diff --git a/clothing_workflow.ipynb b/clothing_workflow.ipynb
index 8dcff681ec..5b0e00b0d9 100644
--- a/clothing_workflow.ipynb
+++ b/clothing_workflow.ipynb
@@ -13,7 +13,10 @@
     "import cv2\n",
     "\n",
     "from invokeai.backend.vto_workflow.overlay_pattern import generate_dress_mask\n",
-    "from invokeai.backend.vto_workflow.extract_channel import extract_channel, ImageChannel\n"
+    "from invokeai.backend.vto_workflow.extract_channel import extract_channel, ImageChannel\n",
+    "from invokeai.backend.vto_workflow.seamless_mapping import map_seamless_tiles\n",
+    "\n",
+    "\n"
    ]
   },
   {
@@ -83,6 +86,28 @@
    "id": "dbb53794",
    "metadata": {},
    "outputs": [],
+   "source": [
+    "expanded_pattern = map_seamless_tiles(seamless_tile=pattern_image, target_hw=(model_image.height, model_image.width), num_repeats_h=5.0)\n",
+    "expanded_pattern"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2a12c166",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expanded_pattern = map_seamless_tiles(seamless_tile=pattern_image, target_hw=(model_image.height, model_image.width), num_repeats_h=1.0)\n",
+    "expanded_pattern"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f4f22d02",
+   "metadata": {},
+   "outputs": [],
    "source": []
   }
  ],
diff --git a/invokeai/backend/vto_workflow/seamless_mapping.py b/invokeai/backend/vto_workflow/seamless_mapping.py
new file mode 100644
index 0000000000..4a6fb8578a
--- /dev/null
+++ b/invokeai/backend/vto_workflow/seamless_mapping.py
@@ -0,0 +1,31 @@
+import math
+
+import numpy as np
+from PIL import Image
+
+
+def map_seamless_tiles(seamless_tile: Image.Image, target_hw: tuple[int, int], num_repeats_h: float) -> Image.Image:
+    """Map seamless tiles to a target size with a given number of repeats along the height dimension."""
+    # TODO(ryand): Add option to flip odd rows and columns if the tile is not seamless.
+    # - May also want the option to decide on a per-axis basis.
+
+    target_h, target_w = target_hw
+
+    # Calculate the height of the tile that is necessary to achieve the desired number of repeats.
+    # Take the ceiling so that the last tile overflows the target height.
+    target_tile_h = math.ceil(target_h / num_repeats_h)
+
+    # Resize the tile to the target height.
+    # Determine the target_tile_w that preserves the original aspect ratio.
+    target_tile_w = int(target_tile_h / seamless_tile.height * seamless_tile.width)
+    resized_tile = seamless_tile.resize((target_tile_w, target_tile_h))
+
+    # Repeat the tile along the height and width dimensions.
+    num_repeats_h_int = math.ceil(num_repeats_h)
+    num_repeats_w_int = math.ceil(target_w / target_tile_w)
+    seamless_tiles_np = np.array(resized_tile)
+    repeated_tiles_np = np.tile(seamless_tiles_np, (num_repeats_h_int, num_repeats_w_int, 1))
+
+    # Crop the repeated tiles to the target size.
+    output_pattern = Image.fromarray(repeated_tiles_np[:target_h, :target_w])
+    return output_pattern