docstr: MTCNN is able to detect faces and landmarks on an image
  :return:
code: def test_detect_faces(self):
      """
      MTCNN is able to detect faces and landmarks on an image
      :return:
      """
      ivan = cv2.imread("ivan.jpg")
  
      result = mtcnn.detect_faces(ivan)  # type: list
  
      self.assertEqual(len(result), 1)
  
      first = result[0]
  
      self.assertIn("box", first)
      self.assertIn("keypoints", first)
      self.assertTrue(len(first["box"]), 1)
      self.assertTrue(len(first["keypoints"]), 5)
  
      keypoints = first["keypoints"]  # type: dict
      self.assertIn("nose", keypoints)
      self.assertIn("mouth_left", keypoints)
      self.assertIn("mouth_right", keypoints)
      self.assertIn("left_eye", keypoints)
      self.assertIn("right_eye", keypoints)
  
      self.assertEqual(len(keypoints["nose"]), 2)
      self.assertEqual(len(keypoints["mouth_left"]), 2)
      self.assertEqual(len(keypoints["mouth_right"]), 2)
      self.assertEqual(len(keypoints["left_eye"]), 2)
      self.assertEqual(len(keypoints["right_eye"]), 2)
  
file_path: mtcnn/tests/test_mtcnn.py
imports: import unittest
  import cv2
  from mtcnn.exceptions import InvalidImage
  from mtcnn import MTCNN
label_desc: Use image node_id 2 for calling the TestMTCNN obj's underlying member method code with example usage: obj.test_detect_faces() without return types