  
          if faces_count > 1 and self.arguments.verbose:
              self.verify_output = True
  
      def load_filter(self):
          nfilter_files = self.arguments.nfilter
          if not isinstance(self.arguments.nfilter, list):
              nfilter_files = [self.arguments.nfilter]
          nfilter_files = list(filter(lambda fn: Path(fn).exists(), nfilter_files))
  
          filter_files = self.arguments.filter
          if not isinstance(self.arguments.filter, list):
              filter_files = [self.arguments.filter]
          filter_files = list(filter(lambda fn: Path(fn).exists(), filter_files))
 
</s> remove         filter_files = self.arguments.filter
        if not isinstance(self.arguments.filter, list):
            filter_files = [self.arguments.filter]
        filter_files = list(filter(lambda fn: Path(fn).exists(), filter_files))
        
        if filter_files:
            import_FaceFilter()
            print('Loading reference images for filtering: %s' % filter_files)
            return FaceFilter(filter_files, nfilter_files, self.arguments.ref_threshold)
 </s> add     @staticmethod
    def get_optional_arguments():
        """ Put the arguments in a list so that they are accessible from both argparse and gui """
        argument_list = []
        argument_list.append({"opts": ("-r", "--rotate-images"),
                              "type": str,
                              "dest": "rotate_images",
                              "default": None,
                              "help": "If a face isn't found, rotate the images to try to "
                                      "find a face. Can find more faces at the cost of extraction "
                                      "speed. Pass in a single number to use increments of that "
                                      "size up to 360, or pass in a list of numbers to enumerate "
                                      "exactly what angles to check"})
        argument_list.append({"opts": ("-bt", "--blur-threshold"),
                              "type": int,
                              "dest": "blur_thresh",
                              "default": None,
                              "help": "Automatically discard images blurrier than the specified "
                                      "threshold. Discarded images are moved into a \"blurry\" "
                                      "sub-folder. Lower values allow more blur"})
        argument_list.append({"opts": ("-j", "--processes"),
                              "type": int,
                              "default": 1,
                              "help": "Number of CPU processes to use. WARNING: ONLY USE THIS "
                                      " IF YOU ARE NOT EXTRACTING ON A GPU. Anything above 1 "
                                      " process on a GPU will run out of memory and will crash"})
        argument_list.append({"opts": ("-s", "--skip-existing"),
                              "action": "store_true",
                              "dest": "skip_existing",
                              "default": False,
                              "help": "Skips frames that have already been extracted"})
        argument_list.append({"opts": ("-dl", "--debug-landmarks"),
                              "action": "store_true",
                              "dest": "debug_landmarks",
                              "default": False,
                              "help": "Draw landmarks on the ouput faces for debug"})
        argument_list.append({"opts": ("-ae", "--align-eyes"),
                              "action": "store_true",
                              "dest": "align_eyes",
                              "default": False,
                              "help": "Perform extra alignment to ensure left/right eyes "
                                      "are  at the same height"})
        return argument_list </s> remove         if faces_count > 1 and self.arguments.verbose:
            self.verify_output = True
 </s> add     @staticmethod
    def get_argument_list():
        """ Put the arguments in a list so that they are accessible from both argparse and gui """
        argument_list = []
        argument_list.append({"opts": ("-i", "--input-dir"),
                              "action": FullPaths,
                              "dest": "input_dir",
                              "default": "input",
                              "help": "Input directory. A directory containing the files "
                                      "you wish to process. Defaults to 'input'"})
        argument_list.append({"opts": ("-o", "--output-dir"),
                              "action": FullPaths,
                              "dest": "output_dir",
                              "default": "output",
                              "help": "Output directory. This is where the converted files will "
                                      "be stored. Defaults to 'output'"})
        argument_list.append({"opts": ("--alignments", ),
                              "type": str,
                              "dest": "alignments_path",
                              "help": "optional path to alignments file"})
        argument_list.append({"opts": ("--serializer", ),
                              "type": str.lower,
                              "dest": "serializer",
                              "choices": ("yaml", "json", "pickle"),
                              "help": "serializer for alignments file"})
        argument_list.append({"opts": ("-D", "--detector"),
                              "type": str,
                              # case sensitive because this is used to load a plugin.
                              "choices": ("hog", "cnn"),
                              "default": "hog",
                              "help": "Detector to use. 'cnn' detects many more angles but "
                                      "will be much more resource intensive and may fail "
                                      "on large files"})
        argument_list.append({"opts": ("-l", "--ref_threshold"),
                              "type": float,
                              "dest": "ref_threshold",
                              "default": 0.6,
                              "help": "Threshold for positive face recognition"})
        argument_list.append({"opts": ("-n", "--nfilter"),
                              "type": str,
                              "dest": "nfilter",
                              "nargs": "+",
                              "default": None,
                              "help": "Reference image for the persons you do not want to "
                                      "process. Should be a front portrait. Multiple images"
                                      "can be added space separated"})
        argument_list.append({"opts": ("-f", "--filter"),
                              "type": str,
                              "dest": "filter",
                              "nargs": "+",
                              "default": None,
                              "help": "Reference images for the person you want to process. "
                                      "Should be a front portrait. Multiple images"
                                      "can be added space separated"})
        argument_list.append({"opts": ("-v", "--verbose"),
                              "action": "store_true",
                              "dest": "verbose",
                              "default": False,
                              "help": "Show verbose output"})
        return argument_list </s> remove             yield faces_count, face
            self.num_faces_detected += 1
            faces_count += 1
        if faces_count > 1 and self.arguments.verbose:
            print('Note: Found more than one face in an image! File: %s' % filename)
            self.verify_output = True
 </s> add  </s> remove     def get_faces(self, image, rotation=0):
        import_faces_detect()
        faces_count = 0
        faces = detect_faces(image, self.arguments.detector, self.arguments.verbose, rotation)
        
        for face in faces:
            if self.filter is not None and not self.filter.check(face):
                if self.arguments.verbose:
                    print('Skipping not recognized face!')
                continue
            yield faces_count, face
 </s> add class ExtractConvertArgs(FaceSwapArgs):
    """ This class is used as a parent class to capture arguments that
        will be used in both the extract and convert process. </s> remove             self.num_faces_detected += 1
            faces_count += 1
 </s> add         Arguments that can be used in both of these processes should be
        placed here, but no further processing should be done. This class
        just captures arguments """
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
  
          if faces_count > 1 and self.arguments.verbose:
              self.verify_output = True
  
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
class ExtractArgs(ExtractConvertArgs):
    """ Class to parse the command line arguments for extraction.
        Inherits base options from ExtractConvertArgs where arguments
        that are used for both extract and convert should be placed """
  
          filter_files = self.arguments.filter
          if not isinstance(self.arguments.filter, list):
              filter_files = [self.arguments.filter]
          filter_files = list(filter(lambda fn: Path(fn).exists(), filter_files))
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 cli/scripts Refactor (#367)

* Refactor for PEP 8 and split process function

* Remove backwards compatibility for skip frames

* Split optional functions into own class. Make functions more modular

* Conform scripts folder to PEP 8

* train.py - Fix write image bug. Make more modular

* extract.py - Make more modular, Put optional actions into own class

* cli.py - start PEP 8

* cli,py - Pep 8. Refactor and make modular. Bugfixes

* 1st round refactor. Completely untested and probably broken.

* convert.py: Extract alignments from frames if they don't exist

* BugFix: SkipExisting broken since face name refactor

* Extract.py tested

* Minor formatting

* convert.py + train.py amended not tested

* train.py - Semi-fix for hang on reaching target iteration. Now quits on preview mode
Make tensorflow / system warning less verbose

* 2nd pass refactor. Semi tested

bugfixes

* Remove obsolete code. imread/write to Utils

* rename inout.py to fsmedia.py

* Final bugfixes 
lib/cli.py