VideoChat3
Collection
7 items • Updated
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Failed to parse string: 'COCO_train2014_000000332069' as a scalar of type int64
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table 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/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, 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 1852, 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 2143, 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 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2006, 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
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Failed to parse string: 'COCO_train2014_000000332069' as a scalar of type 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 1683, 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 1869, 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.
id int64 | messages list |
|---|---|
1 | [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "ytb_--X2lih9mrA"
},
"video_metadata": {
"total_num_frames": 582,
"duration": 145.5,
"fps": 4,
"width": 644,
"height": 392,
... |
2 | [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "ytb_-0C1fjLJnII"
},
"video_metadata": {
"total_num_frames": 614,
"duration": 153.5,
"fps": 4,
"width": 644,
"height": 392,
... |
3 | [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "ytb_-0NVfUcoq-4"
},
"video_metadata": {
"total_num_frames": 533,
"duration": 133.25,
"fps": 4,
"width": 644,
"height": 392,
... |
4 | [
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "ytb_-0rFpS4BIao"
},
"video_metadata": {
"total_num_frames": 517,
"duration": 129.25,
"fps": 4,
"width": 644,
"height": 392,
... |
5 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-1tnjH_LcHU"},"video_metadata(...TRUNCATED) |
6 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-24Qn0JGBD0"},"video_metadata(...TRUNCATED) |
7 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-307KeddHWI"},"video_metadata(...TRUNCATED) |
8 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-335dC6u2oI"},"video_metadata(...TRUNCATED) |
9 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-3X7LW2cZrs"},"video_metadata(...TRUNCATED) |
10 | [{"role":"user","content":[{"type":"video_url","video_url":{"url":"ytb_-3ZXWr0aDbQ"},"video_metadata(...TRUNCATED) |
End of preview.
VideoChat3-OL617K
VideoChat3-OL617K is the online video instruction data used by VideoChat3. It is designed to train proactive streaming video assistants that continuously observe incoming video, accumulate visual evidence, and respond at the appropriate moment.
The dataset converts video-question-answer triples into causal streaming supervision. Visual clue intervals are first localized and verified, then transformed into streaming sequences with explicit response-state tokens: </Silence>, </Standby>, and </Response>. These tokens teach the model when to remain silent, continue collecting evidence, and provide an answer.
This repository provides JSONL annotation files. The original videos are not duplicated here; users should resolve videos from the original dataset paths listed below.
Data Sources
VideoChat3-OL617K use the following video datasets:
| Source dataset | Original video dataset path |
|---|---|
| StreamForest | https://huggingface.co/datasets/MCG-NJU/StreamForest-Annodata |
| Streamo | https://huggingface.co/datasets/maifoundations/Streamo-Instruct-465K |
| Seeker | https://huggingface.co/datasets/MCG-NJU/Seeker-173K |
| AVA (Supplement) | https://github.com/cvdfoundation/ava-dataset |
| EgoQA (Supplement) | https://ego4d-data.org/ |
The ol617k.json file provides the mapping between dataset annotations and video sources. You can refer to it when organizing the dataset structure.
Citation
If you use this data, please cite VideoChat3 and the original video datasets used by the annotations.
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