Brad Dwyer

Greyhound Example

Object Detection

Greyhound Example Image Dataset

v6

2022-12-07 12:46pm

Generated on Dec 7, 2022

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Dataset Split

Train Set 96%
400Images
Valid Set 3%
11Images
Test Set 2%
7Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 10
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -5° and +5°
Shear: ±3° Horizontal, ±3° Vertical
Grayscale: Apply to 3% of images
Hue: Between -10° and +10°
Saturation: Between -10% and +10%
Brightness: Between -10% and +10%
Exposure: Between -5% and +5%