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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import cv2
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import glob
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import random
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import logging
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import numpy as np
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from paddle.io import Dataset
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from .base_sr_dataset import BaseDataset
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from .builder import DATASETS
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@DATASETS.register()
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class VSRVimeo90KDataset(BaseDataset):
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"""Vimeo90K dataset for video super resolution for recurrent networks.
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The dataset loads several LQ (Low-Quality) frames and GT (Ground-Truth)
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frames. Then it applies specified transforms and finally returns a dict
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containing paired data and other information.
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It reads Vimeo90K keys from the txt file. Each line contains video frame folder
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Examples:
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00001/0233
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00001/0234
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Args:
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lq_folder (str): Path to a low quality image folder.
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gt_folder (str): Path to a ground truth image folder.
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ann_file (str): Path to the annotation file.
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preprocess (list[dict|callable]): A list functions of data transformations.
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"""
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def __init__(self, lq_folder, gt_folder, ann_file, preprocess):
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super().__init__(preprocess)
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self.lq_folder = str(lq_folder)
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self.gt_folder = str(gt_folder)
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self.ann_file = str(ann_file)
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self.data_infos = self.prepare_data_infos()
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def prepare_data_infos(self):
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with open(self.ann_file, 'r') as fin:
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keys = [line.strip() for line in fin]
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data_infos = []
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for key in keys:
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lq_paths = sorted(
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glob.glob(os.path.join(self.lq_folder, key, '*.png')))
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gt_paths = sorted(
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glob.glob(os.path.join(self.gt_folder, key, '*.png')))
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data_infos.append(dict(lq_path=lq_paths, gt_path=gt_paths, key=key))
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return data_infos
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