# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
#
# 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,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import os

from ....utils.misc import abspath
from ..text_rec.config import TextRecConfig


class TextDetConfig(TextRecConfig):
    """Text Detection Config"""

    def update_batch_size(self, batch_size: int):
        """update batch size setting

        Args:
            batch_size (int): the batch size number of training loader to set.
        """
        _cfg = {
            "Train.loader.batch_size_per_card": batch_size,
        }
        self.update(_cfg)

    def update_dataset(self, dataset_path: str, dataset_type=None):
        """update dataset settings

        Args:
            dataset_path (str): the root path of dataset.
            dataset_type (str, optional): dataset type. Defaults to None.

        Raises:
            ValueError: the dataset_type error.
        """
        dataset_path = abspath(dataset_path)
        if dataset_type is None:
            dataset_type = "TextDetDataset"
        if dataset_type == "TextDetDataset":
            _cfg = {
                "Train.dataset.name": dataset_type,
                "Train.dataset.data_dir": dataset_path,
                "Train.dataset.label_file_list": [
                    os.path.join(dataset_path, "train.txt")
                ],
                "Eval.dataset.name": dataset_type,
                "Eval.dataset.data_dir": dataset_path,
                "Eval.dataset.label_file_list": [os.path.join(dataset_path, "val.txt")],
            }
            self.update(_cfg)
        else:
            raise ValueError(f"{repr(dataset_type)} is not supported.")