SDNET2018\D\CD\PUB Dataset

v3

2022-05-19 11:50am

Generated on May 19, 2022

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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.
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Dataset Split

Train Set 88%
732Images
Valid Set 9%
72Images
Test Set 4%
31Images

Preprocessing

Auto-Orient: Applied
Static Crop: 10-90% Horizontal Region, 10-90% Vertical Region
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Grayscale: Apply to 25% of images
Brightness: Between -25% and +25%
Exposure: Between -15% and +15%
Blur: Up to 0.25px
Noise: Up to 1% of pixels
Cutout: 1 boxes with 10% size each
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise