Update app.py

app.py

@@ -28,27 +28,34 @@ def extract_slice(data, view, slice_index):
     elif view == 'Sagittal':
         return data[slice_index, :, :]
 
-def resize_slice(slice_image, view, data_shape):
-    if view == 'Axial':
-        return slice_image  # No resizing needed for Axial view
+def resize_slice(slice_image, max_size=(500, 200)):
+    # Convert the NumPy array to a PIL image
+    slice_pil = Image.fromarray(slice_image)
+    
+    # Get original dimensions
+    original_width, original_height = slice_pil.size
+    
+    # Calculate aspect ratio
+    aspect_ratio = original_width / original_height
+    
+    # Determine new dimensions based on the aspect ratio
+    if original_width > original_height:
+        new_width = min(max_size[0], original_width)
+        new_height = int(new_width / aspect_ratio)
     else:
-        # For Coronal and Sagittal views, find the two largest dimensions
-        if view == 'Coronal':
-            resize_dims = (data_shape[0], data_shape[2])  # (x, z)
-        elif view == 'Sagittal':
-            resize_dims = (data_shape[1], data_shape[2])  # (y, z)
-        
-        # Resize the slice image while maintaining the aspect ratio
-        resized_image = Image.fromarray(slice_image).resize(resize_dims, Image.ANTIALIAS)
-        return np.array(resized_image)
+        new_height = min(max_size[1], original_height)
+        new_width = int(new_height * aspect_ratio)
+    
+    # Resize the image
+    resized_image = slice_pil.resize((new_width, new_height), Image.ANTIALIAS)
+    return np.array(resized_image)
 
 def visualize_slice(file_obj, view, slice_index):
     data = load_nrrd(file_obj)
-    data_shape = data.shape  # Get the original x, y, z dimensions
     slice_image = extract_slice(data, view, slice_index)
     
-    # Resize the slice image if necessary
-    slice_image = resize_slice(slice_image, view, data_shape)
+    # Resize the slice image while maintaining aspect ratio
+    slice_image = resize_slice(slice_image)
     
     # Plot the slice
     fig, ax = plt.subplots()