Source code for mmedit.datasets.sr_vimeo90k_dataset

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp

from .base_sr_dataset import BaseSRDataset
from .registry import DATASETS

[docs]@DATASETS.register_module() class SRVimeo90KDataset(BaseSRDataset): """Vimeo90K dataset for video super resolution. The dataset loads several LQ (Low-Quality) frames and a center GT (Ground-Truth) frame. Then it applies specified transforms and finally returns a dict containing paired data and other information. It reads Vimeo90K keys from the txt file. Each line contains: 1. image name; 2, image shape, separated by a white space. Examples: :: 00001/0266 (256, 448, 3) 00001/0268 (256, 448, 3) Args: lq_folder (str | :obj:`Path`): Path to a lq folder. gt_folder (str | :obj:`Path`): Path to a gt folder. ann_file (str | :obj:`Path`): Path to the annotation file. num_input_frames (int): Window size for input frames. pipeline (list[dict | callable]): A sequence of data transformations. scale (int): Upsampling scale ratio. test_mode (bool): Store `True` when building test dataset. Default: `False`. """ def __init__(self, lq_folder, gt_folder, ann_file, num_input_frames, pipeline, scale, test_mode=False): super().__init__(pipeline, scale, test_mode) assert num_input_frames % 2 == 1, ( f'num_input_frames should be odd numbers, ' f'but received {num_input_frames}.') self.lq_folder = str(lq_folder) self.gt_folder = str(gt_folder) self.ann_file = str(ann_file) self.num_input_frames = num_input_frames self.data_infos = self.load_annotations()
[docs] def load_annotations(self): """Load annoations for VimeoK dataset. Returns: dict: Returned dict for LQ and GT pairs. """ # get keys with open(self.ann_file, 'r') as fin: keys = [line.strip().split(' ')[0] for line in fin] # get frame index list for LQ frames frame_index_list = [] for i in range(self.num_input_frames): # Each clip of Vimeo90K has 7 frames starting from 1. So we use 9 # for generating frame_index_list: # N | frame_index_list # 1 | 4 # 3 | 3,4,5 # 5 | 2,3,4,5,6 # 7 | 1,2,3,4,5,6,7 frame_index_list.append(i + (9 - self.num_input_frames) // 2) data_infos = [] for key in keys: folder, subfolder = key.split('/') lq_paths = [] for i in frame_index_list: lq_paths.append( osp.join(self.lq_folder, folder, subfolder, f'im{i}.png')) gt_paths = [osp.join(self.gt_folder, folder, subfolder, 'im4.png')] data_infos.append( dict(lq_path=lq_paths, gt_path=gt_paths, key=key)) return data_infos
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