imagedegrade

It is a python package to degrade image data.

Usage

Import sample

from imagedegrade import np as degrade

imagedegrade.np.blur( input, blur_sigma )

Blur input data by Gaussian kernel.It simply calls: scipy.ndimage.gaussian_filter(input, sigma=[blur_sigma,blur_sigma,0], truncate=3.0, mode='nearest' )

• input numpy.ndarray Three dimensional array of [height, width, channel]. Note that it should be three dimensional array even if it is a gray image data.

• blur_sigma float It specifies the standard deviation of Gaussian blur kernel.

• output numpy.ndarray Blurred data.

imagedegrade.np.noise( input, noise_sigma )

Add Gaussian noise to input data. It simply calls: input + numpy.random.normal(0., noise_sigma, input.shape )

• input numpy.ndarray

• noise_sigma float It specifies the standard deviaion of Gaussian noise.

• output numpy.ndarray Noisy data.

imagedegrade.np.saltpepper( input, p, intensity_range = (0,1) )

Add Salt-and-Pepper noise to input data.

• input numpy.ndarray

• p float It specifies the probability of the intensity_range[0] and intensity_range[1].

• intensity_range tuple of floats It specifys intensity range of the input image data. Actually, intensity_range is the values for the pepper and the salt.

• output numpy.ndarray Noisy data.

imagedegrade.np.jpeg( input, jpeg_quality, intensity_range = (0,1), **kwargs )

Add JPEG compression distortion. Gray image version is not debugged.

• input numpy.ndarray Three dimensional array of [height, width, channel]. Note that it should be three dimensional array even if it is a gray image data.

• jpeg_quality int It specifys jpeg quality. The range is 1 to 100. Note that even if you specify 100, the output is included some JPEG compression distortion.

• intensity_range tuple of floats It specifys intensity range of the input image data.

JPEG compression is caluclated in uint8. Before JPEG compression, data is applied:

( data - intensity_range[0] ) / ( intensity_range[1] - intensity_range[0] ) * 255.0

After JPEG compression, data is applied:

data / 255.0 * ( intensity_range[1] - intensity_range[0] ) + intensity_range[0]

If dtype of input is uint8, those calculation is not applied.

• **kwargs Options for the JPEG. For details, plesae visit the pillow document.

• output numpy.ndarray The image data with JPEG compression distortion.

imagedegrade.np.blur_noise_jpeg( input, blur_sigma, noise_sigma, jpeg_quality, intensity_range = (0,1) )

It sequentially applys blur, noise, and jpeg compression distortion. Please check the above descriptions for the parameters.

Install

% pip install imagedegrade

or

% pip install git+https://github.com/mastnk/imagedegrade

Author

Masayuki Tanaka