Dataset Versions

v5

ROV_2

Generated on Mar 31, 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%
588Images
Valid Set 8%
53Images
Test Set 4%
27Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-72% Horizontal Region, 30-95% Vertical Region
Resize: Stretch to 416x416
Grayscale: Applied
Auto-Adjust Contrast: Using Adaptive Equalization

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 5% Maximum Zoom
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Brightness: Between -49% and +49%
Blur: Up to 3px
Noise: Up to 11% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Brightness: Between -30% and +30%
Bounding Box: Blur: Up to 10px
Bounding Box: Noise: Up to 8% of pixels