Datasets:
metadata
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
- Install datasets:
pip install datasets
- How to use in Python
from datasets import load_dataset
train_data = load_dataset("Honaker/eurosat_dataset", split="train")
Dataset Description
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:
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:
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64>,
'labels': 0
}
With the type of each field being defined as:
{
'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