Dataset Versions

v4

2022-08-30 12:55am

Generated on Aug 29, 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.
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Dataset Split

Train Set 89%
4138Images
Valid Set 5%
245Images
Test Set 5%
252Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 416x416

Augmentations

Outputs per training example: 2
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -45° and +45°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 50% of images
Hue: Between -180° and +180°
Saturation: Between -50% and +50%
Brightness: Between -50% and +50%
Exposure: Between -5% and +5%
Blur: Up to 1px
Noise: Up to 1% of pixels
Cutout: 10 boxes with 4% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -10% and +10%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 1px
Bounding Box: Noise: Up to 1% of pixels

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