Datasets:
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: IndexError
Message: list index out of range
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1859, in _prepare_split_single
original_shard_lengths[original_shard_id] += len(table)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
IndexError: list index out of range
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 1694, 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 1880, 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.
text string |
|---|
0 0.329821 0.567692 0.080084 0.381538 |
0 0.801471 0.282020 0.108824 0.426108 |
0 0.575446 0.807576 0.119342 0.351515 |
0 0.669558 0.272727 0.089905 0.345083 |
0 0.461656 0.628037 0.763804 0.654206 |
0 0.367708 0.695030 0.339583 0.537651 |
0 0.517514 0.588305 0.103955 0.618138 |
0 0.594872 0.699859 0.273504 0.572034 |
0 0.475728 0.295283 0.158576 0.469811 |
0 0.409444 0.739917 0.130000 0.358832 |
0 0.402439 0.317073 0.075388 0.257840 |
0 0.253425 0.374611 0.181507 0.559190 |
0 0.799194 0.395763 0.162903 0.211864 |
0 0.234332 0.457612 0.351499 0.849481 |
0 0.079646 0.444828 0.074336 0.217241 |
0 0.615196 0.237520 0.155229 0.433172 |
0 0.381313 0.691412 0.171717 0.442504 |
0 0.265741 0.831433 0.142593 0.268730 |
0 0.646833 0.395543 0.080614 0.225627 |
0 0.621981 0.677083 0.570048 0.635417 |
0 0.194615 0.258648 0.072308 0.272013 |
0 0.165746 0.732117 0.180479 0.483212 |
0 0.733755 0.360775 0.048736 0.266344 |
0 0.926806 0.563158 0.055133 0.160902 |
0 0.208333 0.720445 0.285556 0.417246 |
0 0.314897 0.506466 0.284661 0.573276 |
0 0.223926 0.477690 0.198364 0.834646 |
0 0.638333 0.659944 0.061111 0.251739 |
0 0.678025 0.497368 0.221140 1.000000 |
0 0.776393 0.318750 0.142229 0.334375 |
0 0.879507 0.763602 0.138520 0.457786 |
0 0.598396 0.476522 0.069519 0.302609 |
0 0.744763 0.277890 0.131202 0.555781 |
0 0.845886 0.450317 0.122827 0.735729 |
0 0.135155 0.383142 1.000000 1.000000 |
0 0.856150 0.560000 0.167914 0.643478 |
0 0.498420 0.479564 0.244866 1.000000 |
0 0.310300 0.186469 0.052151 0.178218 |
0 0.278986 0.496222 0.140097 0.987406 |
0 0.161466 0.335180 0.141966 0.592798 |
0 0.662162 0.475560 0.549550 0.788187 |
0 0.593947 0.528017 0.080706 0.308908 |
0 0.746344 0.808402 0.034871 0.256148 |
0 0.811198 0.640212 0.039062 0.197531 |
0 0.493056 0.598517 0.195707 0.413136 |
0 0.192835 0.262915 0.031612 0.193727 |
0 0.401887 0.526258 0.324528 0.925602 |
0 0.101613 0.844068 0.103226 0.277966 |
0 0.498805 0.729873 0.041816 0.247881 |
0 0.838129 0.683453 0.089928 0.256115 |
0 0.512970 0.518548 0.216602 0.508065 |
0 0.356925 0.572967 0.220700 0.720096 |
0 0.815847 0.459155 0.335519 0.256338 |
0 0.491924 0.466615 0.784141 0.386646 |
0 0.212466 0.511544 0.167560 0.336219 |
0 0.391351 0.706633 0.075676 0.540816 |
0 0.000000 0.441007 1.000000 0.758273 |
0 0.190949 0.661098 0.260486 0.429594 |
0 0.964286 0.588636 0.038690 0.140909 |
0 0.460317 0.466507 0.180952 0.913876 |
0 0.834633 0.515235 0.258970 0.775623 |
0 0.380749 0.126957 0.057754 0.233043 |
0 0.630378 0.452970 0.118644 0.371287 |
0 0.363057 0.393039 0.181529 0.578947 |
0 0.380137 0.890187 0.058219 0.138629 |
0 0.571201 0.506144 0.517535 0.360983 |
0 0.596175 0.442928 0.051744 0.454094 |
0 0.513843 0.673585 0.578073 0.505660 |
0 0.122832 0.466265 0.190751 0.715663 |
0 0.842803 0.451237 0.246212 0.579330 |
0 0.523148 0.331433 0.483333 0.330619 |
0 0.419492 0.464639 1.000000 0.790665 |
0 0.757867 0.478261 0.201049 0.757033 |
0 0.624230 0.664820 0.114990 0.470914 |
0 0.930631 0.226069 0.081081 0.297352 |
0 0.856072 0.766154 0.140930 0.421538 |
0 0.194795 0.493409 0.108833 0.338983 |
0 0.669791 0.494318 0.100331 0.534091 |
0 0.642764 0.289238 0.067797 0.303438 |
0 0.751488 0.164483 0.086310 0.273654 |
0 0.877968 0.730900 0.104222 0.456706 |
0 0.911842 0.612573 0.047368 0.116959 |
0 0.329801 0.470067 0.140397 0.749446 |
0 0.602313 0.469159 0.528470 0.527103 |
0 0.391419 0.731423 0.047669 0.350318 |
0 0.125132 0.660745 0.055966 0.252115 |
0 0.907002 0.510499 0.146608 0.968504 |
0 0.128389 0.385653 0.164274 0.362216 |
0 0.705357 0.778912 0.128571 0.387755 |
0 0.401252 0.484416 0.666203 0.636364 |
0 0.419458 0.435369 0.430622 0.384943 |
0 0.719637 0.298405 0.061294 0.492027 |
0 0.475904 0.455208 0.041499 0.256250 |
0 0.666120 0.642254 0.180328 0.647887 |
0 0.402597 0.556579 0.307359 0.781579 |
0 0.193584 0.851415 0.084071 0.234277 |
0 0.779241 0.377306 0.152792 0.710332 |
0 0.835075 0.798544 0.144776 0.334951 |
0 0.192724 0.484586 0.178019 0.718690 |
0 0.584142 0.841986 0.055016 0.288939 |
End of preview.
Microduck Detection Dataset
Single-class object detection dataset (class 0 = microduck, the 25 cm biped robot duck announced by Pollen Robotics / Hugging Face on 2026-08-27) in YOLO format, built to train a tiny (<5M param) detector.
Composition
- Synthetic scene renders (train ~1,040 / val ~60): the robot from the open-source MuJoCo model in
pollen-robotics/microduck_rl(full visual-mesh model,scene_allcollisions.xml), rendered headlessly with randomized pose (STAND/SIT/FOLD keyframes + joint noise + yaw), all four official colorways (Cream/Graphite/Lavender/Sky), camera distance/azimuth/elevation/FOV, lighting and floor color. Boxes are exact, obtained by projecting all 140 robot-body geom meshes into the camera. - Synthetic composites (train ~655 / val ~45): the robot cutout (segmented by a robotless render diff, feathered edges) pasted onto ~220 CC0 background photos (picsum.photos) with random scale, position, flip, brightness, 12% occlusion rectangles. Boxes are pixel-exact from the pasted alpha mask.
- Synthetic negatives (train ~225 / val ~20): empty floor renders and background-only images with empty labels.
- Real press-kit photos (8 train, 4 val): 13 official launch photos from the Pollen Robotics microduck press kit, pre-labeled by an ensemble of two zero-shot detectors (OWLv2 ∩ Grounding DINO, IoU≥0.35 agreement), threshold ≥0.4 (team photo keeps 2 boxes at ≥0.25 — it shows two robots). Train real photos are duplicated 15x to balance against the synthetic majority.
microduck-skate.jpghad no confident box and is excluded from labels (kept for qualitative checks).
Splits
| split | images |
|---|---|
| train | 2,048 |
| val | 134 |
Files
images/{train,val}/*.jpg,labels/{train,val}/*.txt(YOLO:class cx cy w h, normalized)data.yaml,gen_meta.json(per-sample generation parameters)
Caveats
- Synthetic robot appearance comes from the open-source MuJoCo mesh model; real-photo coverage is only the 13 press photos, so expect the remaining gap to be real-world variation.
- Zero-shot labels on the 4 real val images are model-ensemble-verified but not human-verified; treat real-photo mAP as approximate.
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