Dataset Versions

v8

2022-09-29 7:11am

Generated on Sep 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 87%
6504Images
Valid Set 9%
656Images
Test Set 5%
356Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 29-76% Horizontal Region, 19-66% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 25% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±24° Horizontal, ±24° Vertical
Grayscale: Apply to 15% of images
Hue: Between -180° and +180°
Saturation: Between -96% and +96%
Brightness: Between -25% and +25%
Exposure: Between -50% and +50%
Blur: Up to 2.75px
Noise: Up to 6% of pixels
Mosaic: Applied
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical

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