| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546 |
- # 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 .common_dataset import CommonDataset
- class LogoDataset(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("\t")
- if l[0] == 'image_id':
- continue
- self.images.append(os.path.join(self._img_root, l[3]))
- self.labels.append(np.int64(l[1]) - 1)
- assert os.path.exists(self.images[-1])
|