Smil <-> NumPy interface

Table of Contents

• Generalities
• Some examples
  • From Numpy to Smil
  • From Smil to Numpy
  • From Smil to Numpy to Smil

Generalities

NumPy is a package for scientific computing with Python. Smil allows to

• access, with NumPy functions, the Smil image pixels with the method Image::getNumArray().
  • This is not a copy of the data but a real access to the image pixels via NumPy.
• create a Smil image from a NumPy array with one of the methods Image::fromNumArray(arr) or Image(arr) or NumpyInt(arr).

Note

These functions are available only inside Python environnment.

Some examples

From Numpy to Smil

• Create a Smil image from a Numpy array with Image()

  import smilPython as sp
  import numpy as np
   
  # create a 10x10 NumPy array
  ar = np.zeros((32, 32), 'uint8')
  ar[8,:] = 255
  ar[:, 16] = 255
   
  # creates a Smil image and set it's content to "ar"
  img = sp.Image(ar)

• Create a Smil image from a Numpy array with fromNumArray()

  import smilPython as sp
  import numpy as np
   
  # create a 10x10 NumPy array
  a = np.array(range(100), 'uint8')
  a = a.reshape(10, 10)
   
  # creates a Smil image and set it's content to "a"
  img = sp.Image()
  img.fromNumArray(a)

Note

• The content of the image is a copy of the content of the Numpy array;
• The image size will be derived from the array shape;
• for a more complex example, take a look on "how to read 3D Tiff images" at smilPyGoodies/smilPyRead3D.

From Smil to Numpy

From a Smil image, do some operation under Numpy. Use getNumArray().

 
import smilPython as sm
import numpy as np
 
# read a PNG image file (8 bits gray image)
file = "my-image.png")
img = sm.Image(file)
 
# show the image
img.show(file)
 
# get a NumPy array
p = img.getNumArray()
 
# let's threshold the image
t = 127
p[p >= t] = 255
p[p <  t] = 0
 
# Call the "modified" method in order to update the viewer content
img.modified()
 

Note

• the array returned by getNumArray() is a pointer to the Smil image, not a copy.

From Smil to Numpy to Smil

1. From a 16 bits Smil Image, use Numpy to convert it to 8 bits image

    
   import smilPython as sm
   import numpy as np
    
   # read a 16 bits RAW Image
   file = "Slices-16.raw"
   im16 = sm.Image('UINT16')
   sp.readRAW(file, 700, 700, 700, im16)
    
   # Let's convert 8 bit input image
    
   # get a pointer to a numpy array
   p16 = im16.getNumArray()
    
   # scale pixel values from 2**16 to 2**8
   p16 //= 256
    
   # get a new 8 bit numpy array
   p8 = p.astype('uint8')
    
   # create a 8 bits image with the same dimensions of the 16 bit image
   im8 = sm.Image(im16, 'UINT8')
   # come back to Smil Image
   im8.fromNumArray(p8)
    

2. Use Numpy to easily create a Smil image with a circle inside it.

    
   import smilPython as sp
   import numpy as np
    
   # Create an image
   sx = 256
   sy = 384
   im1 = sp.Image(sx, sy)
   im1.show()
    
   # Create a numpy array containing the real image pixels
   imArr = im1.getNumArray()
    
   # Display the dimensions of the created array
   print("Array dims:", imArr.shape)
    
   # Do something with the array... E.g., draw a circle
   imArr[:] = 0
   # the circle will be centered at the center of the image
   radius, cx, cy = 64, sy//2, sx//2
   y, x = np.ogrid[0:sx, 0:sy]
   # get the indexes of the pixels inside the circle
   index = (x - cx)**2 + (y - cy)**2 <= radius**2
   imArr[:,:][index] = 255
    
   # Call the "modified" method in order to update the viewer content
   im1.modified()
    
   input()