code: def bbox_overlaps(bboxes1, bboxes2, mode="iou", eps=1e-6):
      """Calculate the ious between each bbox of bboxes1 and bboxes2.
  
      Args:
          bboxes1(ndarray): shape (n, 4)
          bboxes2(ndarray): shape (k, 4)
          mode(str): iou (intersection over union) or iof (intersection
              over foreground)
  
      Returns:
          ious(ndarray): shape (n, k)
      """
  
      assert mode in ["iou", "iof"]
  
      bboxes1 = bboxes1.astype(np.float32)
      bboxes2 = bboxes2.astype(np.float32)
      rows = bboxes1.shape[0]
      cols = bboxes2.shape[0]
      ious = np.zeros((rows, cols), dtype=np.float32)
      if rows * cols == 0:
          return ious
      exchange = False
      if bboxes1.shape[0] > bboxes2.shape[0]:
          bboxes1, bboxes2 = bboxes2, bboxes1
          ious = np.zeros((cols, rows), dtype=np.float32)
          exchange = True
      area1 = (bboxes1[:, 2] - bboxes1[:, 0]) * (
          bboxes1[:, 3] - bboxes1[:, 1]
      )
      area2 = (bboxes2[:, 2] - bboxes2[:, 0]) * (
          bboxes2[:, 3] - bboxes2[:, 1]
      )
      for i in range(bboxes1.shape[0]):
          x_start = np.maximum(bboxes1[i, 0], bboxes2[:, 0])
          y_start = np.maximum(bboxes1[i, 1], bboxes2[:, 1])
          x_end = np.minimum(bboxes1[i, 2], bboxes2[:, 2])
          y_end = np.minimum(bboxes1[i, 3], bboxes2[:, 3])
          overlap = np.maximum(x_end - x_start, 0) * np.maximum(
              y_end - y_start, 0
          )
          if mode == "iou":
              union = area1[i] + area2 - overlap
          else:
              union = area1[i] if not exchange else area2
          union = np.maximum(union, eps)
          ious[i, :] = overlap / union
      if exchange:
          ious = ious.T
      return ious
  
label_desc: Use image node_id 1 for calling a global function with example usage: bbox_overlaps(bboxes1, bboxes2, mode, eps) and returns: ious, ious