metadata

annotations_creators: []
language: en
license: other
size_categories:
  - 1K<n<10K
task_categories:
  - image-to-image
task_ids: []
pretty_name: Urban100
tags:
  - fiftyone
  - image
  - super-resolution
dataset_summary: >



  ![image/png](dataset_preview.gif)



  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2200
  samples.


  ## Installation


  If you haven't already, install FiftyOne:


  ```bash

  pip install -U fiftyone

  ```


  ## Usage


  ```python

  import fiftyone as fo

  import fiftyone.utils.huggingface as fouh


  # Load the dataset

  # Note: other available arguments include 'max_samples', etc

  dataset = fouh.load_from_hub("jamarks/Urban100")


  # Launch the App

  session = fo.launch_app(dataset)

  ```

Dataset Card for Urban100

This is a FiftyOne dataset with 2200 samples.

Installation

If you haven't already, install FiftyOne:

pip install -U fiftyone

Usage

import fiftyone as fo
import fiftyone.utils.huggingface as fouh

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("jamarks/Urban100")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details

Dataset Description

The Urban100 dataset contains 100 images of urban scenes. It commonly used as a test set to evaluate the performance of super-resolution models.

Curated by: Jia-Bin Huang, Abhishek Singh, Narendra Ahuja
Language(s) (NLP): en
License: other

Dataset Sources

Repository: https://github.com/jbhuang0604/SelfExSR
Paper: https://openaccess.thecvf.com/content_cvpr_2015/papers/Huang_Single_Image_Super-Resolution_2015_CVPR_paper.pdf
Demo: https://try.fiftyone.ai/datasets/urban100/samples

Citation

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}
}

Dataset Card Authors

Jacob Marks