                        desc="Sorting",
                        file=sys.stdout):
              min_score = float("inf")
              j_min_score = i + 1
              for j in range(i + 1, len(img_list)):
                  fl1 = img_list[i][1]
                  fl2 = img_list[j][1]
                  score = np.sum(np.absolute((fl2 - fl1).flatten()))
  
                  if score < min_score:
 
</s> remove             for j in range(i + 1, len(img_list)):
                score = cv2.compareHist(img_list[i][1],
                                        img_list[j][1],
                                        cv2.HISTCMP_BHATTACHARYYA)
 </s> add             for j in range(i + 1, img_list_len):
                score = cv2.compareHist(img_list[i][1], img_list[j][1], distance) </s> remove             for j in range(i + 1, len(img_list)):
 </s> add             for j in range(i + 1, img_list_len): </s> remove         for i in tqdm(range(0, img_list_len - 1),
                      desc="Sorting",
                      file=sys.stdout):
 </s> add         for i in tqdm(range(0, img_list_len - 1), desc="Comparing...", file=sys.stdout): </s> remove         for i in tqdm(range(0, img_list_len - 1), desc="Sorting",
                      file=sys.stdout):
 </s> add         for i in tqdm(range(0, img_list_len - 1), desc="Comparing", file=sys.stdout):
            for j in range(i + 1, img_list_len):
                        desc="Sorting",
                        file=sys.stdout):
              min_score = float("inf")
              j_min_score = i + 1
            for j in range(i + 1, img_list_len):
                  fl1 = img_list[i][1]
                  fl2 = img_list[j][1]
                  score = np.sum(np.absolute((fl2 - fl1).flatten()))
  
                  if score < min_score:
keep keep keep keep replace keep keep keep keep keep
 ENHANCEMENT: Sort image multi-threading and code clarity (#912)

* Use multi-threaded loading

* fast reload

* remove landmark stub

* saves

* correct face sort

* pep8 
tools/sort.py