diff --git a/CHANGELOG.md b/CHANGELOG.md
index e9b58ffd..07064935 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,12 @@
+## 1.5.4
+
+### Enhancement
+- Use `np.full()` instead of `np.ones() * scalar` in YoloX preprocessing to avoid a redundant temporary array
+
 ## 1.5.3
 
+### Enhancement
+
 - Store routing in LayoutElement
 
 ## 1.5.2
diff --git a/unstructured_inference/__version__.py b/unstructured_inference/__version__.py
index e375e78d..e4b9acb5 100644
--- a/unstructured_inference/__version__.py
+++ b/unstructured_inference/__version__.py
@@ -1 +1 @@
-__version__ = "1.5.3"  # pragma: no cover
+__version__ = "1.5.4"  # pragma: no cover
diff --git a/unstructured_inference/models/yolox.py b/unstructured_inference/models/yolox.py
index 932242ec..f467857d 100644
--- a/unstructured_inference/models/yolox.py
+++ b/unstructured_inference/models/yolox.py
@@ -150,9 +150,9 @@ def image_processing(
 def preprocess(img, input_size, swap=(2, 0, 1)):
     """Preprocess image data before YoloX inference."""
     if len(img.shape) == 3:
-        padded_img = np.ones((input_size[0], input_size[1], 3), dtype=np.uint8) * 114
+        padded_img = np.full((input_size[0], input_size[1], 3), 114, dtype=np.uint8)
     else:
-        padded_img = np.ones(input_size, dtype=np.uint8) * 114
+        padded_img = np.full(input_size, 114, dtype=np.uint8)
 
     r = min(input_size[0] / img.shape[0], input_size[1] / img.shape[1])
     resized_img = cv2.resize(