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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
                  for key, record 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/webdataset/webdataset.py", line 127, 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 1400, 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 977, 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 786, 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'
              
              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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hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_0439a75ec264a43d88d6a34e
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_0441ed46d07c78b53271eff0
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_0451b8888650f945032d39b9
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_0456323c24d810b6de9f68ff
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_045c020dab89b62cc204ee25
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_045ff86465f27171e2171ef3
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
images/public_dad_0481afec93204aa67d3eed06
hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
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hf://datasets/dad887/DAD-Public-Repro@3bb269530b4012591e7f359dfaf445e6ad0477de/images/test-public_dad-000.tar
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DAD public experiment data

Fixed public-data splits for Detect Anything in Graphic Design: Element-Level Rewards for Autoregressive Detection.

Split Records Image IDs Sources
SFT 90,000 57,083 18,000 records each from DAD, ChartGalaxy, Crello, PrismLayersPro, and LICA
RL 5,000 5,000 Released DAD examples
Test 5,000 5,000 Released DAD examples

The SFT split repeats examples from smaller sources to preserve equal source sampling. repeat_index records these repetitions. This package contains 67,083 composited image files and their detection annotations; the full DAD release contains additional images and layered assets.

Download and use

The inference code downloads only the requested split, verifies archive and image checksums, and extracts images:

python -m inference.predict --variant elerpo --output outputs/elerpo.jsonl

For manual use, download annotations/<split>.jsonl, manifests/images.jsonl, and manifests/shards.json, then fetch the archives whose split matches the requested split. Extract archives into a common dataset directory. Images are losslessly encoded PNGs; archive members use the same relative image paths as the annotations.

annotations/sft.jsonl
annotations/rl.jsonl
annotations/test.jsonl
images/<split>-<source>-<shard>.tar
manifests/images.jsonl
manifests/shards.json
manifests/sources.json

Record format

{
  "id": "test_000000",
  "image_id": "public_dad_<identifier>",
  "image": "images/public_dad_<identifier>.png",
  "source": "public_dad",
  "width": 1000,
  "height": 1000,
  "boxes": [[100, 200, 400, 600]],
  "types": ["visual"],
  "repeat_index": 0
}

The example illustrates the schema, not a specific dataset record. id uniquely identifies a split record; image_id identifies an image and is shared by repeated SFT records. Boxes are pixel-space [x1,y1,x2,y2], paired with text or visual types and stored in annotation order. Source annotation conventions are preserved. The model's [0,1000] coordinates are handled by the inference/evaluation code.

Image metadata has been removed and identifiers standardized. Original image dimensions and decoded RGB pixels are retained. Invalid source boxes were excluded when forming the experiment manifests. The provided split membership and repetitions are fixed.

Sources and licenses

Source Unique SFT images License
DAD 18,000 CC BY 4.0 for the contributed DAD portion of this release
ChartGalaxy 18,000 CC BY-NC 4.0, following the source dataset card metadata
Crello 1,955 CDLA Permissive 2.0
PrismLayersPro 18,000 Apache 2.0
LICA 1,128 CC BY 4.0

See LICENSE.md, source metadata, and the included license texts. Each source retains its own terms; this mixed-source package does not replace them with a single blanket license. Attribute DAD and the original datasets when using their examples.

The corresponding public models and code are released separately.

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