Reading Analog Dial Guages via VLMs
Collection
2 items • Updated
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Float value 2.500000 was truncated converting to int64
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 765, 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 773, 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 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2015, in array_cast
return array.cast(pa_type)
~~~~~~~~~~^^^^^^^^^
File "pyarrow/array.pxi", line 1147, in pyarrow.lib.Array.cast
File "/usr/local/lib/python3.14/site-packages/pyarrow/compute.py", line 412, in cast
return call_function("cast", [arr], options, memory_pool)
File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
result = GetResultValue(
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Float value 2.500000 was truncated converting to int64
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.
filename string | actual_val float64 | min_val int64 | max_val int64 |
|---|---|---|---|
out2_handpicked_frame_00m_00s.jpg | 0 | 0 | 4 |
out2_handpicked_frame_00m_01s.jpg | 0.05 | 0 | 4 |
out2_handpicked_frame_00m_02s.jpg | 0.18 | 0 | 4 |
out2_handpicked_frame_00m_03s.jpg | 0.25 | 0 | 4 |
out2_handpicked_frame_00m_04s.jpg | 0.55 | 0 | 4 |
out2_handpicked_frame_00m_05s.jpg | 0.7 | 0 | 4 |
out2_handpicked_frame_00m_06s.jpg | 0.79 | 0 | 4 |
out2_handpicked_frame_00m_07s.jpg | 0.88 | 0 | 4 |
out2_handpicked_frame_00m_08s.jpg | 0.99 | 0 | 4 |
out2_handpicked_frame_00m_09s.jpg | 1.08 | 0 | 4 |
out2_handpicked_frame_00m_10s.jpg | 1.08 | 0 | 4 |
out2_handpicked_frame_00m_22s.jpg | 0.8 | 0 | 4 |
out2_handpicked_frame_00m_43s.jpg | 1.07 | 0 | 4 |
out2_handpicked_frame_00m_56s.jpg | 1.22 | 0 | 4 |
out2_handpicked_frame_01m_49s.jpg | 0.34 | 0 | 4 |
out2_handpicked_frame_01m_54s.jpg | 0 | 0 | 4 |
out3_handpicked_frame_00m_01s.jpg | 0 | 0 | 4 |
out3_handpicked_frame_00m_02s.jpg | 0 | 0 | 4 |
out3_handpicked_frame_00m_03s.jpg | 0.1 | 0 | 4 |
out3_handpicked_frame_00m_04s.jpg | 0.18 | 0 | 4 |
out3_handpicked_frame_00m_05s.jpg | 0.36 | 0 | 4 |
out3_handpicked_frame_00m_06s.jpg | 0.65 | 0 | 4 |
out3_handpicked_frame_00m_07s.jpg | 0.74 | 0 | 4 |
out3_handpicked_frame_00m_08s.jpg | 0.83 | 0 | 4 |
out3_handpicked_frame_00m_09s.jpg | 0.91 | 0 | 4 |
out3_handpicked_frame_00m_10s.jpg | 1.05 | 0 | 4 |
out3_handpicked_frame_00m_11s.jpg | 1.09 | 0 | 4 |
out3_handpicked_frame_00m_12s.jpg | 0.98 | 0 | 4 |
out3_handpicked_frame_00m_48s.jpg | 1.04 | 0 | 4 |
out3_handpicked_frame_00m_58s.jpg | 1.14 | 0 | 4 |
out3_handpicked_frame_01m_07s.jpg | 1.2 | 0 | 4 |
out3_handpicked_frame_01m_14s.jpg | 1.22 | 0 | 4 |
out3_handpicked_frame_01m_39s.jpg | 0.67 | 0 | 4 |
out3_handpicked_frame_01m_43s.jpg | 0.59 | 0 | 4 |
out3_handpicked_frame_01m_52s.jpg | 0.31 | 0 | 4 |
out3_handpicked_frame_01m_53s.jpg | 0.21 | 0 | 4 |
out3_handpicked_frame_01m_54s.jpg | 0.14 | 0 | 4 |
out3_handpicked_frame_01m_57s.jpg | 0 | 0 | 4 |
out3_handpicked_frame_02m_00s.jpg | 0 | 0 | 4 |
out5_handpicked_frame_00m_00s.jpg | 0.04 | 0 | 4 |
out5_handpicked_frame_00m_01s.jpg | 0.18 | 0 | 4 |
out5_handpicked_frame_00m_02s.jpg | 0.36 | 0 | 4 |
out5_handpicked_frame_00m_03s.jpg | 0.55 | 0 | 4 |
out5_handpicked_frame_00m_04s.jpg | 0.7 | 0 | 4 |
out5_handpicked_frame_00m_05s.jpg | 0.78 | 0 | 4 |
out5_handpicked_frame_00m_06s.jpg | 0.88 | 0 | 4 |
out5_handpicked_frame_00m_07s.jpg | 0.98 | 0 | 4 |
out5_handpicked_frame_00m_08s.jpg | 1.08 | 0 | 4 |
out5_handpicked_frame_00m_10s.jpg | 0.88 | 0 | 4 |
out5_handpicked_frame_00m_11s.jpg | 0.85 | 0 | 4 |
out5_handpicked_frame_00m_57s.jpg | 1.12 | 0 | 4 |
out5_handpicked_frame_01m_05s.jpg | 1.17 | 0 | 4 |
out5_handpicked_frame_01m_19s.jpg | 1.2 | 0 | 4 |
out5_handpicked_frame_01m_43s.jpg | 0.51 | 0 | 4 |
out5_handpicked_frame_01m_44s.jpg | 0.5 | 0 | 4 |
out5_handpicked_frame_01m_55s.jpg | 0 | 0 | 4 |
out5_handpicked_frame_01m_58s.jpg | 0 | 0 | 4 |
v_0286_f_0000_rgba.png | 2.4 | -1 | 5 |
v_0224_f_0000_rgba.png | 4.4 | 0 | 10 |
v_0403_f_0000_rgba.png | 6.5 | 0 | 8 |
v_0260_f_0000_rgba.png | 3.2 | -1 | 7 |
v_0247_f_0000_rgba.png | 4.3 | 0 | 9 |
v_0102_f_0000_rgba.png | 1.7 | 0 | 9 |
v_0006_f_0000_rgba.png | -1.2 | -1 | 6 |
v_0212_f_0000_rgba.png | 4.2 | 0 | 10 |
v_0004_f_0000_rgba.png | -0.2 | 0 | 9 |
v_0072_f_0000_rgba.png | -0.2 | -1 | 6 |
v_0405_f_0000_rgba.png | 5.5 | -1 | 7 |
v_0480_f_0000_rgba.png | 8.8 | 0 | 9 |
v_0037_f_0000_rgba.png | -0.8 | -1 | 5 |
v_0365_f_0000_rgba.png | 6.6 | 0 | 9 |
v_0456_f_0000_rgba.png | 7.4 | 0 | 8 |
v_0023_f_0000_rgba.png | -0.8 | -1 | 8 |
v_0441_f_0000_rgba.png | 8.1 | 0 | 9 |
v_0166_f_0000_rgba.png | 0.5 | -1 | 4 |
v_0040_f_0000_rgba.png | -0.8 | -1 | 4 |
v_0145_f_0000_rgba.png | 1.1 | -1 | 7 |
v_0025_f_0000_rgba.png | -2 | -2 | 3 |
v_0121_f_0000_rgba.png | 0.8 | -1 | 7 |
v_0442_f_0000_rgba.png | 2.6 | -2 | 3 |
v_0438_f_0000_rgba.png | 3.3 | -2 | 4 |
v_0299_f_0000_rgba.png | 3.7 | -1 | 7 |
v_0277_f_0000_rgba.png | 2.8 | -1 | 6 |
v_0269_f_0000_rgba.png | 2.6 | -1 | 6 |
v_0109_f_0000_rgba.png | -1.1 | -2 | 3 |
v_0115_f_0000_rgba.png | 0.6 | -1 | 7 |
v_0071_f_0000_rgba.png | -1.5 | -2 | 3 |
v_0010_f_0000_rgba.png | -0 | 0 | 9 |
v_0407_f_0000_rgba.png | 2.1 | -2 | 3 |
v_0302_f_0000_rgba.png | 4.8 | 0 | 8 |
v_0384_f_0000_rgba.png | 3.7 | -1 | 5 |
v_0152_f_0000_rgba.png | 0.7 | -1 | 5 |
v_0190_f_0000_rgba.png | 1.2 | -1 | 5 |
v_0230_f_0000_rgba.png | 2.7 | -1 | 7 |
v_0382_f_0000_rgba.png | 5.9 | -1 | 8 |
v_0435_f_0000_rgba.png | 2.4 | -2 | 3 |
v_0167_f_0000_rgba.png | 2.5 | 0 | 8 |
v_0236_f_0000_rgba.png | 2.7 | -1 | 7 |
v_0279_f_0000_rgba.png | 4.9 | 0 | 9 |
v_0105_f_0000_rgba.png | 0.3 | -1 | 6 |
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