Duplicate from blanchon/EuroSAT_RGB

Co-authored-by: Julien BLANCHON <blanchon@users.noreply.huggingface.co>

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README.md

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+---
+language: en
+license: unknown
+size_categories:
+- 10K<n<100K
+task_categories:
+- image-classification
+paperswithcode_id: eurosat
+pretty_name: EuroSAT RGB
+tags:
+- remote-sensing
+- earth-observation
+- geospatial
+- satellite-imagery
+- land-cover-classification
+- sentinel-2
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': Annual Crop
+          '1': Forest
+          '2': Herbaceous Vegetation
+          '3': Highway
+          '4': Industrial Buildings
+          '5': Pasture
+          '6': Permanent Crop
+          '7': Residential Buildings
+          '8': River
+          '9': SeaLake
+  - name: filename
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 104485303.0
+    num_examples: 16200
+  - name: test
+    num_bytes: 34726245.0
+    num_examples: 5400
+  - name: validation
+    num_bytes: 34781690.0
+    num_examples: 5400
+  download_size: 174279561
+  dataset_size: 173993238.0
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+  - split: validation
+    path: data/validation-*
+---
+
+# EuroSAT RGB
+
+<!-- Dataset thumbnail -->
+![EuroSAT RGB](./thumbnail.jpg)
+
+<!-- Provide a quick summary of the dataset. -->
+EUROSAT RGB is the RGB version of the EUROSAT dataset based on Sentinel-2 satellite images covering 13 spectral bands and consisting of 10 classes with 27000 labeled and geo-referenced samples.
+- **Paper:** https://arxiv.org/abs/1709.00029
+- **Homepage:** https://github.com/phelber/EuroSAT
+
+## Description
+
+<!-- Provide a longer summary of what this dataset is. -->
+
+The EuroSAT dataset is a comprehensive land cover classification dataset that focuses on images taken by the [ESA Sentinel-2 satellite](https://sentinel.esa.int/web/sentinel/missions/sentinel-2). It contains a total of 27,000 images, each with a resolution of 64x64 pixels. These images cover 10 distinct land cover classes and are collected from over 34 European countries.
+
+The dataset is available in two versions: **RGB only** (this repo) and all 13 [Multispectral (MS) Sentinel-2 bands](https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/resolutions/spatial). EuroSAT is considered a relatively easy dataset, with approximately 98.6% accuracy achievable using a ResNet-50 architecture.
+
+- **Total Number of Images**: 27000
+- **Bands**: 3 (RGB)
+- **Image Resolution**: 64x64m
+- **Land Cover Classes**: 10
+- Classes: Annual Crop, Forest, Herbaceous Vegetation, Highway, Industrial Buildings, Pasture, Permanent Crop, Residential Buildings, River, SeaLake
+
+
+## Usage
+
+To use this dataset, simply use `datasets.load_dataset("blanchon/EuroSAT_RGB")`.
+<!-- Provide any additional information on how to use this dataset. -->
+```python
+from datasets import load_dataset
+EuroSAT_RGB = load_dataset("blanchon/EuroSAT_RGB")
+```
+
+## Citation 
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+If you use the EuroSAT dataset in your research, please consider citing the following publication:
+
+
+```bibtex
+@article{helber2017eurosat,
+   title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
+   author={Helber, et al.},
+   journal={ArXiv preprint arXiv:1709.00029},
+   year={2017}
+}
+```

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