egordm/tracking-demo-clips

Kubrick Tracking Demo Clips

Curated single-object tracking clips for demos, notebooks, and lightweight CI in the kubrick-tracking project.

Each clip is a short video sequence (50-300 frames) with per-frame bounding-box ground truth, drawn from established tracking benchmarks.

Sources & Licensing

Source	License	Sequences	Citation
LaSOT	CC-BY-NC-SA 4.0	lasot/person-{1,2,3,5,6,10,15,18}	Fan et al., CVPR 2019
VisDrone-SOT	CC-BY-NC-SA 3.0	visdrone-sot/*	Zhu et al., TPAMI 2021

This dataset is a curated subset redistributed under CC-BY-NC-SA 4.0 (the more restrictive of the two source licenses). Non-commercial use only.

Layout

<clip_id>/
    frames/
        0000001.jpg
        0000002.jpg
        ...
    groundtruth.txt      # x,y,w,h per line (one line per frame)
    meta.json            # source, license, frame_count, image_size, category

Usage with huggingface_hub

from huggingface_hub import snapshot_download

# Download a single clip
clip_dir = snapshot_download(
    repo_id="egordm/tracking-demo-clips",
    repo_type="dataset",
    allow_patterns=["lasot/person-3/**"],
)

Usage with kubrick-tracking

from pathlib import Path
from kubrick.tracking import Tracker

tracker = Tracker.from_bundle("kubrick://efficienttam-ti-512@fp16")
# ... load frames from the downloaded clip and track

Citations

@inproceedings{fan2019lasot,
  title={LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking},
  author={Fan, Heng and Lin, Liting and Yang, Fan and Chu, Peng and Deng, Ge and Yu, Sijia and Bai, Hexin and Xu, Yong and Liao, Chunyuan and Ling, Haibin},
  booktitle={CVPR},
  year={2019}
}

@article{zhu2021detection,
  title={Detection and Tracking Meet Drones Challenge},
  author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
  journal={IEEE TPAMI},
  volume={44},
  number={11},
  pages={7380--7399},
  year={2021}
}