def save(self):
# if self.
if not self.isInit:
save_dir = QtGui.QFileDialog.getExistingDirectory(
None, 'Select a folder to save the result', self.default_dir,
QtGui.QFileDialog.ShowDirsOnly)
self.isInit = True
self.save_dir = str(save_dir)
utils.mkdirs(self.save_dir)
self.html = image_save.ImageSave(self.save_dir,
'Gui screenshot',
append=True)
print('save the result to (%s)' % self.save_dir)
if self.z is not None:
self.z_dir = os.path.join(self.save_dir, 'z_vectors')
utils.mkdirs(self.z_dir)
utils.PickleSave(
os.path.join(
self.z_dir, 'z_drawing%3.3d_%3.3d' %
(self.reset_count, self.save_count)), self.z)
if self.ims is not None:
txts = [''] * self.ims.shape[0]
self.html.save_image(
self.ims,
txts=txts,
header='generated images (Drawing %3.3d, Step %3.3d)' %
(self.reset_count, self.save_count),
cvt=True,
width=128)
self.html.save()
self.save_count += 1
npx, n_layers, n_f, nc, nz, niter, niter_decay = getattr(
train_dcgan_config, args.model_name)()
expr_name = args.model_name + args.ext
if not args.cache_dir:
args.cache_dir = './cache/%s/' % expr_name
for arg in vars(args):
print('[%s] =' % arg, getattr(args, arg))
# create directories
rec_dir = os.path.join(args.cache_dir, 'rec')
model_dir = os.path.join(args.cache_dir, 'models')
log_dir = os.path.join(args.cache_dir, 'log')
web_dir = os.path.join(args.cache_dir, 'web_rec')
html = image_save.ImageSave(web_dir, expr_name, append=True)
utils.mkdirs([rec_dir, model_dir, log_dir, web_dir])
# load data
tr_data, te_data, tr_stream, te_stream, ntrain, ntest \
= load_imgs(ntrain=None, ntest=None, batch_size=args.batch_size, data_file=args.data_file)
te_handle = te_data.open()
ntest = int(np.floor(ntest / float(args.batch_size)) * args.batch_size)
# st()
test_x, = te_data.get_data(te_handle, slice(0, ntest))
test_x = train_dcgan_utils.transform(test_x, nc=nc)
predict_params = train_dcgan_utils.init_predict_params(nz=nz,
n_f=n_f,
n_layers=n_layers,
nc=nc)