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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
text: string
to
{'img_path': Value('string'), 'anomaly': Value('int64'), 'z_free': Value('float64'), 'z_ref': Value('float64'), 'boxes': List(List(Value('float64'))), 'logits': List(Value('float64'))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1856, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 810, in write_table
                  self.write_rows_on_file()  # in case there are buffered rows to write first
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 690, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              text: string
              to
              {'img_path': Value('string'), 'anomaly': Value('int64'), 'z_free': Value('float64'), 'z_ref': Value('float64'), 'boxes': List(List(Value('float64'))), 'logits': List(Value('float64'))}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'text'}) and 6 missing columns ({'img_path', 'boxes', 'logits', 'z_ref', 'anomaly', 'z_free'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/sunsean/VerdictAD/refs/loco_k2_s42/refs_breakfast_box.json (at revision 73d6ca8030c9595e07b490f82039f191f4d6fdd6), ['hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s42/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s42/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s42/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s42/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s42/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s43/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s43/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s43/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s43/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s43/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s44/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s44/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s44/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s44/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k1_s44/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s42/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s42/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s42/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s42/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s42/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s43/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s43/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s43/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s43/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s43/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s44/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s44/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s44/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s44/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k2_s44/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s42/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s42/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s42/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s42/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s42/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s43/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s43/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s43/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s43/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s43/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s45/breakfast_box.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s45/juice_bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s45/pushpins.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s45/screw_bag.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/loco_k4_s45/splicing_connectors.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/cable.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/capsule.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/carpet.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/grid.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/hazelnut.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/leather.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/metal_nut.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/pill.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/screw.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/tile.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/toothbrush.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/transistor.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/wood.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s42/zipper.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/cable.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/capsule.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/carpet.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/grid.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/hazelnut.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/leather.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/metal_nut.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/pill.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/screw.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/tile.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/toothbrush.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/transistor.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/wood.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s43/zipper.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/cable.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/capsule.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/carpet.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/grid.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/hazelnut.json', 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'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k1_s44/zipper.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/bottle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/cable.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/capsule.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/carpet.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/grid.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/hazelnut.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/decisions/mvtec_k2_s42/leather.json', 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'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k1_s44/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s42/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s43/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k2_s44/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s42/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s43/refs_pipe_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_candle.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_capsules.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_cashew.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_chewinggum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_fryum.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_macaroni1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_macaroni2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_pcb1.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_pcb2.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_pcb3.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_pcb4.json', 'hf://datasets/sunsean/VerdictAD@73d6ca8030c9595e07b490f82039f191f4d6fdd6/refs/visa_k4_s45/refs_pipe_fryum.json']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1876, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 830, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 690, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              text: string
              to
              {'img_path': Value('string'), 'anomaly': Value('int64'), 'z_free': Value('float64'), 'z_ref': Value('float64'), 'boxes': List(List(Value('float64'))), 'logits': List(Value('float64'))}
              because column names don't match
              
              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 1379, 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 956, 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 1702, 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 1887, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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.

img_path
string
anomaly
int64
z_free
float64
z_ref
float64
boxes
list
logits
list
breakfast_box/test/bad/breakfast_box_logical_anomalies_000.png
1
-4.015625
0.570313
[ [ 0, 0, 0.4, 0.4 ], [ 0.2, 0, 0.6, 0.4 ], [ 0.4, 0, 0.8, 0.4 ], [ 0.6, 0, 1, 0.4 ], [ 0, 0.2, 0.4, 0.6 ], [ 0.2, 0.2, 0.6, 0.6 ], [ 0.4, 0.2, 0.8, 0.6 ], [ 0.6, 0.2, ...
[ -1.02734375, -1.984375, 0.953125, 0.85546875, -1.890625, -2.4765625, -1.40234375, -1.40234375, 0.08984375, -2.2890625, -1.23828125, -1.2890625, -0.798828125, 0.12109375, 0.30859375, 0.01953125, -1.7578125, 0.12890625, -0.41015625, -0.91796875, -2.0546875, -2.1015625, -0.7...
breakfast_box/test/bad/breakfast_box_logical_anomalies_001.png
1
-3.953125
0.65625
[ [ 0, 0, 0.4, 0.4 ], [ 0.2, 0, 0.6, 0.4 ], [ 0.4, 0, 0.8, 0.4 ], [ 0.6, 0, 1, 0.4 ], [ 0, 0.2, 0.4, 0.6 ], [ 0.2, 0.2, 0.6, 0.6 ], [ 0.4, 0.2, 0.8, 0.6 ], [ 0.6, 0.2, ...
[ -0.98046875, -1.6796875, 0.1640625, 0.66015625, -1.77734375, -2.5703125, -0.76171875, -0.98828125, -0.515625, -2.4140625, -0.78515625, -1.578125, -0.421875, -1.6640625, 0.42578125, -0.05859375, -2.3828125, -0.37109375, -1.109375, -1.5078125, -2.2421875, -1.71875, -1.35937...
breakfast_box/test/bad/breakfast_box_logical_anomalies_002.png
1
-3.921875
0.476563
[ [ 0, 0, 0.4, 0.4 ], [ 0.2, 0, 0.6, 0.4 ], [ 0.4, 0, 0.8, 0.4 ], [ 0.6, 0, 1, 0.4 ], [ 0, 0.2, 0.4, 0.6 ], [ 0.2, 0.2, 0.6, 0.6 ], [ 0.4, 0.2, 0.8, 0.6 ], [ 0.6, 0.2, ...
[ -1.23046875, -1.9453125, 0.798828125, 0.94921875, -1.94921875, -2.1171875, -1.4921875, -1.193359375, -0.00390625, -2.4375, -1.08984375, -1.4609375, -0.689453125, -0.1796875, 0.5234375, 0.29296875, -2.421875, -1.9296875, -1.15625, -1.984375, -2.7109375, -2.078125, -1.35937...
breakfast_box/test/bad/breakfast_box_logical_anomalies_003.png
1
-3.953125
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End of preview.

VerdictAD decision cache

Decision-model outputs and reference lists behind every number in VerdictAD: Few-Shot Anomaly Detection via Decision-Guided Refinement (paper, code).

With this cache, evaluate.py reproduces the VerdictAD results on any detector run without running the decision model (Clef-Flash 9B).

Contents

27 runs: MVTec AD, VisA and MVTec LOCO AD × 1/2/4-shot × three reference draws (seeds 42/43/44 for 1- and 2-shot, 42/43/45 for 4-shot); 49,095 test images in total.

refs/<dataset>_k<shots>_s<seed>/refs_<class>.json       the k normal references (paths relative to the dataset root)
decisions/<dataset>_k<shots>_s<seed>/<class>.json       one record per test image

Each record:

Field Meaning
img_path <class>/test/<type>/<file>, relative to the dataset root
anomaly 1 for an anomalous test image
z_free GVR logit, query image alone
z_ref GVR logit, query image against the 2×2 reference mosaic
boxes 32 windows (x0, y0, x1, y1) in [0, 1]: 16 crop windows, then the same 16 as red boxes
logits LVR logit of each window

The references come from the official SubspaceAD sampler at the given seed, and every detector in the paper uses them. LOCO paths follow the layout written by tools/prepare_loco.py; VisA paths follow the 1-class split.

Usage

huggingface-cli download sunsean/VerdictAD --repo-type dataset --local-dir verdictad_cache
python evaluate.py <detector_run> verdictad_cache/decisions/mvtec_k4_s42 --subspacead SubspaceAD

<detector_run> is a SubspaceAD run (patched to save maps) or a detectors.py output that uses refs/mvtec_k4_s42.

Citation

@article{sun2026verdictad,
  title   = {VerdictAD: Few-Shot Anomaly Detection via Decision-Guided Refinement},
  author  = {Sun, Shangquan and Luo, Wenjun and Wang, Yuanzhi and Li, Ruiqi and Chen, Ruoyu and Liu, Jiachen and Lu, Shijian},
  journal = {arXiv preprint arXiv:2611.02654},
  year    = {2026}
}
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