Set14 / README.md
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metadata
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

Dataset Description

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).

Install with pip:

pip install datasets super-image

Evaluate a model with the super-image library:

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 leaderboard for:

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

Licensing Information

Academic use only.

Citation Information

@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 for adding this dataset.