Detect And Classify Instance Segmentation Computer Vision Model
6758 Total Images
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Dataset Split
Train Set 88%
5913Images
Valid Set 8%
563Images
Test Set 4%
282Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 1024x1024
Grayscale: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels