code: def get_crops(xyxy, ori_img, pred_scores, w, h):
      crops = []
      keep_scores = []
      xyxy = xyxy.numpy().astype(np.int64)
      ori_img = ori_img.numpy()
      ori_img = np.squeeze(ori_img, axis=0).transpose(1, 0, 2)
      pred_scores = pred_scores.numpy()
      for i, bbox in enumerate(xyxy):
          if bbox[2] <= bbox[0] or bbox[3] <= bbox[1]:
              continue
          crop = ori_img[bbox[0] : bbox[2], bbox[1] : bbox[3], :]
          crops.append(crop)
          keep_scores.append(pred_scores[i])
      if len(crops) == 0:
          return [], []
      crops = preprocess_reid(crops, w, h)
      return crops, keep_scores
  
imports: import os
  import cv2
  import time
  import paddle
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: get_crops(xyxy, ori_img, pred_scores, w, h) and returns: crops,  keep_scores, list,  list