Overview

The Python Imaging Library adds image processing capabilities to your Python interpreter.

This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities.

The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.

Let’s look at a few possible uses of this library.

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Code Snippets

To Compare two images with python using Pillow

import math, operator

from PIL import Image

def compare(file1, file2):

image1 = Image.open(file1)

image2 = Image.open(file2)

h1 = image1.histogram()

h2 = image2.histogram()

rms = math.sqrt(reduce(operator.add,map(lambda a,b: (a-b)**2, h1, h2))/len(h1))

return rms

if __name__=='__main__':

import sys

file1, file2 = sys.argv[1:]

print compare(file1, file2)

To get all EXIF informations of image using pillow

from PIL import Image

def get_exif_tags(img_obj):

ret = {}

try:

info = img_obj._getexif()

if info:

for tag, value in info.items():

decoded = TAGS.get(tag, tag)

ret[decoded] = value

except: pass

return ret

if __name__ == "__main__":

url="http://www.scipy-lectures.org/_images/face.png"

response = requests.get(url,verify=False).content

img_obj = PIL.Image.open(BytesIO(response))

get_exif_tags(img_obj)

To Get the image size in bytes using PIL

from PIL import Image

image_file = Image.open(filename)

print("File Size In Bytes:- "+str(len(image_file.fp.read()))

Converting Bytes to Human readable format

def sizeof_fmt(self,num, suffix='o'):

"""Readable file size

:param num: Bytes value

:type num: int

:param suffix: Unit suffix (optionnal) default = o

:type suffix: str

:rtype: str

"""

for unit in ['', 'K', 'M', 'G', 'T', 'P', 'E', 'Z']:

if abs(num) < 1024.0:

return "%3.1f %s%s" % (num, unit, suffix)

num /= 1024.0

return "%.1f%s%s" % (num, 'Yi', suffix)