trans10k_v2.py

#  Copyright (c) 2021 PPViT 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 glob
from src.datasets import Dataset
from src.transforms import Compose


class Trans10kV2(Dataset):
    """Trans10kV2 
    
    It contains the first extensive transparent object segmentation dataset,
    which contains 11 fine-grained transparent object categories

    Args:
        transforms (list): Transforms for image.
        dataset_root (str): Trans10kV2 dataset directory.
        mode (str, optional): Which part of dataset to use. Default: 'train'.
        num_classes (int): the number of classes
    """

    def __init__(self, transforms, dataset_root, mode='train', num_classes=12):
        super(Trans10kV2, self).__init__(transforms=transforms, 
            num_classes=num_classes, dataset_root=dataset_root, mode=mode)
        self.dataset_root = dataset_root
        self.transforms = Compose(transforms)
        self.file_list = list()
        mode = mode.lower()
        self.mode = mode
        self.num_classes = num_classes
        self.ignore_index = 255
        if mode == 'val':
            mode = 'validation'
        img_dir = os.path.join(self.dataset_root, mode, 'images')
        label_dir = os.path.join(self.dataset_root, mode, 'masks_12')
        if self.dataset_root is None or not os.path.isdir(
                self.dataset_root) or not os.path.isdir(
                    img_dir) or not os.path.isdir(label_dir):
            raise ValueError("The dataset is not Found or the folder structure" 
                             "is nonconfoumance.")

        label_files = sorted(glob.glob(os.path.join(label_dir, '*_mask.png')), key=lambda x: x.split('_m')[0])
        img_files = sorted(glob.glob(os.path.join(img_dir, '*.jpg')), key=lambda x: x.split('.')[0])

        self.file_list = [[
            img_path, label_path
        ] for img_path, label_path in zip(img_files, label_files)]

        print("mode: {}, file_nums: {}".format(mode, len(self.file_list)))