Python PyHyperNEAT.cleanup 예제들

예제 #1

    def __del__( self ):
        # Save best population.
        self.experiment.saveBest()

        # Cleanup HyperNEAT.
        neat.cleanup()

        # Exit evolve thread.
        try:
            self.evolve_thread.terminate()
            self.evolve_thread.wait( 5000 )
        except NameError:
            print "Evolve thread not created yet, thus not destroyed."

예제 #2

    def __del__( self ):
        # Save best population.
        self.experiment.saveBest()

        # Cleanup HyperNEAT.
        neat.cleanup()

        # Exit evolve thread.
        try:
            self.evolve_thread.terminate()
            self.evolve_thread.wait( 5000 )
        except NameError:
            print "Evolve thread not created yet, thus not destroyed."

예제 #3

파일: distort.py 프로젝트: anthonytw/neat-deform

import gui.PopulationModel

print "-------------------------------------------------------------------"
print "DISTORTING IMAGE"

# Load the file and generate the network.
print "-------------------------------------------------------------------"
print "Loading network..."
neat.initialize()
population = neat.load(argv[1])
individual = population.getIndividual(0, population.getGenerationCount() - 1)
network = individual.spawnFastPhenotypeStack()

# Open the input image.
print "-------------------------------------------------------------------"
print "Distorting image..."
distortion = gui.PopulationModel.PopulationItem()

application = QApplication(argv)
image_map = QPixmap(argv[2])
distorted_image_map = distortion.distort(image_map, network)
distorted_image = QImage(distorted_image_map)
distorted_image.save(argv[3])

# Cleanup.
print "-------------------------------------------------------------------"
print "Done, cleaning up."
print "-------------------------------------------------------------------"
neat.cleanup()

예제 #4

파일: distort.py 프로젝트: anthonytw/neat-deform

import gui.PopulationModel

print "-------------------------------------------------------------------"
print "DISTORTING IMAGE"

# Load the file and generate the network.
print "-------------------------------------------------------------------"
print "Loading network..."
neat.initialize()
population = neat.load( argv[1] )
individual = population.getIndividual( 0, population.getGenerationCount() - 1 )
network = individual.spawnFastPhenotypeStack()

# Open the input image.
print "-------------------------------------------------------------------"
print "Distorting image..."
distortion = gui.PopulationModel.PopulationItem()

application = QApplication( argv )
image_map = QPixmap( argv[2] )
distorted_image_map = distortion.distort( image_map, network )
distorted_image = QImage( distorted_image_map )
distorted_image.save( argv[3] )

# Cleanup.
print "-------------------------------------------------------------------"
print "Done, cleaning up."
print "-------------------------------------------------------------------"
neat.cleanup()