def generate_latent_grid(z_dim,
rows,
cols,
fan,
gradient,
spherical,
gaussian,
anchors,
anchor_images,
mine,
chain,
spacing,
analogy,
rand_uniform=False):
if fan:
z = create_fan_grid(z_dim, cols, rows)
elif gradient:
z = create_gradient_grid(rows, cols, z_dim, analogy, anchors,
spherical, gaussian)
elif mine:
z = create_mine_grid(rows, cols, z_dim, spacing, anchors, spherical,
gaussian)
elif chain:
z = create_chain_grid(rows, cols, z_dim, spacing, anchors, spherical,
gaussian)
else:
if rand_uniform:
z = np.random.uniform(-1, 1, size=(rows * cols, z_dim))
else:
# print("Generating random grid with seed ", np.random.get_state()[1][:5])
z = np.random.normal(loc=0, scale=1, size=(rows * cols, z_dim))
return z
def do(self, callback_name, *args):
"""Sample the model and save images to disk
"""
dmodel = self.interface(model=self.main_loop.model)
anchors = dmodel.encode_images(self.anchor_images)
z = create_chain_grid(self.rows,
self.cols,
self.z_dim,
self.spacing,
anchors=anchors,
spherical=True,
gaussian=False)
grid_from_latents(z,
dmodel,
rows=self.rows,
cols=self.cols,
anchor_images=None,
tight=False,
shoulders=False,
save_path=self.epoch_src,
batch_size=12)
if os.path.exists(self.epoch_src):
epoch_dst = "{0}/epoch-{1:03d}.png".format(self.save_subdir,
self.iteration)
self.iteration = self.iteration + 1
shutil.copy2(self.epoch_src, epoch_dst)
os.system(
"convert -delay 5 -loop 1 {0}/epoch-*.png {0}/training.gif".
format(self.save_subdir))
def do(self, callback_name, *args):
"""Sample the model and save images to disk
"""
dmodel = self.interface(model=self.main_loop.model)
anchors = dmodel.encode_images(self.anchor_images)
z = create_chain_grid(self.rows, self.cols, self.z_dim, self.spacing, anchors=anchors, spherical=True, gaussian=False)
grid_from_latents(z, dmodel, rows=self.rows, cols=self.cols, anchor_images=None, tight=False, shoulders=False, save_path=self.epoch_src, batch_size=12)
if os.path.exists(self.epoch_src):
epoch_dst = "{0}/epoch-{1:03d}.png".format(self.save_subdir, self.iteration)
self.iteration = self.iteration + 1
shutil.copy2(self.epoch_src, epoch_dst)
os.system("convert -delay 5 -loop 1 {0}/epoch-*.png {0}/training.gif".format(self.save_subdir))
def generate_latent_grid(z_dim, rows, cols, fan, gradient, spherical, gaussian, anchors, anchor_images, mine, chain, spacing, analogy, rand_uniform=False):
if fan:
z = create_fan_grid(z_dim, cols, rows)
elif gradient:
z = create_gradient_grid(rows, cols, z_dim, analogy, anchors, spherical, gaussian)
elif mine:
z = create_mine_grid(rows, cols, z_dim, spacing, anchors, spherical, gaussian)
elif chain:
z = create_chain_grid(rows, cols, z_dim, spacing, anchors, spherical, gaussian)
else:
if rand_uniform:
z = np.random.uniform(-1, 1, size=(rows * cols, z_dim))
else:
z = np.random.normal(loc=0, scale=1, size=(rows * cols, z_dim))
return z