class Population: def __init__(self): self.artist = Artist(Population.imageFitnessFunction) def evolve(self): oldFitness = self.artist.fitness self.mutationCommands = self.artist.mutate() [m.execute() for m in self.mutationCommands] if self.artist.fitness > oldFitness: return False return True def unevolve(self): if self.mutationCommands: [c.undo() for c in self.mutationCommands] def bestArtist(self): return self.artist @staticmethod def imageFitnessFunction(image): return ImageTools.compareToArray(image, precachedTarget)
class Population:
def __init__(self):
self.artist = Artist(Population.imageFitnessFunction)
def evolve(self):
oldFitness = self.artist.fitness
self.mutationCommands = self.artist.mutate()
[m.execute() for m in self.mutationCommands]
if self.artist.fitness > oldFitness:
return False
return True
def unevolve(self):
if self.mutationCommands:
[c.undo() for c in self.mutationCommands]
def bestArtist(self):
return self.artist
@staticmethod
def imageFitnessFunction(image):
return ImageTools.compareToArray(image, precachedTarget)
population = int(args['population'])
input_path = args['file']
img = Image.open(input_path)
if args["width"] != None:
img = setSize(int(args["width"]), img)
size = img.size
artist = Artist(None, 50, size)
parent_img = artist.draw(size, (0, 0, 0, 255))
artist.getFittness(parent_img, img)
while (1):
child_artist = Artist(artist.DNA, 50, size)
child_artist.DNA = child_artist.mutate()
child_img = child_artist.draw(size, (0, 0, 0, 255))
child_artist.getFittness(child_img, img)
artists.append(child_artist)
for child_artist in artists:
if child_artist.fittness < artist.fittness:
artist = child_artist
if generation % 50 == 0:
print "[+] Generation: {}".format(generation)
print "[+] Fittness: {}".format(artist.fittness)
artist.draw(size, (0, 0, 0, 255),
save=True,
save_path=output_path,
name=str(generation))
