import datasets
from datasets.data_files import DataFilesDict
from datasets.packaged_modules.imagefolder.imagefolder import ImageFolder, ImageFolderConfig

logger = datasets.logging.get_logger(__name__)


class EuroSAT(ImageFolder):
    R"""
    EuroSAT dataset for image classification.
    """

    BUILDER_CONFIG_CLASS = ImageFolderConfig
    BUILDER_CONFIGS = [
        ImageFolderConfig(
            name="default",
            features=("images", "labels"),
            data_files=DataFilesDict(
                {
                    split: f"data/{split}.zip"
                    for split in ["train", "test"]
                    + ["contrast", "gaussian_noise", "impulse_noise", "jpeg_compression", "motion_blur", "pixelate", "spatter"]
                }
            ),
        )
    ]

    classnames = [
        "annual crop land",
        "forest",
        "brushland or shrubland",
        "highway or road",
        "industrial buildings or commercial buildings",
        "pasture land",
        "permanent crop land",
        "residential buildings or homes or apartments",
        "river",
        "lake or sea",
    ]

    clip_templates = [
        lambda c: f"a centered satellite photo of {c}.",
        lambda c: f"a centered satellite photo of a {c}.",
        lambda c: f"a centered satellite photo of the {c}.",
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description="EuroSAT dataset for image classification.",
            features=datasets.Features(
                {
                    "image": datasets.Image(),
                    "label": datasets.ClassLabel(names=self.classnames),
                }
            ),
            supervised_keys=("image", "label"),
            task_templates=[datasets.ImageClassification(image_column="image", label_column="label")],
        )