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Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'in_F', 'bbox_diag_out', 'bbox_ratio', 'app', 'target_V', 'boundary_edges', 'bbox_diag_in', 'in_V', 'out_F', 'out_V', 'reached_target'}) and 14 missing columns ({'#f', 'status', '#v', 'min_length', 'avg_valence', 'target_vertices', 'wall_sec', 'max_length', 'nonmanifold_vertices', 'reason', 'target_length', 'avg_length', 'triangles', 'vertices'}).
This happened while the csv dataset builder was generating data using
hf://datasets/liuyibo/thingi10k-wmtk-simplification/verification/verification_full_qslim_sec_dedup.csv (at revision ea69283703234657aea0b6c24a2e5cf497febaf8), ['hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/qslim.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec_nolink.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_full_qslim_sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_sample1000_qslim_sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_sample1000_qslim_sec_nolink.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: int64
app: string
in_V: int64
in_F: int64
out_V: int64
out_F: int64
target_V: double
reached_target: bool
boundary_edges: int64
nonmanifold_edges: int64
bbox_diag_in: double
bbox_diag_out: double
bbox_ratio: double
time_sec: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1898
to
{'id': Value('int64'), 'status': Value('string'), 'reason': Value('string'), 'wall_sec': Value('float64'), 'time_sec': Value('float64'), 'vertices': Value('float64'), 'triangles': Value('float64'), '#v': Value('float64'), '#f': Value('float64'), 'target_vertices': Value('float64'), 'target_length': Value('float64'), 'avg_length': Value('float64'), 'min_length': Value('float64'), 'max_length': Value('float64'), 'avg_valence': Value('float64'), 'nonmanifold_edges': Value('float64'), 'nonmanifold_vertices': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
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 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'in_F', 'bbox_diag_out', 'bbox_ratio', 'app', 'target_V', 'boundary_edges', 'bbox_diag_in', 'in_V', 'out_F', 'out_V', 'reached_target'}) and 14 missing columns ({'#f', 'status', '#v', 'min_length', 'avg_valence', 'target_vertices', 'wall_sec', 'max_length', 'nonmanifold_vertices', 'reason', 'target_length', 'avg_length', 'triangles', 'vertices'}).
This happened while the csv dataset builder was generating data using
hf://datasets/liuyibo/thingi10k-wmtk-simplification/verification/verification_full_qslim_sec_dedup.csv (at revision ea69283703234657aea0b6c24a2e5cf497febaf8), ['hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/qslim.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/summaries/sec_nolink.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_full_qslim_sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_sample1000_qslim_sec_dedup.csv', 'hf://datasets/liuyibo/thingi10k-wmtk-simplification@ea69283703234657aea0b6c24a2e5cf497febaf8/verification/verification_sample1000_qslim_sec_nolink.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id int64 | status string | reason null | wall_sec float64 | time_sec float64 | vertices float64 | triangles float64 | #v null | #f null | target_vertices float64 | target_length null | avg_length null | min_length null | max_length null | avg_valence null | nonmanifold_edges null | nonmanifold_vertices null |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
100,026 | success | null | 0.028 | 0.00759 | 27 | 81 | null | null | 11.7 | null | null | null | null | null | null | null |
100,027 | success | null | 0.025 | 0.01306 | 41 | 134 | null | null | 21.8 | null | null | null | null | null | null | null |
100,028 | success | null | 0.023 | 0.001664 | 12 | 12 | null | null | 12 | null | null | null | null | null | null | null |
100,029 | success | null | 0.023 | 0.008894 | 45 | 132 | null | null | 20.2 | null | null | null | null | null | null | null |
100,030 | success | null | 0.033 | 0.01396 | 60 | 194 | null | null | 60.8 | null | null | null | null | null | null | null |
100,031 | success | null | 0.023 | 0.006041 | 31 | 82 | null | null | 31 | null | null | null | null | null | null | null |
100,032 | success | null | 0.066 | 0.018307 | 151 | 398 | null | null | 151.6 | null | null | null | null | null | null | null |
100,033 | success | null | 0.022 | 0.005174 | 20 | 52 | null | null | 20.4 | null | null | null | null | null | null | null |
100,034 | success | null | 0.018 | 0.006016 | 22 | 64 | null | null | 8.4 | null | null | null | null | null | null | null |
100,035 | success | null | 0.017 | 0.004468 | 30 | 56 | null | null | 33.7 | null | null | null | null | null | null | null |
100,036 | success | null | 0.009 | 0.002615 | 12 | 21 | null | null | 12.3 | null | null | null | null | null | null | null |
100,037 | success | null | 0.016 | 0.005544 | 22 | 58 | null | null | 18.1 | null | null | null | null | null | null | null |
100,040 | success | null | 0.017 | 0.004866 | 36 | 84 | null | null | 36.2 | null | null | null | null | null | null | null |
100,045 | success | null | 0.017 | 0.006348 | 26 | 56 | null | null | 20.8 | null | null | null | null | null | null | null |
100,046 | success | null | 0.017 | 0.006193 | 64 | 132 | null | null | 65.6 | null | null | null | null | null | null | null |
100,047 | success | null | 0.033 | 0.011302 | 107 | 214 | null | null | 109.8 | null | null | null | null | null | null | null |
100,070 | success | null | 0.064 | 0.021497 | 249 | 498 | null | null | 251.5 | null | null | null | null | null | null | null |
100,071 | success | null | 0.032 | 0.006394 | 49 | 106 | null | null | 53.1 | null | null | null | null | null | null | null |
100,072 | success | null | 0.016 | 0.003344 | 17 | 34 | null | null | 18 | null | null | null | null | null | null | null |
100,073 | success | null | 0.017 | 0.004018 | 22 | 44 | null | null | 24.6 | null | null | null | null | null | null | null |
100,075 | success | null | 0.016 | 0.008136 | 72 | 152 | null | null | 72.6 | null | null | null | null | null | null | null |
100,077 | success | null | 0.016 | 0.00502 | 26 | 52 | null | null | 26.4 | null | null | null | null | null | null | null |
100,139 | success | null | 0.032 | 0.009973 | 103 | 206 | null | null | 106.6 | null | null | null | null | null | null | null |
100,173 | success | null | 0.008 | 0.002375 | 11 | 17 | null | null | 12.8 | null | null | null | null | null | null | null |
1,001,930 | success | null | 0.114 | 0.06256 | 721 | 1,430 | null | null | 722.5 | null | null | null | null | null | null | null |
1,001,931 | success | null | 0.114 | 0.063729 | 719 | 1,426 | null | null | 722.5 | null | null | null | null | null | null | null |
100,281 | success | null | 0.766 | 0.54163 | 4,693 | 10,260 | null | null | 4,694.9 | null | null | null | null | null | null | null |
100,282 | success | null | 0.867 | 0.612545 | 5,091 | 11,248 | null | null | 5,093.5 | null | null | null | null | null | null | null |
100,322 | success | null | 0.016 | 0.005467 | 36 | 76 | null | null | 38.4 | null | null | null | null | null | null | null |
100,323 | success | null | 0.016 | 0.005848 | 36 | 76 | null | null | 37.8 | null | null | null | null | null | null | null |
100,330 | success | null | 0.016 | 0.006419 | 46 | 96 | null | null | 50.1 | null | null | null | null | null | null | null |
100,331 | success | null | 0.016 | 0.006243 | 46 | 96 | null | null | 50.1 | null | null | null | null | null | null | null |
100,335 | success | null | 0.715 | 0.383785 | 3,484 | 6,947 | null | null | 3,486.3 | null | null | null | null | null | null | null |
100,336 | success | null | 0.264 | 0.127413 | 1,412 | 2,796 | null | null | 1,414.1 | null | null | null | null | null | null | null |
100,339 | success | null | 0.214 | 0.13124 | 771 | 1,538 | null | null | 772.2 | null | null | null | null | null | null | null |
100,340 | success | null | 0.264 | 0.167905 | 958 | 1,912 | null | null | 961.8 | null | null | null | null | null | null | null |
100,342 | success | null | 0.214 | 0.088116 | 905 | 1,806 | null | null | 908.7 | null | null | null | null | null | null | null |
100,343 | success | null | 0.264 | 0.148765 | 806 | 1,608 | null | null | 808.5 | null | null | null | null | null | null | null |
100,344 | success | null | 0.264 | 0.126052 | 1,028 | 2,052 | null | null | 1,029 | null | null | null | null | null | null | null |
100,345 | success | null | 0.114 | 0.059699 | 584 | 1,164 | null | null | 587.9 | null | null | null | null | null | null | null |
100,346 | success | null | 0.365 | 0.182838 | 1,899 | 3,794 | null | null | 1,901.6 | null | null | null | null | null | null | null |
100,349 | success | null | 0.064 | 0.042834 | 467 | 930 | null | null | 469.9 | null | null | null | null | null | null | null |
100,388 | success | null | 0.565 | 0.38475 | 3,756 | 7,508 | null | null | 3,758.2 | null | null | null | null | null | null | null |
100,423 | success | null | 0.016 | 0.002571 | 13 | 22 | null | null | 14 | null | null | null | null | null | null | null |
100,471 | success | null | 0.114 | 0.073021 | 732 | 1,464 | null | null | 735.4 | null | null | null | null | null | null | null |
100,478 | success | null | 0.114 | 0.042676 | 456 | 912 | null | null | 458.5 | null | null | null | null | null | null | null |
1,004,824 | success | null | 0.164 | 0.098556 | 1,129 | 2,220 | null | null | 1,131.6 | null | null | null | null | null | null | null |
1,004,825 | success | null | 0.016 | 0.00259 | 40 | 40 | null | null | 33 | null | null | null | null | null | null | null |
1,004,826 | success | null | 0.016 | 0.004412 | 36 | 68 | null | null | 39.4 | null | null | null | null | null | null | null |
1,004,827 | success | null | 0.064 | 0.01975 | 216 | 419 | null | null | 219 | null | null | null | null | null | null | null |
100,500 | success | null | 0.032 | 0.010207 | 27 | 94 | null | null | 18.1 | null | null | null | null | null | null | null |
100,506 | success | null | 0.164 | 0.098725 | 1,102 | 2,208 | null | null | 1,104.5 | null | null | null | null | null | null | null |
100,507 | success | null | 0.164 | 0.083888 | 934 | 1,872 | null | null | 935.1 | null | null | null | null | null | null | null |
1,005,266 | success | null | 0.064 | 0.038288 | 371 | 742 | null | null | 373.6 | null | null | null | null | null | null | null |
1,005,267 | success | null | 0.064 | 0.0364 | 361 | 718 | null | null | 364.6 | null | null | null | null | null | null | null |
1,005,268 | success | null | 0.114 | 0.046851 | 489 | 974 | null | null | 491.1 | null | null | null | null | null | null | null |
1,005,269 | success | null | 0.064 | 0.025003 | 241 | 478 | null | null | 243.3 | null | null | null | null | null | null | null |
1,005,270 | success | null | 0.064 | 0.037062 | 377 | 750 | null | null | 379.8 | null | null | null | null | null | null | null |
1,005,271 | success | null | 0.114 | 0.048222 | 492 | 988 | null | null | 494.2 | null | null | null | null | null | null | null |
1,005,272 | success | null | 0.064 | 0.031388 | 316 | 628 | null | null | 317.6 | null | null | null | null | null | null | null |
1,005,273 | success | null | 0.064 | 0.039876 | 383 | 766 | null | null | 386.4 | null | null | null | null | null | null | null |
1,005,275 | success | null | 0.114 | 0.047155 | 480 | 956 | null | null | 481.8 | null | null | null | null | null | null | null |
1,005,276 | success | null | 0.114 | 0.06352 | 652 | 1,300 | null | null | 654.8 | null | null | null | null | null | null | null |
1,005,277 | success | null | 0.114 | 0.053704 | 529 | 1,054 | null | null | 532.2 | null | null | null | null | null | null | null |
1,005,278 | success | null | 0.114 | 0.054267 | 550 | 1,096 | null | null | 552.8 | null | null | null | null | null | null | null |
1,005,279 | success | null | 0.064 | 0.035846 | 378 | 752 | null | null | 380.3 | null | null | null | null | null | null | null |
1,005,280 | success | null | 0.064 | 0.036945 | 379 | 758 | null | null | 382.5 | null | null | null | null | null | null | null |
1,005,281 | success | null | 0.114 | 0.045511 | 468 | 936 | null | null | 471.3 | null | null | null | null | null | null | null |
1,005,282 | success | null | 0.064 | 0.031902 | 305 | 606 | null | null | 308.8 | null | null | null | null | null | null | null |
1,005,283 | success | null | 0.064 | 0.037203 | 375 | 746 | null | null | 378.1 | null | null | null | null | null | null | null |
1,005,284 | success | null | 0.114 | 0.043317 | 436 | 868 | null | null | 438.7 | null | null | null | null | null | null | null |
1,005,285 | success | null | 0.016 | 0.003949 | 27 | 50 | null | null | 31.4 | null | null | null | null | null | null | null |
1,005,286 | success | null | 0.064 | 0.035084 | 342 | 680 | null | null | 345 | null | null | null | null | null | null | null |
1,005,287 | success | null | 0.064 | 0.035564 | 381 | 758 | null | null | 383.2 | null | null | null | null | null | null | null |
1,005,288 | success | null | 0.114 | 0.04232 | 448 | 892 | null | null | 451.9 | null | null | null | null | null | null | null |
1,005,289 | success | null | 0.114 | 0.051339 | 511 | 1,018 | null | null | 513.3 | null | null | null | null | null | null | null |
1,005,290 | success | null | 0.114 | 0.049374 | 525 | 1,046 | null | null | 527.7 | null | null | null | null | null | null | null |
1,005,291 | success | null | 0.114 | 0.071608 | 716 | 1,428 | null | null | 719.8 | null | null | null | null | null | null | null |
1,005,292 | success | null | 0.114 | 0.054439 | 545 | 1,090 | null | null | 548.8 | null | null | null | null | null | null | null |
1,005,586 | success | null | 19.805 | 15.65474 | 90,682 | 197,612 | null | null | 90,685.9 | null | null | null | null | null | null | null |
1,005,587 | success | null | 8.828 | 6.727162 | 49,785 | 101,218 | null | null | 49,788.8 | null | null | null | null | null | null | null |
100,606 | success | null | 0.032 | 0.009808 | 97 | 207 | null | null | 101.1 | null | null | null | null | null | null | null |
100,638 | success | null | 0.016 | 0.002375 | 14 | 20 | null | null | 15.6 | null | null | null | null | null | null | null |
100,639 | success | null | 0.064 | 0.017124 | 174 | 344 | null | null | 176.9 | null | null | null | null | null | null | null |
100,640 | success | null | 0.064 | 0.02097 | 217 | 434 | null | null | 219.1 | null | null | null | null | null | null | null |
100,641 | success | null | 0.032 | 0.011755 | 117 | 234 | null | null | 118.4 | null | null | null | null | null | null | null |
100,642 | success | null | 0.114 | 0.039464 | 440 | 884 | null | null | 442 | null | null | null | null | null | null | null |
100,643 | success | null | 0.016 | 0.00172 | 8 | 12 | null | null | 8.8 | null | null | null | null | null | null | null |
100,644 | success | null | 0.114 | 0.043337 | 481 | 958 | null | null | 484.5 | null | null | null | null | null | null | null |
100,645 | success | null | 0.032 | 0.013267 | 149 | 274 | null | null | 152 | null | null | null | null | null | null | null |
100,646 | success | null | 0.114 | 0.045472 | 479 | 954 | null | null | 481.4 | null | null | null | null | null | null | null |
100,678 | success | null | 0.016 | 0.003866 | 20 | 40 | null | null | 21.8 | null | null | null | null | null | null | null |
100,679 | success | null | 0.016 | 0.003584 | 20 | 40 | null | null | 21.8 | null | null | null | null | null | null | null |
100,680 | success | null | 0.016 | 0.003428 | 19 | 38 | null | null | 21.8 | null | null | null | null | null | null | null |
100,681 | success | null | 0.016 | 0.003869 | 20 | 40 | null | null | 21.8 | null | null | null | null | null | null | null |
100,682 | success | null | 0.032 | 0.006466 | 73 | 130 | null | null | 75.4 | null | null | null | null | null | null | null |
100,727 | success | null | 0.064 | 0.016487 | 160 | 320 | null | null | 162.1 | null | null | null | null | null | null | null |
100,728 | success | null | 0.008 | 0.001753 | 5 | 6 | null | null | 5.6 | null | null | null | null | null | null | null |
100,729 | success | null | 0.064 | 0.015573 | 167 | 342 | null | null | 170.9 | null | null | null | null | null | null | null |
100,730 | success | null | 0.064 | 0.018247 | 212 | 424 | null | null | 214.9 | null | null | null | null | null | null | null |
Thingi10K simplified by qslim and shortest edge collapse
Simplified versions of all 10,000 Thingi10K models produced with the
wildmeshing-toolkit
components qslim and shortest_edge_collapse, at target_rel = 0.1
(keep 10 % of the input vertices).
Generated on 2026-10-06/07 with wmtk_app built from upstream commit
76396a0a89. The driver and the checking scripts are in the
code repository
(run_component_sweep.py, verify_results.py) and the full analysis is in
report/thingi10k_qslim_sec.md.
Contents
| File | What it is |
|---|---|
qslim.tar.gz |
qslim outputs, defaults (target_rel=0.1) — 9992 models |
sec_dedup.tar.gz |
shortest edge collapse with remove_duplicate_eps=1e-5 — 9992 models |
sec_nolink.tar.gz |
shortest edge collapse with remove_duplicate_eps=1e-5 and use_link_condition=false — 9992 models |
summaries/ |
per-run summary.csv (per-model vertices/faces/time from the component reports) |
verification/ |
per-model checks: target reached, manifold/boundary edges, bbox agreement |
plots/ |
input-vs-output wireframe comparisons for a few models |
report/ |
the full write-up, including the termination criteria analysis |
Each archive unpacks to <run>/success/<model_id>/ with, per model:
config.json— the exact spec the component was called with<model_id>.out.obj— the simplified meshreport.json— component report (qslim only; shortest edge collapse writes none)console.log,run.log,wall_sec— logs and wall-clock time
8 models fail in every run; they are in <run>/failure/<model_id>/ with a
reason file. These are input defects, not algorithm failures (malformed OBJ
normals, STL with no faces, one truncated STL).
How it was generated
python3 run_component_sweep.py --application qslim \
--input-dir <thingi10k>/raw_meshes --out runs/qslim \
--threads 4 --parallel 24 --timeout 600
python3 run_component_sweep.py --application shortest_edge_collapse \
--input-dir <thingi10k>/raw_meshes --out runs/sec_dedup \
--threads 4 --parallel 24 --timeout 600 \
--param remove_duplicate_eps=1e-5
python3 run_component_sweep.py --application shortest_edge_collapse \
--input-dir <thingi10k>/raw_meshes --out runs/sec_nolink \
--threads 4 --parallel 24 --timeout 600 \
--param remove_duplicate_eps=1e-5 --param use_link_condition=false
Numbers
Reached the target vertex count (out of 9992 successful models, recovered from the run logs):
| run | reached target |
|---|---|
| qslim | 9184 (91.9 %) |
| sec_dedup | 9134 (91.4 %) |
| sec_nolink | 9736 (97.4 %) |
Full verification over 19,984 outputs (qslim + sec_dedup): 18,182 reached the target, 2,007 outputs contain non-manifold edges.
Known caveats
- A shortest edge collapse run with default parameters is useless on STL.
With
remove_duplicate_eps=-1(the default) the STL is loaded as a triangle soup and no edge can be collapsed, so the output equals the input. That run is not included here;summaries/sec_default_summary.csvdocuments it. - Heavily non-manifold inputs stall both components when the link condition
is on (e.g. model 51351 stays at 8,700 vertices). Turning
use_link_condition=falsefixes those but produces non-manifold outputs (11 % → 68 % of sampled outputs). - The stop rule is purely count-based: it stops after
V0 − target − 1successful collapses. There is no error/quality threshold, and a run that cannot reach the target still exits 0 unlessthrow_on_fail=true. - The bounding-box column in
verification/is computed over all vertices written to the OBJ, including slots the writer left unused; extreme ratios there are a measurement artifact, not real deformation. Use the Chamfer numbers in the report for shape fidelity (typically ~0.005 of the model size).
Licence
The models are derived from Thingi10K; each retains the licence of its original Thingiverse upload. Check the source model's licence before any commercial use.
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