diff --git a/mainscripts/Sorter.py b/mainscripts/Sorter.py
index 40d1617..5f8eea7 100644
--- a/mainscripts/Sorter.py
+++ b/mainscripts/Sorter.py
@@ -239,94 +239,6 @@ def sort_by_face_yaw(input_path):
     
     return img_list
 
-class HistSimSubprocessor(SubprocessorBase):
-    #override
-    def __init__(self, img_list): 
-        self.img_list = img_list
-        self.img_list_range = [i for i in range(0, len(img_list) )]       
-        self.result = [0]*len(img_list)
-        super().__init__('HistSim', 60)           
-
-    #override
-    def onHostClientsInitialized(self):
-        pass
-
-    #override
-    def process_info_generator(self):    
-        for i in range(0, multiprocessing.cpu_count()):
-            yield 'CPU%d' % (i), {}, {'device_idx': i,
-                                      'device_name': 'CPU%d' % (i), 
-                                      'img_list' : self.img_list
-                                      }
-
-    #override
-    def get_no_process_started_message(self):
-        print ( 'Unable to start CPU processes.')
-        
-    #override
-    def onHostGetProgressBarDesc(self):
-        return "Computing"
-        
-    #override
-    def onHostGetProgressBarLen(self):
-        return len (self.img_list)
-        
-    #override
-    def onHostGetData(self):
-        if len (self.img_list_range) > 0:        
-            return [self.img_list_range.pop(0)]
-        
-        return None
-    
-    #override
-    def onHostDataReturn (self, data):
-        self.img_list_range.insert(0, data[0])   
-        
-    #override
-    def onClientInitialize(self, client_dict):
-        self.img_list = client_dict['img_list']
-        self.img_list_len = len(self.img_list)
-        
-        self.safe_print ('Running on %s.' % (client_dict['device_name']) )
-        return None
-
-    #override
-    def onClientFinalize(self):
-        pass
-        
-    #override
-    def onClientProcessData(self, data):  
-        i = data[0]
-
-        result = [0]*self.img_list_len
-        for j in range( 0, self.img_list_len):
-            if i == j:
-                continue
-                
-            result[j] = cv2.compareHist(self.img_list[i][1], self.img_list[j][1], cv2.HISTCMP_BHATTACHARYYA) + \
-                        cv2.compareHist(self.img_list[i][2], self.img_list[j][2], cv2.HISTCMP_BHATTACHARYYA) + \
-                        cv2.compareHist(self.img_list[i][3], self.img_list[j][3], cv2.HISTCMP_BHATTACHARYYA)
-
-        return result
-
-    #override
-    def onClientGetDataName (self, data):
-        #return string identificator of your data
-        return self.img_list[data[0]][0]
-        
-    #override
-    def onHostResult (self, data, result):
-        self.result[data[0]] = result
-        return 1
-    
-    #override    
-    def onHostProcessEnd(self):
-        pass
-             
-    #override
-    def get_start_return(self):
-        return self.result
-    
 def sort_by_hist(input_path):
     print ("Sorting by histogram similarity...")
 
@@ -337,30 +249,22 @@ def sort_by_hist(input_path):
                              cv2.calcHist([img], [1], None, [256], [0, 256]),
                              cv2.calcHist([img], [2], None, [256], [0, 256])
                          ])
-     
-    img_list_2D = HistSimSubprocessor(img_list).process() 
-     
-    rem_list = [i for i in range(len(img_list))]
-    
-    s_list = []
-    s_list.append ( rem_list.pop(0) )
-    
-    for x in tqdm( range(len(rem_list)), desc="Sorting"):
-        i = s_list[ len(s_list) -1 ]
-        
-        min_score_id = rem_list[0]        
-        min_score = img_list_2D[i][min_score_id]
-        
-        for score_id in rem_list:
-            score = img_list_2D[i][score_id]
+
+    img_list_len = len(img_list)
+    for i in tqdm( range(0, img_list_len-1), desc="Sorting"):
+        min_score = float("inf")
+        j_min_score = i+1
+        for j in range(i+1,len(img_list)):
+            score = cv2.compareHist(img_list[i][1], img_list[j][1], cv2.HISTCMP_BHATTACHARYYA) + \
+                    cv2.compareHist(img_list[i][2], img_list[j][2], cv2.HISTCMP_BHATTACHARYYA) + \
+                    cv2.compareHist(img_list[i][3], img_list[j][3], cv2.HISTCMP_BHATTACHARYYA)
             if score < min_score:
                 min_score = score
-                min_score_id = score_id
-                
-        s_list.append ( rem_list.pop(rem_list.index(min_score_id)) )
-
-    return [ (img_list[i][0],) for i in s_list ]
+                j_min_score = j
+        img_list[i+1], img_list[j_min_score] = img_list[j_min_score], img_list[i+1]
 
+    return img_list
+    
 class HistDissimSubprocessor(SubprocessorBase):
     #override
     def __init__(self, img_list ):