init

models/sample_model.py

@@ -52,7 +52,7 @@ class SampleModel(BaseModel):
         By default, we use vanilla GAN loss, UNet with batchnorm, and aligned datasets.
         """
         # changing the default values to match the pix2pix paper (https://phillipi.github.io/pix2pix/)
-        parser.set_defaults(norm='batch', netG='unet_256', dataset_mode='noise', num_test = 32, model='sample')
+        parser.set_defaults(norm='batch', netG='unet_256', dataset_mode='noise', num_test = 32)
         parser.add_argument('--pose_path', type=str, default='', help='path for pose net')
         parser.add_argument('--rnn_path', type=str, default='', help='path for rnn net')
         parser.add_argument('--n_frames_G', type=int, default=60)

options/test_options.py

@@ -16,7 +16,7 @@ class TestOptions(BaseOptions):
         parser.add_argument('--eval', action='store_true', help='use eval mode during test time.')
         parser.add_argument('--num_test', type=int, default=50, help='how many test images to run')
         # rewrite devalue values
-        parser.set_defaults(model='test')
+        # parser.set_defaults(model='test')
         # To avoid cropping, the load_size should be the same as crop_size
         parser.set_defaults(load_size=parser.get_default('crop_size'))
         self.isTrain = False