classification Computer Vision Model
13768 Total Images
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Dataset Split
Train Set 88%
12048Images
Valid Set 8%
1148Images
Test Set 4%
572Images
Preprocessing
Tile: 2 rows x 2 columns
Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Modify Classes: 0 remapped, 1 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 26% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -20° and +20°
Saturation: Between -34% and +34%
Brightness: Between -25% and +25%
Exposure: Between -15% and +15%
Blur: Up to 1.2px
Noise: Up to 1.96% of pixels