          return [left, top, right, bottom]
  
      @staticmethod
      def pad_image(box, image):
          """Pad image if facebox falls outside of boundaries """
          width, height = image.shape[:2]
          pad_l = 1 - box[0] if box[0] < 0 else 0
          pad_t = 1 - box[1] if box[1] < 0 else 0
          pad_r = box[2] - width if box[2] > width else 0
          pad_b = box[3] - height if box[3] > height else 0
 
</s> remove fail_count = 0
test_count = 0
 </s> add FAIL_COUNT = 0
TEST_COUNT = 0 </s> remove         retval = 1 if self._is_parallel else 3
 </s> add         retval = 1 if self._is_parallel else len(self._flow) </s> remove         if self._detector.vram == 0 and self._aligner.vram == 0 and self._masker.vram == 0:
            logger.debug("Either detector, aligner or masker have no VRAM requirements. Not "
                         "updating batchsize requirements.")
 </s> add         if sum([plugin.vram for plugin in self._all_plugins]) == 0:
            logger.debug("No plugins use VRAM. Not updating batchsize requirements.") </s> remove     @staticmethod
    def _padding_from_coverage(size, coverage_ratio):
 </s> add     def _padding_from_coverage(self, size, coverage_ratio): </s> remove             logger.trace("{} - {}", key, mask_dict[key] if key != "mask" else type(mask_dict[key]))
 </s> add             logger.trace("%s - %s", key, mask_dict[key] if key != "mask" else type(mask_dict[key]))
        """Pad image if face-box falls outside of boundaries """
          return [left, top, right, bottom]
  
      @staticmethod
      def pad_image(box, image):
        """Pad image if face-box falls outside of boundaries """
          width, height = image.shape[:2]
          pad_l = 1 - box[0] if box[0] < 0 else 0
          pad_t = 1 - box[1] if box[1] < 0 else 0
          pad_r = box[2] - width if box[2] > width else 0
          pad_b = box[3] - height if box[3] > height else 0
keep keep keep keep replace keep keep keep keep keep
 Smart Mask - Extract code review

- Lint simple_tests.py
- Only reformat alignments file if it exists otherwise change filename
- Update legacy alignments to new format at all stages
- faces_detect.Mask.from_dict - logging format fix
- convert.py fix otf for new pipeline
- cli.py - Add note that masks not used. Revert convert masks
- faces_detect.py - Revert non-extract code
- Add .p and .pickle extensions for serializer
- plugins/extract revert some changes
- scripts/fsmedia - Revert code changes
- Pipeline - cleanup
- Consistant alpha channel stripping (fixes single-process)
- Store landmarks as numpy array
- Code attribution
- Normalize feed face and reference face to 0.0 - 1.0 in convert
- Lock in mask VRAM sized
- Add documentation to plugin_loader
- Update alignments tool to work with new format 
plugins/extract/align/cv2_dnn.py