Dataset Versions

v11

2024-03-24 10:22am

Generated on Mar 24, 2024

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.
Other Formats
Choose another format.

Dataset Split

Train Set 79%
258Images
Valid Set 11%
37Images
Test Set 10%
33Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Fit (white edges) in 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 11% Maximum Zoom
Rotation: Between -12° and +12°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -15° and +15°
Saturation: Between -15% and +15%
Brightness: Between -20% and +20%
Exposure: Between -10% and +10%
Blur: Up to 1.6px
Noise: Up to 0.77% of pixels

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