Blur Detection works using the total variance of the laplacian of an image, this provides a quick and accurate method for scoring how blurry an image is.

The repository has two main scripts, single.py and batch.py, which use the same blur detection method located in blur_detection. The blur detection method is highly dependent on the size of the image being processed. To get consistent scores the -f argument can be used to resize the image.

# processing a single image
python single.py -i input_image.py -d -f

# processing a directory
python batch.py -i input_directory/ -s results.json -f

The batch.py script produces a json file with information on the how blurry an image is, the higher the value, the less blurry the image.

{
    "input_dir": "/Users/demo_user/Pictures/Flat/",
    "results": [
        {
            "blurry": false,
            "input_path": "/Users/demo_user/Pictures/Flat/IMG_1666.JPG",
            "score": 6984.8082115095549
        },
    ],
    "threshold": 100.0
}

This is based upon the blogpost Blur Detection With Opencv by Adrian Rosebrock.