File size: 4,302 Bytes
5c96471
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Set14 dataset: An evaluation dataset for the image super resolution task"""


import datasets
from pathlib import Path


_CITATION = """
@inproceedings{zeyde2010single,
  title={On single image scale-up using sparse-representations},
  author={Zeyde, Roman and Elad, Michael and Protter, Matan},
  booktitle={International conference on curves and surfaces},
  pages={711--730},
  year={2010},
  organization={Springer}
}
"""

_DESCRIPTION = """
Set14 is an evaluation dataset with 14 RGB images for the image super resolution task.
"""

_HOMEPAGE = "https://sites.google.com/site/romanzeyde/research-interests"

_LICENSE = "UNK"

_DL_URL = "https://huggingface.co/datasets/eugenesiow/Set14/resolve/main/data/"

_DEFAULT_CONFIG = "bicubic_x2"

_DATA_OPTIONS = {
    "bicubic_x2": {
        "hr": _DL_URL + "Set14_HR.tar.gz",
        "lr": _DL_URL + "Set14_LR_x2.tar.gz",
    },
    "bicubic_x3": {
        "hr": _DL_URL + "Set14_HR.tar.gz",
        "lr": _DL_URL + "Set14_LR_x3.tar.gz",
    },
    "bicubic_x4": {
        "hr": _DL_URL + "Set14_HR.tar.gz",
        "lr": _DL_URL + "Set14_LR_x4.tar.gz",
    }
}


class Set14Config(datasets.BuilderConfig):
    """BuilderConfig for Set14."""

    def __init__(
        self,
        name,
        hr_url,
        lr_url,
        **kwargs,
    ):
        if name not in _DATA_OPTIONS:
            raise ValueError("data must be one of %s" % _DATA_OPTIONS)
        super(Set14Config, self).__init__(name=name, version=datasets.Version("1.0.0"), **kwargs)
        self.hr_url = hr_url
        self.lr_url = lr_url


class Set14(datasets.GeneratorBasedBuilder):
    """Set14 dataset for single image super resolution evaluation."""

    BUILDER_CONFIGS = [
        Set14Config(
            name=key,
            hr_url=values['hr'],
            lr_url=values['lr']
        ) for key, values in _DATA_OPTIONS.items()
    ]

    DEFAULT_CONFIG_NAME = _DEFAULT_CONFIG

    def _info(self):
        features = datasets.Features(
            {
                "hr": datasets.Value("string"),
                "lr": datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        hr_data_dir = dl_manager.download_and_extract(self.config.hr_url)
        lr_data_dir = dl_manager.download_and_extract(self.config.lr_url)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "lr_path": lr_data_dir,
                    "hr_path": str(Path(hr_data_dir) / 'Set14_HR')
                },
            )
        ]

    def _generate_examples(
        self, hr_path, lr_path
    ):
        """ Yields examples as (key, example) tuples. """
        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
        # The `key` is here for legacy reason (tfds) and is not important in itself.
        extensions = {'.jpg', '.jpeg', '.png'}
        for file_path in sorted(Path(lr_path).glob("**/*")):
            if file_path.suffix in extensions:
                file_path_str = str(file_path.as_posix())
                yield file_path_str, {
                    'lr': file_path_str,
                    'hr': str((Path(hr_path) / file_path.name).as_posix())
                }