mantar Computer Vision Dataset
442 Total Images
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Dataset Split
Train Set 89%
392Images
Valid Set 9%
40Images
Test Set 2%
10Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 4
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Grayscale: Apply to 15% of images
Hue: Between -15° and +15°
Brightness: Between -15% and +15%
Blur: Up to 2.5px
Noise: Up to 1.33% of pixels