diff --git a/image_preprocessing.py b/image_preprocessing.py
new file mode 100644
index 0000000..d749524
--- /dev/null
+++ b/image_preprocessing.py
@@ -0,0 +1,48 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import cv2
+
+# Load dataset
+df = pd.read_csv("../../input_data/age_gender_indexed.csv", header=None)
+
+df.columns = ["Index", "Age", "Ethnicity", "Gender", "Image name", "Pixels"]
+
+def preprocess_image(pixel_str):
+    try:
+        # Ensure pixel_str is properly formatted
+        pixel_str = pixel_str.strip("[]").replace("'", "")  # Remove quotes if any
+        pixel_values = np.fromstring(pixel_str, sep=",", dtype=np.uint8)
+
+        # Ensure correct image size (48x48 = 2304 pixels)
+        if pixel_values.size != 48 * 48:
+            return None
+
+        # Reshape into 48x48 grayscale image
+        image = pixel_values.reshape(48, 48)
+
+        # Apply Bilateral Filtering for clarity while preserving edges
+        image = cv2.bilateralFilter(image, d=5, sigmaColor=50, sigmaSpace=50)
+
+        # Normalize pixel values (0 to 1)
+        image = image / 255.0
+        
+        return image
+    except Exception as e:
+        print(f"Error processing image: {e}")
+        return None
+
+def show_image(index):
+    image = preprocess_image(df.iloc[index]["Pixels"])
+    if image is None:
+        print(f"Skipping index {index}: Unexpected pixel size")
+        return
+    
+    plt.imshow(image, cmap="gray")
+    plt.title(f"Age: {df.iloc[index]['Age']}, Gender: {df.iloc[index]['Gender']}")
+    plt.axis("off")
+    plt.show()
+
+# Show first 5 images
+for i in range(5):
+    show_image(i)
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