code: def test_should_return_batches_equivalent_to_number_of_frames(self):
      from evadb.functions.face_detector import FaceDetector
  
      single_face_img = Path("data/facenet/one.jpg")
      multi_face_img = Path("data/facenet/multiface.jpg")
      frame_single_face = {
          "id": 1,
          "data": self._load_image(single_face_img),
      }
      frame_multifaces = {
          "id": 2,
          "data": self._load_image(multi_face_img),
      }
      frame_batch = Batch(
          pd.DataFrame([frame_single_face, frame_single_face])
      )
      detector = FaceDetector()
      result = detector(frame_batch.project(["data"]).frames)
      self.assertEqual(1, len(result.iloc[0]["bboxes"]))
      self.assertEqual(1, len(result.iloc[1]["bboxes"]))
  
      frame_batch = Batch(pd.DataFrame([frame_multifaces]))
      detector = FaceDetector()
      result = detector(frame_batch.project(["data"]).frames)
      self.assertEqual(6, len(result.iloc[0]["bboxes"]))
  
file_path: evadb/test/integration_tests/long/functions/test_facenet_udf.py
imports: import unittest
  from pathlib import Path
  from test.markers import windows_skip_marker
  from test.util import EvaDB_TEST_DATA_DIR
  import pandas
  from evadb.models.storage.batch import Batch
  from evadb.utils.generic_utils import try_to_import_cv2
label_desc: Use image node_id 3 for calling the FaceNet obj's underlying member method code with example usage: obj.test_should_return_batches_equivalent_to_number_of_frames() without return types