Datasets:

---

mairon2300

/

video_retrieval

Like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
label_id: string
display_name: string
definition: string
layers: list<item: string>
  child 0, item: string
label_level: string
entities: list<item: string>
  child 0, item: string
observed_facts: int64
trusted_facts: int64
legacy_flat_key: string
effective_labels: list<item: struct<label_id: string, layer: string, entity: string>>
  child 0, item: struct<label_id: string, layer: string, entity: string>
      child 0, label_id: string
      child 1, layer: string
      child 2, entity: string
image_rel_path: string
schema_version: string
provenance: struct<literal_source: string, effective_source: string, ontology_hash: string>
  child 0, literal_source: string
  child 1, effective_source: string
  child 2, ontology_hash: string
policy: struct<eval_include: bool, exclude_reasons: list<item: string>, is_elevated_camera: bool, policy_ver (... 13 chars omitted)
  child 0, eval_include: bool
  child 1, exclude_reasons: list<item: string>
      child 0, item: string
  child 2, is_elevated_camera: bool
  child 3, policy_version: string
flags: list<item: string>
  child 0, item: string
allowed_labels: list<item: struct<label_id: string, layer: string, entity: string>>
  child 0, item: struct<label_id: string, layer: string, entity: string>
      child 0, label_id: string
      child 1, layer: string
      child 2, entity: string
image_id: string
coverage: struct<camera_position: string, scene_location: string, time_of_day: string, weather_conditions: str (... 164 chars omitted)
  child 0, camera_position: string
  child 1, scene_location: string
  child 2, time_of_day: string
  child 3, weather_conditions: string
  child 4, image_quality: string
  child 5, road_situation: string
  child 6, other_features: string
  child 7, city_infrastructure_objects: string
  child 8, common_city_buildings: string
  child 9, indoor_type: string
to
{'schema_version': Value('string'), 'image_id': Value('string'), 'image_rel_path': Value('string'), 'legacy_flat_key': Value('string'), 'allowed_labels': List({'label_id': Value('string'), 'layer': Value('string'), 'entity': Value('string')}), 'effective_labels': List({'label_id': Value('string'), 'layer': Value('string'), 'entity': Value('string')}), 'coverage': {'camera_position': Value('string'), 'scene_location': Value('string'), 'time_of_day': Value('string'), 'weather_conditions': Value('string'), 'image_quality': Value('string'), 'road_situation': Value('string'), 'other_features': Value('string'), 'city_infrastructure_objects': Value('string'), 'common_city_buildings': Value('string'), 'indoor_type': Value('string')}, 'flags': List(Value('string')), 'policy': {'eval_include': Value('bool'), 'exclude_reasons': List(Value('string')), 'is_elevated_camera': Value('bool'), 'policy_version': Value('string')}, 'provenance': {'literal_source': Value('string'), 'effective_source': Value('string'), 'ontology_hash': Value('string')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              label_id: string
              display_name: string
              definition: string
              layers: list<item: string>
                child 0, item: string
              label_level: string
              entities: list<item: string>
                child 0, item: string
              observed_facts: int64
              trusted_facts: int64
              legacy_flat_key: string
              effective_labels: list<item: struct<label_id: string, layer: string, entity: string>>
                child 0, item: struct<label_id: string, layer: string, entity: string>
                    child 0, label_id: string
                    child 1, layer: string
                    child 2, entity: string
              image_rel_path: string
              schema_version: string
              provenance: struct<literal_source: string, effective_source: string, ontology_hash: string>
                child 0, literal_source: string
                child 1, effective_source: string
                child 2, ontology_hash: string
              policy: struct<eval_include: bool, exclude_reasons: list<item: string>, is_elevated_camera: bool, policy_ver (... 13 chars omitted)
                child 0, eval_include: bool
                child 1, exclude_reasons: list<item: string>
                    child 0, item: string
                child 2, is_elevated_camera: bool
                child 3, policy_version: string
              flags: list<item: string>
                child 0, item: string
              allowed_labels: list<item: struct<label_id: string, layer: string, entity: string>>
                child 0, item: struct<label_id: string, layer: string, entity: string>
                    child 0, label_id: string
                    child 1, layer: string
                    child 2, entity: string
              image_id: string
              coverage: struct<camera_position: string, scene_location: string, time_of_day: string, weather_conditions: str (... 164 chars omitted)
                child 0, camera_position: string
                child 1, scene_location: string
                child 2, time_of_day: string
                child 3, weather_conditions: string
                child 4, image_quality: string
                child 5, road_situation: string
                child 6, other_features: string
                child 7, city_infrastructure_objects: string
                child 8, common_city_buildings: string
                child 9, indoor_type: string
              to
              {'schema_version': Value('string'), 'image_id': Value('string'), 'image_rel_path': Value('string'), 'legacy_flat_key': Value('string'), 'allowed_labels': List({'label_id': Value('string'), 'layer': Value('string'), 'entity': Value('string')}), 'effective_labels': List({'label_id': Value('string'), 'layer': Value('string'), 'entity': Value('string')}), 'coverage': {'camera_position': Value('string'), 'scene_location': Value('string'), 'time_of_day': Value('string'), 'weather_conditions': Value('string'), 'image_quality': Value('string'), 'road_situation': Value('string'), 'other_features': Value('string'), 'city_infrastructure_objects': Value('string'), 'common_city_buildings': Value('string'), 'indoor_type': Value('string')}, 'flags': List(Value('string')), 'policy': {'eval_include': Value('bool'), 'exclude_reasons': List(Value('string')), 'is_elevated_camera': Value('bool'), 'policy_version': Value('string')}, 'provenance': {'literal_source': Value('string'), 'effective_source': Value('string'), 'ontology_hash': Value('string')}}
              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 1694, 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 1880, 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