Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError Exception: ArrowInvalid Message: Schema at index 1 was different: _id: struct<$oid: string> name: string slug: string version: string created_at: struct<$date: string> last_modified_at: struct<$date: string> last_loaded_at: struct<$date: string> sample_collection_name: string persistent: bool media_type: string group_media_types: struct<> tags: list<item: null> info: struct<categories: list<item: struct<supercategory: string, id: int64, name: string>>> app_config: struct<dynamic_groups_target_frame_rate: int64, grid_media_field: string, media_fallback: bool, media_fields: list<item: string>, modal_media_field: string, plugins: struct<>> classes: struct<> default_classes: list<item: string> mask_targets: struct<> default_mask_targets: struct<> skeletons: struct<> sample_fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: null>, db_field: string, description: null, info: null, read_only: bool, created_at: null>>, db_field: string, description: null, info: null, read_only: bool, created_at: struct<$date: string>>>, db_field: string, description: null, info: null, read_only: bool, created_at: struct<$date: string>>> frame_fields: list<item: null> saved_views: list<item: null> workspaces: list<item: null> annotation_runs: struct<> brain_methods: struct<> evaluations: struct<> runs: struct<> vs samples: list<item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: string>, metadata: struct<_cls: string, width: int64, height: int64>, _media_type: string, _rand: double, categories: struct<_cls: string, detections: list<item: struct<_id: struct<$oid: string>, _cls: string, attributes: struct<>, tags: list<item: null>, label: string, bounding_box: list<item: double>, supercategory: string, iscrowd: int64, ignore: int64>>>, _dataset_id: struct<$oid: string>, created_at: struct<$date: string>, last_modified_at: struct<$date: string>>> Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response iterable_dataset = iterable_dataset._resolve_features() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3335, in _resolve_features features = _infer_features_from_batch(self.with_format(None)._head()) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2096, in _head return next(iter(self.iter(batch_size=n))) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2296, in iter for key, example in iterator: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__ for key, pa_table in self._iter_arrow(): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow yield from self.ex_iterable._iter_arrow() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow yield new_key, pa.Table.from_batches(chunks_buffer) File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: Schema at index 1 was different: _id: struct<$oid: string> name: string slug: string version: string created_at: struct<$date: string> last_modified_at: struct<$date: string> last_loaded_at: struct<$date: string> sample_collection_name: string persistent: bool media_type: string group_media_types: struct<> tags: list<item: null> info: struct<categories: list<item: struct<supercategory: string, id: int64, name: string>>> app_config: struct<dynamic_groups_target_frame_rate: int64, grid_media_field: string, media_fallback: bool, media_fields: list<item: string>, modal_media_field: string, plugins: struct<>> classes: struct<> default_classes: list<item: string> mask_targets: struct<> default_mask_targets: struct<> skeletons: struct<> sample_fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: null>, db_field: string, description: null, info: null, read_only: bool, created_at: null>>, db_field: string, description: null, info: null, read_only: bool, created_at: struct<$date: string>>>, db_field: string, description: null, info: null, read_only: bool, created_at: struct<$date: string>>> frame_fields: list<item: null> saved_views: list<item: null> workspaces: list<item: null> annotation_runs: struct<> brain_methods: struct<> evaluations: struct<> runs: struct<> vs samples: list<item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: string>, metadata: struct<_cls: string, width: int64, height: int64>, _media_type: string, _rand: double, categories: struct<_cls: string, detections: list<item: struct<_id: struct<$oid: string>, _cls: string, attributes: struct<>, tags: list<item: null>, label: string, bounding_box: list<item: double>, supercategory: string, iscrowd: int64, ignore: int64>>>, _dataset_id: struct<$oid: string>, created_at: struct<$date: string>, last_modified_at: struct<$date: string>>>
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.
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