Clytia Hemispherica Segmentation Computer Vision Model
84296 Total Images
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Dataset Split
Train Set 92%
77640Images
Valid Set 5%
4436Images
Test Set 3%
2220Images
Preprocessing
Tile: 2 rows x 2 columns
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Do not filter any null images.
Augmentations
Outputs per training example: 5
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels