HanDrawer: Leveraging Spatial Information to Render Realistic Hands Using a Conditional Diffusion Model in Single Stage
Paper • 2503.02127 • Published
Datasets:
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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 1520, 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 130, 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 34, 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 1382, 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 1560, 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.
json dict | full_rgb.png imagewidth (px) 512 512 | full_depth.png imagewidth (px) 512 512 | hand_rgb.png imagewidth (px) 225 225 | hand_depth.png imagewidth (px) 225 225 | hand_bbox.json dict | hand_depth_bbox.json dict | vertices.json dict | mesh_front.png imagewidth (px) 512 512 | mesh_back.png imagewidth (px) 512 512 | mesh_left.png imagewidth (px) 512 512 | mesh_right.png imagewidth (px) 512 512 | mesh_top.png imagewidth (px) 512 512 | mesh_bottom.png imagewidth (px) 512 512 | six_view_bbox_front.json dict | six_view_bbox_back.json dict | six_view_bbox_left.json dict | six_view_bbox_right.json dict | six_view_bbox_top.json dict | six_view_bbox_bottom.json dict | extra_view_image_primary.png imagewidth (px) 512 512 | extra_view_image_complementary.png imagewidth (px) 512 512 | extra_view_bbox_primary.json dict | extra_view_bbox_complementary.json dict | __key__ stringlengths 35 35 | __url__ stringclasses 6
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
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"mesh_back",
"mesh_left",
"mesh_right",
"mesh_top",
"mesh_bottom",
"six_view_bbox_front",
"six_view_bbox_back",
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} | dexycb_test_000001_processed_000001 | hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-test-000000.tar | ||||||||||||
{
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} | dexycb_test_000002_processed_000002 | hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-test-000000.tar | ||||||||||||
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} | dexycb_test_000003_processed_000002 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) | ||||||||||||
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} | dexycb_test_000004_processed_000002 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) | ||||||||||||
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} | dexycb_test_000007_processed_000002 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) | ||||||||||||
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} | dexycb_test_000008_processed_000001 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) | ||||||||||||
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} | dexycb_test_000009_processed_000002 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) | ||||||||||||
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} | {"bbox":[14.706302642822266,1.8804473876953125,347.008056640625,81.1260986328125],"vertices_local":[(...TRUNCATED) | {
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} | dexycb_test_000011_processed_000002 | "hf://datasets/QFun/MANUS-DexYCB@fa1790884ff4591f97cc5f3acb4ac324c95c5031/data/dexycb/test/dexycb-te(...TRUNCATED) |
End of preview.
MANUS-DexYCB: DexYCB-derived Multimodal Annotated Naturalistic Hand Understanding Dataset
MANUS-DexYCB is the DexYCB-derived subset of the Multimodal Annotated Naturalistic Hand Understanding (MANUS) dataset family. It is released as a source-specific repository because MANUS subsets are governed by different upstream licenses.
This repository contains only the DexYCB-derived MANUS test split. HaGRID/HaGRIDv2-derived data is released separately as MANUS-HaGRID.
Dataset Features in This Release
MANUS-DexYCB provides the following modalities where available:
- full-scene RGB image;
- full-scene depth map;
- hand-region RGB crop;
- hand-region depth map;
- 2D bounding boxes for hand regions;
- estimated MANO-style hand mesh annotations or related mesh metadata;
- rendered mesh views from six canonical viewpoints: front, rear, left, right, top, and bottom;
- primary and complementary mesh projection views where available;
- companion text prompts describing image content, provided as the split-level prompt file listed below;
- per-sample metadata recording source dataset, source id, split, available modalities, and license metadata.
Text prompts are provided in DexYCB_test_prompt.txt as a companion split-level file.
Configs and Splits
| Config/Split | Samples | WebDataset shards | Size |
|---|---|---|---|
dexycb/test |
7,836 | 7 | 5.58 GB |
The canonical sample count is based on DexYCB_test_OG_image_paths.txt; other modalities are aligned to this OG image list.
Data Format
Data is stored as uncompressed WebDataset tar shards. Files belonging to the same sample share the same prefix:
dexycb_test_000001_processed_000001.json
dexycb_test_000001_processed_000001.full_rgb.png
dexycb_test_000001_processed_000001.full_depth.png
dexycb_test_000001_processed_000001.hand_rgb.png
dexycb_test_000001_processed_000001.hand_depth.png
dexycb_test_000001_processed_000001.hand_bbox.json
dexycb_test_000001_processed_000001.vertices.json
dexycb_test_000001_processed_000001.mesh_front.png
The per-sample .json member records source and license metadata, source id, split, available modalities, and the number of files available for that sample. See docs/data_structure.md and docs/annotation_format.md for details.
Text Prompt Files
The following companion prompt file has been added at the repository root:
| File | Split | Records/Lines | Format | Notes |
|---|---|---|---|---|
DexYCB_test_prompt.txt |
dexycb/test |
7,836 | TXT | One text prompt per line, aligned to the canonical DexYCB test OG image order. |
Prompt files are optional companion annotations and are not packed into the WebDataset shards. Use this file when text conditioning or image-content descriptions are needed.
Metadata Files
metadata/dexycb_manifest.parquetmetadata/dexycb_manifest.csvmetadata/dexycb_manifest.jsonlmetadata/source_licenses.csvmetadata/release_schema.jsonmetadata/release_report.jsonmetadata/checksums.sha256DexYCB_test_prompt.txt
The public manifest files do not contain local absolute source paths. They contain portable source and audit metadata, including sample id, source id, source license, available modalities, and shard path.
Loading
See docs/loading_examples.md.
Source Dataset Reference
This release is derived from DexYCB. Please acknowledge the upstream DexYCB dataset when using MANUS-DexYCB.
@inproceedings{chao2021dexycb,
title={DexYCB: A benchmark for capturing hand grasping of objects},
author={Chao, Yu-Wei and Yang, Wei and Xiang, Yu and Molchanov, Pavlo and Handa, Ankur and Tremblay, Jonathan and Narang, Yashraj S and Van Wyk, Karl and Iqbal, Umar and Birchfield, Stan and others},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={9044--9053},
year={2021}
}
Citation
If you use MANUS-DexYCB, please cite both the MANUS / HanDrawer work and the upstream DexYCB dataset.
MANUS / HanDrawer
@misc{fu2025handrawer,
title = {HanDrawer: Leveraging Spatial Information to Render Realistic Hands Using a Conditional Diffusion Model in Single Stage},
author = {Qifan Fu and Xu Chen and Muhammad Asad and Shanxin Yuan and Changjae Oh and Gregory Slabaugh},
year = {2025},
eprint = {2503.02127},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
doi = {10.48550/arXiv.2503.02127},
url = {https://arxiv.org/abs/2503.02127}
}
DexYCB
Use the DexYCB citation listed in the source dataset reference above.
License
MANUS-DexYCB is derived from DexYCB and is distributed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Commercial use is not permitted unless separately authorized by the DexYCB rights holders.
This repository does not grant any rights beyond those granted by the upstream DexYCB license. Users are responsible for complying with the upstream license, attribution requirements, change notices, and applicable laws.
Intended Uses
MANUS-DexYCB is intended for research on hand-object interaction, hand-aware image generation, 2D/3D hand understanding, depth estimation, and multimodal hand representation learning.
Out-of-Scope Uses
This dataset should not be used for biometric identification, person recognition, surveillance, or privacy-invasive applications.
Privacy and Takedown
MANUS-DexYCB is derived from images of people interacting with objects. Some images may include identifiable visual context. If you are a rights holder or data subject and request removal of a sample, please contact the dataset maintainers through the repository contact channel.
Related MANUS Repositories
- MANUS landing page:
MANUS - MANUS-HaGRID: HaGRID/HaGRIDv2-derived MANUS release
This repository contains only DexYCB-derived data.
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