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vitra_tile

Classification

vitra_tile Image Dataset

Versions
2022-07-21 1:17pm
v15
Jul 21, 2022
2022-07-21 1:15pm
v14
Jul 21, 2022
2022-07-21 1:14pm
v13
Jul 21, 2022
2022-07-21 1:12pm
v12
Jul 21, 2022
2022-07-21 1:12pm
v11
Jul 21, 2022
2022-07-21 1:11pm
v10
Jul 21, 2022
2022-07-21 1:10pm
v9
Jul 21, 2022
2022-07-21 1:07pm
v8
Jul 21, 2022
2022-07-21 1:06pm
v7
Jul 21, 2022
2022-07-21 1:06pm
v6
Jul 21, 2022
2022-07-21 1:05pm
v5
Jul 21, 2022
2022-07-15 3:44pm
v4
Jul 15, 2022
2022-07-15 2:08pm
v3
Jul 15, 2022
2022-07-06 6:37pm
v2
Jul 6, 2022
2022-07-06 2:31pm
v1
Jul 6, 2022
v4

2022-07-15 3:44pm

Generated on Jul 15, 2022
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2784 Total Images

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Dataset Split

Train Set 100%
2784Images
Valid Set %
0Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Auto-Adjust Contrast: Using Contrast Stretching
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Shear: ±15° Horizontal, ±15° Vertical
Hue: Between -19° and +19°
Saturation: Between -20% and +20%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 5.25px
Noise: Up to 2% of pixels