multilabel_dataset.py

#   Copyright (c) 2021 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.

from __future__ import print_function

import io
import tarfile
import numpy as np
from PIL import Image  #all use default backend

import paddle
from paddle.io import Dataset
import pickle
import os
import cv2
import random

from ppcls.data import preprocess
from ppcls.data.preprocess import transform
from ppcls.utils import logger

from .common_dataset import CommonDataset

class MultiLabelDataset(CommonDataset):

    def _load_anno(self):
        assert os.path.exists(self._cls_path)
        assert os.path.exists(self._img_root)
        self.images = []
        self.labels = []
        with open(self._cls_path) as fd:
            lines = fd.readlines()
            for l in lines:
                l = l.strip().split(" ")
                self.images.append(os.path.join(self._img_root, l[0]))

                labels = l[1].split(',')
                labels = [int(i) for i in labels]

                self.labels.append(labels)
                assert os.path.exists(self.images[-1])

    def __getitem__(self, idx):
        try:
            img = cv2.imread(self.images[idx])
            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
            if self._transform_ops:
                img = transform(img, self._transform_ops)
            img = img.transpose((2, 0, 1))
            label = np.array(self.labels[idx]).astype("float32")
            return (img, label)
        except Exception as ex:
            logger.error("Exception occured when parse line: {} with msg: {}".
                         format(self.images[idx], ex))
            rnd_idx = np.random.randint(self.__len__())
            return self.__getitem__(rnd_idx)