OnePiece_Characters / README.md
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---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 145592052
num_examples: 294
download_size: 145391733
dataset_size: 145592052
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
language:
- en
task_categories:
- text-to-image
pretty_name: One Piece Characters
size_categories:
- n<1K
---
# Dataset Card for One Piece Image Dataset
## Metadata
* **Identifier:** `OnePiece_Characters`
* **Contributions:** Mohd Hozaifa Khan
* **License:** apache-2.0
## Dataset Description
This dataset contains images of famous One Piece characters scraped from the web using simple image search. It includes approximately 15 images per character for a total of 20 characters.
## Intended Use
This dataset is intended for educational and research purposes, including:
* **Image classification:** Train models to recognize different One Piece characters.
* **Image generation:** Fine-tune text-to-image models to generate images of One Piece characters.
<!-- ## Format
The dataset is organized as follows:
* **Data Folder:** `one_piece_images`
* `train`: Contains all the images, named as `character_name_index.jpg`.
* **Metadata File:** `metadata.jsonl`
* Contains metadata for each image, with each line being a JSON object containing:
* `file_name`: The name of the image file. (type: string)
* `text`: A caption or description of the image. (type: string) -->
## Features
* **image (jpg):** The image of the One Piece character. (expected type: PIL Image, JPG format)
* **text (str):** A caption or description of the image. (expected type: string)
#TODO: Add image samples
<!-- ## Slices
The dataset is split into a single training split (`train`).
-->
## Acknowledgements
This dataset uses images primarily from Google Images. Used `simple_image_download` for downloading images using character queries.
## BibTeX citation
```bibtex
@misc{OnePiece_Characters,
title={One Piece Characters Image Dataset},
author={khanitachi},
year={2024}
}