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* to define the range, use:{{{#!python from scipy.misc import toimage import numpy a = numpy.random.rand(25,50) #between 0. and 1. toimage(a, cmin=0., cmax=2.).save('low_contrast_snow.png') }}} (adapted from http://telin.ugent.be/~slippens/drupal/scipy_unscaledimsave ) |
Image processing often works on gray scale images that were stored as PNG files. How do we import / export that file into python?
Here is a recipy to do this with Matplotlib using the imread function (your image is called lena.png).
1 from pylab import imread, imshow, gray, mean 2 a = imread('lena.png') 3 #generates a RGB image, so do 4 aa=mean(a,2) # to get a 2-D array 5 imshow(aa) 6 gray()
This permits to do some processing for further exporting such as for converting a matrix to a raster image. In the newest version of pylab (check that your pylab.matplotlib.__version__ is superior to '0.98.0') you get directly a 2D numpy array if the image is grayscale.
to write an image, do
1 import Image 2 mode = 'L' 3 size= (256, 256) 4 imNew=Image.new(mode , size) 5 mat = numpy.random.uniform(size = size) 6 data = numpy.ravel(mat) 7 data = numpy.floor(data * 256) 8 9 imNew.putdata(data) 10 imNew.save("rand.png")
this kind of functions live also under scipy.misc, see for instance scipy.misc.imsave to create a color image:
1 from scipy.misc import imsave 2 import numpy 3 a = numpy.zeros((4,4,3)) 4 a[0,0,:] = [128, 0 , 255] 5 imsave('graybackground_with_a_greyish_blue_square_on_top.png',a)
to define the range, use:
1 from scipy.misc import toimage 2 import numpy 3 a = numpy.random.rand(25,50) #between 0. and 1. 4 toimage(a, cmin=0., cmax=2.).save('low_contrast_snow.png')
(adapted from http://telin.ugent.be/~slippens/drupal/scipy_unscaledimsave )
there was another (more direct) method suggested by http://jehiah.cz/archive/creating-images-with-numpy

