Dataset Versions
v3
cgtech_segment_v2
Generated on Jun 28, 2024
67 Total Images
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Dataset Split
Train Set 85%
57Images
Valid Set 7%
5Images
Test Set 7%
5Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Shear: ±11° Horizontal, ±11° Vertical
Saturation: Between -25% and +25%
Brightness: Between -38% and +38%
Exposure: Between -10% and +10%
Blur: Up to 1.6px
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Noise: Up to 1.54% of pixels