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Div2k.py

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+# 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.
+"""DIV2K dataset: DIVerse 2K resolution high quality images.
+Adapted from TF Datasets: https://github.com/tensorflow/datasets/"""
+
+import os
+from pathlib import Path
+
+import datasets
+
+_CITATION = """
+@InProceedings{Agustsson_2017_CVPR_Workshops,
+author = {Agustsson, Eirikur and Timofte, Radu},
+title = {NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study},
+booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
+url = "http://www.vision.ee.ethz.ch/~timofter/publications/Agustsson-CVPRW-2017.pdf",
+month = {July},
+year = {2017}
+} 
+"""
+
+_DESCRIPTION = """
+DIV2K dataset: DIVerse 2K resolution high quality images as used for the challenges @ NTIRE (CVPR 2017 and 
+CVPR 2018) and @ PIRM (ECCV 2018)
+"""
+
+_HOMEPAGE = "https://data.vision.ee.ethz.ch/cvl/DIV2K/"
+
+_LICENSE = """
+Please notice that this dataset is made available for academic research purpose only. All the images are
+collected from the Internet, and the copyright belongs to the original owners. If any of the images belongs to 
+you and you would like it removed, please kindly inform the authors, and they will remove it from the dataset 
+immediately.
+"""
+
+_DL_URL = "https://data.vision.ee.ethz.ch/cvl/DIV2K/"
+
+_DL_URLS = {
+    "train_hr": _DL_URL + "DIV2K_train_HR.zip",
+    "valid_hr": _DL_URL + "DIV2K_valid_HR.zip",
+    "train_bicubic_x2": _DL_URL + "DIV2K_train_LR_bicubic_X2.zip",
+    "train_unknown_x2": _DL_URL + "DIV2K_train_LR_unknown_X2.zip",
+    "valid_bicubic_x2": _DL_URL + "DIV2K_valid_LR_bicubic_X2.zip",
+    "valid_unknown_x2": _DL_URL + "DIV2K_valid_LR_unknown_X2.zip",
+    "train_bicubic_x3": _DL_URL + "DIV2K_train_LR_bicubic_X3.zip",
+    "train_unknown_x3": _DL_URL + "DIV2K_train_LR_unknown_X3.zip",
+    "valid_bicubic_x3": _DL_URL + "DIV2K_valid_LR_bicubic_X3.zip",
+    "valid_unknown_x3": _DL_URL + "DIV2K_valid_LR_unknown_X3.zip",
+    "train_bicubic_x4": _DL_URL + "DIV2K_train_LR_bicubic_X4.zip",
+    "train_unknown_x4": _DL_URL + "DIV2K_train_LR_unknown_X4.zip",
+    "valid_bicubic_x4": _DL_URL + "DIV2K_valid_LR_bicubic_X4.zip",
+    "valid_unknown_x4": _DL_URL + "DIV2K_valid_LR_unknown_X4.zip",
+    "train_bicubic_x8": _DL_URL + "DIV2K_train_LR_x8.zip",
+    "valid_bicubic_x8": _DL_URL + "DIV2K_valid_LR_x8.zip",
+    "train_realistic_mild_x4": _DL_URL + "DIV2K_train_LR_mild.zip",
+    "valid_realistic_mild_x4": _DL_URL + "DIV2K_valid_LR_mild.zip",
+    "train_realistic_difficult_x4": _DL_URL + "DIV2K_train_LR_difficult.zip",
+    "valid_realistic_difficult_x4": _DL_URL + "DIV2K_valid_LR_difficult.zip",
+    "train_realistic_wild_x4": _DL_URL + "DIV2K_train_LR_wild.zip",
+    "valid_realistic_wild_x4": _DL_URL + "DIV2K_valid_LR_wild.zip",
+}
+
+_DATA_OPTIONS = [
+    "bicubic_x2", "bicubic_x3", "bicubic_x4", "bicubic_x8", "unknown_x2",
+    "unknown_x3", "unknown_x4", "realistic_mild_x4", "realistic_difficult_x4",
+    "realistic_wild_x4"
+]
+
+
+class Div2kConfig(datasets.BuilderConfig):
+    """BuilderConfig for Div2k."""
+
+    def __init__(self, name, **kwargs):
+        """Constructs a Div2kConfig."""
+        if name not in _DATA_OPTIONS:
+            raise ValueError("data must be one of %s" % _DATA_OPTIONS)
+
+        super(Div2kConfig, self).__init__(name=name, **kwargs)
+        self.data = name
+        self.download_urls = {
+            "train_lr_url": _DL_URLS["train_" + self.data],
+            "valid_lr_url": _DL_URLS["valid_" + self.data],
+            "train_hr_url": _DL_URLS["train_hr"],
+            "valid_hr_url": _DL_URLS["valid_hr"],
+        }
+
+
+class Div2k(datasets.GeneratorBasedBuilder):
+    """DIV2K dataset: DIVerse 2K resolution high quality images."""
+
+    BUILDER_CONFIGS = [
+        Div2kConfig(version=datasets.Version("2.0.0"), name=data) for data in _DATA_OPTIONS
+    ]
+
+    DEFAULT_CONFIG_NAME = "bicubic_x2"
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "lr": datasets.Value("string"),
+                "hr": 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."""
+        extracted_paths = dl_manager.download_and_extract(
+            self.config.download_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "lr_path": extracted_paths["train_lr_url"],
+                    "hr_path": os.path.join(extracted_paths["train_hr_url"], "DIV2K_train_HR"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "lr_path": extracted_paths["valid_lr_url"],
+                    "hr_path": str(os.path.join(extracted_paths["valid_hr_url"], "DIV2K_valid_HR")),
+                },
+            ),
+        ]
+
+    def _generate_examples(
+            self, lr_path, hr_path
+    ):
+        """ Yields examples as (key, example) tuples. """
+        extensions = {'.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) / f"{str(file_path.name)[:4]}.png").as_posix())
+                }

README.md

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+---
+annotations_creators:
+- machine-generated
+language_creators:
+- found
+languages: []
+licenses:
+- other-academic-use
+multilinguality:
+- monolingual
+pretty_name: Div2k
+size_categories:
+- unknown
+source_datasets:
+- original
+task_categories:
+- other
+task_ids:
+- other-other-image-super-resolution
+---
+
+# Dataset Card for Div2k
+
+## 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: https://data.vision.ee.ethz.ch/cvl/DIV2K/**
+- **Repository: https://huggingface.co/datasets/eugenesiow/Div2k**
+- **Paper: http://www.vision.ee.ethz.ch/~timofter/publications/Agustsson-CVPRW-2017.pdf**
+- **Leaderboard: https://github.com/eugenesiow/super-image#scale-x2**
+- **Point of Contact: [email protected]**
+
+### Dataset Summary
+
+DIV2K is a dataset of RGB images (2K resolution high quality images) with a large diversity of contents.
+
+The DIV2K dataset is divided into:
+
+- train data: starting from 800 high definition high resolution images we obtain corresponding low resolution images and provide both high and low resolution images for 2, 3, and 4 downscaling factors
+- validation data: 100 high definition high resolution images are used for genereting low resolution corresponding images, the low res are provided from the beginning of the challenge and are meant for the participants to get online feedback from the validation server; the high resolution images will be released when the final phase of the challenge starts.
+
+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/Div2k', 'bicubic_x2', split='validation')
+eval_dataset = EvalDataset(dataset)
+model = EdsrModel.from_pretrained(input_dir, scale=scale)
+EvalMetrics.evaluate(model, eval_dataset)
+```
+
+### Supported Tasks and Leaderboards
+
+The dataset is commonly used for training and 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
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+An example of `train` for `bicubic_x2` looks as follows.
+```
+{
+    "hr": "/.cache/huggingface/datasets/downloads/extracted/DIV2K_valid_HR/0801.png",
+    "lr": "/.cache/huggingface/datasets/downloads/extracted/DIV2K_valid_LR_bicubic/X2/0801x2.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  |train |validation|
+|-------|-----:|---:|
+|bicubic_x2|800|100|
+|bicubic_x3|800|100|
+|bicubic_x4|800|100|
+|bicubic_x8|800|100|
+|unknown_x2|800|100|
+|unknown_x3|800|100|
+|unknown_x4|800|100|
+|realistic_mild_x4|800|100|
+|realistic_difficult_x4|800|100|
+|realistic_wild_x4|800|100|
+
+
+## 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
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+All the images are collected from the Internet, and the copyright belongs to the original owners. If any of the images 
+belongs to you and you would like it removed, please kindly inform the authors, and they will remove it from the dataset 
+immediately.
+
+## 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
+
+[More Information Needed]
+
+### Licensing Information
+
+Please notice that this dataset is made available for academic research purpose only. All the images are
+collected from the Internet, and the copyright belongs to the original owners. If any of the images belongs to 
+you and you would like it removed, please kindly inform the authors, and they will remove it from the dataset 
+immediately.
+
+### Citation Information
+
+```bibtex
+@InProceedings{Agustsson_2017_CVPR_Workshops,
+    author = {Agustsson, Eirikur and Timofte, Radu},
+    title = {NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study},
+    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
+    url = "http://www.vision.ee.ethz.ch/~timofter/publications/Agustsson-CVPRW-2017.pdf",
+    month = {July},
+    year = {2017}
+} 
+```
+
+### Contributions
+
+Thanks to [@eugenesiow](https://github.com/eugenesiow) for adding this dataset.