---
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:

```python
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:

```python
from datasets import load_dataset

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

Access individual samples as follows:

```python
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