Dataset Versions

v3

2023-04-24 12:00am

Generated on Apr 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 65%
535Images
Valid Set 4%
34Images
Test Set 31%
253Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Grayscale: Applied
Tile: 2 rows x 2 columns
Modify Classes: 0 remapped, 0 dropped
Filter Null: Require at least 48% of images to contain annotations.

Augmentations

Outputs per training example: 2
Flip: Horizontal
Crop: 0% Minimum Zoom, 34% Maximum Zoom
Rotation: Between -15° and +15°
Grayscale: Apply to 52% of images
Hue: Between -78° and +78°
Saturation: Between -68% and +68%
Brightness: Between -35% and +35%
Blur: Up to 4.5px
Noise: Up to 4% of pixels
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise