Dataset Versions

v11

2024-11-07 9:22am

Generated on Nov 7, 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 86%
10653Images
Valid Set 9%
1065Images
Test Set 5%
647Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-67% Horizontal Region, 25-76% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Grayscale: Applied
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±5° Horizontal, ±9° Vertical
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -14% and +14%
Exposure: Between -10% and +10%
Blur: Up to 1px
Noise: Up to 0.22% of pixels