main experiment 2 Computer Vision Model
Versions
1056 Total Images
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Dataset Split
Train Set 96%
1011Images
Valid Set 4%
44Images
Test Set 0%
1Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 576x576
Auto-Adjust Contrast: Using Histogram Equalization
Modify Classes: 0 remapped, 6 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -20% and +20%
Exposure: Between -10% and +10%
Noise: Up to 1% of pixels
Mosaic: Applied