import os

import datasets


_HOMEPAGE = ""

_CITATION = ""

_DESCRIPTION = """\
This is a dataset of particle samples to be classified for the ancient mortars project.
"""

_URLS = {
    "train": "https://huggingface.co./datasets/apetulante/mortars_test/resolve/main/data/train.zip",
    "validation": "https://huggingface.co./datasets/apetulante/mortars_test/resolve/main/data/valid.zip",
    "test": "https://huggingface.co./datasets/apetulante/mortars_test/resolve/main/data/test.zip",
}

#names_list = open("https://huggingface.co./datasets/apetulante/mortars_test/resolve/main/data/particle_names.txt","r").read().split("\n")
_NAMES = ["kurkar", "sand", "soil", "chert", "obsidian", "arch_18", "kurkar_nahal","sand_beach","volcanicash_pozzuoli","arch","volcanicash"]

class MortarsTest(datasets.GeneratorBasedBuilder):
    """Ancient particles 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"),
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    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"]]),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "files": dl_manager.iter_files([data_files["test"]]),
                },
            ),
        ]

    def _generate_examples(self, files):
        for i, path in enumerate(files):
            file_name = os.path.basename(path)
            if file_name.endswith(".bmp"):
                yield i, {
                    "image_file_path": path,
                    "image": path,
                    "labels": os.path.basename(file_name).lower().split('-')[0].split('_')[0],
                }