              loc (tensor): location predictions for loc layers,
                  Shape: [num_priors,4]
              priors (tensor): Prior boxes in center-offset form.
                  Shape: [num_priors,4].
              variances: (list[float]) Variances of priorboxes
          Return:
              decoded bounding box predictions
          """
          variances = [0.1, 0.2]
          boxes = np.concatenate((priors[:, :2] + loc[:, :2] * variances[0] * priors[:, 2:],
 
</s> remove     def _nms(self, boxes, threshold):
 </s> add     @staticmethod
    def _nms(boxes, threshold): </s> remove         # TODO modify detected face to hold this data as a matrix
 </s> add  </s> remove         batch["feed"] = self.model.prepare_batch(batch["scaled_image"])
 </s> add         batch["feed"] = self.model.prepare_batch(batch["image"]) </s> remove         # TODO improve rudimentary subpixel logic to centroid of 3x3 window algorithm
 </s> add         # TODO improve rudimentary sub-pixel logic to centroid of 3x3 window algorithm </s> remove         dict
            A ``dict`` for each frame containing the ``image``, ``filename`` and list of
            :class:`lib.faces_detect.DetectedFace` objects.

 </s> add         :class:`~plugins.extract.pipeline.ExtractMedia`
            The :attr:`DetectedFaces` list will be populated for this class with the bounding boxes
            and landmarks for the detected faces found in the frame.
            variances: (list[float]) Variances of prior boxes
              loc (tensor): location predictions for loc layers,
                  Shape: [num_priors,4]
              priors (tensor): Prior boxes in center-offset form.
                  Shape: [num_priors,4].
            variances: (list[float]) Variances of prior boxes
          Return:
              decoded bounding box predictions
          """
          variances = [0.1, 0.2]
          boxes = np.concatenate((priors[:, :2] + loc[:, :2] * variances[0] * priors[:, 2:],
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/s3fd.py