Source code for mmedit.datasets.sr_folder_gt_dataset

# Copyright (c) OpenMMLab. All rights reserved.
from .base_sr_dataset import BaseSRDataset
from .registry import DATASETS

[docs]@DATASETS.register_module() class SRFolderGTDataset(BaseSRDataset): """General ground-truth image folder dataset for image restoration. The dataset loads gt (Ground-Truth) image only, applies specified transforms and finally returns a dict containing paired data and other information. This is the "gt folder mode", which needs to specify the gt folder path, each folder containing the corresponding images. Image lists will be generated automatically. For example, we have a folder with the following structure: :: data_root ├── gt │ ├── 0001.png │ ├── 0002.png then, you need to set: .. code-block:: python gt_folder = data_root/gt Args: gt_folder (str | :obj:`Path`): Path to a gt folder. pipeline (List[dict | callable]): A sequence of data transformations. scale (int | tuple): Upsampling scale or upsampling scale range. test_mode (bool): Store `True` when building test dataset. Default: `False`. """ def __init__(self, gt_folder, pipeline, scale, test_mode=False, filename_tmpl='{}'): super().__init__(pipeline, scale, test_mode) self.gt_folder = str(gt_folder) self.filename_tmpl = filename_tmpl self.data_infos = self.load_annotations()
[docs] def load_annotations(self): """Load annoations for SR dataset. It loads the GT image path from folder. Returns: dict: Returned dict for GT. """ data_infos = [] gt_paths = self.scan_folder(self.gt_folder) for gt_path in gt_paths: data_infos.append(dict(gt_path=gt_path)) return data_infos
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