Dataset Versions

v3

2022-10-03 7:16pm

Generated on Oct 3, 2022

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 70%
660Images
Valid Set 20%
192Images
Test Set 10%
94Images

Preprocessing

Auto-Orient: Applied
Static Crop: 9-82% Horizontal Region, 30-95% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Histogram Equalization
Grayscale: Applied
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 1
Flip: Horizontal, Vertical
Rotation: Between -22° and +22°
Shear: ±15° Horizontal, ±5° Vertical
Hue: Between -19° and +19°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 1.5px
Noise: Up to 4% of pixels
Cutout: 5 boxes with 20% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal

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