license:apache-2.0 format:parquet library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: apache-2.0
dataset_info:
  features:
  - name: image
    dtype: 'null'
  - name: label
    dtype: 'null'
  splits:
  - name: train
    num_bytes: 0
    num_examples: 0
  download_size: 720
  dataset_size: 0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Artwork Dataset

## Overview

This dataset contains images of artworks from various art movements. It is designed to help in training generative models to create new artwork pieces inspired by different art styles. The dataset includes images categorized into five major art movements:

- Renaissance
- Impressionism
- Cubism
- Surrealism
- Abstract

## Dataset Structure

The dataset is organized into subdirectories, each representing an art movement. The images are stored in the following format:

artwork_dataset/
renaissance_art/
renaissance_art_0001.jpg
renaissance_art_0002.jpg
...
impressionism_art/
impressionism_art_0001.jpg
impressionism_art_0002.jpg
...
cubism_art/
cubism_art_0001.jpg
...
surrealism_art/
surrealism_art_0001.jpg
...
abstract_art/
abstract_art_0001.jpg
...


Each subdirectory contains images related to a specific art style. Images are named sequentially for consistent organization.

## Dataset Details

- **Total Number of Images**: [Insert Total Number of Images]
- **Number of Images per Art Style**: Approximately [Insert Number of Images per Art Style]
- **Image Format**: JPEG
- **Image Size**: Varies

## Purpose

This dataset is intended for use in training generative models such as GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders) to create new and diverse artwork. It can also be used for tasks such as style transfer, artistic style classification, and more.

## Usage

To use this dataset, you can load it using the `datasets` library from Hugging Face or manually access the images from the provided directories.

### Example Code to Load Dataset

```python
from datasets import load_dataset

dataset = load_dataset("your_huggingface_username/artwork_dataset")
