def make_grid(latent,
lat_mean,
lat_comp,
lat_stdev,
act_mean,
act_comp,
act_stdev,
scale=1,
n_rows=10,
n_cols=5,
make_plots=True,
edit_type='latent'):
from notebooks.notebook_utils import create_strip_centered
inst.remove_edits()
x_range = np.linspace(-scale, scale, n_cols,
dtype=np.float32) # scale in sigmas
rows = []
for r in range(n_rows):
curr_row = []
out_batch = create_strip_centered(inst, edit_type, layer_key, [latent],
act_comp[r], lat_comp[r],
act_stdev[r], lat_stdev[r], act_mean,
lat_mean, scale, 0, -1, n_cols)[0]
for i, img in enumerate(out_batch):
curr_row.append(('c{}_{:.2f}'.format(r, x_range[i]), img))
rows.append(curr_row[:n_cols])
inst.remove_edits()
if make_plots:
# If more rows than columns, make several blocks side by side
n_blocks = 2 if n_rows > n_cols else 1
for r, data in enumerate(rows):
# Add white borders
imgs = pad_frames([img for _, img in data])
coord = ((r * n_blocks) % n_rows) + ((r * n_blocks) // n_rows)
plt.subplot(n_rows // n_blocks, n_blocks, 1 + coord)
plt.imshow(np.hstack(imgs))
# Custom x-axis labels
W = imgs[0].shape[1] # image width
P = imgs[1].shape[1] # padding width
locs = [(0.5 * W + i * (W + P)) for i in range(n_cols)]
plt.xticks(locs, ["{:.2f}".format(v) for v in x_range])
plt.yticks([])
plt.ylabel(f'C{r}')
plt.tight_layout()
plt.subplots_adjust(top=0.96) # make room for suptitle
return [img for row in rows for img in row]
def img_list_generator(latent,
lat_mean,
lat_comp,
lat_stdev,
act_mean,
act_comp,
act_stdev,
scale=1,
num_frames=5,
make_plots=True,
edit_type='latent',
english_name=None,
allrand=False,
args=None):
"""
:param latent:
:param lat_mean:
:param lat_comp:
:param lat_stdev:
:param act_mean:
:param act_comp:
:param act_stdev:
:param scale:
:param num_frames:
:param make_plots:
:param edit_type:
:return: The image list : tuple (imgname, image_np_array)
"""
from notebooks.notebook_utils import create_strip_centered
x_range = np.linspace(-scale, scale, num_frames, dtype=np.float32)
inst.remove_edits()
r = 0
curr_row = []
sigs = None
if allrand:
sigma_range = np.linspace(-scale, scale, num_frames)
selected = random.sample([i for i in range(num_frames)], allrand)
sigs = sigma_range[selected]
out_batch = create_strip_centered(
inst,
mode=edit_type,
layer=layer_key,
latents=[latent],
x_comp=act_comp[r],
z_comp=lat_comp[r],
act_stdev=act_stdev[r],
lat_stdev=lat_stdev[r],
act_mean=act_mean,
lat_mean=lat_mean,
sigma=scale,
layer_start=0,
layer_end=-1,
num_frames=num_frames,
allrand=allrand,
sigs=sigs,
args=args)[0] # use [0] since only one latent layer
for i, img in enumerate(out_batch):
if allrand:
curr_row.append(
('{}_sigma_{:.2f}_{}.png'.format(i, sigs[i],
english_name), img))
else:
curr_row.append(
('{}_sigma_{:.2f}_{}.png'.format(i, x_range[i],
english_name), img))
return curr_row # The image list : tuple (imgname, image_np_array)