Dataset Versions

v3

Unadjusted TrainTestSpit w-Augments

Generated on Aug 20, 2024

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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.
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Dataset Split

Train Set 92%
8871Images
Valid Set 5%
504Images
Test Set 2%
234Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 30% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 20% of images
Hue: Between -25° and +25°
Saturation: Between -34% and +34%
Brightness: Between -25% and +25%
Exposure: Between -15% and +15%
Blur: Up to 4.9px
Noise: Up to 1.88% of pixels

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