task_categories:image-classification license:mit region:us
---
license: mit
dataset_info:
  features:
  - name: image
    dtype: image
  - name: labels
    dtype:
      class_label:
        names:
          '0': AnnualCrop
          '1': Forest
          '2': HerbaceousVegetation
          '3': Highway
          '4': Industrial
          '5': Pasture
          '6': PermanentCrop
          '7': Residential
          '8': River
          '9': SeaLake
  splits:
  - name: train
    num_bytes: 70666516.8
    num_examples: 21600
  - name: validation
    num_bytes: 8700747.8
    num_examples: 2700
  - name: test
    num_bytes: 8631409.1
    num_examples: 2700
  download_size: 93886613
  dataset_size: 87998673.69999999
task_categories:
- image-classification
---

# Dataset Card for EuroSat

## Table of Contents
- [How to Use](#How-to-Use)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)


## How to Use

- Install [datasets](https://pypi.org/project/datasets/):

```bash
pip install datasets
```
- How to use in Python
```py
from datasets import load_dataset
train_data = load_dataset("Honaker/eurosat_dataset", split="train")
```

## Dataset Description
- **Homepage:** https://zenodo.org/record/7711810#.ZAm3k-zMKEA

### Dataset Summary
EuroSat is an image classification dataset with 10 different classes on satellite imagery. There is over 27,000 labeled images.


## Dataset Structure

The dataset is structured as follows:
```py
DatasetDict({
    train: Dataset({
        features: ['image', 'labels'],
        num_rows: 21600
    })
    validation: Dataset({
        features: ['image', 'labels'],
        num_rows: 2700
    })
    test: Dataset({
        features: ['image', 'labels'],
        num_rows: 2700
    })
})
```

### Data Instances

An example of the data for one image is:
```py
{
 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64>,
 'labels': 0
}
 ```
 
 With the type of each field being defined as:
 ```py
{
 'image': <PIL.JpegImagePlugin.JpegImageFile>,
 'labels': Integer
```
### Data Fields

The dataset has the following fields:

 - 'image': Satellite image that is of type <PIL.TiffImagePlugin.TiffImageFile image>
 - 'labels': the label of the Satellite image as an integer

### Data Splits

|                | Train  | Validation | Test |
|----------------|--------|------------|------|
| Images         | 21600  | 2700       | 2700    |


## Additional Information

### Licensing Information
EuroSat is licensed under a MIT