Dataset Versions

v5

2023-05-23 9:55pm

Generated on May 23, 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%
2274Images
Valid Set 8%
216Images
Test Set 4%
115Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Fit (reflect edges) in 720x720
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, 20% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Brightness: Between -25% and +25%
Noise: Up to 5% of pixels
Bounding Box: Flip: Horizontal
Bounding Box: Brightness: Between -25% and +25%