          """ If we have no alignments for this image, skip it """
          have_alignments = self.faces.have_face(filename)
          if not have_alignments:
              tqdm.write("No alignment found for {}, "
                         "skipping".format(os.path.basename(filename)))
          return have_alignments
  
      def convert(self, converter, item):
          """ Apply the conversion transferring faces onto frames """
          try:
 
</s> remove         have_alignments = self.faces.have_face(filename)
 </s> add         have_alignments = self.alignments.frame_exists(frame) </s> remove     def check_alignments(self, filename):
 </s> add     def check_alignments(self, frame): </s> remove             yield filename, image, faces
 </s> add         for rawface in faces:
            face = DetectedFace()
            face.from_alignment(rawface, image=image)
            detected_faces.append(face)
        return image, detected_faces </s> remove         return input_images
 </s> add     def load(self):
        """ Load the alignments data if it exists or create empty dict """
        data = dict()
        skip_faces = None
        if self.is_extract:
            skip_existing = bool(hasattr(self.args, 'skip_existing')
                                 and self.args.skip_existing)
            skip_faces = bool(hasattr(self.args, 'skip_faces')
                              and self.args.skip_faces)

            if not self.have_alignments_file:
                if skip_existing or skip_faces:
                    print("Skip Existing/Skip Faces selected, but no "
                          "alignments file found!")
                return data
            if not skip_existing and not skip_faces:
                return data
                       "skipping".format(frame))
          """ If we have no alignments for this image, skip it """
          have_alignments = self.faces.have_face(filename)
          if not have_alignments:
              tqdm.write("No alignment found for {}, "
                       "skipping".format(frame))
          return have_alignments
  
      def convert(self, converter, item):
          """ Apply the conversion transferring faces onto frames """
          try:
keep keep keep keep replace keep keep keep keep keep
 Extraction - Speed improvements (#522) (#523)

* Extraction - Speed improvements (#522)

* Initial Plugin restructure

* Detectors to plugins. Detector speed improvements

* Re-implement dlib aligner, remove models, FAN to TF. Parallel processing

* Update manual, update convert, implement parallel/serial switching

* linting + fix cuda check (setup.py). requirements update keras 2.2.4

* Add extract size option. Fix dlib hog init

* GUI: Increase tooltip width

* Update alignment tool to support new DetectedFace

* Add skip existing faces option

* Fix sort tool to new plugin structure

* remove old align plugin

* fix convert -skip faces bug

* Fix convert skipping no faces frames

* Convert - draw onto transparent layer

* Fix blur threshold bug

* fix skip_faces convert bug

* Fix training 
scripts/convert.py