Datasets:
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End of preview. Expand in Data Studio
YAML Metadata Warning:The task_categories "multiple-object-tracking" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
UAVSwarm Dataset
Unmanned Aerial Vehicle Swarm dataset for multiple object tracking and detection.
Images are preprocessed with a simulated Monochrome Near-Infrared (NIR) filter
(CLAHE-enhanced, red-channel dominant channel mixing).
- 13 scenes, 19+ UAV types, 12,598 annotated images
- Single class:
uav(id=0) - Bounding boxes in COCO format
[x, y, w, h]
Load
from datasets import load_dataset
dataset = load_dataset("bnina-ayoub/UAV-Swarm")
categories = dataset["train"].features["objects"].feature["category"].names
id2label = {i: c for i, c in enumerate(categories)}
Citation
@article{wang2022uavswarm,
title = {UAVSwarm Dataset: An Unmanned Aerial Vehicle Swarm Dataset for Multiple Object Tracking},
author = {Wang, C. and Su, Y. and Wang, J. and Wang, T. and Gao, Q.},
journal = {Remote Sensing},
volume = {14},
number = {11},
pages = {2601},
year = {2022},
doi = {10.3390/rs14112601}
}
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