Differences between revisions 10 and 11

 Deletions are marked like this. Additions are marked like this. Line 32: Line 32: import numpy Line 36: Line 37: * 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
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')

• there was another (more direct) method suggested by http://jehiah.cz/archive/creating-images-with-numpy

Cookbook/Matplotlib/LoadImage (last edited 2008-12-08 10:12:28 by LaurentPerrinet)