Eye_diabetic.py

import os

import datasets
from datasets.tasks import ImageClassification


_HOMEPAGE = "https://github.com/AI-Lab-Makerere/ibean/"

_CITATION = """\
@ONLINE {beansdata,
    author="Makerere AI Lab",
    title="Bean disease dataset",
    month="January",
    year="2020",
    url="https://github.com/AI-Lab-Makerere/ibean/"
}
"""

_DESCRIPTION = """\
Beans is a dataset of images of beans taken in the field using smartphone
cameras. It consists of 3 classes: 2 disease classes and the healthy class.
Diseases depicted include Angular Leaf Spot and Bean Rust. Data was annotated
by experts from the National Crops Resources Research Institute (NaCRRI) in
Uganda and collected by the Makerere AI research lab.
"""

_URLS = {
    "train": "https://huggingface.co/datasets/NawinCom/Eye_diabetic/resolve/main/train_val2/train.zip",
    "validation": "https://huggingface.co/datasets/NawinCom/Eye_diabetic/resolve/main/train_val2/val.zip"
}

_NAMES = ["0", "1", "2", "3", "4"]


class Beans(datasets.GeneratorBasedBuilder):
    """Beans plant leaf images dataset."""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "image_file_path": datasets.Value("string"),
                    "image": datasets.Image(),
                    "labels": datasets.features.ClassLabel(names=_NAMES),
                }
            ),
            supervised_keys=("image", "labels"),
            citation=_CITATION,
            task_templates=[ImageClassification(image_column="image", label_column="labels")],
        )

    def _split_generators(self, dl_manager):
        data_files = dl_manager.download_and_extract(_URLS)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "files": dl_manager.iter_files([data_files["train"]]),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "files": dl_manager.iter_files([data_files["validation"]]),
                },
            ),
        ]

    def _generate_examples(self, files):
        for i, path in enumerate(files):
            file_name = os.path.basename(path)
            if file_name.endswith(".jpg"):
                yield i, {
                    "image_file_path": path,
                    "image": path,
                    "labels": os.path.basename(os.path.dirname(path)).lower(),
                }