Jimma university 1

KIDNEY STONE DETECTION

Object Detection

KIDNEY STONE DETECTION Image Dataset

v2

2023-06-29 7:28am

Generated on Jun 29, 2023

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Dataset Split

Train Set 90%
5469Images
Valid Set 6%
335Images
Test Set 4%
249Images

Preprocessing

Auto-Orient: Applied
Static Crop: 28-69% Horizontal Region, 33-78% Vertical Region
Resize: Stretch to 250x250
Grayscale: Applied
Modify Classes: 0 remapped, 1 dropped

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 18% Maximum Zoom
Rotation: Between -8° and +8°
Shear: ±9° Horizontal, ±22° Vertical
Grayscale: Apply to 25% of images
Hue: Between -180° and +180°
Saturation: Between -61% and +61%
Brightness: Between -67% and +67%
Exposure: Between -5% and +5%
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 33% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±15° Horizontal, ±7° Vertical
Bounding Box: Brightness: Between -64% and +64%
Bounding Box: Exposure: Between -25% and +25%