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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'preprocessing' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1539, in _prepare_split_single
                  for key, record in generator:
                                     ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 131, in _generate_examples
                  for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
                                              ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  for filename, f in tar_iterator:
                                     ^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
                  for x in self.generator(*self.args):
                           ~~~~~~~~~~~~~~^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1419, in _iter_from_urlpath
                  with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
                       ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 976, in xopen
                  file_obj = fs.open(paths[0], mode)
                File "<string>", line 3, in open
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
                  return self._mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
                  return self._execute_mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
                  result = effect(*args, **kwargs)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 794, in wrapped
                  tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
                                                               ~~~^^^^^^^^
              TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
              
              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 1570, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 835, in finalize
                  self._build_writer(self.schema)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 861, in _build_writer
                  self.pa_writer = pq.ParquetWriter(
                                   ~~~~~~~~~~~~~~~~^
                      self.stream,
                      ^^^^^^^^^^^^
                  ...<3 lines>...
                      **get_parquet_column_options(self._features, self._schema),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 1115, in __init__
                  self.writer = _parquet.ParquetWriter(
                                ~~~~~~~~~~~~~~~~~~~~~~^
                      sink, schema,
                      ^^^^^^^^^^^^^
                  ...<20 lines>...
                      max_rows_per_page=max_rows_per_page,
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      **options)
                      ^^^^^^^^^^
                File "pyarrow/_parquet.pyx", line 2430, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'preprocessing' with no child field to Parquet. Consider adding a dummy child field.
              
              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 1401, 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 1579, 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

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high.mp4
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json
dict
__key__
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hf://datasets/Anna-SY/CineCraft-120K@2b18b33698053f1fe19fa012a48607999db5909b/data/baseline-000000.tar
{ "pair_id": "cc_47478aa6078b669909ac", "canonical_high_key": "10-o/10-Scene-0506_part2.mp4", "sample_id": "10-Scene-0506_part2", "source_group": "10-o", "population": "baseline", "low": { "archive": "baseline/final_output.zip", "member": "final_output/low_cost_video/10-o/10-Scene-0506_part2.mp4", ...
cc_47478aa6078b669909ac
hf://datasets/Anna-SY/CineCraft-120K@2b18b33698053f1fe19fa012a48607999db5909b/data/baseline-000000.tar
{ "pair_id": "cc_7d5e44fa3ed9caf51a1d", "canonical_high_key": "10-o/10-Scene-0508_part1.mp4", "sample_id": "10-Scene-0508_part1", "source_group": "10-o", "population": "baseline", "low": { "archive": "baseline/final_output.zip", "member": "final_output/low_cost_video/10-o/10-Scene-0508_part1.mp4", ...
cc_7d5e44fa3ed9caf51a1d
hf://datasets/Anna-SY/CineCraft-120K@2b18b33698053f1fe19fa012a48607999db5909b/data/baseline-000000.tar
{ "pair_id": "cc_ac2f034e9ba508bb0d3e", "canonical_high_key": "10-o/10-Scene-0508_part2.mp4", "sample_id": "10-Scene-0508_part2", "source_group": "10-o", "population": "baseline", "low": { "archive": "baseline/final_output.zip", "member": "final_output/low_cost_video/10-o/10-Scene-0508_part2.mp4", ...
cc_ac2f034e9ba508bb0d3e
hf://datasets/Anna-SY/CineCraft-120K@2b18b33698053f1fe19fa012a48607999db5909b/data/baseline-000000.tar
End of preview.

CineCraft-120K

This release is being prepared incrementally. It currently contains 30120 pairs in data/. This is not a claim that the entire source collection has been published.

Source inventory

  • Existing paired archive: 102,881 low/high pairs.
  • Additional uniquely matched low videos: 22,020.
  • Unique candidate pairs: 124,901.
  • Duplicate smoke clips held out: 2.

Source revisions and unresolved items are recorded in audit/. Videos are published as their original source bytes without resampling, cropping, resizing, or re-encoding. New low videos have 81 frames at 832x480; their raw high counterparts retain their original frame counts and resolutions.

Contents and validation

data/*.tar contains MP4 pairs joined by source directory and video ID, plus per-pair JSON metadata; metadata/ contains corresponding JSONL records. Source bytes are checked with ZIP CRC or repository SHA256, and every published video receives its own SHA256. ffprobe validates container/stream metadata; a deterministic 1% sample receives a full frame scan. Per-side dimensions, frames, FPS and durations are retained. Frame counts and timing may differ across a pair; temporal_metadata_match records this rather than implying frame alignment. These checks do not constitute a per-example aesthetic rating or proof of per-frame spatial/temporal alignment.

pilot/ is a separate packaging test and must not be combined with data/ as additional unique examples. Dataset splits remain unassigned until the original split mapping is recovered.

Prompts

The original source supplies high-to-low prompts for 102,881 existing pairs. They are stored as prompt_high_to_low. prompt_low_to_high is currently null; reverse instructions are not inferred or relabeled. The additional low-video ZIPs do not include prompt files.

Sources

No new data license is assigned by this preparation process.

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