Dataset Versions

v4

2023-05-30 7:17pm

Generated on May 30, 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 77%
3129Images
Valid Set 10%
409Images
Test Set 13%
516Images

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 Adaptive Equalization
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
Rotation: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Exposure: Between -25% and +25%
Bounding Box: Noise: Up to 5% of pixels