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Error code: ConfigNamesError Exception: BadZipFile Message: zipfiles that span multiple disks are not supported Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 164, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1686, in dataset_module_factory return HubDatasetModuleFactoryWithoutScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1071, in get_module module_name, default_builder_kwargs = infer_module_for_data_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 593, in infer_module_for_data_files split_modules = { File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 594, in <dictcomp> split: infer_module_for_data_files_list(data_files_list, download_config=download_config) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 535, in infer_module_for_data_files_list return infer_module_for_data_files_list_in_archives(data_files_list, download_config=download_config) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 563, in infer_module_for_data_files_list_in_archives for f in xglob(extracted, recursive=True, download_config=download_config)[ File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1012, in xglob fs, *_ = url_to_fs(urlpath, **storage_options) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs fs = filesystem(protocol, **inkwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem return cls(**storage_options) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__ obj = super().__call__(*args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__ self.zip = zipfile.ZipFile( File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__ self._RealGetContents() File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents endrec = _EndRecData(fp) File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData return _EndRecData64(fpin, -sizeEndCentDir, endrec) File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64 raise BadZipFile("zipfiles that span multiple disks are not supported") zipfile.BadZipFile: zipfiles that span multiple disks are not supported
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Danbooru Artists 10k
Dataset Summary
This dataset contains images from 10,000 artists collected from Danbooru. The images are primarily sourced from a mirror here. However, there are six images that are missing/broken in this mirror, which have been directly sourced from Danbooru. Each artist is represented by 30 images. This dataset is intended for use in metric learning or fine-grained classification tasks related to art styles. The artists are split into train, validation, and test sets at a ratio of 80%, 10%, and 10%, respectively. Similarly, each artist's 30 images are also split into train, validation, and test sets at the same ratio.
Size
300,000 images (10,000 artists * 30 images/artist)
Format
The images are stored as WebP files packaged in a10k.zip
. The dataset splits are provided in split.txt
. Each line of split.txt
follows this format: artist_split image_split artist_name file_path
.
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