
## 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)}
```
task_categories:image-classification size_categories:1K<n<10K source_datasets:original language:en license:cc0-1.0 region:us
{"language": ["en"], "license": ["cc0-1.0"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["image-classification"], "pretty_name": "Cat and Dog", "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}}
TAGS
#task_categories-image-classification #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc0-1.0 #region-us 

Dataset Description
-------------------


* Homepage: Cat and Dog
* Download Size 217.30 MiB
* Generated Size 198.89 MiB
* Total Size 416.20 MiB


### Dataset Summary


A dataset from kaggle 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:


### Data Splits




### Dataset Summary


A dataset from kaggle 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: ### Data Splits
TAGS
#task_categories-image-classification #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc0-1.0 #region-us 
 ### Dataset Summary


A dataset from kaggle 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: ### Data Splits