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README.md

@@ -1,187 +0,0 @@
----
-annotations_creators:
-- machine-generated
-language_creators:
-- found
-language: []
-license:
-- other
-multilinguality:
-- monolingual
-size_categories:
-- unknown
-source_datasets:
-- original
-task_categories:
-- other
-task_ids: []
-pretty_name: Set5
-tags:
-- other-image-super-resolution
----
-
-# Dataset Card for Set5
-
-## Table of Contents
-- [Table of Contents](#table-of-contents)
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage**: http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html
-- **Repository**: https://huggingface.co/datasets/eugenesiow/Set5
-- **Paper**: http://people.rennes.inria.fr/Aline.Roumy/publi/12bmvc_Bevilacqua_lowComplexitySR.pdf
-- **Leaderboard**: https://github.com/eugenesiow/super-image#scale-x2
-
-### Dataset Summary
-
-Set5 is a evaluation dataset with 5 RGB images for the image super resolution task. The 5 images of the dataset are (“baby”, “bird”, “butterfly”, “head”, “woman”).
-
-Install with `pip`:
-```bash
-pip install datasets super-image
-```
-
-Evaluate a model with the [`super-image`](https://github.com/eugenesiow/super-image) library:
-```python
-from datasets import load_dataset
-from super_image import EdsrModel
-from super_image.data import EvalDataset, EvalMetrics
-
-dataset = load_dataset('eugenesiow/Set5', 'bicubic_x2', split='validation')
-eval_dataset = EvalDataset(dataset)
-model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
-EvalMetrics().evaluate(model, eval_dataset)
-```
-
-### Supported Tasks and Leaderboards
-
-The dataset is commonly used for evaluation of the `image-super-resolution` task.
-
-Unofficial [`super-image`](https://github.com/eugenesiow/super-image) leaderboard for:
-- [Scale 2](https://github.com/eugenesiow/super-image#scale-x2)
-- [Scale 3](https://github.com/eugenesiow/super-image#scale-x3)
-- [Scale 4](https://github.com/eugenesiow/super-image#scale-x4)
-- [Scale 8](https://github.com/eugenesiow/super-image#scale-x8)
-
-### Languages
-
-Not applicable.
-
-## Dataset Structure
-
-### Data Instances
-
-An example of `validation` for `bicubic_x2` looks as follows.
-```
-{
-    "hr": "/.cache/huggingface/datasets/downloads/extracted/Set5_HR/baby.png",
-    "lr": "/.cache/huggingface/datasets/downloads/extracted/Set5_LR_x2/baby.png"
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-- `hr`: a `string` to the path of the High Resolution (HR) `.png` image.
-- `lr`: a `string` to the path of the Low Resolution (LR) `.png` image.
-
-### Data Splits
-
-| name  |validation|
-|-------|---:|
-|bicubic_x2|5|
-|bicubic_x3|5|
-|bicubic_x4|5|
-
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-No annotations.
-
-#### Who are the annotators?
-
-No annotators.
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-- **Original Authors**: [Bevilacqua et al.](http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html)
-
-### Licensing Information
-
-Academic use only.
-
-### Citation Information
-
-```bibtex
-@article{bevilacqua2012low,
-  title={Low-complexity single-image super-resolution based on nonnegative neighbor embedding},
-  author={Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line},
-  year={2012},
-  publisher={BMVA press}
-}
-```
-
-### Contributions
-
-Thanks to [@eugenesiow](https://github.com/eugenesiow) for adding this dataset.

Set5.py

@@ -1,133 +0,0 @@
-# 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.
-"""Set5 dataset: An evaluation dataset for the image super resolution task"""
-
-
-import datasets
-from pathlib import Path
-
-
-_CITATION = """
-@article{bevilacqua2012low,
-  title={Low-complexity single-image super-resolution based on nonnegative neighbor embedding},
-  author={Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line},
-  year={2012},
-  publisher={BMVA press}
-}
-"""
-
-_DESCRIPTION = """
-Set5 is a evaluation dataset with 5 RGB images for the image super resolution task.
-"""
-
-_HOMEPAGE = "http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html"
-
-_LICENSE = "UNK"
-
-_DL_URL = "https://huggingface.co/datasets/eugenesiow/Set5/resolve/main/data/"
-
-_DEFAULT_CONFIG = "bicubic_x2"
-
-_DATA_OPTIONS = {
-    "bicubic_x2": {
-        "hr": _DL_URL + "Set5_HR.tar.gz",
-        "lr": _DL_URL + "Set5_LR_x2.tar.gz",
-    },
-    "bicubic_x3": {
-        "hr": _DL_URL + "Set5_HR.tar.gz",
-        "lr": _DL_URL + "Set5_LR_x3.tar.gz",
-    },
-    "bicubic_x4": {
-        "hr": _DL_URL + "Set5_HR.tar.gz",
-        "lr": _DL_URL + "Set5_LR_x4.tar.gz",
-    }
-}
-
-
-class Set5Config(datasets.BuilderConfig):
-    """BuilderConfig for Set5."""
-
-    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(Set5Config, self).__init__(name=name, version=datasets.Version("1.0.0"), **kwargs)
-        self.hr_url = hr_url
-        self.lr_url = lr_url
-
-
-class Set5(datasets.GeneratorBasedBuilder):
-    """Set5 dataset for single image super resolution evaluation."""
-
-    BUILDER_CONFIGS = [
-        Set5Config(
-            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) / 'Set5_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())
-                }

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