code: def test_frcnn_estimator():
      from gluoncv.auto.estimators import FasterRCNNEstimator
  
      est = FasterRCNNEstimator(
          {"train": {"epochs": 1}, "gpus": list(range(get_gpu_count()))}
      )
      (
          OBJECT_DETECTION_TRAIN_MINI,
          OBJECT_DETECTION_VAL_MINI,
          OBJECT_DETECTION_TEST_MINI,
      ) = OBJECT_DETECTION_TRAIN.random_split(
          val_size=0.3, test_size=0.2
      )
      res = est.fit(OBJECT_DETECTION_TRAIN_MINI)
      assert res.get("valid_map", 0) > 0
      test_result = est.predict(OBJECT_DETECTION_TEST_MINI)
      est.predict(OBJECT_DETECTION_TEST.iloc[0]["image"])
      with Image.open(
          OBJECT_DETECTION_TEST.iloc[0]["image"]
      ) as pil_image:
          est.predict(pil_image)
      evaluate_result = est.evaluate(OBJECT_DETECTION_VAL_MINI)
      # test save/load
      _save_load_test(est, "frcnn.pkl")
  
file_path: gluon-cv/tests/auto/test_auto_estimators.py
imports: from PIL import Image
  import numpy
  from gluoncv.auto.tasks import ImageClassification, ImagePrediction
  from gluoncv.auto.tasks import ObjectDetection
  from autogluon.core.scheduler.resource import get_cpu_count, get_gpu_count
label_desc: Use image node_id 7 for calling a global function with example usage: test_frcnn_estimator() without return types