          elif group_method == 'group_face_cnn':
              import_FaceLandmarksExtractor()
              temp_list = []
              for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout):
                  d = FaceLandmarksExtractor.extract(cv2.imread(x), 'cnn', True, input_is_predetected_face=True)
                  temp_list.append([x, np.array(d[0][1]) if len(d) > 0 else np.zeros((68, 2))])
          elif group_method == 'group_hist':
              temp_list = [[x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])] for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)]
          else:
              raise ValueError("{} group_method not found.".format(group_method))
 
</s> remove             temp_list = [[x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])] for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)]
 </s> add             temp_list = [
                [x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])]
                for x in
                tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)
            ] </s> remove             temp_list = [[x, face_recognition.face_encodings(cv2.imread(x))] for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)]
 </s> add             temp_list = [[x, face_recognition.face_encodings(cv2.imread(x))]
                         for x in
                         tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)] </s> remove             temp_list = [[x, self.estimate_blur(cv2.imread(x))] for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)]
 </s> add             temp_list = [[x, self.estimate_blur(cv2.imread(x))]
                         for x in
                         tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)] </s> remove         input_dir = self.arguments.input_dir
 </s> add         input_dir = self.args.input_dir </s> remove             img_list.append( [x, np.array(d[0][1]) if len(d) > 0 else np.zeros ( (68,2) ) ] )
 </s> add             img_list.append([x, np.array(d[0][1]) if len(d) > 0 else np.zeros((68, 2))])
                d = FaceLandmarksExtractor.extract(cv2.imread(x), 'cnn', True,
                                                   input_is_predetected_face=True)
          elif group_method == 'group_face_cnn':
              import_FaceLandmarksExtractor()
              temp_list = []
              for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout):
                d = FaceLandmarksExtractor.extract(cv2.imread(x), 'cnn', True,
                                                   input_is_predetected_face=True)
                  temp_list.append([x, np.array(d[0][1]) if len(d) > 0 else np.zeros((68, 2))])
          elif group_method == 'group_hist':
              temp_list = [[x, cv2.calcHist([cv2.imread(x)], [0], None, [256], [0, 256])] for x in tqdm(self.find_images(input_dir), desc="Reloading", file=sys.stdout)]
          else:
              raise ValueError("{} group_method not found.".format(group_method))
keep keep keep keep replace keep keep keep keep keep
 GUI v0.2.1b (#352)

* Code refactor

* Console Added

* Add graphing with matplotlib

* Add GUI preview support

* Improve import handling.

* Add GUI integration for tools.py (Launch tools.py with the gui command)

* Reformat to conform to PEP8.

* Add Tooltips, 

* Make panels user adjustable

* Fix convert.py Sharpen default value 
tools/sort.py