Update app.py

app.py

@@ -26,7 +26,7 @@ def dict2namespace(config):
         setattr(namespace, key, new_value)
     return namespace
 
-def load_img (filename, norm=True,):
+def load_img(filename, norm=True):
     img = np.array(Image.open(filename).convert("RGB"))
     h, w = img.shape[:2]
     
@@ -39,20 +39,19 @@ def load_img (filename, norm=True,):
         img = img.astype(np.float32)
     return img
 
-def process_img (image):
+def process_img(image):
     img = np.array(image)
     img = img / 255.
     img = img.astype(np.float32)
-    y = torch.tensor(img).permute(2,0,1).unsqueeze(0).to(device)
+    y = torch.tensor(img).permute(2, 0, 1).unsqueeze(0).to(device)
     
     with torch.no_grad():
         x_hat = model(y)
 
-    restored_img = x_hat.squeeze().permute(1,2,0).clamp_(0, 1).cpu().detach().numpy()
-    restored_img = np.clip(restored_img, 0. , 1.)
+    restored_img = x_hat.squeeze().permute(1, 2, 0).clamp_(0, 1).cpu().detach().numpy()
+    restored_img = np.clip(restored_img, 0., 1.)
 
     restored_img = (restored_img * 255.0).round().astype(np.uint8)  # float32 to uint8
-    #return Image.fromarray(restored_img) #
     return (image, Image.fromarray(restored_img))
 
 def load_network(net, load_path, strict=True, param_key='params'):
@@ -87,23 +86,21 @@ model = seemore.SeemoRe(scale=cfg.model.scale, in_chans=cfg.model.in_chans,
                         recursive=cfg.model.recursive, lr_space=cfg.model.lr_space, topk=cfg.model.topk)
 
 model = model.to(device)
-print ("IMAGE MODEL CKPT:", MODEL_NAME)
+print("IMAGE MODEL CKPT:", MODEL_NAME)
 load_network(model, MODEL_NAME, strict=True, param_key='params')
 
-
-
-
-title = "Enhane Quality"
-
-
+title = "Enhance Quality"
+description = "This application enhances the quality of images using a super-resolution model."
+article = "This is an article about the application."
+examples = [["images/0878x4.png"]]
+css = None
 
 demo = gr.Interface(
     fn=process_img,
-    inputs=[gr.Image(type="pil", label="Input", value="images/0878x4.png"),],
+    inputs=[gr.Image(type="pil", label="Input", value="images/0878x4.png")],
     outputs=ImageSlider(label="Super-Resolved Image", 
                         type="pil",
-                        show_download_button=True,
-                        ), #[gr.Image(type="pil", label="Ouput", min_width=500)],
+                        show_download_button=True),
     title=title,
     description=description,
     article=article,