metadata

license: apache-2.0
task_categories:
  - image-classification
language:
  - en
tags:
  - image
  - shoe-type
  - classification
  - video
  - 10k
  - rgb
size_categories:
  - 1K<n<10K

Shoe-Net-10K Dataset

The Shoe-Net-10K dataset is a curated collection of 10,000 shoe images annotated for multi-class image classification. This dataset is suitable for training deep learning models to recognize different types of shoes from images.

Dataset Details

Total Images: 10,000
Image Size: Varies (typical width range: 94 px to 519 px)
Format: Parquet
Split:
- train: 10,000 images
Modality: Image
License: Apache 2.0

Labels

The dataset includes 5 distinct shoe categories:

labels_list = [
  'Ballet Flat',
  'Boat',
  'Brogue',
  'Clog',
  'Sneaker'
]

Each image is labeled with one of the above shoe types.

Usage

You can load this dataset using the Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Shoe-Net-10K")

Access individual samples as follows:

sample = dataset["train"][0]
image = sample["image"]
label = sample["label"]

Applications

This dataset can be used for:

Image classification
Shoe-type detection
Retail recommendation systems
Style and fashion recognition models