class_docstr: apply affine transform to image and coords
  
  Args:
      trainsize (list): [w, h], the standard size used to train
      use_udp (bool): whether to use Unbiased Data Processing.
      records(dict): the dict contained the image and coords
  
  Returns:
      records (dict): contain the image and coords after tranformed
code: def __init__(self, trainsize, use_udp=False):
      self.trainsize = trainsize
      self.use_udp = use_udp
  
file_path: PaddleHub/modules/image/keypoint_detection/pp-tinypose/keypoint_preprocess.py
imports: import cv2
  import numpy
label_desc: Use image node_id 1 to create a new TopDownEvalAffine object from inherited base classes: object with example: obj = TopDownEvalAffine(trainsize, use_udp)