Dataset Versions

v3

2023-01-24 5:57pm

Generated on Jan 24, 2023

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%
4255Images
Valid Set 7%
333Images
Test Set 6%
295Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 17-67% Horizontal Region, 23-76% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive 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
Crop: 0% Minimum Zoom, 24% Maximum Zoom
Rotation: Between -36° and +36°
Saturation: Between -27% and +27%
Brightness: Between -36% and +36%
Exposure: Between -37% and +37%
Blur: Up to 1.5px
Noise: Up to 10% of pixels
Cutout: 18 boxes with 9% size each
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise