| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119 |
- # 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
- 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"
|