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 "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 406, in hf_raise_for_status
response.raise_for_status()
File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/models.py", line 1024, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 416 Client Error: Requested Range Not Satisfiable for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/e9/0a/e90af387ae459401c9631f5290d2a03239426f97149c62e3d803962dc64e4cd6/285923524e3a1a7d41f252943fc152d71b30fb1ef2d4ea55e77cb2881c784b59?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQLC2QXPN7%2F20250413%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20250413T172536Z&X-Amz-Expires=3600&X-Amz-Signature=59ed267bf3d7889639fbbd4c3ced4ecb1e433bf2c1816e983d9fbef0f4d8e08d&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27123ff6f2871e6234b4127bb0e694c564691ec8ac8f272f6fcfcffe1397a2a3dad8ffee8113a3b46b875f15eeabb90fc85bf01a30ba6e372f5036115ad5dfb51f.zip%3B%20filename%3D%22123ff6f2871e6234b4127bb0e694c564691ec8ac8f272f6fcfcffe1397a2a3dad8ffee8113a3b46b875f15eeabb90fc85bf01a30ba6e372f5036115ad5dfb51f.zip%22%3B&response-content-type=application%2Fzip&x-id=GetObject
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 273, in _EndRecData
data = fpin.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 1013, in read
return super().read(length)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1846, in read
out = self.cache._fetch(self.loc, self.loc + length)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/caching.py", line 189, in _fetch
self.cache = self.fetcher(start, end) # new block replaces old
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 976, in _fetch_range
hf_raise_for_status(r)
File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 473, in hf_raise_for_status
raise _format(HfHubHTTPError, message, response) from e
huggingface_hub.errors.HfHubHTTPError: 416 Client Error: Requested Range Not Satisfiable for url: https://hf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com/repos/e9/0a/e90af387ae459401c9631f5290d2a03239426f97149c62e3d803962dc64e4cd6/285923524e3a1a7d41f252943fc152d71b30fb1ef2d4ea55e77cb2881c784b59?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA2JU7TKAQLC2QXPN7%2F20250413%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20250413T172536Z&X-Amz-Expires=3600&X-Amz-Signature=59ed267bf3d7889639fbbd4c3ced4ecb1e433bf2c1816e983d9fbef0f4d8e08d&X-Amz-SignedHeaders=host&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27123ff6f2871e6234b4127bb0e694c564691ec8ac8f272f6fcfcffe1397a2a3dad8ffee8113a3b46b875f15eeabb90fc85bf01a30ba6e372f5036115ad5dfb51f.zip%3B%20filename%3D%22123ff6f2871e6234b4127bb0e694c564691ec8ac8f272f6fcfcffe1397a2a3dad8ffee8113a3b46b875f15eeabb90fc85bf01a30ba6e372f5036115ad5dfb51f.zip%22%3B&response-content-type=application%2Fzip&x-id=GetObject. Requested range: bytes=10602558-10602579. Content-Range: None.
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>InvalidRange</Code><Message>The requested range is not satisfiable</Message><RangeRequested>bytes=10602558-10602579</RangeRequested><ActualObjectSize>10248412</ActualObjectSize><RequestId>AMTBV8M4SVVSZ3CN</RequestId><HostId>mkiyxNlJFIqIAkGzoSfj8uzs+OIlBmzWDiiCPgH0bF1e0L0rExSe2CSI44jjGgGETsZTHbEgyB4=</HostId></Error>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 299, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 125, in _split_generators
analyze(archives, downloaded_dirs, split_name)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 99, in analyze
for downloaded_dir_file in dl_manager.iter_files(downloaded_dir):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1364, in _iter_from_urlpaths
if xisfile(urlpath, download_config=download_config):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 747, in xisfile
fs, *_ = url_to_fs(path, **storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1331, in _RealGetContents
raise BadZipFile("File is not a zip file")
zipfile.BadZipFile: File is not a zip file
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 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 353, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 304, 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.
🚁 VOT-RGBT 2019 Challenge Dataset
Visual Object Tracking for RGB and Thermal Imagery
Dataset Summary
The VOT-RGBT 2019 dataset is part of the Visual Object Tracking (VOT) initiative — a series of challenges that provide the computer vision community with standardized benchmarks for evaluating short-term and long-term visual object trackers. This particular edition focuses on RGB-T (Visible + Thermal) imagery, encouraging robust object tracking in challenging multimodal environments.
Supported Tasks and Leaderboards
- 📦 Visual Object Tracking (Short-Term & Long-Term)
- Track object location across RGB and thermal frames
- Evaluate robustness to occlusion, illumination changes, and environmental conditions
Dataset Structure
- Sequences: 60+ sequences with aligned RGB and thermal imagery
- Annotations: Per-frame ground truth bounding boxes in both modalities
- Modalities: RGB, Thermal (LWIR)
- Frame Rate: 20-30 FPS (varies by sequence)
- Resolution: Varies by sensor and sequence (mostly HD and VGA)
Usage
To use the dataset:
from datasets import load_dataset
# This assumes dataset is hosted on Hugging Face datasets hub
dataset = load_dataset("langutang/vot-rgbt2019")
Alternatively, you can download it from the official VOT site.
Evaluation Protocol
VOT-RGBT 2019 uses the standard VOT evaluation protocol:
- Accuracy (A): Overlap between predicted and ground truth bounding boxes
- Robustness (R): Number of tracking failures
- Expected Average Overlap (EAO): Combines A and R for a unified score
Both short-term and long-term tracker performance can be evaluated using the provided toolkit.
Citation
If you use this dataset in your research, please cite:
@inproceedings{votrgbt2019,
title={RGB-Thermal Object Tracking: Benchmark and Baselines},
author={Liang, Jianan and Hu, Jiakai and Zhang, Yu and others},
booktitle={ECCV Workshops},
year={2019}
}
License
Please refer to the license and usage terms outlined on the official VOT website.
Acknowledgements
Thanks to the VOT committee and contributing authors for their continued efforts in pushing forward the field of visual object tracking.
Tags
computer-vision, object-tracking, rgbt, thermal-imaging, vot, multimodal, benchmark
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