diff --git a/train.py b/train.py
index f398155..f7516f5 100644
--- a/train.py
+++ b/train.py
@@ -30,6 +30,7 @@
 BATCH_SIZE = 10
 EPOCH = 100
 EPOCH_LOSSES = []
+SHUFFLED_INDECES = []
 # ============================== END ============================== #
 
 if __name__ == '__main__':
@@ -43,12 +44,17 @@
         BATCH = int(len(keys) / BATCH_SIZE)
 
     def next_batch():
-        global buff
+        global buff, BATCH_SIZE ,SHUFFLED_INDECES
         mini_batch = []
         actual_data = []
-        indicies = np.random.choice(len(keys), BATCH_SIZE)
 
-        for idx in indicies:
+        if 0 == len(SHUFFLED_INDECES):
+            SHUFFLED_INDECES = list(np.random.permutation(len(keys)))
+
+        indices = SHUFFLED_INDECES[:min(BATCH_SIZE, len(SHUFFLED_INDECES))]
+        del SHUFFLED_INDECES[:min(BATCH_SIZE, len(SHUFFLED_INDECES))]
+
+        for idx in indices:
             # make images mini batch
 
             img = load_image('voc2007/'+keys[idx])
@@ -103,12 +109,14 @@ def draw_marker(image_name, save):
 
     # saver.restore(sess, './checkpoints/params.ckpt')
 
+    SHUFFLED_INDECES = list(np.random.permutation(len(keys)))
+
     print('\nSTART LEARNING')
     print('==================== '+str(datetime.datetime.now())+' ====================')
 
     for _ in range(5):
         next_batch()
-
+        
     for ep in range(EPOCH):
         BATCH_LOSSES = []
         for ba in trange(BATCH):