diff --git a/featureExtraction.py b/featureExtraction.py
index 00cd278..9d6e277 100644
--- a/featureExtraction.py
+++ b/featureExtraction.py
@@ -48,23 +48,14 @@ def psnr(y_true, y_pred):
     return 10.0 * K.log((max_pixel ** 2) / (K.mean(K.square(y_pred - y_true)))) / K.log(10.0)
 
 
-def preprocess_frame(frame, crf, speed):
+def preprocess_frame(frame):
+    #Preprocesses a single frame, cropping it if needed
+    
     # Check frame dimensions and resize if necessary
     if frame.shape[:2] != (HEIGHT, WIDTH):
-        frame = cv2.resize(frame, (WIDTH, HEIGHT), interpolation=cv2.INTER_NEAREST)
+        frame = cv2.resize(frame, (WIDTH, HEIGHT), interpolation=cv2.INTER_LINEAR)
     
     # Scale frame to [0, 1]
     compressed_frame = frame / 255.0
 
-    # Scale CRF and SPEED to [0, 1] (assuming they are within known bounds)
-    crf_scaled = crf / 51
-    speed_scaled = speed / NUM_PRESET_SPEEDS
-
-    # Create images with the CRF and SPEED values, filling extra channels
-    crf_image = np.full((HEIGHT, WIDTH, 1), crf_scaled) # Note the added dimension
-    speed_image = np.full((HEIGHT, WIDTH, 1), speed_scaled) # Note the added dimension
-
-    # Combine the frames with the CRF and SPEED images
-    combined_frame = np.concatenate([compressed_frame, crf_image, speed_image], axis=-1)
-
-    return combined_frame
+    return compressed_frame
diff --git a/video_compression_model.py b/video_compression_model.py
index 7bfe485..03bfeb4 100644
--- a/video_compression_model.py
+++ b/video_compression_model.py
@@ -13,6 +13,15 @@ from globalVars import HEIGHT, LOGGER, NUM_COLOUR_CHANNELS, NUM_PRESET_SPEEDS, P
 #policy = Policy('mixed_float16')
 #tf.keras.mixed_precision.set_global_policy(policy)
 
+def combine_batch(frame, crf_array, speed_array):
+    # Preprocess the compressed frame (target)
+    processed_frame = preprocess_frame(frame)
+    
+    # Combine the frames with the CRF and SPEED images
+    combined = np.concatenate([processed_frame, crf_array, speed_array], axis=-1)
+    
+    return combined
+
 def data_generator(videos, batch_size):
     # Infinite loop to keep generating batches
     while True:
@@ -24,7 +33,15 @@ def data_generator(videos, batch_size):
             uncompressed_video_path = os.path.join(base_dir, video_details["original_video_file"])
             
             CRF = video_details["crf"] / 51
-            SPEED = PRESET_SPEED_CATEGORIES.index(video_details["preset_speed"])
+            SPEED = PRESET_SPEED_CATEGORIES.index(video_details["preset_speed"]) / NUM_PRESET_SPEEDS
+            
+            # Create images with the CRF and SPEED values, filling extra channels
+            compressed_crf_array = np.full((HEIGHT, WIDTH, 1), CRF) # Note the added dimension
+            compressed_speed_array = np.full((HEIGHT, WIDTH, 1), SPEED) # Note the added dimension
+            
+            # Create images with the CRF and SPEED values, filling extra channels
+            uncompressed_crf_array = np.full((HEIGHT, WIDTH, 1), 0) # Note the added dimension
+            uncompressed_speed_array = np.full((HEIGHT, WIDTH, 1), PRESET_SPEED_CATEGORIES.index("veryslow") / NUM_PRESET_SPEEDS) # Note the added dimension
             
             # Open the video files
             cap_compressed = cv2.VideoCapture(video_path)
@@ -41,15 +58,13 @@ def data_generator(videos, batch_size):
                 if not ret_compressed or not ret_uncompressed:
                     break
                 
-                # Preprocess the compressed frame (target)
-                compressed_frame = preprocess_frame(compressed_frame, CRF, SPEED)
+                compressed_combined = combine_batch(compressed_frame, compressed_crf_array, compressed_speed_array)
                 
-                # Preprocess the uncompressed frame (input)
-                uncompressed_frame = preprocess_frame(uncompressed_frame, 0, PRESET_SPEED_CATEGORIES.index("veryslow")) # Modify if different preprocessing is needed for target frames
+                uncompressed_combined = combine_batch(uncompressed_frame, uncompressed_crf_array, uncompressed_speed_array)
                 
                 # Append processed frames to batches
-                compressed_frame_batch.append(compressed_frame)
-                uncompressed_frame_batch.append(uncompressed_frame)
+                compressed_frame_batch.append(compressed_combined)
+                uncompressed_frame_batch.append(uncompressed_combined)
 
                 # If batch is complete, yield it
                 if len(compressed_frame_batch) == batch_size: