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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
balanced_f1_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 473 chars omitted)
  child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
  child 1, native_false_detections: int64
  child 2, native_false_events: int64
  child 3, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
  child 4, onnx_false_detections: int64
  child 5, onnx_false_events: int64
  child 6, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
  child 7, thresholds: struct<handgun: double, knife: double, long_gun: double>
      child 0, handgun: double
      child 1, knife: double
      child 2, long_gun: double
elapsed_seconds: double
image_count: int64
images_per_second_end_to_end: double
native_predictions: string
native_predictions_sha256: string
onnx_predictions: string
onnx_predictions_sha256: string
passed: bool
raw_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 287 chars omitted)
  child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
  child 1, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
  child 2, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
      child 0, ap50: double
      child 1, ap50_95: double
      child 2, average_recall: double
      child 3, precision_at_iou50: double
      child 4, recall_at_iou50: double
schema_version: int64
split: string
status: string
to
{'bbox': List(Value('float64')), 'category_id': Value('int64'), 'image_id': Value('int64'), 'score': 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 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 764, 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 663, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              balanced_f1_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 473 chars omitted)
                child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 1, native_false_detections: int64
                child 2, native_false_events: int64
                child 3, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 4, onnx_false_detections: int64
                child 5, onnx_false_events: int64
                child 6, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 7, thresholds: struct<handgun: double, knife: double, long_gun: double>
                    child 0, handgun: double
                    child 1, knife: double
                    child 2, long_gun: double
              elapsed_seconds: double
              image_count: int64
              images_per_second_end_to_end: double
              native_predictions: string
              native_predictions_sha256: string
              onnx_predictions: string
              onnx_predictions_sha256: string
              passed: bool
              raw_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 287 chars omitted)
                child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 1, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 2, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
              schema_version: int64
              split: string
              status: string
              to
              {'bbox': List(Value('float64')), 'category_id': Value('int64'), 'image_id': Value('int64'), 'score': 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 1839, 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 13 new columns ({'schema_version', 'native_predictions_sha256', 'status', 'split', 'native_predictions', 'onnx_predictions_sha256', 'images_per_second_end_to_end', 'passed', 'image_count', 'onnx_predictions', 'raw_quality', 'balanced_f1_quality', 'elapsed_seconds'}) and 4 missing columns ({'image_id', 'category_id', 'bbox', 'score'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/calibration-valid-invalid-predictions.json (at revision fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f), ['hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-LONG-D4-EMA-S17-100E/exports/onnx-fp32-static-b1/validation-parity/onnx-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-LONG-D4-EMA-S17-100E/exports/onnx-fp32-static-b1/validation-parity/quality-parity.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-COSINE/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA-COSINE/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S29-EMA/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/LARGE-CONFIRM-D4-012E-S43-COSINE/calibration-D4-valid/frozen-test-metrics.json', 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'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-MEDIUM-S17-019E/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-NANO-S17-019E/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-SMALL-S17-019E/calibration-D4-valid/telemetry-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/calibration-valid-invalid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/calibration-valid-prediction-metadata.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/calibration-valid-predictions-raw.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/calibration-valid-predictions.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/evaluation-summary.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/frozen-test-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/hard-negative-metrics.json', 'hf://datasets/Peacockery/weapon-detection-runs-backup-2026-07-24@fb9f26dd328d3e271ddc9e27f3ada58e5fa4825f/SIZE-SWEEP-D4-XL-S17-019E/calibration-D4-valid/telemetry-summary.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 1858, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              balanced_f1_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 473 chars omitted)
                child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 1, native_false_detections: int64
                child 2, native_false_events: int64
                child 3, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 4, onnx_false_detections: int64
                child 5, onnx_false_events: int64
                child 6, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 7, thresholds: struct<handgun: double, knife: double, long_gun: double>
                    child 0, handgun: double
                    child 1, knife: double
                    child 2, long_gun: double
              elapsed_seconds: double
              image_count: int64
              images_per_second_end_to_end: double
              native_predictions: string
              native_predictions_sha256: string
              onnx_predictions: string
              onnx_predictions_sha256: string
              passed: bool
              raw_quality: struct<native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: dou (... 287 chars omitted)
                child 0, native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 1, onnx: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
                child 2, onnx_minus_native: struct<ap50: double, ap50_95: double, average_recall: double, precision_at_iou50: double, recall_at_ (... 14 chars omitted)
                    child 0, ap50: double
                    child 1, ap50_95: double
                    child 2, average_recall: double
                    child 3, precision_at_iou50: double
                    child 4, recall_at_iou50: double
              schema_version: int64
              split: string
              status: string
              to
              {'bbox': List(Value('float64')), 'category_id': Value('int64'), 'image_id': Value('int64'), 'score': 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 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 1683, 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 1869, 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.

bbox
list
category_id
int64
image_id
int64
score
float64
[ 410.5934753418, 735.0858154297, 147.0757141113, 160.4830932617 ]
2
1
0.430021
[ 411.5989074707, 735.6245727539, 145.5629577637, 157.8504638672 ]
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1
0.125997
[ 410.5934753418, 735.0858154297, 147.0757141113, 160.4830932617 ]
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1
0.06921
[ 324.6505126953, 660.2752685547, 59.0144958496, 168.8017578125 ]
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1
0.063215
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0.057117
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0.055951
[ 410.7706604004, 734.8217773438, 67.185760498, 63.9375 ]
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0.044059
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0.041683
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0.04104
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0.040547
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1
0.036587
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0.034474
[ 342.3157653809, 656.7295532227, 31.9537963867, 90.7788085938 ]
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1
0.030883
[ 329.4143371582, 724.2636108398, 46.7898254395, 60.0303955078 ]
2
1
0.030019
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2
1
0.029784
[ 436.8319702148, 738.6698608398, 46.406463623, 54.2283935547 ]
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1
0.029417
[ 7.6430954933, 3.840328455, 232.0942854881, 96.7903935909 ]
2
1
0.029165
[ 17.9515209198, 229.8982086182, 233.4138660431, 89.3694610596 ]
2
1
0.029115
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2
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0.028844
[ 10.0208950043, 3.2944345474, 374.1603183746, 75.5591344833 ]
2
1
0.027486
[ 436.8319702148, 738.6698608398, 46.406463623, 54.2283935547 ]
1
1
0.026786
[ 30.1094512939, 78.1282348633, 113.5916290283, 82.8174591064 ]
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0.026645
[ 348.6159362793, 574.2528686523, 153.7503356934, 209.2711791992 ]
2
1
0.02622
[ 13.5080833435, 53.2241477966, 110.3873939514, 139.4933815002 ]
2
1
0.026078
[ 12.5229854584, 241.0639801025, 156.202173233, 111.9283294678 ]
2
1
0.025849
[ 13.1817264557, 20.5846652985, 327.1975765228, 217.3515377045 ]
2
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0.025479
[ 27.3180675507, 119.9690322876, 272.1301746368, 123.8641586304 ]
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0.025434
[ 410.7706604004, 734.8217773438, 67.185760498, 63.9375 ]
1
1
0.025218
[ 11.7621269226, 76.1944198608, 232.8634223938, 185.6161270142 ]
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0.025018
[ 8.6720151901, 35.1549072266, 183.2616090775, 136.8511199951 ]
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0.024878
[ 100.9502182007, 578.3905639648, 262.1519851685, 225.2442016602 ]
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0.02485
[ 50.732925415, 178.9032440186, 96.6781768799, 196.7624969482 ]
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0.024331
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0.024018
[ 27.409072876, 182.5302886963, 326.8101654053, 169.2497711182 ]
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0.023842
[ 329.4143371582, 724.2636108398, 46.7898254395, 60.0303955078 ]
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0.023641
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0.023635
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0.01789
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