diff --git a/nodes/image_nodes.py b/nodes/image_nodes.py
index 1ccdbf5..a16a741 100644
--- a/nodes/image_nodes.py
+++ b/nodes/image_nodes.py
@@ -211,8 +211,8 @@ Concatenates the image2 to image1 in the specified direction.
 
     def concanate(self, image1, image2, direction, match_image_size, first_image_shape=None):
         # Check if the batch sizes are different
-        batch_size1 = image1.size(0)
-        batch_size2 = image2.size(0)
+        batch_size1 = image1.shape[0]
+        batch_size2 = image2.shape[0]
 
         if batch_size1 != batch_size2:
             # Calculate the number of repetitions needed
@@ -223,21 +223,45 @@ Concatenates the image2 to image1 in the specified direction.
             # Repeat the images to match the largest batch size
             image1 = image1.repeat(repeats1, 1, 1, 1)
             image2 = image2.repeat(repeats2, 1, 1, 1)
+
         if match_image_size:
-            first_image_shape = first_image_shape if first_image_shape is not None else image1.shape
-            image2_resized = image2.movedim(-1,1)
-            image2_resized = common_upscale(image2_resized, first_image_shape[2], first_image_shape[1], "lanczos", "disabled").movedim(1,-1)
+            # Use first_image_shape if provided; otherwise, default to image1's shape
+            target_shape = first_image_shape if first_image_shape is not None else image1.shape
+
+            original_height = image2.shape[1]
+            original_width = image2.shape[2]
+            original_aspect_ratio = original_width / original_height
+
+            if direction in ['left', 'right']:
+                # Match the height and adjust the width to preserve aspect ratio
+                target_height = target_shape[1]  # B, H, W, C format
+                target_width = int(target_height * original_aspect_ratio)
+            elif direction in ['up', 'down']:
+                # Match the width and adjust the height to preserve aspect ratio
+                target_width = target_shape[2]  # B, H, W, C format
+                target_height = int(target_width / original_aspect_ratio)
+            
+            # Adjust image2 to the expected format for common_upscale
+            image2_for_upscale = image2.movedim(-1, 1)  # Move C to the second position (B, C, H, W)
+            
+            # Resize image2 to match the target size while preserving aspect ratio
+            image2_resized = common_upscale(image2_for_upscale, target_width, target_height, "lanczos", "disabled")
+            
+            # Adjust image2 back to the original format (B, H, W, C) after resizing
+            image2_resized = image2_resized.movedim(1, -1)
         else:
             image2_resized = image2
+
+        # Concatenate based on the specified direction
         if direction == 'right':
-            row = torch.cat((image1, image2_resized), dim=2)
+            concatenated_image = torch.cat((image1, image2_resized), dim=2)  # Concatenate along width
         elif direction == 'down':
-            row = torch.cat((image1, image2_resized), dim=1)
+            concatenated_image = torch.cat((image1, image2_resized), dim=1)  # Concatenate along height
         elif direction == 'left':
-            row = torch.cat((image2_resized, image1), dim=2)
+            concatenated_image = torch.cat((image2_resized, image1), dim=2)  # Concatenate along width
         elif direction == 'up':
-            row = torch.cat((image2_resized, image1), dim=1)
-        return (row,)
+            concatenated_image = torch.cat((image2_resized, image1), dim=1)  # Concatenate along height
+        return concatenated_image,
     
 class ImageGridComposite2x2:
     @classmethod