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72 lines
2.3 KiB
72 lines
2.3 KiB
# 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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