          self.model.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)  # pylint: disable=no-member
  
      def process_input(self, batch):
          """ Compile the detection image(s) for prediction """
          batch["feed"] = cv2.dnn.blobFromImages(batch["scaled_image"],  # pylint: disable=no-member
                                                 scalefactor=1.0,
                                                 size=(self.input_size, self.input_size),
                                                 mean=[104, 117, 123],
                                                 swapRB=False,
                                                 crop=False)
 
</s> remove         faces, batch["roi"] = self.align_image(batch["detected_faces"])
 </s> add         faces, batch["roi"] = self.align_image(batch) </s> remove         batch["feed"] = self.model.prepare_batch(batch["scaled_image"])
 </s> add         batch["feed"] = self.model.prepare_batch(batch["image"]) </s> remove         batch["feed"] = (batch["scaled_image"] - 127.5) / 127.5
 </s> add         batch["feed"] = (batch["image"] - 127.5) / 127.5 </s> remove         batch["feed"] = batch["scaled_image"]
 </s> add         batch["feed"] = batch["image"] </s> remove     def _compile_detection_image(self, input_image):
        """ Compile the detection image for feeding into the model"""
        image = self._convert_color(input_image)
 </s> add     def _compile_detection_image(self, item):
        """ Compile the detection image for feeding into the model
        batch["feed"] = cv2.dnn.blobFromImages(batch["image"],  # pylint: disable=no-member
          self.model.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)  # pylint: disable=no-member
  
      def process_input(self, batch):
          """ Compile the detection image(s) for prediction """
        batch["feed"] = cv2.dnn.blobFromImages(batch["image"],  # pylint: disable=no-member
                                                 scalefactor=1.0,
                                                 size=(self.input_size, self.input_size),
                                                 mean=[104, 117, 123],
                                                 swapRB=False,
                                                 crop=False)
keep keep keep keep replace keep keep keep keep keep
 plugins.extract - Create ExtractMedia class for pipeline flow
Bugfix - Fix memory leak in extract 
plugins/extract/detect/cv2_dnn.py