USM

SIDEAM

Object Detection

SIDEAM Image Dataset

v2

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Generated on May 23, 2022

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.
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Dataset Split

Train Set 88%
6240Images
Valid Set 8%
594Images
Test Set 4%
297Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 416x416
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Filter Null: Require at least 59% of images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Grayscale: Apply to 30% of images
Brightness: Between -44% and +44%
Blur: Up to 1.75px
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Brightness: Between -36% and +36%
Bounding Box: Blur: Up to 14.25px
Bounding Box: Noise: Up to 5% of pixels