  
          print("Sorting by histogram similarity...")
  
          img_list = [
              [x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])]
              for x in
              tqdm(self.find_images(input_dir), desc="Loading", file=sys.stdout)
          ]
  
          img_list_len = len(img_list)
          for i in tqdm(range(0, img_list_len - 1), desc="Sorting",
 
</s> remove             [x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256]), 0]
            for x in
 </s> add             [img,
             cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256]), 0]
            for img in </s> remove                 [x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])]
                for x in
 </s> add                 [img,
                 cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256])]
                for img in </s> remove                     [x, self.calc_landmarks_face_yaw(np.array(d[0][1]))])
 </s> add                     [img,
                     self.calc_landmarks_face_yaw(np.array(landmarks[0][1]))]) </s> remove             img_list.append([x, np.array(d[0][1])
                             if len(d) > 0
 </s> add             img_list.append([img, np.array(landmarks[0][1])
                             if landmarks </s> remove         img_list = [[x, face_recognition.face_encodings(cv2.imread(x))]
                    for x in
 </s> add         img_list = [[img, face_recognition.face_encodings(cv2.imread(img))]
                    for img in
            [img, cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256])]
            for img in
  
          print("Sorting by histogram similarity...")
  
          img_list = [
            [img, cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256])]
            for img in
            [img, cv2.calcHist([cv2.imread(img)], [0], None, [256], [0, 256])]
            for img in
              tqdm(self.find_images(input_dir), desc="Loading", file=sys.stdout)
          ]
  
          img_list_len = len(img_list)
          for i in tqdm(range(0, img_list_len - 1), desc="Sorting",
keep keep keep keep replace replace keep keep keep keep keep
 Merge staging to Master (#470)

* DLib scaling amends (#461)

* Scaling area fix and rework of frames and bounding boxes

* Update DLib scaling and initialization

* Extract - Detector reinitialization bugfix

* Slight OriginaHightRes Model re-factoring (#464)

* Model re-factoring, might fix red screen of death on multi-gpu configurations

* Limited trainer support for various INPUT_SIZE

* Auto Extraction multiprocess bugfix

* Sort tool bugfixes and linting 
tools/sort.py