diff --git a/remtime.py b/remtime.py
index 7782529..f76d26a 100644
--- a/remtime.py
+++ b/remtime.py
@@ -1,5 +1,3 @@
-import tensorflow as tf
-
 def printTime(remtime):
 	hrs = int(remtime)/3600
 	mins = int((remtime/60-hrs*60))
@@ -11,21 +9,3 @@ def printTime(remtime):
 		timedisp+=str(mins)+"Mins "
 	timedisp += str(secs)+"Secs"
 	print(timedisp)
-
-def dataBatch(data_path, BATCH_SIZE, N_EPOCHS=1):
-	reader = tf.TFRecordReader()
-	filename_queue = tf.train.string_input_producer([data_path], num_epochs=N_EPOCHS)
-	_, serialized_example = reader.read(filename_queue)
-	# Decode the record read by the reader
-	feature = {'train/image': tf.FixedLenFeature([], tf.string), 'train/label': tf.FixedLenFeature([], tf.string)}
-	features = tf.parse_single_example(serialized_example, features=feature)
-	# Convert the image data from string back to the numbers
-	image = tf.decode_raw(features['train/image'], tf.float32)
-	label = tf.decode_raw(features['train/label'], tf.float32)
-	# Reshape image data into the original shape
-	image = tf.reshape(image, [224, 224, 3])
-	label = tf.reshape(label, [5])
-
-	images, labels = tf.train.shuffle_batch([image, label], batch_size=BATCH_SIZE, capacity=100, min_after_dequeue=BATCH_SIZE, allow_smaller_final_batch=True)
-	return images, labels
-