  
          for item in batch.iterator():
              self.convert(converter, item)
      
      def check_skip(self, filename):
          try:
              idx = int(self.imageidxre.findall(filename)[0])
              return not any(map(lambda b: b[0]<=idx<=b[1], self.frame_ranges))
          except:
              return False
 
</s> remove             skip = self.check_skip(filename)

            if not skip: # process as normal
 </s> add             if not self.check_skipframe(filename): # process as normal </s> remove         self.images_found = len(self.input_dir)
 </s> add  </s> remove         encodings = face_recognition.face_encodings(detected_face.image)[0] # we could use detected landmarks, but I did not manage to do so
        score = face_recognition.face_distance([self.encoding], encodings)
        print(score)
        return score <= self.threshold

 </s> add         encodings = face_recognition.face_encodings(detected_face.image) # we could use detected landmarks, but I did not manage to do so. TODO The copy/paste below should help
        if encodings is not None and len(encodings) > 0:
            score = face_recognition.face_distance([self.encoding], encodings[0])
            print(score)
            return score <= self.threshold
        else:
            print("No face encodings found")
            return False
 </s> remove         for filename in tqdm(self.input_dir):
            if self.arguments.verbose:
                print('Processing: {}'.format(os.path.basename(filename)))

            yield filename
            self.images_processed = self.images_processed + 1
 </s> add         self.images_found = len(self.input_dir)
        return self.input_dir
    def check_skipframe(self, filename):
  
          for item in batch.iterator():
              self.convert(converter, item)
      
    def check_skipframe(self, filename):
          try:
              idx = int(self.imageidxre.findall(filename)[0])
              return not any(map(lambda b: b[0]<=idx<=b[1], self.frame_ranges))
          except:
              return False
keep keep keep keep replace keep keep keep keep keep
 Misc updates on master before GAN. Added multithreading + mmod face detector (#109)

* Preparing GAN plugin

* Adding multithreading for extract

* Adding support for mmod human face detector

* Adding face filter argument

* Added process number argument to multiprocessing extractor.

Fixed progressbar for multiprocessing.

* Added tiff as image type.
compression artefacts hurt my feelings.

* Cleanup 
scripts/convert.py