Datasets:
metadata
annotations_creators: []
language: en
license: other
size_categories:
- n<1K
task_categories:
- image-to-image
task_ids: []
pretty_name: Set5
tags:
- fiftyone
- image
- superresolution
dataset_summary: >
![image/png](dataset_preview.gif)
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 135
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("Voxel51/Set5")
# Launch the App
session = fo.launch_app(dataset)
```
Dataset Card for Set5
This is a FiftyOne dataset with 135 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("Voxel51/Set5")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details
Dataset Description
The Set5 dataset is a dataset consisting of 5 images (“baby”, “bird”, “butterfly”, “head”, “woman”) commonly used for testing performance of Image Super-Resolution models.
- Curated by: Bevilacqua, Marco and Roumy, Antoine and Guillemot, Christine and Alberi-Morel, Marie-Line
- Language(s) (NLP): en
- License: other
Dataset Sources
- Repository: https://github.com/ChaofWang/Awesome-Super-Resolution/blob/master/dataset.md
- Paper: Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding
- Homepage: https://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html
Uses
Super-resolution
Dataset Creation
Citation
BibTeX:
@inproceedings{bevilacqua2012low,
title={Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding},
author={Bevilacqua, Marco and Roumy, Antoine and Guillemot, Christine and Alberi-Morel, Marie-Line},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
year={2012}
}