README.md

---
license: apache-2.0
metrics:
- accuracy
- f1
base_model:
- google/vit-base-patch16-224-in21k
pipeline_tag: image-classification
library_name: transformers
---
Returns the clothes category with about 78% accuracy based on an image.

See https://www.kaggle.com/code/dima806/clothes-image-detection-vit for details.

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6449300e3adf50d864095b90/nHatsaQxttuXETO_3XM8I.png)

```
Classification report:

               precision    recall  f1-score   support

       Blazer     0.7419    0.6900    0.7150       200
         Coat     0.7512    0.7550    0.7531       200
 Denim Jacket     0.8592    0.9150    0.8862       200
      Dresses     0.8603    0.7700    0.8127       200
       Hoodie     0.6985    0.9500    0.8051       200
       Jacket     0.7686    0.4650    0.5794       200
        Jeans     0.8657    0.8700    0.8678       200
   Long Pants     0.8112    0.7950    0.8030       200
         Polo     0.7929    0.5550    0.6529       200
        Shirt     0.7430    0.7950    0.7681       200
       Shorts     0.9149    0.8600    0.8866       200
        Skirt     0.8102    0.8750    0.8413       200
Sports Jacket     0.6562    0.7350    0.6934       200
      Sweater     0.7758    0.8650    0.8180       200
      T-shirt     0.7743    0.8750    0.8216       200

     accuracy                         0.7847      3000
    macro avg     0.7883    0.7847    0.7803      3000
 weighted avg     0.7883    0.7847    0.7803      3000
```