code: def flip_detect(net, img, device):
      img = cv2.flip(img, 1)
      b = detect(net, img, device)
  
      bboxlist = np.zeros(b.shape)
      bboxlist[:, 0] = img.shape[1] - b[:, 2]
      bboxlist[:, 1] = b[:, 1]
      bboxlist[:, 2] = img.shape[1] - b[:, 0]
      bboxlist[:, 3] = b[:, 3]
      bboxlist[:, 4] = b[:, 4]
      return bboxlist
  
file_path: face-alignment/face_alignment/detection/blazeface/detect.py
imports: import torch
  import torch.nn.functional
  import cv2
  import numpy
  from .utils import *
label_desc: Use image node_id 3 for calling a global function with example usage: flip_detect(net, img, device) and returns: bboxlist