Hard-soft object Detection Dataset

v3

2024-03-19 9:15pm

Generated on Mar 19, 2024

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Dataset Split

Train Set 92%
12Images
Valid Set 8%
1Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Dynamic Crop: Class: hard
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Rotation: Between -6° and +6°
Shear: ±8° Horizontal, ±4° Vertical
Saturation: Between -14% and +14%
Blur: Up to 0.7px
Noise: Up to 1.45% of pixels
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Bounding Box: Rotation: Between -18° and +18°
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Noise: Up to 0.86% of pixels