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.
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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