          logger.debug("Reload Images: Start. Detected Faces Count: %s", len(detected_faces))
          load_queue = self.extractor.input_queue
          for filename, image in self.images.load():
              idx += 1
              if load_queue.shutdown.is_set():
                  logger.debug("Reload Queue: Stop signal received. Terminating")
 
</s> remove         predicted = self.predictor(feed)
 </s> add         predicted = self.predictor(feed, batch_size=batch_size) </s> remove                     predicted = self.predict(feed_faces)
 </s> add                     batch_size = None
                    if is_plaidml and feed_faces.shape[0] != self.batchsize:
                        logger.verbose("Fallback to BS=1")
                        batch_size = 1
                    predicted = self.predict(feed_faces, batch_size) </s> remove         dims = (int(width * scale), int(height * scale))

        if scale < 1.0:
            logger.trace("Resizing image from %sx%s to %s.",
                         width, height, "x".join(str(i) for i in dims))
 </s> add         if scale != 1.0:
            dims = (int(width * scale), int(height * scale))
            if scale < 1.0:
                logger.verbose("Resizing image from %sx%s to %s. Scale=%s",
                               width, height, "x".join(str(i) for i in dims), scale)
            image = cv2.resize(image, dims, interpolation=interpln)
        if pad_to:
            image = Detector.pad_image(image, pad_to)
        return image
        idx = 0
          logger.debug("Reload Images: Start. Detected Faces Count: %s", len(detected_faces))
          load_queue = self.extractor.input_queue
        idx = 0
          for filename, image in self.images.load():
              idx += 1
              if load_queue.shutdown.is_set():
                  logger.debug("Reload Queue: Stop signal received. Terminating")
keep add keep keep keep keep
 Added s3fd-amd + minor fixes (#837) 
scripts/extract.py