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# Copyright (c) OpenMMLab. All rights reserved.
from typing import List
from mmengine import get_file_backend, list_from_file
from mmpretrain.registry import DATASETS
from .base_dataset import BaseDataset
from .categories import SUN397_CATEGORIES
@DATASETS.register_module()
class SUN397(BaseDataset):
"""The SUN397 Dataset.
Support the `SUN397 Dataset <https://vision.princeton.edu/projects/2010/SUN/>`_ Dataset.
After downloading and decompression, the dataset directory structure is as follows.
SUN397 dataset directory: ::
SUN397
├── SUN397
│ ├── a
│ │ ├── abbey
│ | | ├── sun_aaalbzqrimafwbiv.jpg
│ | | └── ...
│ │ ├── airplane_cabin
│ | | ├── sun_aadqdkqaslqqoblu.jpg
│ | | └── ...
│ | └── ...
│ ├── b
│ │ └── ...
│ ├── c
│ │ └── ...
│ └── ...
└── Partitions
├── ClassName.txt
├── Training_01.txt
├── Testing_01.txt
└── ...
Args:
data_root (str): The root directory for Stanford Cars dataset.
split (str, optional): The dataset split, supports "train" and "test".
Default to "train".
Examples:
>>> from mmpretrain.datasets import SUN397
>>> train_dataset = SUN397(data_root='data/SUN397', split='train')
>>> train_dataset
Dataset SUN397
Number of samples: 19850
Number of categories: 397
Root of dataset: data/SUN397
>>> test_dataset = SUN397(data_root='data/SUN397', split='test')
>>> test_dataset
Dataset SUN397
Number of samples: 19850
Number of categories: 397
Root of dataset: data/SUN397
**Note that some images are not a jpg file although the name ends with ".jpg".
The backend of SUN397 should be "pillow" as below to read these images properly,**
.. code-block:: python
pipeline = [
dict(type='LoadImageFromFile', imdecode_backend='pillow'),
dict(type='RandomResizedCrop', scale=224),
dict(type='PackInputs')
]
""" # noqa: E501
METAINFO = {'classes': SUN397_CATEGORIES}
def __init__(self, data_root: str, split: str = 'train', **kwargs):
splits = ['train', 'test']
assert split in splits, \
f"The split must be one of {splits}, but get '{split}'"
self.split = split
self.backend = get_file_backend(data_root, enable_singleton=True)
if split == 'train':
ann_file = self.backend.join_path('Partitions', 'Training_01.txt')
else:
ann_file = self.backend.join_path('Partitions', 'Testing_01.txt')
data_prefix = 'SUN397'
test_mode = split == 'test'
super(SUN397, self).__init__(
ann_file=ann_file,
data_root=data_root,
test_mode=test_mode,
data_prefix=data_prefix,
**kwargs)
def load_data_list(self):
pairs = list_from_file(self.ann_file)
data_list = []
for pair in pairs:
img_path = self.backend.join_path(self.img_prefix, pair[1:])
items = pair.split('/')
class_name = '_'.join(items[2:-1])
gt_label = self.METAINFO['classes'].index(class_name)
info = dict(img_path=img_path, gt_label=gt_label)
data_list.append(info)
return data_list
def __getitem__(self, idx: int) -> dict:
try:
return super().__getitem__(idx)
except AttributeError:
raise RuntimeError(
'Some images in the SUN397 dataset are not a jpg file '
'although the name ends with ".jpg". The backend of SUN397 '
'should be "pillow" to read these images properly.')
def extra_repr(self) -> List[str]:
"""The extra repr information of the dataset."""
body = [
f'Root of dataset: \t{self.data_root}',
]
return body
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