class_docstr: Flip image horizontally.
docstr: Args:
      img (numpy.ndarray): Images to be flipped with a probability flip_ratio
  Returns:
      numpy.ndarray: Cropped image.
docstr_tok: ["Args",":","img","(","numpy.ndarray",")",":","Images","to","be","flipped","with","a","probability","flip_ratio","Returns",":","numpy.ndarray",":","Cropped","image","."]
code: def __call__(self, frames):
      """
      Args:
          img (numpy.ndarray): Images to be flipped with a probability flip_ratio
      Returns:
          numpy.ndarray: Cropped image.
      """
      t, h, w = frames.shape
      if random.random() < self.flip_ratio:
          for index in range(t):
              frames[index] = cv2.flip(frames[index], 1)
      return frames
  
imports: import random
  import cv2
  import numpy
  import torch
  from scipy import signal
label_desc: Use image node_id 2 for calling the HorizontalFlip obj's underlying member method code with example usage: obj.__call__(frames) and returns: frames