solar cell defect detection using semantic segmentation

Semantic Segmentation

Dataset Versions

v6

version_2

Generated on Mar 1, 2023

Dataset Split

Train Set 88%
1344Images
Valid Set 12%
180Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Grayscale: Applied
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Saturation: Between -5% and +5%
Blur: Up to 0.5px