Skip to main content

Why I love Python

I was reading "The remarkable inefficiency of word recognition" (Pelli et al. 2003) and I wanted to generate some of the stimuli they were using. In Python it took me a few hours total, starting cold using the Python Imaging Library. The code is below....
"""This contains routines to generate degraded letter stimuli"""

import Image #The PIL
import ImageDraw
import ImageFont

import numpy

def generate_letter(contrast_energy = .01, #michelson contrast energy
                   noise = 30.,
                   bg_luminance = 128.,
                   letter = "a",
                   letter_size = 400):
 N = 300 #size of image in pixels

 #first figure out what is the ink-area of the letter

 font = ImageFont.truetype("Data/arial.ttf", letter_size)
 #we copy the .ttf file to the local directory to avoid problems

 im_temp = Image.new("1", (1,1), 0)
 draw = ImageDraw.Draw(im_temp)
 #now we can draw on this

 sz = draw.textsize(letter, font=font)
 #this tells us the size of the letter

 im_temp = Image.new("1", sz, 0)
 #this is a temporary binary image created solely for the purpose of computing
 #the ink-area of the letter
 draw = ImageDraw.Draw(im_temp)
 #now we can draw on this
 draw.text((0,0), letter, font=font, fill=1)
 pix = im_temp.load()
 #pix is now an addressable array of pixel values
 area_in_pixels = 0.
 for row in xrange(sz[0]):
   for col in xrange(sz[1]):
     area_in_pixels += pix[row,col]

 #since contrast_energy = contrast^2 * pixel_area
 contrast = (contrast_energy/area_in_pixels)**0.5
 fg_luminance = bg_luminance*(1+contrast)/(1-contrast)
 print area_in_pixels
 print contrast
 print fg_luminance


 im = Image.new("L", (N,N), bg_luminance)
 #im is now a NxN luminance image with luminance set to bg_luminance

 draw = ImageDraw.Draw(im)
 #now we can draw on this

 draw.text(((N-sz[0])/2, (N-sz[1])/2), letter, font=font, fill=fg_luminance)
 #this centers the letter

 if noise > 0:
   pix = im.load()
   #pix is now an addressable array of pixel values
  
   rd = numpy.random.normal(scale=noise, size=(N,N))
   for row in xrange(N):
     for col in xrange(N):
       pix[row,col] += rd[row,col]

 im.show()

Labels:

Comments

Post a Comment

Popular posts from this blog

A note on Python's __exit__() and errors

Python's context managers are a very neat way of handling code that needs a teardown once you are done. Python objects have do have a destructor method ( __del__ ) called right before the last instance of the object is about to be destroyed. You can do a teardown there. However there is a lot of fine print to the __del__ method. A cleaner way of doing tear-downs is through Python's context manager , manifested as the with keyword. class CrushMe: def __init__(self): self.f = open('test.txt', 'w') def foo(self, a, b): self.f.write(str(a - b)) def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() return True with CrushMe() as c: c.foo(2, 3) One thing that is important, and that got me just now, is error handling. I made the mistake of ignoring all those 'junk' arguments ( exc_type, exc_val, exc_tb ). I just skimmed the docs and what popped out is that you need to return True or...
Post a Comment
Read more

Remove field code from Word document

e.g. before submitting a MS, or hand manipulating some formatting because Word does things (like cross-references) so half-assed [from here ] Select all the text (CTRL-A) Press Ctrl+Shift+F9 Editing to remove anonymous comments that only contain thanks. I really appreciate the thanks, but it makes it harder to find comments that carry pertinent information. I'm also going to try and paste informative comments in the body of the post to make them easier to find.
24 comments
Read more

h5py and multiprocessing

The HDF5 format has been working awesome for me, but I ran into danger when I started to mix it with multiprocessing. It was the worst kind of danger: the intermittent error. Here are the dangers/issues in order of escalation (TL;DR is use a generator to feed data from your file into the child processes as they spawn. It's the easiest way. Read on for harder ways.) An h5py file handle can't be pickled and therefore can't be passed as an argument using pool.map() If you set the handle as a global and access it from the child processes you run the risk of racing which leads to corrupted reads. My personal runin was that my code sometimes ran fine but sometimes would complain that there are NaNs or Infinity in the data. This wasted some time tracking down. Other people have had this kind of problem [ 1 ]. Same problem if you pass the filename and have the different processes open individual instances of the file separately. The hard way to solve this problem is to sw...
Post a Comment
Read more