compressMeDim.py

#run this in any directory with the max width parameter add -v for verbose 

#image will be scalled in proportion to confine within the max width parameter
#this allows you to get images that are within a box dimension for online publishing (i.e. 400x400) without distorting the image

#get Pillow (fork of PIL) from pip before running --> pip install Pillow

#regarding timing: 42 seconds for 4938 so max 15 minutes for 100,000 images

from __future__ import division
from PIL import Image
import os
import sys

def compressMeReturn(file, maxDim, verbose=False):
	filepath = os.path.join(os.getcwd(), file)
	oldsize = os.stat(filepath).st_size
	picture = Image.open(filepath)
	dim = picture.size
	
	ratio = (maxDim/dim[0],maxDim/dim[1])
	
	picture.thumbnail((dim[0]*ratio[0],dim[1]*ratio[1]), Image.ANTIALIAS)
	picture.save("Compressed_"+file,"JPEG",optimize=True,quality=85) 
	
	newsize = os.stat(os.path.join(os.getcwd(),"Compressed_"+file)).st_size
	percent = (oldsize-newsize)/float(oldsize)*100
	if (verbose):
		print "File compressed from {0} to {1} or {2}%".format(oldsize,newsize,percent)
	return percent

def main():
	maxDimension = sys.argv[1]
	verbose = False
	if (len(sys.argv)>2):
		if (sys.argv[2].lower()=="-v"):
			verbose = True

	pwd = os.getcwd()
	tot = 0
	num = 0
	for file in os.listdir(pwd):
		if os.path.splitext(file)[1].lower() in ('.jpg', '.jpeg'):
			num+=1
			tot += compressMeReturn(file, int(maxDimension),verbose)
	print "Average Compression: %d" % (float(tot)/num)
	print "Done"

if __name__ == "__main__":
	main()