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# TorchGeo-Compatible Download: Solar Plants Brazil

To simplify integration with PyTorch and the [TorchGeo](https://github.com/microsoft/torchgeo) library, this dataset is also available as a single compressed archive.

The `.zip` file contains the full dataset folder structure:

```
solarplantsbrazil.zip
β”œβ”€β”€ train/
β”‚ β”œβ”€β”€ input/
β”‚ └── labels/
β”œβ”€β”€ val/
β”‚ β”œβ”€β”€ input/
β”‚ └── labels/
└── test/
β”œβ”€β”€ input/
└── labels/
```

---

## Direct Download URL (for TorchGeo `download=True` usage)

```
https://huggingface.co/datasets/FederCO23/solar-plants-brazil/resolve/main/solarplantsbrazil.zip
```

---

## TorchGeo Integration Example

When using this dataset in TorchGeo, your dataset class should include the following `_download()` method:

```python
from .utils import download_and_extract_archive

def _download(self) -> None:
download_and_extract_archive(
url=self.url,
download_root=self.root,
filename="solarplantsbrazil.zip"
)
```

This allows users to load the dataset with:

```python
from torchgeo.datasets import SolarPlantsBrazil

dataset = SolarPlantsBrazil(split="train", root="data/", download=True)
```

No manual downloading or extraction is required.

---

## Questions or Suggestions?

Feel free to reach out via the [dataset discussion tab](https://huggingface.co/datasets/FederCO23/solar-plants-brazil/discussions) or contact the creator directly:

- πŸ‘€ **Federico Bessi**
- πŸ“§ [email protected]
- πŸ”— [LinkedIn](https://www.linkedin.com/in/federico-bessi)

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