PaddleX/paddlex/modules/ts_classification/dataset_checker/__init__.py

# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
# 
# 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
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import os
import os.path as osp
from collections import defaultdict, Counter

from PIL import Image
import json

from ...base import BaseDatasetChecker
from .dataset_src import check, convert, split_dataset, deep_analyse

from ..support_models import SUPPORT_MODELS


class TSCLSDatasetChecker(BaseDatasetChecker):
    """ Dataset Checker for TS Classification Model """
    support_models = SUPPORT_MODELS
    sample_num = 10

    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(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_dir, self.output_dir)

    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 deep_analyse(dataset_dir, self.output_dir)

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

        Returns:
            str: show type
        """
        return "csv"

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

        Returns:
            str: dataset type
        """
        return "TSCLSDataset"