code: def _eval_seq_jde_single_image(
      self, iterator, save_dir=None, show_image=False, draw_threshold=0
  ):
      if save_dir:
          if not os.path.exists(save_dir):
              os.makedirs(save_dir)
      tracker = self.model.tracker
      results = []
      frame_id = 0
      self.status["mode"] = "track"
      self.model.eval()
      timer = Timer()
      while True:
          try:
              data = next(iterator)
              timer.tic()
              pred_dets, pred_embs = self.model(data)
              online_targets = self.model.tracker.update(
                  pred_dets, pred_embs
              )
              online_tlwhs, online_ids = [], []
              online_scores = []
              for t in online_targets:
                  tlwh = t.tlwh
                  tid = t.track_id
                  tscore = t.score
                  if tscore < draw_threshold:
                      continue
                  vertical = tlwh[2] / tlwh[3] > 1.6
                  if (
                      tlwh[2] * tlwh[3] > tracker.min_box_area
                      and not vertical
                  ):
                      online_tlwhs.append(tlwh)
                      online_ids.append(tid)
                      online_scores.append(tscore)
              timer.toc()
              # save results
              results.append(
                  (
                      frame_id + 1,
                      online_tlwhs,
                      online_scores,
                      online_ids,
                  )
              )
              self.save_results(
                  data,
                  frame_id,
                  online_ids,
                  online_tlwhs,
                  online_scores,
                  timer.average_time,
                  show_image,
                  save_dir,
              )
              frame_id += 1
  
              yield results, frame_id
  
          except StopIteration as e:
              return
  
imports: import os
  import cv2
  import glob
  import paddle
  import numpy
  import collections
  from ppdet.core.workspace import create
  from ppdet.utils.checkpoint import load_weight, load_pretrain_weight
  from ppdet.metrics import Metric, MOTMetric, KITTIMOTMetric
  import ppdet.utils.stats
  from ppdet.engine.callbacks import Callback, ComposeCallback
  from ppdet.utils.logger import setup_logger
  from .dataset import MOTVideoStream, MOTImageStream
  from .utils import Timer
  from .modeling.mot.utils import Detection, get_crops, scale_coords, clip_box
  from .modeling.mot import visualization
label_desc: Use image node_id 4 for calling the StreamTracker obj's underlying member method code with example usage: obj._eval_seq_jde_single_image(iterator, save_dir, show_image, draw_threshold) without return types