code: def images_to_paddle(frames):
      frames = (
          paddle.to_tensor(frames.transpose([0, 3, 1, 2]))
          .astype("float32")
          .unsqueeze(0)
          / 255
      )
      b, t, c, h, w = frames.shape
      for ti in range(t):
          frames[0, ti] = im_normalization(frames[0, ti])
      return frames
  
file_path: PaddleSeg/EISeg/eiseg/plugin/video/util/tensor_util.py
imports: import numpy
  import paddle
  import paddle.nn.functional
  from paddle.vision import transforms
label_desc: Use image node_id 1 for calling a global function with example usage: images_to_paddle(frames) and returns: frames