
Exception: ValueError
Message: Invalid string class label anime_image_segmentation@2fdb127ad6b6e6cbc123723fe19855d6f7ea476b
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1537, in _prepare_split_single
example = self.info.features.encode_example(record) if self.info.features is not None else record
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
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 anime_image_segmentation@2fdb127ad6b6e6cbc123723fe19855d6f7ea476b
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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1382, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1560, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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This dataset consists of 26,000 anime style images, half of which are foreground characters or objects, and the other half of which are backgrounds. It is intended for training segmentation or matting models where the foreground subject can be extracted from the background. The foundation of this dataset is based upon https://huggingface.co/datasets/skytnt/anime-segmentation
I found the overall quality of that dataset did not meet my needs, so I did a lot of automated and manual inspection of the images, resulting in removing more than half of them, and then adding many more new images.
For the foreground images, I have removed ones containing nudity or extreme lewdness. I also carefully examined the images to remove ones containing the following issues: stray pixels in the image or the alpha channel, images that are cut off at the edge of the frame, semi-transparent areas, fuzzy/blurry areas in the alpha channel, drop shadows, text and other unrelated items appear in the image, partial backgrounds are behind the characters. The foreground images are mostly taken from booru image sites, but I have also added some sprites from games and visual novels, as well as images from various "transparent png" archives. I also tried to bring in more images of male characters and non-human creatures.
For the background images, I wanted to ensure that there was a stronger representation of backgrounds from actual anime videos. The original anime-segmentation dataset contained many abstract backgrounds and patterns, and most of the images were from anime-style illustrations rather than anime video. While some of those images have been preserved, I removed a large portion of them, and replaced them with backgrounds obtained from a variety of other sources, such as torrents and twitter, as well as manually capturing images from numerous anime videos myself. I also added a number of solid color background images, but these are located at the very end of the dataset and can be easily removed if you wish.
Across the entire dataset, I have also made efforts to remove duplicate and similar images. The backgrounds all have a minimum size of 1024x1024. The foreground images are all various sizes, but should generally be small enough not to obscure the entire background image.
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