diff --git a/mediapipe/tasks/python/test/vision/image_classification_test.py b/mediapipe/tasks/python/test/vision/image_classification_test.py index 51dcb1adf..0d7f9e7f0 100644 --- a/mediapipe/tasks/python/test/vision/image_classification_test.py +++ b/mediapipe/tasks/python/test/vision/image_classification_test.py @@ -92,36 +92,6 @@ class ImageClassifierTest(parameterized.TestCase): test_util.get_test_data_path(_IMAGE_FILE)) self.model_path = test_util.get_test_data_path(_MODEL_FILE) - def test_create_from_file_succeeds_with_valid_model_path(self): - # Creates with default option and valid model file successfully. - with _ImageClassifier.create_from_model_path(self.model_path) as classifier: - self.assertIsInstance(classifier, _ImageClassifier) - - def test_create_from_options_succeeds_with_valid_model_path(self): - # Creates with options containing model file successfully. - base_options = _BaseOptions(file_name=self.model_path) - options = _ImageClassifierOptions(base_options=base_options) - with _ImageClassifier.create_from_options(options) as classifier: - self.assertIsInstance(classifier, _ImageClassifier) - - def test_create_from_options_fails_with_invalid_model_path(self): - # Invalid empty model path. - with self.assertRaisesRegex( - ValueError, - r"ExternalFile must specify at least one of 'file_content', " - r"'file_name' or 'file_descriptor_meta'."): - base_options = _BaseOptions(file_name='') - options = _ImageClassifierOptions(base_options=base_options) - _ImageClassifier.create_from_options(options) - - def test_create_from_options_succeeds_with_valid_model_content(self): - # Creates with options containing model content successfully. - with open(self.model_path, 'rb') as f: - base_options = _BaseOptions(file_content=f.read()) - options = _ImageClassifierOptions(base_options=base_options) - classifier = _ImageClassifier.create_from_options(options) - self.assertIsInstance(classifier, _ImageClassifier) - @parameterized.parameters( (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) @@ -151,141 +121,6 @@ class ImageClassifierTest(parameterized.TestCase): # a context. classifier.close() - @parameterized.parameters( - (ModelFileType.FILE_NAME, 4, _EXPECTED_CLASSIFICATION_RESULT), - (ModelFileType.FILE_CONTENT, 4, _EXPECTED_CLASSIFICATION_RESULT)) - def test_classify_in_context(self, model_file_type, max_results, - expected_classification_result): - if model_file_type is ModelFileType.FILE_NAME: - base_options = _BaseOptions(file_name=self.model_path) - elif model_file_type is ModelFileType.FILE_CONTENT: - with open(self.model_path, 'rb') as f: - model_content = f.read() - base_options = _BaseOptions(file_content=model_content) - else: - # Should never happen - raise ValueError('model_file_type is invalid.') - - classifier_options = _ClassifierOptions(max_results=max_results) - options = _ImageClassifierOptions( - base_options=base_options, classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs object detection on the input. - image_result = classifier.classify(self.test_image) - # Comparing results. - self.assertEqual(image_result, expected_classification_result) - - def test_score_threshold_option(self): - classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - score = entry.categories[0].score - self.assertGreaterEqual( - score, _SCORE_THRESHOLD, - f'Classification with score lower than threshold found. ' - f'{classification}') - - def test_max_results_option(self): - classifier_options = _ClassifierOptions(score_threshold=_SCORE_THRESHOLD) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - categories = image_result.classifications[0].entries[0].categories - - self.assertLessEqual( - len(categories), _MAX_RESULTS, 'Too many results returned.') - - def test_allow_list_option(self): - classifier_options = _ClassifierOptions(category_allowlist=_ALLOW_LIST) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - label = entry.categories[0].category_name - self.assertIn(label, _ALLOW_LIST, - f'Label {label} found but not in label allow list') - - def test_deny_list_option(self): - classifier_options = _ClassifierOptions(category_denylist=_DENY_LIST) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - classifications = image_result.classifications - - for classification in classifications: - for entry in classification.entries: - label = entry.categories[0].category_name - self.assertNotIn(label, _DENY_LIST, - f'Label {label} found but in deny list.') - - def test_combined_allowlist_and_denylist(self): - # Fails with combined allowlist and denylist - with self.assertRaisesRegex( - ValueError, - r'`category_allowlist` and `category_denylist` are mutually ' - r'exclusive options.'): - classifier_options = _ClassifierOptions(category_allowlist=['foo'], - category_denylist=['bar']) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - - def test_empty_classification_outputs(self): - classifier_options = _ClassifierOptions(score_threshold=1) - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - classifier_options=classifier_options) - with _ImageClassifier.create_from_options(options) as classifier: - # Performs image classification on the input. - image_result = classifier.classify(self.test_image) - self.assertEmpty(image_result.classifications[0].entries[0].categories) - - def test_missing_result_callback(self): - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - running_mode=_RUNNING_MODE.LIVE_STREAM) - with self.assertRaisesRegex(ValueError, - r'result callback must be provided'): - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - - @parameterized.parameters((_RUNNING_MODE.IMAGE), (_RUNNING_MODE.VIDEO)) - def test_illegal_result_callback(self, running_mode): - - def pass_through(unused_result: _ClassificationResult): - pass - - options = _ImageClassifierOptions( - base_options=_BaseOptions(file_name=self.model_path), - running_mode=running_mode, - result_callback=pass_through) - with self.assertRaisesRegex(ValueError, - r'result callback should not be provided'): - with _ImageClassifier.create_from_options(options) as unused_classifier: - pass - if __name__ == '__main__': absltest.main()