Dataset Versions

v6

2630

Generated on Mar 21, 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 87%
5511Images
Valid Set 8%
529Images
Test Set 4%
261Images

Preprocessing

Auto-Orient: Applied
Static Crop: 22-85% Horizontal Region, 17-100% Vertical Region
Resize: Fit within 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Grayscale: Applied
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -12° and +12°
Shear: ±10° Horizontal, ±13° Vertical
Grayscale: Apply to 15% of images
Hue: Between -14° and +14°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 1.72% of pixels