Use state_dict for saving, update LICENSE, vgg-download link

LICENSE

@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2016 Abhishek Kadian
+Copyright (c) 2017 Abhishek Kadian
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

neural_style/neural_style.py

@@ -110,7 +110,7 @@ def train(args):
     save_model_filename = "epoch_" + str(args.epochs) + "_" + str(time.ctime()).replace(' ', '_') + "_" + str(
         args.content_weight) + "_" + str(args.style_weight) + ".model"
     save_model_path = os.path.join(args.save_model_dir, save_model_filename)
-    torch.save(transformer, save_model_path)
+    torch.save(transformer.state_dict(), save_model_path)
 
     print("\nDone, trained model saved at", save_model_path)
 
@@ -133,7 +133,8 @@ def stylize(args):
     if args.cuda:
         content_image = content_image.cuda()
     content_image = Variable(utils.preprocess_batch(content_image))
-    style_model = torch.load(args.model)
+    style_model = TransformerNet()
+    style_model.load_state_dict(torch.load(args.model))
 
     if args.cuda:
         style_model.cuda()

neural_style/utils.py

@@ -45,7 +45,6 @@ def gram_matrix(y):
 
 
 def subtract_imagenet_mean_batch(batch):
-    """Subtract ImageNet mean pixel-wise from a BGR image."""
     tensortype = type(batch.data)
     mean = tensortype(batch.data.size())
     mean[:, 0, :, :] = 103.939
@@ -63,11 +62,10 @@ def preprocess_batch(batch):
 
 
 def init_vgg16(model_folder):
-    """load the vgg16 model feature"""
     if not os.path.exists(os.path.join(model_folder, 'vgg16.weight')):
         if not os.path.exists(os.path.join(model_folder, 'vgg16.t7')):
             os.system(
-                'wget http://cs.stanford.edu/people/jcjohns/fast-neural-style/models/vgg16.t7 -O ' + os.path.join(model_folder, 'vgg16.t7'))
+                'wget https://www.dropbox.com/s/76l3rt4kyi3s8x7/vgg16.t7?dl=1 -O ' + os.path.join(model_folder, 'vgg16.t7'))
         vgglua = load_lua(os.path.join(model_folder, 'vgg16.t7'))
         vgg = Vgg16()
         for (src, dst) in zip(vgglua.parameters()[0], vgg.parameters()):