Dataset Versions

v4

2024-12-11 1:23pm

Generated on Dec 11, 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
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Dataset Split

Train Set 88%
7074Images
Valid Set 8%
675Images
Test Set 4%
333Images

Preprocessing

Auto-Orient: Applied
Static Crop: 19-74% Horizontal Region, 7-79% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 3 rows x 3 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -10° and +10°
Shear: ±12° Horizontal, ±11° Vertical
Grayscale: Apply to 18% of images
Hue: Between -10° and +10°
Saturation: Between -29% and +29%
Brightness: Between -12% and +12%
Exposure: Between -13% and +13%
Blur: Up to 2.2px
Noise: Up to 1.76% of pixels
Bounding Box: Rotation: Between -12° and +12°
Bounding Box: Shear: ±6° Horizontal, ±7° Vertical
Bounding Box: Brightness: Between -17% and +17%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 2px
Bounding Box: Noise: Up to 0.74% of pixels