hr
stringclasses 14
values | lr
stringclasses 14
values |
---|---|
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Dataset Card for Set14
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
: astring
to the path of the High Resolution (HR).png
image.lr
: astring
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.
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.
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