def make_img(self, x, l, s, num_lm, random=0):
if random == 0:
lm = Variable(xp.clip(l.data, 0, 1))
sm = Variable(xp.clip(s.data, 0, 1))
else:
eps = xp.random.normal(0, 1, size=l.data.shape).astype(xp.float32)
epss = xp.random.normal(0, 1, size=s.data.shape).astype(xp.float32)
sm = xp.clip((s.data + xp.sqrt(self.var) * epss), 0,
1).astype(xp.float32)
lm = xp.clip(
l.data + xp.power(10, sm - 1) * eps * xp.sqrt(self.vars), 0, 1)
sm = Variable(sm)
lm = Variable(lm.astype(xp.float32))
if self.use_gpu:
xm = make_sampled_image.generate_xm_gpu(lm.data,
sm.data,
x,
num_lm,
g_size=self.gsize,
img_size=256)
else:
xm = make_sampled_image.generate_xm(lm.data,
sm.data,
x,
num_lm,
g_size=self.gsize,
img_size=256)
return xm, lm, sm
def make_img(self, x, l, num_lm, random=0):
s = xp.log10(xp.ones((1, 1)) * self.gsize / self.img_size) + 1
sm = xp.repeat(s, num_lm, axis=0)
if random == 0:
lm = Variable(xp.clip(l.data, 0, 1))
else:
eps = xp.random.normal(0, 1, size=l.data.shape).astype(xp.float32)
lm = xp.clip(l.data + eps * xp.sqrt(self.vars), 0, 1)
lm = Variable(lm.astype(xp.float32))
if self.use_gpu:
xm = make_sampled_image.generate_xm_gpu(lm.data, sm, x, num_lm, g_size=self.gsize)
else:
xm = make_sampled_image.generate_xm(lm.data, sm, x, num_lm, g_size=self.gsize)
return xm, lm