Dataset Versions

v6

2023-10-08 11:56am

Generated on Oct 8, 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%
1674Images
Valid Set 8%
163Images
Test Set 5%
91Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require at least 1% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Rotation: Between -27° and +27°
Grayscale: Apply to 67% of images
Saturation: Between -59% and +59%
Brightness: Between -63% and +63%
Blur: Up to 1.75px
Noise: Up to 5% of pixels
Bounding Box: Brightness: Between -65% and +65%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 5% of pixels

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