Update utils.py

utils.py

@@ -35,11 +35,22 @@ base_model = tf.keras.applications.ResNet50V2(include_top=False, input_shape=inp
 base_model.trainable = True
 
 def preprocess(img_path):
-    img = Image.open(img_path)
-    img = img.resize((256, 256))
-    img_array = np.array(img)
-    img_array = np.expand_dims(img_array, axis=0)
-    return img_array
+    try:
+        img = Image.open(img_path)
+        img = img.resize((256, 256))
+        img = img.convert('RGB')  # Ensure the image is in RGB format
+        
+        # Convert the image to a TensorFlow tensor
+        img_tensor = tf.keras.preprocessing.image.img_to_array(img)
+        img_tensor = tf.expand_dims(img_tensor, axis=0)  # Create a batch-like shape
+        
+        # Apply rescaling (aligning with the training rescaling)
+        img_tensor = tf.keras.applications.resnet.preprocess_input(img_tensor)
+        
+        return img_tensor
+    except Exception as e:
+        print(f"Error preprocessing image: {e}")
+        return None
 
 def model_arc():
     model = tf.keras.Sequential([