Dataset Versions

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2023-11-15 10:08am
v9
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a year ago
2023-11-13 8:04pm
v8
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a year ago
2023-11-12 5:21pm
v7
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a year ago
2023-11-12 2:13pm
v6
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a year ago
2023-11-12 2:08pm
v5
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a year ago
2023-11-12 2:01pm
v4
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a year ago
2023-11-12 12:11pm
v3
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a year ago
2023-11-04 4:14pm
v2
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a year ago
2023-11-04 1:31pm
v1
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a year ago
v6

2023-11-12 2:13pm

Generated on Nov 12, 2023
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96 Total Images

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Dataset Split

Train Set 86%
83Images
Valid Set 8%
8Images
Test Set 5%
5Images

Preprocessing

Auto-Orient: Applied
Filter Null: Require at least 80% of images to contain annotations.

Augmentations

Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Saturation: Between -56% and +56%

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