Bingsu/Cat_and_Dog

---
language:
- en
license:
- cc0-1.0
pretty_name: Cat and Dog
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- image-classification
dataset_info:
features:
- name: image
dtype: image
- name: labels
dtype:
class_label:
names:
'0': cat
'1': dog
splits:
- name: train
num_bytes: 166451650.0
num_examples: 8000
- name: test
num_bytes: 42101650.0
num_examples: 2000
download_size: 227859268
dataset_size: 208553300.0
size_in_bytes: 436412568.0
---

## Dataset Description
- **Homepage:** [Cat and Dog](https://www.kaggle.com/datasets/tongpython/cat-and-dog)
- **Download Size** 217.30 MiB
- **Generated Size** 198.89 MiB
- **Total Size** 416.20 MiB

### Dataset Summary

A dataset from [kaggle](https://www.kaggle.com/datasets/tongpython/cat-and-dog) with duplicate data removed.

### Data Fields

The data instances have the following fields:
- `image`: A `PIL.Image.Image` object containing the 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]`.
- `labels`: an `int` classification label.

### Class Label Mappings:

```
{
"cat": 0,
"dog": 1,
}
```

### Data Splits
| | train | test |
|---------------|-------|-----:|
| # of examples | 8000 | 2000 |

```python
>>> from datasets import load_dataset

>>> dataset = load_dataset("Bingsu/Cat_and_Dog")
>>> dataset
DatasetDict({
train: Dataset({
features: ['image', 'labels'],
num_rows: 8000
})
test: Dataset({
features: ['image', 'labels'],
num_rows: 2000
})
})

>>> dataset["train"].features
{'image': Image(decode=True, id=None), 'labels': ClassLabel(num_classes=2, names=['cat', 'dog'], id=None)}
```

原始信息汇总

数据集概述

基本信息

• 名称: Cat and Dog
• 语言: 英语
• 许可证: CC0-1.0
• 大小: 1K<n<10K
• 来源: 原始数据
• 任务类别: 图像分类

数据集特征

• image: 图像数据类型
• labels: 分类标签，包含两个类别：
  • 0: cat
  • 1: dog

数据分割

• 训练集:
  • 示例数量: 8000
  • 字节数: 166451650.0
• 测试集:
  • 示例数量: 2000
  • 字节数: 42101650.0

数据集大小

• 下载大小: 227859268字节
• 数据集大小: 208553300.0字节
• 总大小: 436412568.0字节