Datasets:

bmmv-9x2q7
/

bmm-vit-datasets

Tags:

computer-vision

reproducibility

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train

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:    CastError
Message:      Couldn't cast
name: string
repo_id: string
contains_raw_images: bool
generated_from: string
files: struct<eurosat_split.csv: struct<sha256: string, rows: int64, counts: struct<train: int64, val: int6 (... 203 chars omitted)
  child 0, eurosat_split.csv: struct<sha256: string, rows: int64, counts: struct<train: int64, val: int64, test: int64>, columns:  (... 36 chars omitted)
      child 0, sha256: string
      child 1, rows: int64
      child 2, counts: struct<train: int64, val: int64, test: int64>
          child 0, train: int64
          child 1, val: int64
          child 2, test: int64
      child 3, columns: list<item: string>
          child 0, item: string
      child 4, purpose: string
  child 1, README.md: struct<sha256: string, bytes: int64, purpose: string>
      child 0, sha256: string
      child 1, bytes: int64
      child 2, purpose: string
  child 2, data_sources.json: struct<sha256: string, bytes: int64, purpose: string>
      child 0, sha256: string
      child 1, bytes: int64
      child 2, purpose: string
datasets: struct<Cars: struct<source: string, processing: string>, DTD: struct<source: string, processing: str (... 316 chars omitted)
  child 0, Cars: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 1, DTD: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 2, EuroSAT: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 3, GTSRB: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 4, MNIST: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 5, RESISC45: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 6, SVHN: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
  child 7, SUN397: struct<source: string, processing: string>
      child 0, source: string
      child 1, processing: string
to
{'contains_raw_images': Value('bool'), 'datasets': {'Cars': {'source': Value('string'), 'processing': Value('string')}, 'DTD': {'source': Value('string'), 'processing': Value('string')}, 'EuroSAT': {'source': Value('string'), 'processing': Value('string')}, 'GTSRB': {'source': Value('string'), 'processing': Value('string')}, 'MNIST': {'source': Value('string'), 'processing': Value('string')}, 'RESISC45': {'source': Value('string'), 'processing': Value('string')}, 'SVHN': {'source': Value('string'), 'processing': Value('string')}, 'SUN397': {'source': Value('string'), 'processing': Value('string')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              name: string
              repo_id: string
              contains_raw_images: bool
              generated_from: string
              files: struct<eurosat_split.csv: struct<sha256: string, rows: int64, counts: struct<train: int64, val: int6 (... 203 chars omitted)
                child 0, eurosat_split.csv: struct<sha256: string, rows: int64, counts: struct<train: int64, val: int64, test: int64>, columns:  (... 36 chars omitted)
                    child 0, sha256: string
                    child 1, rows: int64
                    child 2, counts: struct<train: int64, val: int64, test: int64>
                        child 0, train: int64
                        child 1, val: int64
                        child 2, test: int64
                    child 3, columns: list<item: string>
                        child 0, item: string
                    child 4, purpose: string
                child 1, README.md: struct<sha256: string, bytes: int64, purpose: string>
                    child 0, sha256: string
                    child 1, bytes: int64
                    child 2, purpose: string
                child 2, data_sources.json: struct<sha256: string, bytes: int64, purpose: string>
                    child 0, sha256: string
                    child 1, bytes: int64
                    child 2, purpose: string
              datasets: struct<Cars: struct<source: string, processing: string>, DTD: struct<source: string, processing: str (... 316 chars omitted)
                child 0, Cars: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 1, DTD: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 2, EuroSAT: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 3, GTSRB: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 4, MNIST: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 5, RESISC45: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 6, SVHN: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
                child 7, SUN397: struct<source: string, processing: string>
                    child 0, source: string
                    child 1, processing: string
              to
              {'contains_raw_images': Value('bool'), 'datasets': {'Cars': {'source': Value('string'), 'processing': Value('string')}, 'DTD': {'source': Value('string'), 'processing': Value('string')}, 'EuroSAT': {'source': Value('string'), 'processing': Value('string')}, 'GTSRB': {'source': Value('string'), 'processing': Value('string')}, 'MNIST': {'source': Value('string'), 'processing': Value('string')}, 'RESISC45': {'source': Value('string'), 'processing': Value('string')}, 'SVHN': {'source': Value('string'), 'processing': Value('string')}, 'SUN397': {'source': Value('string'), 'processing': Value('string')}}}
              because column names don't match

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BMM ViT Dataset Specs

This directory contains small metadata files only. It does not contain raw dataset images.

eurosat_split.csv records the EuroSAT 80/10/10 ImageFolder split expected by the ViT-B/32 8-task scripts.
dataset_specs_manifest.json records checksums and row counts.

The same files are mirrored in the anonymous Hugging Face dataset repository:

https://huggingface.co/datasets/bmmv-9x2q7/bmm-vit-datasets

The setup script downloads raw images from public dataset sources, applies these specs when a fixed split is needed, and materializes the local layout under BMM_DATA_ROOT.

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Total file size:

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