diff --git a/README.md b/README.md index 3e9a1fca9d33c9ee98d2011884ef83fb2df905ce..f0c76736c65b0d6e2ed646d81e1788dbe3d8036f 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,242 @@ --- -license: cc0-1.0 +license: cc-by-4.0 +language: +- en +pretty_name: "Drone Maneuver Test-Clip Library" +task_categories: +- object-detection +- video-classification +tags: +- biology +- image +- animals +- CV +- drone +- UAV +- KABR +- zebra +- giraffe +- behavior +- pose +- animal-tracking +- Mpala Research Centre +size_categories: +- n<1K +description: "A library of 6-second aerial drone clips derived from the KABR dataset (Mpala Research Centre, Kenya), each indexed by the autonomous-flight maneuver it is suitable for testing, with per-frame-per-track labels (bounding box, species, behaviour, persistent track id, ground-truth pose where available, telemetry)." --- + +# Dataset Card for Drone Maneuver Test-Clip Library + +A benchmark of **41 six-second drone clips** (180 frames @ 30 fps) +cut from 20 KABR videos across 17 survey sessions at the Mpala Research Centre, +Kenya. Each clip is indexed by which autonomous-flight **maneuver** it can test +(launch / follow / behavior-adaptive / SoI-aware) and ships with a per-frame-per-track label table. +The library is intended for evaluating drone navigation policies against real wildlife footage. + +## Dataset Details + +### Dataset Description + +- **Curated by:** Kline et al. (derived from the KABR dataset) +- **Language(s) (NLP):** en +- **Homepage:** https://github.com/Imageomics/wildwing +- **Repository:** autonomous_drone_simulator (`clip_library/`) +- **Paper:** ACSOS 2026 artifact (forthcoming); Journal of Field Robotics (in prep) +- **Related dataset:** [imageomics/KABR](https://huggingface.co/datasets/imageomics/KABR), + [imageomics/KABR-poses](https://huggingface.co/datasets/imageomics/KABR-poses) + +This dataset repackages the KABR aerial behavior dataset into short, mix-and-match clips that each +exercise a specific drone maneuver, so navigation policies can be benchmarked per-maneuver rather +than only end-to-end. Labels are aligned per frame per tracked individual. + +### Supported Tasks and Leaderboards + +Object detection / tracking, behaviour recognition, pose (viewpoint) estimation, and +**maneuver-conditioned navigation-policy evaluation** (the primary intended use). + +## Dataset Structure + +``` +kabr_clips/ + catalog/ + video_index.csv # per source video: frame summary, metadata, resolved raw video + clip_index.csv # one row per clip (the master index) + coverage_report.md # species x habitat x bbox-size x maneuver coverage + pose_audit.csv # per-video GT-pose assignment audit + clips/ + / + clip.mp4 # 6 s, 180 frames @ 30 fps + labels.csv # one row per frame per track + maneuver_labels.csv # per-frame ground-truth drone action, per maneuver + DATASET_CARD.md +``` + +`clip_id = -