This example is an application for displaying an image with the ability to stretch the window size arbitrarily (thus enabling to zoom in on the image):


from Tkinter import *
import Image, ImageTk
import sys

#
# an image viewer

class UI(Canvas):

def __init__(self, master, im):


x, y, orig_w, orig_h = im.getbbox()
Canvas.__init__(self, master,width=orig_w, height=orig_h)
tmpim = ImageTk.PhotoImage(im)
self.origim = im
self.image = tmpim
self.create_image(orig_w/2, orig_h/2, image=tmpim)

self.bind('',self.resizeImage)

top=self.winfo_toplevel()
top.rowconfigure(0, weight=1)
top.columnconfigure(0, weight=1)
self.rowconfigure(0, weight=1)
self.columnconfigure(0, weight=1)
self.grid(sticky=N+S+E+W)


def resizeImage(self,event):

im = self.origim.resize((event.width, event.height),Image.ANTIALIAS)
tmpim = ImageTk.PhotoImage(im)
self.image = tmpim
self.create_image(event.width/2, event.height/2, image=tmpim)

if not sys.argv[1:]:

print 'need an image name!'
exit()

else:

filename = sys.argv[1]

root = Tk()
root.title(filename)
im = Image.open(filename)

UI(root, im)
root.mainloop()

converting 8bit image to 32 bit image

If you have an 8bit source image and you want to convert it to a 32 bit image you do it using cvConvertScale:

newim = cvCreateImage (cvSize (src.rows, src.cols, 32, 1)
cvConvertScale(src,newim)

How to crop images with opencv in python

Found this helpful tip from a fellow python-opencv user:
find it here

Opencv example

Here's a short example showing how to use openCV with Python.It reads an image from a file, displays the image, the Harris corner detector on that image and the Canny edge image:
(save this in a file named tmp.py and run with: python tmp.py )

import Image
import os
import sys
from opencv.cv import *
from opencv.highgui import *

def analyzeImage(f,name):

im=Image.open(f)
try:

if(im.size[0]==1 or im.size[1]==1):

return

print (name+' : '+str(im.size[0])+','+ str(im.size[1]))
le=1
if(type(im.getpixel((0,0)))==type((1,2))):

le=len(im.getpixel((0,0)))

gray = cvCreateImage (cvSize (im.size[0], im.size[1]), 8, 1)
edge1 = cvCreateImage (cvSize (im.size[0], im.size[1]), 32, 1)
edge2 = cvCreateImage (cvSize (im.size[0], im.size[1]), 8, 1)
edge3 = cvCreateImage (cvSize (im.size[0], im.size[1]), 32, 3)

for h in range(im.size[1]):

for w in range(im.size[0]):

p=im.getpixel((w,h))
if(type(p)==type(1)):

gray[h][w] = im.getpixel((w,h))

else:

gray[h][w] = im.getpixel((w,h))[0]



cvCornerHarris(gray,edge1,5,5,0.1)
cvCanny(gray,edge2,20,100)

cvNamedWindow("win")
cvShowImage("win", gray);
cvNamedWindow("win2")
cvShowImage("win2", edge1);
cvNamedWindow("win3")
cvShowImage("win3", edge2);

cvWaitKey()

f.close()

except Exception,e:

print e
print 'ERROR: problem handling '+ name

f = open(sys.argv[1],'r')
analyzeImage(f,sys.argv[1])

Image processing tools for python

The most basic library is PIL. it provides pretty basic tools for reading,writing and displaying images, some tools for drawing. In terms of image processing it has some functions for cropping, resizing, sharpening images. For more complex operations I found it insufficient.
The library I found to be useful so far is the Python binding for OpenCV. It can be found here. Installing it should not be too difficult, though I could not get it working until I installed the following:
sudo apt-get install python-opencv

I will describe here my short experience in trying to develop image processing applications using python.

I am developing on Ubuntu, which I highly recommend. For anyone familiar with Linux but is afraid of all the trouble in installing it, Ubuntu is an extremely user friendly environment with an almost Plug-and-Play installation process (you can download it here Ubuntu Download).
For developers linux/ubuntu offers many opensource tools which are easily accessible and ready to use.

The application I am working on involves crawling the web, searching for images, creating a DB of these images and then processing theses images in order to create a useful indexing (you might say it is sort of an image retrieval search engine). It is still in it's very early stages and much of the work is experimental. I will describe here some of the hardships I had to overcome in the process, hopefully it might save some other people's time.

So.... Let's dive right into the WEE BUFETS (Warnings,Errors, Exceptions, Bugs, Unanticipated results, Features, and other Excrements of Toxic Software)

Convert string to file handle:
Here's one sucker I had to deal with yesterday. It goes a little something like this:
Let's say you have a string which is a binary buffer holding the contents of a file. You want to
convert it to a file handle but you don't want to go through the trouble of of writing it to a file and then opening it and getting the file handle. You can do this using the following python code:
import StringIO
f = StringIO.StringIO("string containing file data")

That's it! now you can treat f as a regular file handle much the same way you would after a call to the 'open' function - I encountered this when I saved an image file in a mysql DB as a blob object, then reading from the database.