I have written a small program (my first Tkinter-based app) to play
around the idea mentioned on
http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/
and, in doing so, have encountered a memory leak problem. I have
seen mentions on the web of using the delete() method of canvas to
prevent such problems - which I have tried to do with limited
success. Below is the code I wrote; to run it, you will need a small
image file
(I used the one found on http://alteredqualia.com/visualization/evolve/)
that is saved under "mona_lisa.png".
Any help would be greatly appreciated.
André
==
from Tkinter import Canvas, Tk, Label
import Image, ImageTk, ImageChops, ImageStat # PIL
import aggdraw
from random import randint
import time
import copy
FITNESS_OFFSET = 0
saved = [None, None]
def fitness(im1, im2):
"""Calculate a value derived from the root mean squared of the
difference
between two images. It is normalized so that when a black image
is
compared with the original one (img1), the fitness given is 0, and
when the
image is identical, the fitness value is 100."""
global FITNESS_OFFSET
stat = ImageStat.Stat(ImageChops.difference(im1, im2))
fit = 1. - sum(stat.rms[:3])/(255*3)
if FITNESS_OFFSET == 0:
black_image = aggdraw.Draw("RGBA", im1.size, "black")
s = black_image.tostring()
raw = Image.fromstring('RGBA', im1.size, s)
stat = ImageStat.Stat(ImageChops.difference(im1, raw))
FITNESS_OFFSET = 1. - sum(stat.rms[:3])/(255*3)
return 100*(fit-FITNESS_OFFSET)/(1.-FITNESS_OFFSET)
class DNA(object):
def __init__(self, width, height, polygons=50, edges=6):
self.polygons = polygons
self.edges = edges
self.width = width
self.height = height
self.dna = []
def init_dna(self):
for i in range(self.polygons):
self.dna.append(self.random_polygon())
def random_polygon(self):
edges = []
for i in range(self.edges):
edges.append(randint(0, self.width))
edges.append(randint(0, self.height))
col = [randint(0, 255), randint(0, 255), randint(0, 255),
randint(0, 255)]
return edges, col
def mutate(self):
selected = randint(0, self.polygons-1)
_type = randint(0, 2)
if _type == 0: # colour
col_index = randint(0, 3)
self.dna[selected][1][col_index] = randint(0, 255)
elif _type == 1: # x coordinate
coord = randint(0, self.edges-1)
self.dna[selected][0][2*coord] = randint(0, self.width)
elif _type == 2: # y coordinate
coord = randint(0, self.edges-1)
self.dna[selected][0][2*coord+1] = randint(0, self.height)
class AggDrawCanvas(Canvas):
def __init__(self, width, height, win):
Canvas.__init__(self, win)
self.image_id = None
self.win = win
self._width = width
self._height = height
self._size = width, height
self.config(width=width, height=height+20)
self.info = self.create_text(width/2, height+20)
self.pack()
self.dna = DNA(self._width, self._height)
self.mutations = 0
def draw_dna(self):
img = Image.new("RGBA", self._size, "black")
self.context = aggdraw.Draw(img)
for gene in self.dna.dna:
brush = aggdraw.Brush(tuple(gene[1][0:3]), opacity=gene[1]
[3])
self.context.polygon(gene[0], brush)
self.delete(img)
self.redraw()
def redraw(self):
self.mutations += 1
s = self.context.tostring()
self.delete(self.context)
raw = Image.fromstring('RGBA', self._size, s)
self.fitness = fitness(mona_lisa, raw)
self.itemconfig(self.info,
text="%2.2f %d"%(self.fitness,
self.mutations),
fill="black")
self.image = ImageTk.PhotoImage(raw)
self.delete(self.image_id)
self.image_id = self.create_image(self._width/2, self._height/
2, image=self.image)
self.update()
win = Tk()
mona_lisa = Image.open("mona_lisa.png")
img = ImageTk.PhotoImage(mona_lisa)
original_image = Canvas(win)
original_image.pack()
fitness_label = Label(win)
_w, _h = img.width(), img.height()
original_image.config(width=_w, height=_h)
original_image.create_image(_w/2, _h/2, image=img)
best_fit = AggDrawCanvas(_w, _h, win)
best_fit.dna.dna = []
best_fit.draw_dna()
current_fit = AggDrawCanvas(_w, _h, win)
current_fit.dna.init_dna()
current_fit.draw_dna()
while True:
current_fit.dna.mutate()
current_fit.draw_dna()
if current_fit.fitness > best_fit.fitness:
best_fit.dna.dna = copy.deepcopy(current_fit.dna.dna)
best_fit.draw_dna()
else:
current_fit.dna.dna = copy.deepcopy(best_fit.dna.dna)
if __name__ == '__main__':
win.mainloop()
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