lewtun/dog_food

---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: Dog vs Food Dataset
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
---

# Dataset Card for the Dog 🐶 vs. Food 🍔 (a.k.a. Dog Food) Dataset

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:**: https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-
- **Repository:** : https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-
- **Paper:** : N/A
- **Leaderboard:**: N/A
- **Point of Contact:**: @sasha

### Dataset Summary

This is a dataset for multiclass image classification, between 'dog', 'chicken', and 'muffin' classes.

The 'dog' class contains images of dogs that look like fried chicken and some that look like images of muffins, while the 'chicken' and 'muffin' classes contains images of (you guessed it) fried chicken and muffins 😋

### Supported Tasks and Leaderboards

TBC

### Languages

The labels are in English (['dog', 'chicken', 'muffin'])

## Dataset Structure

### Data Instances
A sample from the training set is provided below:

```
{
{'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=300x470 at 0x7F176094EF28>,
'label': 0}

}
```

### Data Fields

- img: A `PIL.JpegImageFile` object containing the 300x470. image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
- label: 0-1 with the following correspondence
0 dog
1 food

### Data Splits

Train (1875 images) and Test (625 images)

## Dataset Creation

### Curation Rationale

N/A

### Source Data

#### Initial Data Collection and Normalization

This dataset was taken from the [qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins?](https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-) Github repository and randomly splitting 25% of the data for validation.

### Annotations

#### Annotation process

This data was scraped from the internet and annotated based on the query words.

### Personal and Sensitive Information

N/A

## Considerations for Using the Data

### Social Impact of Dataset

N/A

### Discussion of Biases

This dataset is balanced -- it has an equal number of images of dogs (1000) compared to chicken (1000 and muffin (1000). This should be taken into account when evaluating models.

### Other Known Limitations

N/A

## Additional Information

### Dataset Curators

This dataset was created by @lanceyjt, @yl3829, @wesleytao, @qw2243c and @asyouhaveknown

### Licensing Information

No information is indicated on the original [github repository](https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-).

### Citation Information

N/A

### Contributions

Thanks to [@lewtun](https://github.com/lewtun) for adding this dataset.

原始信息汇总

数据集概述

数据集基本信息

• 名称: Dog vs Food Dataset
• 语言: 英语 (en)
• 许可证: 未知
• 多语言性: 单语
• 大小: 1K<n<10K
• 来源: 原始数据
• 任务类别: 图像分类
• 任务ID: 多类图像分类

数据集描述

数据集摘要

• 目的: 用于多类图像分类，区分dog, chicken, muffin三个类别。
• 内容: dog类包含看起来像炸鸡和松饼的狗的图像，chicken和muffin类包含炸鸡和松饼的图像。

支持的任务和排行榜

• 任务: 多类图像分类
• 排行榜: 未提供

语言

• 标签语言: 英语 ([dog, chicken, muffin])

数据集结构

数据实例

• 示例: 包含图像和标签的数据实例。

数据字段

• 图像: 300x470像素的图像文件。
• 标签: 0代表dog，1代表food。

数据分割

• 分割: 训练集1875张图像，测试集625张图像。

数据集创建

源数据

• 来源: 从GitHub仓库qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins获取，随机分割25%数据用于验证。

注释

• 注释过程: 数据从互联网上抓取，并根据查询词进行标注。

使用数据注意事项

偏见讨论

• 平衡性: 数据集平衡，包含等量的狗、鸡和松饼图像各1000张。

附加信息

数据集创建者

• 创建者: @lanceyjt, @yl3829, @wesleytao, @qw2243c, @asyouhaveknown

许可证信息

• 许可证: 未在原始GitHub仓库中指明。