Dataset Versions

v3

augmented-train-from-scratch

Generated on Aug 20, 2021

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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
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Dataset Split

Train Set 88%
948Images
Valid Set 8%
90Images
Test Set 4%
45Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 416x416
Modify Classes: 8 remapped, 0 dropped

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 77% Maximum Zoom
Rotation: Between -45° and +45°
Shear: ±15° Horizontal, ±15° Vertical
Hue: Between -22° and +22°
Saturation: Between -27% and +27%
Brightness: Between -33% and +33%
Exposure: Between -25% and +25%
Blur: Up to 3px
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Mosaic: Applied
Bounding Box: Brightness: Between -25% and +25%

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