YOLOV5-classification Dataset
Versions
v1
2022-11-06 1:00pm
Generated on Nov 6, 2022
30 Total Images
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Dataset Split
Train Set 70%
21Images
Valid Set 20%
6Images
Test Set 10%
3Images
Preprocessing
Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Grayscale: Applied
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 1
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%