Beispiel #1
0
def demo_wgan_ab():
    noise = tf.constant(np.random.normal(size=(64, 128)).astype('float32'))
    model = Net(train=False)
    model.output_dim = 2
    colorized = model.GAN_G(noise)
    saver = tf.train.Saver()

    with tf.Session() as sess:
        saver.restore(sess, _CKPT_PATH)
        ab = sess.run(colorized)  # [-1, 1]
        ab *= 110.
        l = np.full((64, 64, 64, 1), 50)
        lab = np.concatenate((l, ab), axis=-1)
        rgbs = []
        for i in xrange(64):
            rgb = color.lab2rgb(lab[i, :, :, :])
            rgbs.append(rgb)
        rgbs = np.array(rgbs)
        save_images(rgbs, '/srv/glusterfs/xieya/image/color/samples_ab.png')
Beispiel #2
0
def demo_wgan_rgb():
    noise = tf.constant(np.random.normal(size=(64, 128)).astype('float32'))
    model = Net(train=False)
    model.output_dim = 3
    colorized = model.GAN_G(noise)
    saver = tf.train.Saver()

    with tf.Session() as sess:
        saver.restore(sess, _CKPT_PATH)
        rgb = sess.run(colorized)  # [-1, 1]
        rgb = ((rgb + 1.) * (255.99 / 2)).astype('uint8')
        save_images(rgb, '/srv/glusterfs/xieya/image/color/samples_rgb.png')
        rgb_new = []
        for i in xrange(64):
            lab = color.rgb2lab(rgb[i, :, :, :])
            lab[:, :, 0] = 50.  # Remove l.
            rgb_new.append(color.lab2rgb(lab))
        rgb_new = np.array(rgb_new)
        save_images(rgb_new,
                    '/srv/glusterfs/xieya/image/color/samples_rgb_ab.png')