Danielxsy/safedrive-vla
Robotics • Updated • 33 • 4
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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 71, 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.
SimLingo Dataset
Overview
SimLingo-Data is a large-scale autonomous driving CARLA 2.0 dataset containing sensor data, action labels, a wide range of simulator state information, and language labels for VQA, commentary and instruction following. The driving data is collected with the privileged rule-based expert PDM-Lite.
Dataset Statistics
- Large-scale dataset: 3,308,315 total samples (note: these are not from unique routes as the provided CARLA route files are limited)
- Diverse Scenarios: Covers 38 complex scenarios, including urban traffic, participants violating traffic rules, and high-speed highway driving
- Focused Evaluation: Short routes with 1 scenario (62.1%) or 3 scenarios (37.9%) per route
- Data Types: RGB images (.jpg), LiDAR point clouds (.laz), Sensor measurements (.json.gz), Bounding boxes (.json.gz), Language annotations (.json.gz)
Dataset Structure
The dataset is organized hierarchically with the following main components:
data/: Raw sensor data (RGB, LiDAR, measurements, bounding boxes)commentary/: Natural language descriptions of driving decisionsdreamer/: Instruction following data with multiple instruction/action pairs per sampledrivelm/: VQA data, based on DriveLM
Data Details
- RGB Images: 1024x512 front-view camera image
- Augmented RGB Images: 1024x512 front-view camera image with a random shift and orientation offset of the camera
- LiDAR: Point cloud data saved in LAZ format
- Measurements: Vehicle state, simulator state, and sensor readings in JSON format
- Bounding Boxes: Detailed information about each object in the scene.
- Commentary, Dreamer, VQA: Language annotations
Usage
This dataset is chunked into groups of multiple routes for efficient download and processing.
Download the whole dataset using git with Git LFS
# Clone the repository
git clone https://huggingface.co/datasets/RenzKa/simlingo
# Navigate to the directory
cd simlingo
# Pull the LFS files
git lfs pull
Download a single file with wget
# Download individual files (replace with actual file URLs from Hugging Face)
wget https://huggingface.co/datasets/RenzKa/simlingo/resolve/main/[filename].tar.gz
Extract to a single directory - please specify the location where you want to store the dataset
# Create output directory
mkdir -p database/simlingo
# Extract all archives to the same directory
for file in *.tar.gz; do
echo "Extracting $file to database/simlingo/..."
tar -xzf "$file" -C database/simlingo/
done
License
Please refer to the license file for usage terms and conditions.
Citation
If you use this dataset in your research, please cite:
@inproceedings{renz2025simlingo,
title={SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment},
author={Renz, Katrin and Chen, Long and Arani, Elahe and Sinavski, Oleg},
booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2025},
}
@inproceedings{sima2024drivelm,
title={DriveLM: Driving with Graph Visual Question Answering},
author={Chonghao Sima and Katrin Renz and Kashyap Chitta and Li Chen and Hanxue Zhang and Chengen Xie and Jens Beißwenger and Ping Luo and Andreas Geiger and Hongyang Li},
booktitle={European Conference on Computer Vision},
year={2024},
}
- Downloads last month
- 4,115
