code: def multi_gmc(stracks, H=np.eye(2, 3)):
      if len(stracks) > 0:
          multi_mean = np.asarray([st.mean.copy() for st in stracks])
          multi_covariance = np.asarray(
              [st.covariance for st in stracks]
          )
  
          R = H[:2, :2]
          R8x8 = np.kron(np.eye(4, dtype=float), R)
          t = H[:2, 2]
  
          for i, (mean, cov) in enumerate(
              zip(multi_mean, multi_covariance)
          ):
              mean = R8x8.dot(mean)
              mean[:2] += t
              cov = R8x8.dot(cov).dot(R8x8.transpose())
  
              stracks[i].mean = mean
              stracks[i].covariance = cov
  
imports: import numpy
  from collections import defaultdict
  from collections import deque, OrderedDict
  from ..matching import jde_matching
  from ppdet.core.workspace import register, serializable
  import warnings
label_desc: Use image node_id 5 for calling the STrack obj's underlying member method code with example usage: obj.multi_gmc(stracks, H) without return types