Blur Dataset

Blur Dataset

Datasets

Blur Dataset

File

Blur Dataset

Use Case

Computer Vision

Description

The dataset was created to validate the blur detection algorithm. The dataset can also be used for testing image deblurring.

Blur Dataset

About Dataset

Content

This dataset contains 1050 blurred and sharp images (350 triplets), each image triplet is a set of three photos of the same scene: sharp, defocused-blurred and motion-blurred images.

Context

The dataset was created to validate the blur detection algorithm. The dataset can also be used for testing image deblurring, hovewer, the triplets are not “pixel-to-pixel” images, so, one cannot compare blurred and sharp images on the basis of PSNR or SSIM but sharp images can be used for visual comparison.

Dataset structure

The dataset contains three folders: sharp, defocused-blurred and motion-blurred images.

The filename structure is as follows: id_device_type.extension where

ID – a number from 0 to349;
device – the image capture device;
type – one of [S, F, M]. S stands for Sharp image, F – deFocused-blurred image and M – Motion-blurred image.

The dataset contains 66 devices, these are typically smartphones, but several cameras are also provided.

Download

The dataset on Kaggle was scaled to 2048 pixels by the widest side, you can download full images from Google drive: https://drive.google.com/file/d/1RObmCDPeQ1Lg-V6u7dT02Pf0qH-QMcTp/view

The github page of the dataset: https://github.com/Kwentar/blur_dataset

How to cite

Here, at kaggle page

Acknowledgements

Thanks to my friends, colleagues and yandex.toloka who helps to collect this dataset.

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