hackathon26 Computer Vision Model
3085 Total Images
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Dataset Split
Train Set 91%
2787Images
Valid Set 6%
195Images
Test Set 3%
103Images
Preprocessing
Auto-Orient: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -10° and +10°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Hue: Between -40° and +40°
Saturation: Between -40% and +40%
Brightness: Between -40% and +40%
Exposure: Between -11% and +11%
Blur: Up to 1.7px
Noise: Up to 2% of pixels