Dataset Versions

v2

2022-09-01 12:41pm

Generated on Sep 1, 2022

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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 83%
15Images
Valid Set 6%
1Images
Test Set 11%
2Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -45° and +45°
Shear: ±45° Horizontal, ±45° Vertical
Grayscale: Apply to 26% of images
Blur: Up to 4.75px
Cutout: 4 boxes with 32% size each
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 22% Maximum Zoom
Bounding Box: Rotation: Between -45° and +45°
Bounding Box: Shear: ±45° Horizontal, ±45° Vertical
Bounding Box: Blur: Up to 4.25px

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