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https://github.com/alibaba/EasyCV.git
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36a3c45efa
* add caltech, flower, mnist data source * add det lvis data source * add pose crowdPose data source * add pose of OC Human data source * add pose of mpii data source * add Seg of voc data source * add Seg of coco data source * add Det of wider person datasource * add Det of african wildlife datasource * add Det of fruit datasource * add Det of pet datasource * add Det of artaxor and tiny person datasource * add Det of wider face datasource * add Det of crowd human datasource * add Det of object365 datasource * add Seg of coco stuff 10k and 164k datasource Co-authored-by: Cathy0908 <30484308+Cathy0908@users.noreply.github.com>
92 lines
3.2 KiB
Python
92 lines
3.2 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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from pathlib import Path
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from PIL import Image
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from scipy.io import loadmat
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from torchvision.datasets.utils import (check_integrity,
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download_and_extract_archive,
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download_url)
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from easycv.datasets.registry import DATASOURCES
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@DATASOURCES.register_module
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class ClsSourceFlowers102(object):
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_download_url_prefix = 'https://www.robots.ox.ac.uk/~vgg/data/flowers/102/'
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_file_dict = dict( # filename, md5
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image=('102flowers.tgz', '52808999861908f626f3c1f4e79d11fa'),
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label=('imagelabels.mat', 'e0620be6f572b9609742df49c70aed4d'),
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setid=('setid.mat', 'a5357ecc9cb78c4bef273ce3793fc85c'))
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_splits_map = {'train': 'trnid', 'val': 'valid', 'test': 'tstid'}
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def __init__(self, root, split, download=False) -> None:
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assert split in ['train', 'test', 'val']
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self._base_folder = Path(root) / 'flowers-102'
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self._images_folder = self._base_folder / 'jpg'
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if download:
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self.download()
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# verify that the path exists
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if not self._check_integrity():
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raise FileNotFoundError(
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f'The data in the {self._base_folder} file directory is incomplete'
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)
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# Data reading in progress
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set_ids = loadmat(
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self._base_folder / self._file_dict['setid'][0], squeeze_me=True)
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image_ids = set_ids[self._splits_map[split]].tolist()
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labels = loadmat(
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self._base_folder / self._file_dict['label'][0], squeeze_me=True)
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image_id_to_label = dict(enumerate((labels['labels'] - 1).tolist(), 1))
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self._labels = []
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self._image_files = []
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for image_id in image_ids:
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self._labels.append(image_id_to_label[image_id])
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self._image_files.append(self._images_folder /
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f'image_{image_id:05d}.jpg')
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def __len__(self):
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return len(self._labels)
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def __getitem__(self, idx):
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image_file, label = self._image_files[idx], self._labels[idx]
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img = Image.open(image_file).convert('RGB')
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result_dict = {'img': img, 'gt_labels': label}
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return result_dict
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# verify that the path exists
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def _check_integrity(self):
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if not (self._images_folder.exists() and self._images_folder.is_dir()):
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return False
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for id in ['label', 'setid']:
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filename, md5 = self._file_dict[id]
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if not check_integrity(str(self._base_folder / filename), md5):
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return False
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return True
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def download(self):
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os.makedirs(self._base_folder, exist_ok=True)
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if self._check_integrity():
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return
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# Download and extract
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download_and_extract_archive(
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f"{self._download_url_prefix}{self._file_dict['image'][0]}",
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str(self._base_folder),
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md5=self._file_dict['image'][1],
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remove_finished=True)
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for id in ['label', 'setid']:
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filename, md5 = self._file_dict[id]
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download_url(
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self._download_url_prefix + filename,
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str(self._base_folder),
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md5=md5)
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