eurosat
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EuroSAT dataset is based on Sentinel-2 satellite images covering 13 spectral
bands and consisting of 10 classes with 27000 labeled and geo-referenced
samples.
Two datasets are offered: - rgb: Contains only the optical R, G, B frequency
bands encoded as JPEG image. - all: Contains all 13 bands in the original value
range (float32).
URL: https://github.com/phelber/eurosat
Split |
Examples |
'train' |
27,000 |
@misc{helber2017eurosat,
title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
author={Patrick Helber and Benjamin Bischke and Andreas Dengel and Damian Borth},
year={2017},
eprint={1709.00029},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
eurosat/rgb (default config)
FeaturesDict({
'filename': Text(shape=(), dtype=string),
'image': Image(shape=(64, 64, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
filename |
Text |
|
string |
|
image |
Image |
(64, 64, 3) |
uint8 |
|
label |
ClassLabel |
|
int64 |
|

eurosat/all
FeaturesDict({
'filename': Text(shape=(), dtype=string),
'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
'sentinel2': Tensor(shape=(64, 64, 13), dtype=float32),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
filename |
Text |
|
string |
|
label |
ClassLabel |
|
int64 |
|
sentinel2 |
Tensor |
(64, 64, 13) |
float32 |
|
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Last updated 2022-12-06 UTC.
[null,null,["Last updated 2022-12-06 UTC."],[],[],null,["# eurosat\n\n\u003cbr /\u003e\n\n- **Description**:\n\nEuroSAT dataset is based on Sentinel-2 satellite images covering 13 spectral\nbands and consisting of 10 classes with 27000 labeled and geo-referenced\nsamples.\n\nTwo datasets are offered: - rgb: Contains only the optical R, G, B frequency\nbands encoded as JPEG image. - all: Contains all 13 bands in the original value\nrange (float32).\n\nURL: \u003chttps://github.com/phelber/eurosat\u003e\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/eurosat)\n\n- **Homepage** :\n \u003chttps://github.com/phelber/eurosat\u003e\n\n- **Source code** :\n [`tfds.image_classification.Eurosat`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/image_classification/eurosat.py)\n\n- **Versions**:\n\n - **`2.0.0`** (default): No release notes.\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 27,000 |\n\n- **Citation**:\n\n @misc{helber2017eurosat,\n title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},\n author={Patrick Helber and Benjamin Bischke and Andreas Dengel and Damian Borth},\n year={2017},\n eprint={1709.00029},\n archivePrefix={arXiv},\n primaryClass={cs.CV}\n }\n\neurosat/rgb (default config)\n----------------------------\n\n- **Config description**: Sentinel-2 RGB channels\n\n- **Download size** : `89.91 MiB`\n\n- **Dataset size** : `89.50 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Feature structure**:\n\n FeaturesDict({\n 'filename': Text(shape=(), dtype=string),\n 'image': Image(shape=(64, 64, 3), dtype=uint8),\n 'label': ClassLabel(shape=(), dtype=int64, num_classes=10),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|----------|--------------|-------------|--------|-------------|\n| | FeaturesDict | | | |\n| filename | Text | | string | |\n| image | Image | (64, 64, 3) | uint8 | |\n| label | ClassLabel | | int64 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('image', 'label')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\neurosat/all\n-----------\n\n- **Config description**: 13 Sentinel-2 channels\n\n- **Download size** : `1.93 GiB`\n\n- **Dataset size** : `5.36 GiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Feature structure**:\n\n FeaturesDict({\n 'filename': Text(shape=(), dtype=string),\n 'label': ClassLabel(shape=(), dtype=int64, num_classes=10),\n 'sentinel2': Tensor(shape=(64, 64, 13), dtype=float32),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|-----------|--------------|--------------|---------|-------------|\n| | FeaturesDict | | | |\n| filename | Text | | string | |\n| label | ClassLabel | | int64 | |\n| sentinel2 | Tensor | (64, 64, 13) | float32 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('sentinel2', 'label')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]