Dataset Versions

v3

labelAssist-v2-478rawImages-RoboflowTrain-FastModel

Generated on Mar 26, 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 96%
3330Images
Valid Set 3%
93Images
Test Set 1%
52Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640
Modify Classes: 2 remapped, 0 dropped

Augmentations

Outputs per training example: 10
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 15% Maximum Zoom
Rotation: Between -10° and +10°
Shear: ±3° Horizontal, ±3° Vertical
Grayscale: Apply to 10% of images
Hue: Between -20° and +20°
Saturation: Between -20% and +20%
Brightness: Between -20% and +20%
Exposure: Between -10% and +10%
Blur: Up to 0.75px
Noise: Up to 1% of pixels
Cutout: 5 boxes with 2% size each

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