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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'flags' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'flags' with no child field to Parquet. Consider adding a dummy child field.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1886, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'flags' 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 1420, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1052, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, 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.
version string | flags dict | shapes list | imagePath string | imageData null | imageHeight int64 | imageWidth int64 |
|---|---|---|---|---|---|---|
5.1.1 | {} | [
{
"label": "straight-6",
"points": [
[
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],
[
296.3207,
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],
[
337.1603,
819.732
],
[
429.2677,
668.0417
],
[
429.2667,
653.0458
],
[
... | 000000000001.jpg | null | 1,920 | 2,160 |
5.1.1 | {} | [
{
"label": "straight-5",
"points": [
[
2160,
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],
[
2160,
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],
[
2127.3016,
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],
[
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],
[
2160,
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],
[
2160,
... | 000000000002.jpg | null | 1,647 | 2,160 |
4.5.9 | {} | [
{
"label": "straight-9",
"points": [
[
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[
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[
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[
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]
],
"group_id": null,
"shape_type": "polygon",
... | 000000000003.jpg | null | 1,264 | 1,976 |
5.1.1 | {} | [
{
"label": "straight-5",
"points": [
[
0,
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],
[
200.0646,
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],
[
364.0666,
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[
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],
[
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],
[
107... | 000000000004.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-12",
"points": [
[
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],
[
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],
[
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],
[
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]
],
"group_id": null,
"shape_type": "polygon",
"fla... | 000000000005.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-10",
"points": [
[
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],
[
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],
[
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],
[
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]
],
"group_id": null,
"shape_type": "polygon",
"flags":... | 000000000006.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-10",
"points": [
[
646.7067,
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],
[
651.8011,
158.9012
],
[
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],
[
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]
],
"group_id": null,
"shape_type": "polygon",
"flags... | 000000000007.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-10",
"points": [
[
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],
[
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],
[
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],
[
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]
],
"group_id": null,
"shape_type": "polygon",
"flags"... | 000000000008.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-13",
"points": [
[
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],
[
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],
[
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],
[
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]
],
"group_id": null,
"shape_type": "polygon",
"flags": {}
},
{... | 000000000009.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-12",
"points": [
[
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],
[
667.7638,
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],
[
667.6423,
190.6435
],
[
748.2859,
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],
[
847.5233,
189.8016
],
[
... | 000000000010.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-15",
"points": [
[
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],
[
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],
[
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],
[
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],
[
1715.7028,
491.3092
],
... | 000000000011.jpg | null | 1,080 | 1,920 |
5.1.1 | {} | [
{
"label": "straight-7",
"points": [
[
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],
[
1358.3048,
224.0383
],
[
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],
[
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],
[
1813.0174,
250.4841
],
[
... | 000000000012.jpg | null | 1,647 | 2,160 |
5.1.1 | {} | [
{
"label": "straight-7",
"points": [
[
0,
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],
[
140.1877,
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],
[
236.6958,
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],
[
256.4692,
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],
[
254.1124,
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],
[
24... | 000000000013.jpg | null | 2,169 | 2,160 |
End of preview.
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)
ROI-1555: Rebar Detection and Instance Segmentation Dataset
- ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
- Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
- Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python labelme2coco_instance.py
#Annotation instances_train2017.json(MSCOCO 2017 format) will be generated in tools/annotations
Paper
Deep Learning-based Rebar Detection and Instance Segmentation in Images
Tao Sun,
Qipei Fan,
Yi Shao*
Advanced Engineering Informatics
If you use the dataset in your work, please cite our paper:
@article{sun2025deep,
title={Deep learning-based rebar detection and instance segmentation in images},
author={Sun, Tao and Fan, Qipei and Shao, Yi},
journal={Advanced Engineering Informatics},
volume={65},
pages={103224},
year={2025},
publisher={Elsevier}
}
Highlights
Mask2Former trained on our dataset shows good generalization ability in unseen data
Benchmark test shows the performance and limitations of the popular networks
Six data augmentation strategies were introduced and tested to improve the SOTA method, which can guide the selection of suitable data augmentation strategies for rebar perception.
| Methods | Epochs | mAP | mAP50 | mAP75 | mAPstraight | mAPhoop |
|---|---|---|---|---|---|---|
| Without additional data augmentation | 178 | 68.6 | 93.6 | 79.9 | 76.0 | 61.1 |
| With Random Vertical-Flip | 178 | 60.1 | 91.7 | 65.8 | 70.1 | 50.1 |
| With Random Rotation | 178 | 66.9 | 94.4 | 77.6 | 75.1 | 58.8 |
| With Mosaic | 178 | 54.1 | 85.6 | 58.7 | 61.4 | 46.8 |
| With MixUp | 356 | 64.0 | 94.1 | 71.8 | 72.6 | 55.4 |
| With Cutout | 356 | 70.2 | 94.2 | 81.9 | 77.5 | 62.8 |
| With Simple Copy-Paste | 718 | 71.4 | 93.9 | 84.7 | 78.5 | 64.3 |
Contact
If you have any questions on the dataset, please email tao.sun@mail.mcgill.ca.
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