The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
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/split_names.py", line 66, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
VLN-CE Annotation Archive Tools
Utilities for packaging VLN-CE semantic annotation sidecars into plain tar archives that are easier to upload to Hugging Face and restore on a cluster.
Suggested Hugging Face dataset repo:
shaoyoubo/internnav-vlnce-semantic-bbox-annotations
Archive Layout
The packer writes two artifact families:
semantic_maps/
vln_ce_semantic_metadata.tar
r2r/<scene-id>.semantic.tar
rxr/<scene-id>.semantic.tar
bbox_parquet/
r2r/<scene-id>.bbox.tar
rxr/<scene-id>.bbox.tar
manifest.jsonl
Semantic scene archives contain:
traj_data/<dataset>/<scene-id>/videos/
traj_data/<dataset>/<scene-id>/meta/
BBox archives contain:
traj_data/<dataset>/<scene-id>/data/
vln_ce_semantic_metadata.tar contains semantic_metadata/, which is needed
when regenerating bbox parquet from semantic maps.
Pack
Pack all R2R and RxR annotations:
cd /root/InternNav
python scripts/vln_ce_semantic/archive_tools/pack_vlnce_annotations.py \
--annotation-root data/annotations/vln_ce \
--output-root /workspace/vlnce_annotation_archives \
--dataset r2r \
--dataset rxr \
--artifact all \
--jobs 8 \
--checksum sha256
Dry-run one scene:
python scripts/vln_ce_semantic/archive_tools/pack_vlnce_annotations.py \
--annotation-root data/annotations/vln_ce \
--output-root /workspace/vlnce_annotation_archives \
--dataset r2r \
--scene-id 1pXnuDYAj8r \
--artifact all \
--dry-run
Extract
Extract on a cluster into the current annotation layout:
cd /root/InternNav
python scripts/vln_ce_semantic/archive_tools/extract_vlnce_annotations.py \
/workspace/vlnce_annotation_archives \
--annotation-root data/annotations/vln_ce \
--jobs 8
Use --overwrite to replace archive-owned roots such as one scene's videos/,
meta/, or data/. Without --overwrite, existing roots cause extraction to
fail before tar is run.
Download
Download the uploaded archive folder from Hugging Face:
cd /root/InternNav
/root/miniconda3/envs/internnav-habitat/bin/python \
scripts/vln_ce_semantic/archive_tools/download_vlnce_annotation_archives.py \
--archive-root /workspace/vlnce_annotation_archives
Resume is handled by huggingface_hub through the local download cache. Add
--verify to check downloaded tar files against the sha256 values in
manifest.jsonl.
You can download a smaller subset before extracting:
/root/miniconda3/envs/internnav-habitat/bin/python \
scripts/vln_ce_semantic/archive_tools/download_vlnce_annotation_archives.py \
--archive-root /workspace/vlnce_annotation_archives \
--dataset r2r \
--artifact bbox
Upload
After packing finishes and manifest.jsonl exists, upload with:
/root/miniconda3/envs/internnav-habitat/bin/python \
scripts/vln_ce_semantic/archive_tools/upload_vlnce_annotation_archives.py \
--archive-root /workspace/vlnce_annotation_archives
The script creates the dataset repo by default if it does not exist. Add
--private if you want the newly created repo to be private. It uses
huggingface_hub's resumable upload_large_folder path by default; rerunning
the same command resumes from .cache/.huggingface/ under the archive root.
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