Dataset Versions

v3

2023-12-27 8:58pm

Generated on Dec 27, 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%
159Images
Valid Set 10%
19Images
Test Set 2%
4Images

Preprocessing

Auto-Orient: Applied
Static Crop: 0-46% Horizontal Region, 31-95% Vertical Region
Auto-Adjust Contrast: Using Contrast Stretching
Modify Classes: 5 remapped, 0 dropped
Filter Null: Require at least 50% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -28° and +28°
Grayscale: Apply to 70% of images
Hue: Between -78° and +78°
Saturation: Between -71% and +71%
Brightness: Between -59% and +59%
Exposure: Between -46% and +46%
Blur: Up to 12px
Noise: Up to 14% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 11% of pixels