Dataset Versions

v2

2024-02-15 6:09pm

Generated on Feb 15, 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.
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Dataset Split

Train Set 88%
324Images
Valid Set 8%
28Images
Test Set 4%
16Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Shear: ±27° Horizontal, ±24° Vertical
Grayscale: Apply to 15% of images
Hue: Between -44° and +44°
Saturation: Between -69% and +69%
Brightness: Between -48% and +48%
Blur: Up to 1.6px
Noise: Up to 1.05% of pixels
Mosaic: Applied
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Noise: Up to 0.1% of pixels

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