def create_random_mask(self):
if self.mask_type == 'random':
if self.opt.mask_sub_type == 'fractal':
mask = util.create_walking_mask(
) # create an initial random mask.
elif self.opt.mask_sub_type == 'rect':
mask = util.create_rand_mask()
elif self.opt.mask_sub_type == 'island':
mask = util.wrapper_gmask(self.opt)
return mask
def create_random_mask(self):
if self.opt.mask_type == 'random':
if self.opt.mask_sub_type == 'fractal':
assert 1==2, "It is broken somehow, use another mask_sub_type please"
mask = util.create_walking_mask() # create an initial random mask.
elif self.opt.mask_sub_type == 'rect':
mask, rand_t, rand_l = util.create_rand_mask(self.opt)
self.rand_t = rand_t
self.rand_l = rand_l
return mask
elif self.opt.mask_sub_type == 'island':
mask = util.wrapper_gmask(self.opt)
return mask
import util.util as util
import os
from PIL import Image
import glob
mask_folder = 'masks'
test_folder = './datasets/Paris/test'
util.mkdir(mask_folder)
opt = TrainOptions().parse()
f = glob.glob(test_folder + '/*.png')
print(f)
for fl in f:
mask = torch.zeros(opt.fineSize, opt.fineSize)
if opt.mask_sub_type == 'fractal':
mask = util.create_walking_mask() # create an initial random mask.
elif opt.mask_sub_type == 'rect':
mask, rand_t, rand_l = util.create_rand_mask(opt)
elif opt.mask_sub_type == 'island':
mask = util.wrapper_gmask(opt)
print('Generating mask for test image: ' + os.path.basename(fl))
util.save_image(
mask.squeeze().numpy() * 255,
os.path.join(mask_folder,
os.path.splitext(os.path.basename(fl))[0] + '_mask.png'))
