eugenesiow/Set14
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--- 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: Set14 tags: - other-image-super-resolution --- # Dataset Card for Set14 ## 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://sites.google.com/site/romanzeyde/research-interests - **Repository**: https://huggingface.co/datasets/eugenesiow/Set14 - **Paper**: http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2010/CS/CS-2010-12.pdf - **Leaderboard**: https://github.com/eugenesiow/super-image#scale-x2 ### Dataset Summary Set14 is an evaluation dataset with 14 RGB images for the image super resolution task. It was first used as the test set of the paper "On single image scale-up using sparse-representations" by [Zeyde et al. (2010)](http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2010/CS/CS-2010-12.pdf). 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/Set14', '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/Set14_HR/baboon.png", "lr": "/.cache/huggingface/datasets/downloads/extracted/Set14_LR_x2/baboon.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|14| |bicubic_x3|14| |bicubic_x4|14| ## 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**: [Zeyde et al.](http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2010/CS/CS-2010-12.pdf) ### Licensing Information Academic use only. ### Citation Information ```bibtex @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} } ``` ### Contributions Thanks to [@eugenesiow](https://github.com/eugenesiow) for adding this dataset.
annotations_creators: - 机器生成 language_creators: - 公开获取 language: [] license: - 其他 multilinguality: - 单语言 size_categories: - 未知规模 source_datasets: - 原始数据集 task_categories: - 其他 task_ids: [] pretty_name: Set14 tags: - 其他图像超分辨率 --- # Set14 数据集卡片 ## 目录 - [目录](#table-of-contents) - [数据集描述](#dataset-description) - [数据集概述](#dataset-summary) - [支持任务与排行榜](#supported-tasks-and-leaderboards) - [语言信息](#languages) - [数据集结构](#dataset-structure) - [数据实例](#data-instances) - [数据字段](#data-fields) - [数据划分](#data-splits) - [数据集构建](#dataset-creation) - [构建初衷](#curation-rationale) - [源数据](#source-data) - [标注信息](#annotations) - [个人与敏感信息](#personal-and-sensitive-information) - [数据集使用注意事项](#considerations-for-using-the-data) - [数据集的社会影响](#social-impact-of-dataset) - [偏差讨论](#discussion-of-biases) - [其他已知局限性](#other-known-limitations) - [附加信息](#additional-information) - [数据集整理者](#dataset-curators) - [许可信息](#licensing-information) - [引用信息](#citation-information) - [贡献致谢](#contributions) ## 数据集描述 - **项目主页**：https://sites.google.com/site/romanzeyde/research-interests - **代码仓库**：https://huggingface.co/datasets/eugenesiow/Set14 - **相关论文**：http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2010/CS/CS-2010-12.pdf - **排行榜**：https://github.com/eugenesiow/super-image#scale-x2 ### 数据集概述 Set14是一款包含14张RGB图像的图像超分辨率（image super resolution）评估数据集，其首次被用作Zeyde等人2010年发表的论文《On single image scale-up using sparse-representations》的测试集。 可通过pip进行安装： bash pip install datasets super-image 可借助[`super-image`](https://github.com/eugenesiow/super-image)库完成模型评估： python from datasets import load_dataset from super_image import EdsrModel from super_image.data import EvalDataset, EvalMetrics dataset = load_dataset('eugenesiow/Set14', 'bicubic_x2', split='validation') eval_dataset = EvalDataset(dataset) model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2) EvalMetrics().evaluate(model, eval_dataset) ### 支持任务与排行榜 该数据集通常用于图像超分辨率（image super resolution）任务的模型评估。 非官方的[`super-image`](https://github.com/eugenesiow/super-image)排行榜涵盖以下缩放倍率： - [2倍缩放](https://github.com/eugenesiow/super-image#scale-x2) - [3倍缩放](https://github.com/eugenesiow/super-image#scale-x3) - [4倍缩放](https://github.com/eugenesiow/super-image#scale-x4) - [8倍缩放](https://github.com/eugenesiow/super-image#scale-x8) ### 语言信息 不适用。 ## 数据集结构 ### 数据实例 `bicubic_x2`划分下的`validation`集数据示例如下： { "hr": "/.cache/huggingface/datasets/downloads/extracted/Set14_HR/baboon.png", "lr": "/.cache/huggingface/datasets/downloads/extracted/Set14_LR_x2/baboon.png" } ### 数据字段 所有数据划分的数据字段格式保持一致： - `hr`：字符串类型，指向高分辨率（High Resolution, HR）`.png`图像的存储路径。 - `lr`：字符串类型，指向低分辨率（Low Resolution, LR）`.png`图像的存储路径。 ### 数据划分 | 划分名称 | validation样本数 | |----------------|-----------------:| | bicubic_x2 | 14 | | bicubic_x3 | 14 | | bicubic_x4 | 14 | ## 数据集构建 ### 构建初衷 [需补充更多信息] ### 源数据 #### 初始数据采集与归一化 [需补充更多信息] #### 语言生成者是谁？ [需补充更多信息] ### 标注信息 #### 标注流程 无标注流程。 #### 标注人员是谁？ 无标注人员。 ### 个人与敏感信息 [需补充更多信息] ## 数据集使用注意事项 ### 数据集的社会影响 [需补充更多信息] ### 偏差讨论 [需补充更多信息] ### 其他已知局限性 [需补充更多信息] ## 附加信息 ### 数据集整理者 - **原始作者**：[Zeyde等人](http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2010/CS/CS-2010-12.pdf) ### 许可信息 仅可用于学术用途。 ### 引用信息 bibtex @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} } ### 贡献致谢 感谢[@eugenesiow](https://github.com/eugenesiow)添加该数据集。
数据集概述
数据集描述
数据集总结
Set14是一个包含14张RGB图像的评估数据集，用于图像超分辨率任务。该数据集首次在Zeyde等人的论文"On single image scale-up using sparse-representations"中作为测试集使用。
支持的任务和排行榜
该数据集主要用于评估图像超分辨率任务。
数据集结构
数据实例
数据集中的每个实例包含两个字段：
hr: 高分辨率图像的路径。lr: 低分辨率图像的路径。
数据字段
hr: 字符串类型，指向高分辨率.png图像的路径。lr: 字符串类型，指向低分辨率.png图像的路径。
数据分割
数据集分为多个部分，每个部分包含14个实例。
数据集创建
来源数据
数据集的来源是原始数据。
注释
数据集没有注释。
许可证信息
数据集仅限学术使用。
引用信息
bibtex @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} }
