Datasets:

blackbeedrones
/

medicalkit-drone-dataset

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MedicalKitDrone v3 Detection Dataset

Object detection dataset for medical kit drone delivery missions. Two classes: 'Package' (the medical kit) and 'Base' (the landing/dropoff pad).

Dataset Structure

Split	Images
train	1000
validation	250

Total images: 1250

Classes: base, package

Annotation format: COCO bbox [x_min, y_min, width, height].

Usage

Load with HuggingFace Datasets

from datasets import load_dataset

dataset = load_dataset("blackbeedrones/medicalkit-drone-dataset")
example = dataset["train"][0]
print(example["objects"])

Use with Nectar SDK

from nectar.ai.detection.datasets import HuggingFaceHandler

handler = HuggingFaceHandler("data/local")
handler.download(repo_id="blackbeedrones/medicalkit-drone-dataset", format_type="coco")
# data/local now contains train/_annotations.coco.json and image files

Downloads last month: 94