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2023-11-07 5:01pm
v10
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a year ago
2023-11-07 1:08pm
v9
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a year ago
2023-11-07 4:58am
v8
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a year ago
2023-11-07 4:52am
v7
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a year ago
2023-11-07 2:00am
v6
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a year ago
2023-10-26 12:43pm
v5
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a year ago
2023-10-26 10:02am
v4
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a year ago
2023-10-25 4:37pm
v3
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a year ago
2023-10-24 1:47pm
v2
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a year ago
2023-08-03 9:31am
v1
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a year ago
v4

2023-10-26 10:02am

Generated on Oct 26, 2023
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3987 Total Images

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Dataset Split

Train Set 88%
3489Images
Valid Set 8%
332Images
Test Set 4%
166Images

Preprocessing

Resize: Stretch to 200x200
Auto-Adjust Contrast: Using Histogram Equalization

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
Grayscale: Apply to 25% of images
Hue: Between -80° and +80°
Saturation: Between -58% and +58%
Brightness: Between -32% and +0%
Exposure: Between -19% and +19%
Blur: Up to 0.75px
Noise: Up to 5% of pixels
Cutout: 9 boxes with 8% size each
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: Brightness: Between -25% and +25%
Bounding Box: Exposure: Between -4% and +4%
Bounding Box: Blur: Up to 0.5px
Bounding Box: Noise: Up to 1% of pixels

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