metadata
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
num_examples: 15000
download_size: 44156942
dataset_size: 45518549
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.