Dataset Versions

v3

2024-10-16 5:51pm

Generated on Oct 16, 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 80%
1056Images
Valid Set 10%
134Images
Test Set 10%
134Images

Preprocessing

Auto-Orient: Applied
Static Crop: 0-100% Horizontal Region, 0-100% Vertical Region
Resize: Stretch to 640x640
Filter Null: Require at least 70% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -33% and +33%
Brightness: Between -23% and +23%
Exposure: Between -14% and +14%
Blur: Up to 1.1px
Noise: Up to 1.76% of pixels
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Brightness: Between -7% and +7%
Bounding Box: Exposure: Between -1% and +1%
Bounding Box: Blur: Up to 0.6px
Bounding Box: Noise: Up to 0.18% of pixels

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