Update app.py

app.py

@@ -13,7 +13,7 @@ from huggingface_hub import hf_hub_download
 from gradio_imageslider import ImageSlider
 
 ## local code
-from models import seemore
+from models.smfanet_arch import  SMFANet
 
 
 def dict2namespace(config):
@@ -71,8 +71,8 @@ def load_network(net, load_path, strict=True, param_key='params'):
     net.load_state_dict(load_net, strict=strict)
 
 CONFIG = "configs/SMFANet_plus_x4SR.yml"
-hf_hub_download(repo_id="eduardzamfir/SeemoRe-T", filename="SeemoRe_T_X4.pth", local_dir="./")
-MODEL_NAME = "SeemoRe_T_X4.pth"
+# hf_hub_download(repo_id="eduardzamfir/SeemoRe-T", filename="SeemoRe_T_X4.pth", local_dir="./")
+MODEL_NAME = "pth/SMFANet_DF2K_100w_x4SR.pth"
 
 # parse config file
 with open(os.path.join(CONFIG), "r") as f:
@@ -81,10 +81,7 @@ with open(os.path.join(CONFIG), "r") as f:
 cfg = dict2namespace(config)
 
 device = torch.device("cpu")
-model = seemore.SeemoRe(scale=cfg.model.scale, in_chans=cfg.model.in_chans,
-                        num_experts=cfg.model.num_experts, num_layers=cfg.model.num_layers, embedding_dim=cfg.model.embedding_dim, 
-                        img_range=cfg.model.img_range, use_shuffle=cfg.model.use_shuffle, global_kernel_size=cfg.model.global_kernel_size, 
-                        recursive=cfg.model.recursive, lr_space=cfg.model.lr_space, topk=cfg.model.topk)
+model = SMFANet(dim=cfg.model.dim, n_blocks=cfg.model.n_blocks, ffn_scale=cfg.model.ffn_scale, upscaling_factor=cfg.model.upscaling_factor)
 
 model = model.to(device)
 print ("IMAGE MODEL CKPT:", MODEL_NAME)