Dataset Versions

v3

Full augmentations

Generated on Oct 4, 2023

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Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
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Dataset Split

Train Set 67%
5367Images
Valid Set 11%
899Images
Test Set 22%
1800Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -26° and +26°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 46% of images
Saturation: Between -60% and +60%
Brightness: Between -51% and +51%
Exposure: Between -48% and +48%
Blur: Up to 2.25px
Noise: Up to 10% of pixels
Mosaic: Applied

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