Dataset Versions

v2

2024-09-11 11:53am

Generated on Sep 11, 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%
4338Images
Valid Set 8%
411Images
Test Set 5%
253Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 16% of images
Blur: Up to 2.5px
Noise: Up to 1.92% of pixels
Cutout: 7 boxes with 16% size each
Bounding Box: Shear: ±12° Horizontal, ±12° Vertical
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.34% of pixels