Dataset Versions

v3

Augmented_v1

Generated on Sep 28, 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%
1044Images
Valid Set 8%
99Images
Test Set 4%
52Images

Preprocessing

Auto-Orient: Applied
Static Crop: 0-100% Horizontal Region, 3-96% Vertical Region
Tile: 2 rows x 2 columns
Filter Null: Require at least 90% of images to contain annotations.

Augmentations

Outputs per training example: 3
Rotation: Between -45° and +45°
Shear: ±15° Horizontal, ±15° Vertical
Saturation: Between -30% and +30%
Blur: Up to 5px
Noise: Up to 10% of pixels
Bounding Box: Brightness: Between -20% and +20%