import os
import datasets
import soundfile as sf

_CITATION = ""
_DESCRIPTION = "Audio classification dataset with labels from folder names"
_HOMEPAGE = ""
_LICENSE = ""

class AudioDatasetConfig(datasets.BuilderConfig):
    def __init__(self, **kwargs):
        super(AudioDatasetConfig, self).__init__(**kwargs)

class AudioDataset(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [AudioDatasetConfig(name="default", version=datasets.Version("1.0.0"))]

    def _info(self):
        labels = sorted(os.listdir(os.path.join(self.config.data_dir, "Final data")))
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                "audio": datasets.Audio(sampling_rate=16000),
                "label": datasets.ClassLabel(names=labels)
            }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        data_dir = self.config.data_dir
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"data_dir": data_dir}
            )
        ]

    def _generate_examples(self, data_dir):
        audio_path = os.path.join(data_dir, "Final data")
        label_list = sorted(os.listdir(audio_path))
        id_ = 0
        for label in label_list:
            label_dir = os.path.join(audio_path, label)
            if not os.path.isdir(label_dir):
                continue
            for fname in os.listdir(label_dir):
                if fname.endswith(".wav"):
                    path = os.path.join(label_dir, fname)
                    yield id_, {
                        "audio": path,
                        "label": label
                    }
                    id_ += 1