--- a
+++ b/utils/preprocessing.py
@@ -0,0 +1,30 @@
+import cv2
+import numpy as np
+
+def preprocess_image(image_path, target_size=(256, 256)):
+    """
+    Load and preprocess the image for model prediction.
+    
+    Args:
+        image_path (str): Path to input X-ray image.
+        target_size (tuple): Size expected by the model.
+
+    Returns:
+        preprocessed_img (np.array): Preprocessed image tensor (1, H, W, C)
+        original_img (np.array): Original image for display or saving
+    """
+    # Load image in grayscale (you can also use RGB if model was trained in RGB)
+    img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+    original_img = img.copy()
+
+    # Resize to target shape
+    img = cv2.resize(img, target_size)
+
+    # Normalize to [0, 1]
+    img = img / 255.0
+
+    # Expand dimensions to match model input shape (1, H, W, 1)
+    img = np.expand_dims(img, axis=-1)
+    img = np.expand_dims(img, axis=0)
+
+    return img, original_img