def create_dataset_from_video_annotation_project(
    deeplake_ds_path,
    project_id,
    lb_api_key,
    deeplake_creds=None,
    deeplake_org_id=None,
    deeplake_token=None,
    overwrite=False,
    fail_on_error=False,
    url_presigner=None,
    video_generator_batch_size=100,
    fail_on_labelbox_project_export_error=False,
    project_json=None,
) -> Tuple[deeplake.Dataset, Any]:
    """
    See create_dataset_from_video_annotation_project_with_custom_data_filler for complete documentation.

    The only difference is this function uses default tensor creation and data filling functions:
    - create_tensors_default_: Creates default tensor structure
    - fill_data_default_: Fills tensors with default processing
    """
    return create_dataset_from_video_annotation_project_with_custom_data_filler(
        deeplake_ds_path,
        project_id,
        lb_api_key,
        data_filler={
            "create_tensors": create_tensors_default_,
            "fill_data": fill_data_default_,
        },
        deeplake_creds=deeplake_creds,
        deeplake_org_id=deeplake_org_id,
        deeplake_token=deeplake_token,
        overwrite=overwrite,
        fail_on_error=fail_on_error,
        url_presigner=url_presigner,
        video_generator_batch_size=video_generator_batch_size,
        fail_on_labelbox_project_export_error=fail_on_labelbox_project_export_error,
        project_json=project_json,
    )

    See create_dataset_from_video_annotation_project_with_custom_data_filler for complete documentation.

    The only difference is this function uses default tensor creation and data filling functions:
    - create_tensors_default_: Creates default tensor structure
    - fill_data_default_: Fills tensors with default processing
    
python/deeplake/integrations/labelbox/labelbox_.py