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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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import os
import os.path as osp
from pathlib import Path

from ...base import BaseDatasetChecker
from ..model_list import MODELS
from .dataset_src import anaylse_dataset, check_dataset, convert_dataset, split_dataset


class SegDatasetChecker(BaseDatasetChecker):
    """Dataset Checker for Semantic Segmentation Model"""

    entities = MODELS
    sample_num = 10

    def get_dataset_root(self, dataset_dir: str) -> str:
        """find the dataset root dir

        Args:
            dataset_dir (str): the directory that contain dataset.

        Returns:
            str: the root directory of dataset.
        """
        anno_dirs = list(Path(dataset_dir).glob("**/images"))
        if len(anno_dirs) == 1:
            dataset_dir = anno_dirs[0].parent.as_posix()
        elif len(anno_dirs) == 0:
            dataset_dir = Path(dataset_dir)
        else:
            raise ValueError(
                f"Segmentation Dataset Format Error: We currently only support `PaddleX` and `Labelme` formats. "
                f"For `PaddleX` format, your dataset root must contain exactly one `images` directory. "
                f"For `Labelme` format, your dataset root must contain no `images` directories. "
                f"However, your dataset root contains {len(anno_dirs)} `images` directories. "
                f"Please adjust your dataset structure to comply with the supported formats."
            )
        return dataset_dir

    def convert_dataset(self, src_dataset_dir: str) -> str:
        """convert the dataset from other type to specified type

        Args:
            src_dataset_dir (str): the root directory of dataset.

        Returns:
            str: the root directory of converted dataset.
        """
        return convert_dataset(
            self.check_dataset_config.convert.src_dataset_type, src_dataset_dir
        )

    def split_dataset(self, src_dataset_dir: str) -> str:
        """repartition the train and validation dataset

        Args:
            src_dataset_dir (str): the root directory of dataset.

        Returns:
            str: the root directory of splited dataset.
        """
        return split_dataset(
            src_dataset_dir,
            self.check_dataset_config.split.train_percent,
            self.check_dataset_config.split.val_percent,
        )

    def check_dataset(self, dataset_dir: str, sample_num: int = sample_num) -> dict:
        """check if the dataset meets the specifications and get dataset summary

        Args:
            dataset_dir (str): the root directory of dataset.
            sample_num (int): the number to be sampled.
        Returns:
            dict: dataset summary.
        """
        return check_dataset(dataset_dir, self.output, sample_num)

    def analyse(self, dataset_dir: str) -> dict:
        """deep analyse dataset

        Args:
            dataset_dir (str): the root directory of dataset.

        Returns:
            dict: the deep analysis results.
        """
        return anaylse_dataset(dataset_dir, self.output)

    def get_show_type(self) -> str:
        """get the show type of dataset

        Returns:
            str: show type
        """
        return "image"

    def get_dataset_type(self) -> str:
        """return the dataset type

        Returns:
            str: dataset type
        """
        return "SegDataset"