sh-zheng/vit-base-patch16-224-in21k-fintuned-SurfaceRoughness
Image Classification
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image
imagewidth (px) 634
1.08k
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class label 3
classes |
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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0RoughnessB
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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1RoughnessC
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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2RoughnessD
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Dataset Card for "SurfaceRoughness"
Dataset Summary
A collection of data representing surface roughness categories of B, C, and D according to ASCE 7-16 26.7.2
Data Structure
An example looks like below:
{'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1041x639>,
'label': 0,}
Data Split
| train | validation | test | |
|---|---|---|---|
| # of examples | 66 | 15 | 9 |
- Downloads last month
- 0
Size of downloaded dataset files:
91.3 MB
Size of the auto-converted Parquet files:
91.3 MB
Number of rows:
90
Models trained or fine-tuned on sh-zheng/SurfaceRoughness