Dataset Versions

v1

2024-10-13 4:37pm

Generated on Oct 13, 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%
3840Images
Valid Set 8%
372Images
Test Set 5%
208Images

Preprocessing

Auto-Orient: Applied
Resize: Fit within 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns
Filter Null: Require at least 70% of images to contain annotations.

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -25° and +25°
Saturation: Between -34% and +34%
Brightness: Between -20% and +20%
Exposure: Between -15% and +15%
Blur: Up to 2.5px
Noise: Up to 1.99% of pixels