def get_mask(mask_file_name, real_img, opt):
mask = functions.read_image_dir(mask_file_name, opt)
if mask.shape[3] != real_img.shape[3]:
mask = imresize_to_shape(mask, [real_img.shape[2], real_img.shape[3]],
opt)
mask = functions.dilate_mask(mask, opt)
return mask
if opt.train_mode == "editing":
fixed_noise[0] = fixed_noise[0] + opt.noise_scaling * \
functions.generate_noise([opt.nc_im, fixed_noise[0].shape[2],
fixed_noise[0].shape[3]],
device=opt.device)
out = generate_samples(netG, reals_shapes, noise_amp, reconstruct=True)
mask_file_name = '{}_mask{}'.format(opt.naive_img[:-4],
opt.naive_img[-4:])
if os.path.exists(mask_file_name):
mask = functions.read_image_dir(mask_file_name, opt)
if mask.shape[3] != out.shape[3]:
mask = imresize_to_shape(mask, [out.shape[2], out.shape[3]],
opt)
mask = functions.dilate_mask(mask, opt)
out = (1 - mask) * reals[-1] + mask * out
functions.save_image('{}/{}_w_mask.jpg'.format(dir2save, _name),
out.detach())
else:
print("Warning: mask {} not found.".format(mask_file_name))
print("Harmonization/Editing only performed without mask.")
elif opt.train_mode == "animation":
print("Generating GIFs...")
for _start_scale in range(3):
for _beta in range(80, 100, 5):
functions.generate_gif(dir2save,
netG,
fixed_noise,
reals,