Dataset Versions

v12

2023-08-23 6:28pm

Generated on Aug 23, 2023

Popular Download Formats

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 88%
396Images
Valid Set 9%
40Images
Test Set 3%
14Images

Preprocessing

Static Crop: 20-80% Horizontal Region, 0-70% Vertical Region
Resize: Fit (black edges) in 1600x900
Auto-Adjust Contrast: Using Histogram Equalization
Grayscale: Applied

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Grayscale: Apply to 70% of images
Hue: Between -44° and +44°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 1.75px
Noise: Up to 2% of pixels
Cutout: 10 boxes with 3% size each

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