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Datasets:
JonathanJMK
/
falcon-x

Tasks:
Image-to-Text
Visual Question Answering
Image Segmentation
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
x-ray
counterfactual
visual-grounding
panoptic-segmentation
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 falcon-x@7ca15293a551c94e1e65b249f7bcaea29e4b0312
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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2386, 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 2303, 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 2178, in encode_example
                  return encode_nested_example(self, example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, 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 1483, 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 1158, in encode_example
                  example_data = self.str2int(example_data)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
                  output = [self._strval2int(value) for value in values]
                            ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label falcon-x@7ca15293a551c94e1e65b249f7bcaea29e4b0312

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falcon-x

X-ray images, component annotations, and language-and-grounding tasks for FALCON.

Paper · Code · Model

Contents

Split Original images Counterfactual images Task records
Train 5,528 33,156 397,900
Test 1,383 8,298 99,576
Total 6,911 41,454 497,476

The three component categories are detonator (1), explosive (2), and battery (3). Original images have instance annotations and panoptic PNG masks. Counterfactual images remove one or two component categories and retain references to their original image and remaining instances.

Task family Target
source_summary Short scene description
detailed_caption Detailed scene description
instance_description Description of a specified instance
counterfactual_caption Description of an edited image
vqa Answer to a visual question
category_presence Whether a category is present
missing_component_identification JSON list of absent categories
functional_completeness Whether all three categories are present
referring_expression Mask for the described instance
category_or_all_instance_grounding Union mask for the requested category or all instances
referring_functional_grounding Union of present component masks
panoptic_segmentation Visible instance segments and categories
referring_panoptic_segmentation Visible segments of the queried category

Download and use

Download with huggingface_hub:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="JonathanJMK/falcon-x",
    repo_type="dataset",
    local_dir="falcon-x",
)

Extract both archives:

unzip -q -n falcon-x/train.zip -d falcon-x
unzip -q -n falcon-x/test.zip -d falcon-x

Citation 

@inproceedings{michael2026falcon,
  title={FALCON: Functional Assembly and Language for Compositional Reasoning in X-ray},
  author={Michael, Yonathan and Alansari, Mohamad and Takele, Natnael and Henschel, Andreas and Werghi, Naoufel},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  year={2026}
}
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Paper for JonathanJMK/falcon-x