Exemple #1
0
def generator_train():
    image = Gen.generate_img()
    misc.toimage(image).show()

    test_i = Gen.generate_img(50)
    entropy = Dis.use_discrim(test_i, None)
    Gen.train_gen(entropy)

    image = Gen.generate_img()
    misc.toimage(image).show()
Exemple #2
0
    return image_batch, class_batch


def generator_train():
    image = Gen.generate_img()
    misc.toimage(image).show()

    test_i = Gen.generate_img(50)
    entropy = Dis.use_discrim(test_i, None)
    Gen.train_gen(entropy)

    image = Gen.generate_img()
    misc.toimage(image).show()


images, classes = [], []
for i in range(1):
    i_batch, c_batch = create_batch(68)
    images.append(i_batch)
    classes.append(c_batch)

Dis.train_discrim(1, images, classes)

images = Gen.generate_img(32)
classes = [[0] for i in range(32)]

cost = Dis.use_discrim(images, classes)

Gen.train_gen(cost)
Gen.get_img()