The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 257, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/summary/overall/top1_label_counts/[]/[]) changed from string to number in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 271, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Stage2 Exp0 ckpt50 synthetic SD302A 500x10
This dataset contains synthetic rolled fingerprint images generated with the Stage-2 Exp0 ControlNet checkpoint at step 50k. The images are arranged in an SD302A-compatible folder structure:
images/challengers/<SENSOR>/roll/png/<ID>_<SENSOR>_roll_<IMPRESSION>.png
Contents
images/challengers/: 5,000 synthetic PNG images.manifest.json: dataset counts by sensor.selection/selection.csv: source real condition image selected for each synthetic sample.selection/selection_summary.json: label quotas and eligible-label counts.resnet50_real_sd302a_val_eval/: classifier and verification evaluation outputs.
Generation Setup
- Generator: Stage-2 Exp0 self-condition ControlNet.
- Checkpoint:
core_exp0_self_condition_unetinit_bs256_50k/step_0050000. - Base UNet: official IMPOSE Stage-1 UNet.
- DDIM steps: 50.
- Control scale: 1.0.
- Conditions: Sauvola ridge/control maps from SD302A roll images.
- Selection seed: 20260609.
Dataset Size
- Labels: 500 fingers.
- Impressions per label: 10.
- Images: 5,000.
Sensor label counts:
| Sensor | Labels | Images |
|---|---|---|
| A | 69 | 690 |
| B | 69 | 690 |
| C | 69 | 690 |
| D | 68 | 680 |
| E | 68 | 680 |
| F | 68 | 680 |
| G | 68 | 680 |
| H | 21 | 210 |
Sensor H has fewer labels because only 21 SD302A H labels have at least 10 roll impressions.
Evaluation Snapshot
A ResNet50 ArcFace/CosFace classifier was trained on this synthetic dataset with the same paperlike setting used for the SD302A real-data classifier:
- image size: 224
- embedding dim: 512
- epochs: 200
- batch size: 128
- loss: CosFace,
s=64,m=0.35 - augmentation: enabled
- identity mode:
finger
Real SD302A held-out validation split, filtered to these 500 labels:
- Images: 1,000 real images.
- Top1: 0.601.
- Top5: 0.808.
- Verification EER: 0.088.
- TAR@FAR 1%: 0.496.
- TAR@FAR 0.1%: 0.180.
For comparison, the real-data-trained classifier evaluated on the same 500 labels gives EER 0.122, TAR@FAR 1% 0.488, TAR@FAR 0.1% 0.198.
Notes
This dataset is intended for internal research experiments on synthetic fingerprint data utility. Check the applicable NIST SD302A terms and local biometrics data handling requirements before redistribution or downstream use.
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