text: from dlr import DLRModel
  import numpy as np
  import cv2
  from pathlib import Path
  
  MODEL_PATH = Path("../../../build/ssd_mobilenet_v2").resolve()
  DATA_PATH = Path("../../../build/street_small.npy").resolve()
  
  def test_ssd_mobilenet_v2_model():
    model = DLRModel(MODEL_PATH.as_posix())
    data = np.load(DATA_PATH)
    assert model.get_input_names() == ['image_tensor']
    assert model.get_output_names() == ['detection_scores:0', 'detection_classes:0', 'num_detections:0']
    assert model.get_input_dtypes() == ['uint8']
    assert model.get_output_dtypes() == ['float32', 'float32', 'float32']
    outputs = model.run({"image_tensor": data})
    assert outputs[0].shape == (1, 100, 4)
    assert outputs[1].shape == (1, 100)
    assert outputs[2].shape == (1, 100)
    detections = np.multiply(np.ceil(outputs[1]), outputs[2])
    expected = np.zeros(detections.shape)
    expected[:,:6] = np.array([[1., 1., 1., 2., 3., 1]])
    comparison = detections == expected
    assert comparison.all()
  
  if __name__ == '__main__':
      test_ssd_mobilenet_v2_model()
      print('All tests passed!')
  