The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 80, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
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/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SLAKE — grouped QA TARs
Derived from BoKelvin/SLAKE, by Bo Liu, Li-Ming Zhan, Li Xu, and Xiao-Ming Wu. See the official project and publication: SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering, ISBI 2021.
The source is CC BY 4.0; this derived distribution retains CC BY 4.0. This is a modified, unofficial preparation.
| Split | Image rows | QA pairs |
|---|---|---|
| train (original train + validation, after exclusion) | 462 | 10,106 |
| test | 180 | 2,094 |
All test QA are retained. 168 overlapping trainval images and their 1,828 QA were removed. Separation was checked using source image identifiers and exact decoded RGB hashes, and again using the exported image hashes. This does not certify patient-level separation or detect visually similar but pixel-different images.
Images are flattened JPEGs at quality 95 with original dimensions, without resizing or padding. English and Chinese QA are retained. One JSONL row contains all QA for one image; conversation roles are human and gpt.
Each GPT response contains every available image-level organ box, even when the question or answer does not mention that organ: <ref>organ</ref><box>[xmin, ymin, xmax, ymax]</box><answer>original answer</answer>. Boxes come from imgs/*/detection.json inside the original imgs.zip, converted from pixel XYWH to XYXY integers normalized to 0–1000. These are image-level annotations, not question-specific grounding. bbox_annotations retains normalized boxes and original XYWH values. Empty source annotations produce answer-only responses. No reasoning was invented.
Each TAR contains exactly one matching JSONL and an image/ directory. Shards have at most 10,000 image rows; train and test are sharded independently. The JSONL image values are filenames resolved under image/, matching the GEMeX packaging convention, and tar_name identifies the TAR. Standalone JSONL copies are provided beside the archives. Extract each shard separately to avoid same-named members from different splits colliding.
partition is retained as a compatibility field (LLaVA-OneVision-2-Spatial), not a claim that SLAKE is part of that source dataset. See preparation and packaging reports for counts, checksums, and validation. Every archived member was SHA256-checked against its prepared source before upload.
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