Dataset Versions

v6

2024-12-18 12:21am

Generated on Dec 17, 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%
3144Images
Valid Set 8%
300Images
Test Set 4%
148Images

Preprocessing

Auto-Orient: Applied
Static Crop: 21-73% Horizontal Region, 7-77% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram 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: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 20% of images
Hue: Between -10° and +10°
Saturation: Between -30% and +30%
Brightness: Between -25% and +25%
Exposure: Between -14% and +14%
Blur: Up to 3px
Noise: Up to 1.92% of pixels
Bounding Box: Brightness: Between -10% and +10%
Bounding Box: Exposure: Between -5% and +5%
Bounding Box: Blur: Up to 1px
Bounding Box: Noise: Up to 0.7% of pixels