Update app.py

app.py

@@ -22,11 +22,11 @@ pretrain_model_url = {
 
 
 # download weights
-if not os.path.exists('./experiments/pretrained_models/SAFMN_L_Real_LSDIR_x2-v2.pth'):
-	load_file_from_url(url=pretrain_model_url['safmn_x2'], model_dir='./experiments/pretrained_models/', progress=True, file_name=None)
+if not os.path.exists('./pretrained_models/SAFMN_L_Real_LSDIR_x2-v2.pth'):
+	load_file_from_url(url=pretrain_model_url['safmn_x2'], model_dir='./pretrained_models/', progress=True, file_name=None)
 
-if not os.path.exists('./experiments/pretrained_models/SAFMN_L_Real_LSDIR_x4-v2.pth'):
-	load_file_from_url(url=pretrain_model_url['safmn_x4'], model_dir='./experiments/pretrained_models/', progress=True, file_name=None)
+if not os.path.exists('./pretrained_models/SAFMN_L_Real_LSDIR_x4-v2.pth'):
+	load_file_from_url(url=pretrain_model_url['safmn_x4'], model_dir='./pretrained_models/', progress=True, file_name=None)
 
 
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -34,9 +34,9 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 def set_safmn(upscale):
 	model = SAFMN(dim=128, n_blocks=16, ffn_scale=2.0, upscaling_factor=upscale)
 	if upscale == 2:
-		model_path = './experiments/pretrained_models/SAFMN_L_Real_LSDIR_x2.pth'
+		model_path = './pretrained_models/SAFMN_L_Real_LSDIR_x2.pth'
 	elif upscale == 4:
-		model_path = './experiments/pretrained_models/SAFMN_L_Real_LSDIR_x4-v2.pth'
+		model_path = './pretrained_models/SAFMN_L_Real_LSDIR_x4-v2.pth'
 	else:
 		raise NotImplementedError('Only support x2/x4 upscaling!')