How to use the augmentor.aug_pipe function in Augmentor

image = cv.imread(filename)  # BGR
                image = image[:, :, ::-1]  # RGB
                dets = self.detector(image, 1)

                num_faces = len(dets)
                if num_faces > 0:
                    # Find the 5 face landmarks we need to do the alignment.
                    faces = dlib.full_object_detections()
                    for detection in dets:
                        faces.append(self.sp(image, detection))
                    image = dlib.get_face_chip(image, faces[0], size=img_size)
                else:
                    image = cv.resize(image, (img_size, img_size), cv.INTER_CUBIC)

                if self.usage == 'train':
                    image = aug_pipe.augment_image(image)

                batch_inputs[j, i_batch] = preprocess_input(image)

        return [batch_inputs[0], batch_inputs[1], batch_inputs[2]], batch_dummy_target