code: def greedy_assignment(dist):
      matched_indices = []
      if dist.shape[1] == 0:
          return np.array(matched_indices, np.int32).reshape(-1, 2)
      for i in range(dist.shape[0]):
          j = dist[i].argmin()
          if dist[i][j] < 1e16:
              dist[:, j] = 1e18
              matched_indices.append([i, j])
      return np.array(matched_indices, np.int32).reshape(-1, 2)
  
file_path: PaddleDetection/ppdet/modeling/mot/tracker/center_tracker.py
imports: import copy
  import numpy
  import sklearn
  from ppdet.core.workspace import register, serializable
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 for calling a global function with example usage: greedy_assignment(dist) and returns: np, np