def test_get_predictions_uses_model_appropriately(self, mock_path, _Image,
_np, _load, _image):
mock_path.exists.return_value = True
main.get_predictions(self.model_path, self.img_path, self.target_size)
_load.assert_called_once_with(self.model_path)
_load.return_value.predict.assert_called_once()
def test_get_predictions_input_is_preprocessed(self, mock_path, _Image,
_np, _load, _image,
_preprocess):
mock_path.exists.return_value = True
main.get_predictions(self.model_path, self.img_path, self.target_size)
_preprocess.assert_called_once_with(_np.expand_dims.return_value)
_load.return_value.predict.assert_called_once_with(
_preprocess.return_value)
def test_get_predictions_loads_image_appropriately(self, mock_path, _Image,
_np, _load, _image):
mock_path.exists.return_value = True
_Image.open.return_value.size = (6, 6)
main.get_predictions(self.model_path, self.img_path, self.target_size)
_Image.open.assert_called_once_with(self.img_path)
_Image.open.return_value.resize.assert_called_once_with(
self.target_size)
_image.img_to_array.assert_called_once_with(
_Image.open.return_value.resize.return_value)
def test_get_predictions_raises_error_if_model_file_doesnot_exist_only(
self, mock_path, _Image, _np, _load, _image):
# if model path exist, valueerror should not be raised
mock_path.exists.return_value = True
try:
main.get_predictions(self.model_path, self.img_path,
self.target_size)
except ValueError:
self.fail(
"No value error should have been raised while model path existing"
)
# if model path does not exist, valueerror should be raised
mock_path.exists.return_value = False
with self.assertRaises(ValueError) as ve:
main.get_predictions('dummy_path', 'dummy_path', self.target_size)
def test_get_predictions_returns_right_preds_and_its_sorting_index(
self, mock_path, _Image, _np, _load, _image, _preprocess):
mock_path.exists.return_value = True
expected_preds = np.array([2, 3, 1])
_load.return_value.predict.return_value.flatten.return_value = expected_preds
preds, sorrting_index = main.get_predictions(self.model_path,
self.img_path,
self.target_size)
expected_sorting_index = np.array([1, 0, 2])
np.testing.assert_array_equal(preds, expected_preds)
np.testing.assert_array_equal(sorrting_index, expected_sorting_index)