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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 1531, 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 127, 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 32, 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 1393, 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 1571, 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.
jpg image | __key__ string | __url__ string |
|---|---|---|
--Cv18I6gxw/frame_000001 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000002 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000003 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000004 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000005 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000006 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000007 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000008 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000009 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000010 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000011 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000012 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000013 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000014 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000015 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000016 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000017 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000018 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000019 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000020 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000021 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000022 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000023 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000024 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000025 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000026 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000027 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000028 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000029 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000030 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000031 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000032 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000033 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000034 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000035 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000036 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000037 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000038 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000039 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000040 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000041 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000042 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000043 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000044 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000045 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000046 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000047 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000048 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000049 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000050 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000051 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000052 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000053 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000054 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000055 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000056 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000057 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000058 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000059 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000060 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000061 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000062 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000063 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000064 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000065 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000066 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000067 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000068 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000069 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000070 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000071 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000072 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000073 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000074 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000075 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000076 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000077 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000078 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000079 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000080 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000081 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000082 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000083 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000084 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000085 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000086 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000087 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000088 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000089 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000090 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000091 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000092 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000093 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000094 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000095 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000096 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000097 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000098 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000099 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar | |
--Cv18I6gxw/frame_000100 | hf://datasets/groundmore/visp_gmn_training_10k@9d249e7ec3d546e581a3d4879978a45aa316a761/data/frames-00000-of-00078.tar |
End of preview.
VisP GMN Training 10K Frames
This dataset contains 1 FPS JPEG frame extractions for the source videos used by the GMN multi-video training data.
Dataset summary
- Completed videos: 10,088 out of 10,097 targets (99.9109%)
- Missing videos: 9 (source decode failures; see
missing_videos.json) - JPEG frames: 5,852,529
- JPEG payload: 410,962,893,326 bytes (410.963 GB / 382.739 GiB)
- Sampling rate: 1 FPS
- JPEG quality: 75, chroma subsampling 4:2:0 (
jpeg_subsampling=2) - Tar shards: 78, with every video contained wholly in one shard
Operational extraction logs and internal source paths are intentionally excluded. Each archived video directory contains frame_XXXXXX.jpg files and a sanitized frames.json.
Files
README.md
manifest.jsonl
missing_videos.json
shards.jsonl
SHA256SUMS
PORTABLE_SHA256SUMS
DATA_PATHS_AND_KNOWN_ISSUES.md
annotations/raw/*.json
annotations/trajectories/*.json
metadata/*.json
legacy/**/*.parquet
quality/*
data/frames-00000-of-00078.tar
...
manifest.jsonl maps each video_id to its shard and records frame count, JPEG bytes, sampling settings, dimensions, and timestamps. shards.jsonl contains archive-level counts, byte sizes, and SHA-256 hashes.
The annotations, metadata, and legacy directories contain portable copies
whose media paths resolve directly to the extracted frames/<video_id> layout.
Rows that cannot be matched completely are retained with explicit alignment
statuses and issue fields. Read DATA_PATHS_AND_KNOWN_ISSUES.md before training;
the complete machine-readable issue list is in
quality/incomplete_references.jsonl.
Reading a video
Find its shard in manifest.jsonl, then extract the video directory:
tar -xf data/frames-00000-of-00078.tar VIDEO_ID/
To stream the names without extracting:
tar -tf data/frames-00000-of-00078.tar
Verify downloaded shards with:
sha256sum -c SHA256SUMS
Extraction rule
Frames were decoded in presentation order. The first decoded frame at or after each integer second, relative to the first decoded frame, was saved as JPEG. Per-video details are stored in frames.json and the global manifest.
Coverage note
This release is not a literal 100% extraction of all 10,097 target videos. Nine source videos failed decoding and are listed in missing_videos.json.
Source rights
This packaging does not grant rights beyond those associated with the original source videos and the applicable dataset terms. Users are responsible for ensuring that their use and redistribution comply with those terms.
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