S&W detecter Dataset

v2

2023-12-09 11:34pm

Generated on Dec 9, 2023

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Dataset Split

Train Set 87%
1482Images
Valid Set 8%
135Images
Test Set 5%
79Images

Preprocessing

Auto-Orient: Applied
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 -45° and +45°
Shear: ±25° Horizontal, ±25° Vertical
Grayscale: Apply to 20% of images
Hue: Between -12° and +12°
Saturation: Between -20% and +20%
Brightness: Between -20% and +20%
Exposure: Between -20% and +20%
Blur: Up to 7px
Noise: Up to 10% of pixels
Cutout: 10 boxes with 5% size each
Mosaic: Applied

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