People_model Dataset

v3

2023-03-10 4:34pm

Generated on Mar 10, 2023

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Dataset Split

Train Set 75%
12Images
Valid Set 6%
1Images
Test Set 19%
3Images

Preprocessing

Auto-Orient: Applied
Auto-Adjust Contrast: Using Histogram Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 30% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Hue: Between -25° and +25°
Brightness: Between -25% and +25%
Blur: Up to 2.5px
Cutout: 3 boxes with 10% size each

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