---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Boot
          '1': Sandal
          '2': Shoe
  splits:
  - name: train
    num_bytes: 45518549.0
    num_examples: 15000
  download_size: 44156942
  dataset_size: 45518549.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

## Context
This Shoe vs Sandal vs Boot Image Dataset contains 15,000 images of shoes, sandals and boots. 5000 images for each category. The images have a resolution of 136x102 pixels in RGB color model.

## Content
There are three classes here.
- Shoe
- Sandal
- Boot

## Inspiration
This dataset is ideal for performing multiclass classification with deep neural networks like CNNs.
You can use Tensorflow, Keras, Sklearn, PyTorch or other deep/machine learning libraries to build a model from scratch or as an alternative, you can fetch pretrained models as well as fine-tune them.