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17 changes: 11 additions & 6 deletions src/skai/model/inference_lib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,7 +87,7 @@ def predict_scores(self, batch: list[tf.train.Example]) -> np.ndarray:
raise NotImplementedError()


def _extract_image_or_blank(
def extract_image_or_blank(
example: tf.train.Example, feature: str, image_size: int
) -> np.ndarray:
"""Extracts an image from a TF Example.
Expand Down Expand Up @@ -188,12 +188,12 @@ def _extract_images_or_blanks(
Returns:
Numpy array representing the concatenated images.
"""
post_image = _extract_image_or_blank(
post_image = extract_image_or_blank(
example, post_image_feature, self._image_size
)
if self._post_image_only:
return post_image
pre_image = _extract_image_or_blank(
pre_image = extract_image_or_blank(
example, pre_image_feature, self._image_size
)
return np.concatenate([pre_image, post_image], axis=2)
Expand Down Expand Up @@ -355,7 +355,7 @@ def _key_example_by_encoded_coordinates(
)


def _example_to_row(
def example_to_row(
example: tf.train.Example,
threshold: float,
high_precision_threshold: float,
Expand All @@ -372,7 +372,12 @@ def _example_to_row(
Returns:
Inference row.
"""
example_id = utils.get_int64_feature(example, 'int64_id')[0]

try:
example_id = utils.get_int64_feature(example, 'int64_id')[0]
except IndexError:
example_id = utils.get_bytes_feature(example, 'example_id')[0].decode()

building_id = utils.get_bytes_feature(example, 'encoded_coordinates')[
0
].decode()
Expand Down Expand Up @@ -431,7 +436,7 @@ def examples_to_csv(
| 'reshuffle_for_output' >> beam.Reshuffle()
| 'examples_to_rows'
>> beam.Map(
_example_to_row,
example_to_row,
threshold=threshold,
high_precision_threshold=high_precision_threshold,
high_recall_threshold=high_recall_threshold,
Expand Down
4 changes: 2 additions & 2 deletions src/skai/model/inference_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -221,13 +221,13 @@ def test_tf2_model_prediction_no_small_images(self):

def test_example_to_row(self):
example = _create_test_example(224, False, True, 0.7)
row = inference_lib._example_to_row(example, 0.5, 0.75, 0.25)
row = inference_lib.example_to_row(example, 0.5, 0.75, 0.25)
self.assertTrue(row.damaged)
self.assertFalse(row.damaged_high_precision)
self.assertTrue(row.damaged_high_recall)

low_score_example = _create_test_example(224, False, True, 0.1)
row = inference_lib._example_to_row(low_score_example, 0.5, 0.75, 0.25)
row = inference_lib.example_to_row(low_score_example, 0.5, 0.75, 0.25)
self.assertFalse(row.damaged)
self.assertFalse(row.damaged_high_precision)
self.assertFalse(row.damaged_high_recall)
Expand Down