diff --git a/__init__.py b/__init__.py
index 7881729..7aa99e5 100644
--- a/__init__.py
+++ b/__init__.py
@@ -56,6 +56,7 @@ NODE_CONFIG = {
     "ImageGrabPIL": {"class": ImageGrabPIL, "name": "Image Grab PIL"},
     "ImageGridComposite2x2": {"class": ImageGridComposite2x2, "name": "Image Grid Composite 2x2"},
     "ImageGridComposite3x3": {"class": ImageGridComposite3x3, "name": "Image Grid Composite 3x3"},
+    "ImageGridtoBatch": {"class": ImageGridtoBatch, "name": "Image Grid To Batch"},
     "ImageNormalize_Neg1_To_1": {"class": ImageNormalize_Neg1_To_1, "name": "Image Normalize -1 to 1"},
     "ImagePass": {"class": ImagePass},
     "ImagePadForOutpaintMasked": {"class": ImagePadForOutpaintMasked, "name": "Image Pad For Outpaint Masked"},
diff --git a/nodes/image_nodes.py b/nodes/image_nodes.py
index 06dec4b..1701752 100644
--- a/nodes/image_nodes.py
+++ b/nodes/image_nodes.py
@@ -1910,3 +1910,32 @@ class LoadImagesFromFolderKJ:
                     mask1 = torch.cat((mask1, mask2), dim=0)
 
             return (image1, mask1, len(images), image_path_list)
+
+class ImageGridtoBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "image": ("IMAGE", ),
+                    "columns": ("INT", {"default": 3, "min": 2, "max": 8, "tooltip": "The number of columns in the grid."}),
+                    }
+                }
+    
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "decompose"
+    CATEGORY = "KJNodes/image"
+    DESCRIPTION = "Converts a grid of images to a batch of images."
+        
+    def decompose(self, image, columns):
+       B, H, W, C = image.shape
+       orig_h = H // columns
+       orig_w = W // columns
+       
+       # Reshape and permute the image to get the grid
+       image = image.view(B, columns, orig_h, columns, orig_w, C)
+       image = image.permute(0, 1, 3, 2, 4, 5).contiguous()
+       image = image.view(B, columns * columns, orig_h, orig_w, C)
+       
+       # Reshape to the final batch tensor
+       img_tensor = image.view(-1, orig_h, orig_w, C)
+       
+       return img_tensor,
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