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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 FOOD101_CATEGORIES
@DATASETS.register_module()
class Food101(BaseDataset):
"""The Food101 Dataset.
Support the `Food101 Dataset <https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/>`_ Dataset.
After downloading and decompression, the dataset directory structure is as follows.
Food101 dataset directory: ::
food-101
├── images
│ ├── class_x
│ │ ├── xx1.jpg
│ │ ├── xx2.jpg
│ │ └── ...
│ ├── class_y
│ │ ├── yy1.jpg
│ │ ├── yy2.jpg
│ │ └── ...
│ └── ...
├── meta
│ ├── train.txt
│ └── test.txt
└── ....
Args:
data_root (str): The root directory for Food101 dataset.
split (str, optional): The dataset split, supports "train" and "test".
Default to "train".
Examples:
>>> from mmpretrain.datasets import Food101
>>> train_dataset = Food101(data_root='data/food-101', split='train')
>>> train_dataset
Dataset Food101
Number of samples: 75750
Number of categories: 101
Root of dataset: data/food-101
>>> test_dataset = Food101(data_root='data/food-101', split='test')
>>> test_dataset
Dataset Food101
Number of samples: 25250
Number of categories: 101
Root of dataset: data/food-101
""" # noqa: E501
METAINFO = {'classes': FOOD101_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('meta', 'train.txt')
else:
ann_file = self.backend.join_path('meta', 'test.txt')
test_mode = split == 'test'
data_prefix = 'images'
super(Food101, self).__init__(
ann_file=ann_file,
data_root=data_root,
test_mode=test_mode,
data_prefix=data_prefix,
**kwargs)
def load_data_list(self):
"""Load images and ground truth labels."""
pairs = list_from_file(self.ann_file)
data_list = []
for pair in pairs:
class_name, img_name = pair.split('/')
img_name = f'{img_name}.jpg'
img_path = self.backend.join_path(self.img_prefix, class_name,
img_name)
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 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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