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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type string to null
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1562, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 783, in finalize
                  self.write_examples_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 655, in write_examples_on_file
                  self._write_batch(batch_examples=batch_examples)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 752, in _write_batch
                  arrays.append(pa.array(typed_sequence))
                                ~~~~~~~~^^^^^^^^^^^^^^^^
                File "pyarrow/array.pxi", line 256, in pyarrow.lib.array
                File "pyarrow/array.pxi", line 118, in pyarrow.lib._handle_arrow_array_protocol
                  res = obj.__arrow_array__(type=type)
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 291, in __arrow_array__
                  out = self._arrow_array(type=type)
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 362, in _arrow_array
                  out = cast_array_to_feature(
                      out, type, allow_primitive_to_str=not self.trying_type, allow_decimal_to_str=not self.trying_type
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
                  return array_cast(
                      array,
                  ...<2 lines>...
                      allow_decimal_to_str=allow_decimal_to_str,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2014, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type string to null
              
              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 1393, 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 1571, 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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input
image
layer
images list
run_id
string
prompt
null
auto_captioned
null
negative_prompt
null
seed
null
steps
null
layer_count
int64
guidance_scale
null
resolution
null
cfg_normalize
null
use_en_prompt
null
model_id
null
seconds
null
timestamp
null
76ead06bf077
null
null
null
null
null
2
null
null
null
null
null
null
null
a504ea39fc77
null
null
null
null
null
2
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null
null
null
43ed89378e26
null
null
null
null
null
2
null
null
null
null
null
null
null
f024be761689
null
null
null
null
null
2
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null
null
null
null
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08b160d9aa37
null
null
null
null
null
2
null
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Mitosis Generations

Every decomposition run of the Mitosis Space is logged here: the input image, the RGBA layers produced from it, and the settings used.

⚠️ Public log

The Space is public and every run is recorded in this public dataset, including images uploaded by visitors. Do not submit anything that cannot be shared publicly.

Layout

data/
  metadata.jsonl          # one JSON object per run
  <run_id>/
    input.png             # exactly what the model saw (RGB(A) normalized, transparency on white)
    layer_1.png .. N.png  # the RGBA layers produced

Each metadata.jsonl line:

Field Meaning
run_id Folder holding this run's images
steps Denoising steps
input_file_name / layer_file_names Paths relative to data/; the viewer turns these into the input and layer image columns
prompt, negative_prompt Text the user typed; prompt is empty when the model captioned the image itself
auto_captioned Whether the prompt was generated by the model
seed, layer_count, guidance_scale, resolution Generation settings (resolution is a target area: 640 or 1024)
cfg_normalize, use_en_prompt Toggles from Advanced Settings
model_id Model that produced the layers
seconds Pipeline runtime
timestamp UTC ISO-8601

Loading

from datasets import load_dataset

ds = load_dataset("Elfsong/mitosis-generations", split="train")
ds[0]["input"]   # PIL image that was decomposed
ds[0]["layer"]   # list of PIL images, one per layer

Layers are produced by Qwen-Image-Layered.

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