FAU Smart Streetscapes

Raccoon Detector

Object Detection

Raccoon Detector Image Dataset

v4

DiverseRaccoonModelv1

Generated on Jan 18, 2024

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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.
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Dataset Split

Train Set 90%
7266Images
Valid Set 6%
517Images
Test Set 4%
309Images

Preprocessing

Auto-Orient: Applied
Resize: Fit (reflect edges) in 640x640
Auto-Adjust Contrast: Using Histogram Equalization

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -10° and +10°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 10% of images
Hue: Between -10° and +10°
Saturation: Between -10% and +10%
Brightness: Between -10% and +10%