d Image Dataset
Versions
v1
2022-12-27 7:41pm
Generated on Dec 28, 2022
995 Total Images
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Dataset Split
Train Set 96%
954Images
Valid Set 3%
28Images
Test Set 1%
13Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Histogram Equalization
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Saturation: Between -57% and +57%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 4.5px
Noise: Up to 5% of pixels
Cutout: 16 boxes with 10% size each
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