Update app.py

app.py

@@ -11,6 +11,11 @@ import numpy as np
 from modules import PaletteModelV2
 from diffusion import Diffusion_cond
 
+DESCRIPTION = '''
+<div style="display: flex; justify-content: center; align-items: center; flex-direction: column; font-size: 36px; margin-top: 20px;">
+    <h1><a href="https://github.com/fpramunno/MAG2MAG" target="_blank" style="color: black; text-decoration: none;">MAG2MAG</a></h1>
+    <img src="https://raw.githubusercontent.com/fpramunno/MAG2MAG/main/pred.png" alt="teaser" style="width: 100%; max-width: 800px; height: auto;">
+</div>'''
 
 # Check for GPU availability, else use CPU
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
@@ -30,15 +35,29 @@ transform_hmi = transforms.Compose([
 ])
 
 def generate_image(seed_image):
-    seed_image_tensor = transform_hmi(Image.open(seed_image)).reshape(1, 1, 256, 256).to(device)
+    _, file_ext = os.path.splitext(seed_image)
+    
+    if file_ext.lower() == '.jp2':
+        input_img = Image.open(seed_image)
+        input_img_pil = transform_hmi(input_img).reshape(1, 1, 256, 256).to(device)
+    elif file_ext.lower() == '.fits':
+        with fits.open(seed_image) as hdul:
+            data = hdul[0].data
+            
+            input_img_pil = transform_hmi(data).reshape(1, 1, 256, 256).to(device)
+            
     generated_image = diffusion.sample(model, y=seed_image_tensor, labels=None, n=1)
-    # generated_image_pil = transforms.ToPILImage()(generated_image.squeeze().cpu())
+
+    inp_img = seed_image_tensor.reshape(1, 256, 256).permute(1, 2, 0)  
+    inp_img = np.squeeze(inp_img.cpu().numpy())
+    inp = Image.fromarray(inp_img)                # Create a PIL Image from array
+    inp = inp.transpose(Image.FLIP_TOP_BOTTOM) 
     img = generated_image[0].reshape(1, 256, 256).permute(1, 2, 0)              # Permute dimensions to height x width x channels
     img = np.squeeze(img.cpu().numpy())
     v = Image.fromarray(img)                # Create a PIL Image from array
     v = v.transpose(Image.FLIP_TOP_BOTTOM)  
     
-    return v
+    return inp, v
 
 # Create Gradio interface
 iface = gr.Interface(