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drone-detection-second-variation Computer Vision Dataset

byKilobiteTask:

Object Detection

License:CC BY 4.0

Dataset Version

v1

2025-11-18 11:54pm

Generated on Nov 18, 2025

Notes: поворот горизонтальный, вертикальный, поворот на 90 градусов, по часовой, против часовой стрелки, вверх ногами, вращение от -45 до 45 градусов, сдвиг от -45 до 45 по горизонтали и от -45 до 45 градусов по вертикали, насыщенность от -38 до 38 процентов, яркость от -37 до 37 процентов, воздействие освещенности местности от -37 до 37 процентов, размытие до 4.3 пикселя, шум до 10 процентов пикселей.

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Popular Download Formats

TXT annotations and YAML config used with YOLO26.

TXT annotations and YAML config used with YOLOv12.

TXT annotations and YAML config used with YOLOv11.

TXT annotations and YAML config used with YOLOv9.

TXT annotations and YAML config used with YOLOv8.

TXT annotations and YAML config used with YOLOv5.

TXT annotations and YAML config used with YOLOv7.

COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.

Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.

Common XML annotation format for local data munging (pioneered by ImageNet).

TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.

PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.

CreateML JSON format is used with Apple's CreateML and Turi Create tools.

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3285 Total Images

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Dataset Split

Train Set 92%

3036Images

Valid Set 5%

149Images

Test Set 3%

100Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 900x900

Augmentations

Outputs per training example: 3

Flip: Horizontal, Vertical

90° Rotate: Clockwise, Counter-Clockwise, Upside Down

Rotation: Between -45° and +45°

Shear: ±45° Horizontal, ±45° Vertical

Saturation: Between -38% and +38%

Brightness: Between -37% and +37%

Exposure: Between -37% and +37%

Blur: Up to 4.3px

Noise: Up to 10% of pixels

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