Dataset Versions

v1

2022-07-12 5:52pm

Generated on Jul 12, 2022

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 85%
1722Images
Valid Set 9%
188Images
Test Set 5%
111Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-48% Horizontal Region, 25-58% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
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
Crop: 0% Minimum Zoom, 14% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Saturation: Between -25% and +25%
Blur: Up to 10px
Cutout: 8 boxes with 10% size each
Mosaic: Applied