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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 1405, 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 982, 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 datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
png image | json dict | __key__ string | __url__ string |
|---|---|---|---|
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"confidence_scores": null,
"content": "P(A|B) = \\frac{P(A \\cap B)}{P(B)}",
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"top_left_x": 40,
"top_left_y": 46,
"type": "text",
"table_id": null
},
{
"bottom_right... | sample_0000000 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"type": "image",
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{
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"bo... | sample_0000001 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"content": "مجموعة الأداء للاستثمار الصناعي",
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"top_left_y": 10,
"type": "header",
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},
{
"bottom_right_x... | sample_0000002 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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"content": "فرضيات البحث والمتغيرات المعتمدة",
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"type": "title",
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},
{
"bottom_right_x... | sample_0000003 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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"content": "الرؤية المستقبلية وخارطة الطريق",
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"type": "title",
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},
{
"bottom_right_x"... | sample_0000004 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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"content": "التربية المعاصرة وبناء المناهج",
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"top_left_x": 30,
"top_left_y": 30,
"type": "text",
"table_id": null
},
{
"bottom_right_x": 7... | sample_0000005 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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{
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"content": "شركة العزم للنقل والشحن",
"reading_index": 1,
"top_left_x": 544,
"top_left_y": 11,
"type": "header",
"table_id": null
},
{
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... | sample_0000006 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
"blocks": [
{
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"confidence_scores": null,
"content": "منهجية البحث وأدوات جمع البيانات",
"reading_index": 1,
"top_left_x": 40,
"top_left_y": 40,
"type": "title",
"table_id": null
},
{
"bottom_right_x... | sample_0000007 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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{
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"confidence_scores": null,
"content": "هشام بن عمر الطيب",
"reading_index": 1,
"top_left_x": 202,
"top_left_y": 751,
"type": "text",
"table_id": null
}
],
"confidence_scores": {
"average... | sample_0000008 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"content": "المنظور المقارن وأفضل الممارسات",
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"type": "title",
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"bottom_right_x"... | sample_0000009 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"bott... | sample_0000010 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"bo... | sample_0000011 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"bottom_righ... | sample_0000012 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"bottom_right_x": ... | sample_0000013 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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{
"bottom_right_x": 70... | sample_0000014 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
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"bottom_right_x... | sample_0000015 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
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"content": "مجموعة الشروق للصناعة والتجارة",
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"top_left_x": 10,
"top_left_y": 14,
"type": "text",
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{
"bottom_right_x": 2... | sample_0000016 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar | |
{
"blocks": [
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"confidence_scores": null,
"content": "أهداف الدراسة وأهميتها العلمية",
"reading_index": 1,
"top_left_x": 36,
"top_left_y": 36,
"type": "title",
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{
"bottom_right_x":... | sample_0000017 | hf://datasets/OCR-Data/ocr_data@1750d66eabba8f1dba796cd8253e1050aa749b3a/data/Zetati_001.tar |
End of preview.
ocr_data
Synthetic Arabic document images with layout annotations, for OCR training.
Layout
WebDataset .tar shards. Files sharing a basename are one sample, so the
image becomes the image column and the annotation the json column.
data/<contributor>_<NNN>.tar originals (PNG + JSON)
data_aug/<contributor>_<NNN>_aug<K>.tar augmented variants (JPEG/PNG + JSON)
Each shard holds up to 9990 samples (~1.2 GB). data/ and data_aug/
are separate so you can train on clean originals alone.
Loading
from datasets import load_dataset
# one shard
ds = load_dataset("webdataset",
data_files="hf://datasets/OCR-Data/ocr_data/data/<contributor>_001.tar",
split="train", streaming=True)
# a range of shards
ds = load_dataset("webdataset",
data_files="hf://datasets/OCR-Data/ocr_data/data/<contributor>_{001..010}.tar",
split="train", streaming=True)
# everything, originals + augmented
ds = load_dataset("webdataset", data_files={"train": [
"hf://datasets/OCR-Data/ocr_data/data/*.tar",
"hf://datasets/OCR-Data/ocr_data/data_aug/*.tar"]},
split="train", streaming=True)
To get loose files back, use unpack_shard.py from the generator repo.
Annotation schema
{
"dimensions": {"width": 0, "height": 0},
"blocks": [{"type": "...", "text": "...", "top_left_x": 0, "top_left_y": 0,
"bottom_right_x": 0, "bottom_right_y": 0, "reading_index": 0}],
"images": [{"top_left_x": 0, "...": 0}],
"meta": {"template": "...", "hybrid": null, "page_font": "...",
"language": "ar", "script": "arabic", "direction": "rtl",
"augmentation": null}
}
meta.augmentation is null for originals and
{"name": ..., "params": {...}} for augmented variants.
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