fix

1 files changed, 31 insertions, 31 deletions

diff --git a/live-mogrify.py b/live-mogrify.py
index d93991b..0348c54 100644
--- a/live-mogrify.py
+++ b/live-mogrify.py
@@ -158,32 +158,32 @@ def list_sequences(module):
 
 import torchvision.transforms as transforms
 
-def get_transform(opt={}):
-  transform_list = []
-  if opt.resize_or_crop == 'resize_and_crop':
-    osize = [opt.loadSize, opt.loadSize]
-    transform_list.append(transforms.Scale(osize, Image.BICUBIC))
-    if opt.center_crop:
-      transform_list.append(transforms.CenterCrop(opt.fineSize))
-    else:
-      transform_list.append(transforms.RandomCrop(opt.fineSize))
-  # elif opt.resize_or_crop == 'crop':
-  #   transform_list.append(transforms.RandomCrop(opt.fineSize))
-  # elif opt.resize_or_crop == 'scale_width':
-  #   transform_list.append(transforms.Lambda(
-  #     lambda img: __scale_width(img, opt.fineSize)))
-  # elif opt.resize_or_crop == 'scale_width_and_crop':
-  #   transform_list.append(transforms.Lambda(
-  #     lambda img: __scale_width(img, opt.loadSize)))
-  #   transform_list.append(transforms.RandomCrop(opt.fineSize))
+# def get_transform(opt={}):
+#   transform_list = []
+#   if opt.resize_or_crop == 'resize_and_crop':
+#     osize = [opt.loadSize, opt.loadSize]
+#     transform_list.append(transforms.Scale(osize, Image.BICUBIC))
+#     if opt.center_crop:
+#       transform_list.append(transforms.CenterCrop(opt.fineSize))
+#     else:
+#       transform_list.append(transforms.RandomCrop(opt.fineSize))
+#   # elif opt.resize_or_crop == 'crop':
+#   #   transform_list.append(transforms.RandomCrop(opt.fineSize))
+#   # elif opt.resize_or_crop == 'scale_width':
+#   #   transform_list.append(transforms.Lambda(
+#   #     lambda img: __scale_width(img, opt.fineSize)))
+#   # elif opt.resize_or_crop == 'scale_width_and_crop':
+#   #   transform_list.append(transforms.Lambda(
+#   #     lambda img: __scale_width(img, opt.loadSize)))
+#   #   transform_list.append(transforms.RandomCrop(opt.fineSize))
 
-  # if opt.isTrain and not opt.no_flip:
-  #   transform_list.append(transforms.RandomHorizontalFlip())
+#   # if opt.isTrain and not opt.no_flip:
+#   #   transform_list.append(transforms.RandomHorizontalFlip())
 
-  transform_list += [transforms.ToTensor(),
-                     transforms.Normalize((0.5, 0.5, 0.5),
-                                          (0.5, 0.5, 0.5))]
-  return transforms.Compose(transform_list)
+#   transform_list += [transforms.ToTensor(),
+#                      transforms.Normalize((0.5, 0.5, 0.5),
+#                                           (0.5, 0.5, 0.5))]
+#   return transforms.Compose(transform_list)
 
 def load_frame(opt, index):
   A_path = os.path.join(opt.render_dir, "frame_{:05d}.png".format(index))
@@ -309,17 +309,17 @@ def process_live_input(opt, data_opt, rpc_client, model):
   print("generating...")
   sequence_i = 1
   i = 0
-  #for i, data in enumerate(data_loader):
-  while True:
+  # while True:
+
+  #   data = load_frame(opt, i)
+  #   if data is None:
+  #     print("got no frame, exiting")
+  #     break
+  for i, data in enumerate(data_loader):
     if i >= opt.how_many:
       print("generated {} images, exiting".format(i))
       break
 
-    data = load_frame(opt, i)
-    if data is None:
-      print("got no frame, exiting")
-      break
-
     if data_opt.load_checkpoint is True:
       model.save_dir = os.path.join(opt.checkpoints_dir, opt.module_name, data_opt.checkpoint_name)
       model.load_network(model.netG, 'G', data_opt.epoch)