hr
stringclasses
5 values
lr
stringclasses
5 values
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/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/3ac517a00f2bce893d0cfec525d48773fb91f3aac172dc518f51d75e9beae106/Set5_HR/bird.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/77dac4826bcab1a085d28101a075c3a2d799a7b32e4d9318cbdf1ebc637ac084/Set5_LR_x2/bird.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/3ac517a00f2bce893d0cfec525d48773fb91f3aac172dc518f51d75e9beae106/Set5_HR/butterfly.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/77dac4826bcab1a085d28101a075c3a2d799a7b32e4d9318cbdf1ebc637ac084/Set5_LR_x2/butterfly.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/3ac517a00f2bce893d0cfec525d48773fb91f3aac172dc518f51d75e9beae106/Set5_HR/head.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/77dac4826bcab1a085d28101a075c3a2d799a7b32e4d9318cbdf1ebc637ac084/Set5_LR_x2/head.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/3ac517a00f2bce893d0cfec525d48773fb91f3aac172dc518f51d75e9beae106/Set5_HR/woman.png
/storage/hf-datasets-cache/all/datasets/61269473884020-config-parquet-and-info-eugenesiow-Set5-64a92ea9/downloads/extracted/77dac4826bcab1a085d28101a075c3a2d799a7b32e4d9318cbdf1ebc637ac084/Set5_LR_x2/woman.png

Dataset Card for Set5

Dataset Summary

Set5 is a evaluation dataset with 5 RGB images for the image super resolution task. The 5 images of the dataset are (鈥渂aby鈥, 鈥渂ird鈥, 鈥渂utterfly鈥, 鈥渉ead鈥, 鈥渨oman鈥).

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/Set5', '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/Set5_HR/baby.png",
    "lr": "/.cache/huggingface/datasets/downloads/extracted/Set5_LR_x2/baby.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 5
bicubic_x3 5
bicubic_x4 5

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

@article{bevilacqua2012low,
  title={Low-complexity single-image super-resolution based on nonnegative neighbor embedding},
  author={Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line},
  year={2012},
  publisher={BMVA press}
}

Contributions

Thanks to @eugenesiow for adding this dataset.

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