                       "configfile: %s, multiprocess: %s, rotate_images: %s, min_size: %s, "
                       "normalize_method: %s)",
                       self.__class__.__name__, detector, aligner, masker, configfile,
                       multiprocess, rotate_images, min_size, normalize_method)
          self.phase = "detect"
          self._queue_size = 32
          self._vram_buffer = 320  # Leave a buffer for VRAM allocation
          self._detector = self._load_detector(detector, rotate_images, min_size, configfile)
          self._aligner = self._load_aligner(aligner, configfile, normalize_method)
          self._masker = self._load_masker(masker, configfile)
 
</s> remove         self._detector = self._load_detector(detector, rotate_images, min_size, configfile)
        self._aligner = self._load_aligner(aligner, configfile, normalize_method)
        self._masker = self._load_masker(masker, configfile)
 </s> add         self._detect = self._load_detect(detector, rotate_images, min_size, configfile)
        self._align = self._load_align(aligner, configfile, normalize_method)
        self._mask = self._load_mask(masker, configfile) </s> remove         self.input_size = 256  # Overide for model specific input_size
        self.blur_kernel = 5  # Overide for model specific blur_kernel size
        self.coverage_ratio = 1.0  # Overide for model specific coverage_ratio
 </s> add         self.input_size = 256  # Override for model specific input_size
        self.blur_kernel = 5  # Override for model specific blur_kernel size
        self.coverage_ratio = 1.0  # Override for model specific coverage_ratio </s> remove             self.image = image
 </s> add  </s> remove     def _load_detector(detector, rotation, min_size, configfile):
 </s> add     def _load_align(aligner, configfile, normalize_method):
        """ Set global arguments and load aligner plugin """
        aligner_name = aligner.replace("-", "_").lower()
        logger.debug("Loading Aligner: '%s'", aligner_name)
        aligner = PluginLoader.get_aligner(aligner_name)(configfile=configfile,
                                                         normalize_method=normalize_method)
        return aligner

    @staticmethod
    def _load_detect(detector, rotation, min_size, configfile): </s> remove         self._intepolator = interpolator
 </s> add         self._interpolator = interpolator
        self._flow = ["detect", "align", "mask"]
        self.phase = self._flow[0]
                       "configfile: %s, multiprocess: %s, rotate_images: %s, min_size: %s, "
                       "normalize_method: %s)",
                       self.__class__.__name__, detector, aligner, masker, configfile,
                       multiprocess, rotate_images, min_size, normalize_method)
        self._flow = ["detect", "align", "mask"]
        self.phase = self._flow[0]
          self._queue_size = 32
          self._vram_buffer = 320  # Leave a buffer for VRAM allocation
          self._detector = self._load_detector(detector, rotate_images, min_size, configfile)
          self._aligner = self._load_aligner(aligner, configfile, normalize_method)
          self._masker = self._load_masker(masker, configfile)
keep keep keep keep replace keep keep keep keep keep
 Smart Mask - Extract code review

- Lint simple_tests.py
- Only reformat alignments file if it exists otherwise change filename
- Update legacy alignments to new format at all stages
- faces_detect.Mask.from_dict - logging format fix
- convert.py fix otf for new pipeline
- cli.py - Add note that masks not used. Revert convert masks
- faces_detect.py - Revert non-extract code
- Add .p and .pickle extensions for serializer
- plugins/extract revert some changes
- scripts/fsmedia - Revert code changes
- Pipeline - cleanup
- Consistant alpha channel stripping (fixes single-process)
- Store landmarks as numpy array
- Code attribution
- Normalize feed face and reference face to 0.0 - 1.0 in convert
- Lock in mask VRAM sized
- Add documentation to plugin_loader
- Update alignments tool to work with new format 
plugins/extract/pipeline.py