          return batch
  
      def predict(self, batch):
          """ Run model to get predictions """
          batch["prediction"] = np.full(batch["feed"].shape[:-1] + (1,),
                                        fill_value=255,
                                        dtype='uint8')
          return batch
  
      def process_output(self, batch):
          """ Compile found faces for output """
          generator = zip(batch["feed"], batch["detected_faces"], batch["prediction"])
 
</s> remove         predictions = self.model.predict(batch["feed"])
        batch["prediction"] = predictions * 255.
 </s> add         batch["prediction"] = self.model.predict(batch["feed"]) </s> remove         batch["prediction"] = predictions[..., 0:1] * -255. + 255.
 </s> add         batch["prediction"] = predictions[..., 0] * -1.0 + 1.0 </s> remove         batch["feed"] = np.array([face.image for face in batch["detected_faces"]])
 </s> add         batch["feed"] = np.zeros((self.batchsize, self.input_size, self.input_size, 1),
                                 dtype="float32") </s> remove         batch["prediction"] = predictions[..., 1:2] * 255.
 </s> add         batch["prediction"] = predictions[..., -1] </s> remove         batch["feed"] = np.array([face.image for face in batch["detected_faces"]])
 </s> add         batch["feed"] = np.zeros((self.batchsize, self.input_size, self.input_size, 1),
                                 dtype="float32")
        batch["prediction"] = np.ones_like(batch["feed"], dtype="float32")
          return batch
  
      def predict(self, batch):
          """ Run model to get predictions """
        batch["prediction"] = np.ones_like(batch["feed"], dtype="float32")
        batch["prediction"] = np.ones_like(batch["feed"], dtype="float32")
        batch["prediction"] = np.ones_like(batch["feed"], dtype="float32")
          return batch
  
      def process_output(self, batch):
          """ Compile found faces for output """
          generator = zip(batch["feed"], batch["detected_faces"], batch["prediction"])
keep keep keep keep replace replace replace keep keep keep keep keep
 Mask plugin cleanup

- PEP8 Fixes
- Remove config for non NN Masks
- Tidy up defaults helptext
- cli.py fix typos
- Remove unused imports and functions _base.py
- Standardize input_size param
- Enable and update documentation
- Change references from `aligner` to `masker`
- Change  input_size, output_size and coverage_ratio from kwargs to params
- Move load_aligned to batch input iterator
- Remove unnecessary self.input param
- Add softmax layer append function to KSession
- Remove references to KSession protected objects
- Standardize plugin output into finalize method
- Make masks full frame and add to lib.faces_detect
- Add masks to alignments.json (temporary zipped base64 solution) 
plugins/extract/mask/none.py