--- annotations_creators: - machine-generated language_creators: - found language: [] license: - cc-by-4.0 multilinguality: - monolingual pretty_name: Urban100 size_categories: - unknown source_datasets: - original task_categories: - other task_ids: - other-other-image-super-resolution --- # Dataset Card for Urban100 ## 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://github.com/jbhuang0604/SelfExSR - **Repository**: https://huggingface.co/datasets/eugenesiow/Urban100 - **Paper**: https://openaccess.thecvf.com/content_cvpr_2015/html/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.html - **Leaderboard**: https://github.com/eugenesiow/super-image#scale-x2 ### Dataset Summary The Urban100 dataset contains 100 images of urban scenes. It commonly used as a test set to evaluate the performance of super-resolution models. It was first published by [Huang et al. (2015)](https://openaccess.thecvf.com/content_cvpr_2015/html/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.html) in the paper "Single Image Super-Resolution From Transformed Self-Exemplars". 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/Urban100', '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/Urban100_HR/img_001.png", "lr": "/.cache/huggingface/datasets/downloads/extracted/Urban100_LR_x2/img_001.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|100| |bicubic_x3|100| |bicubic_x4|100| ## Dataset Creation ### Curation Rationale The authors have created Urban100 containing 100 HR images with a variety of real-world structures. ### Source Data #### Initial Data Collection and Normalization The authors constructed this dataset using images from Flickr (under CC license) using keywords such as urban, city, architecture, and structure. #### 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**: [Huang et al. (2015)](https://github.com/jbhuang0604/SelfExSR) ### Licensing Information The dataset provided uses images from Flikr under the CC (CC-BY-4.0) license. ### Citation Information ```bibtex @InProceedings{Huang_2015_CVPR, author = {Huang, Jia-Bin and Singh, Abhishek and Ahuja, Narendra}, title = {Single Image Super-Resolution From Transformed Self-Exemplars}, booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2015} } ``` ### Contributions Thanks to [@eugenesiow](https://github.com/eugenesiow) for adding this dataset.