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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 | |
| 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 | |