Added a test for the canned classification of the gesture victory
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@ -53,7 +53,9 @@ _NO_HANDS_IMAGE = 'cats_and_dogs.jpg'
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_TWO_HANDS_IMAGE = 'right_hands.jpg'
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_FIST_IMAGE = 'fist.jpg'
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_FIST_LANDMARKS = 'fist_landmarks.pbtxt'
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_FIST_LABEL = 'Closed_Fist'
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_VICTORY_IMAGE = 'victory.jpg'
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_VICTORY_LANDMARKS = 'victory_landmarks.pbtxt'
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_VICTORY_LABEL = 'Victory'
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_THUMB_UP_IMAGE = 'thumb_up.jpg'
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_THUMB_UP_LANDMARKS = 'thumb_up_landmarks.pbtxt'
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_THUMB_UP_LABEL = 'Thumb_Up'
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@ -276,6 +278,22 @@ class GestureRecognizerTest(parameterized.TestCase):
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self._assert_actual_result_approximately_matches_expected_result(
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recognition_result, expected_recognition_result)
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def test_recognize_succeeds_with_canned_gesture_victory(self):
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# Creates gesture recognizer.
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base_options = _BaseOptions(model_asset_path=self.model_path)
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options = _GestureRecognizerOptions(base_options=base_options, num_hands=1)
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with _GestureRecognizer.create_from_options(options) as recognizer:
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# Load the fist image.
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test_image = _Image.create_from_file(
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test_utils.get_test_data_path(_VICTORY_IMAGE))
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# Performs hand gesture recognition on the input.
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recognition_result = recognizer.recognize(test_image)
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expected_recognition_result = _get_expected_gesture_recognition_result(
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_VICTORY_LANDMARKS, _VICTORY_LABEL)
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# Comparing results.
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self._assert_actual_result_approximately_matches_expected_result(
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recognition_result, expected_recognition_result)
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def test_recognize_succeeds_with_custom_gesture_fist(self):
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# Creates gesture recognizer.
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model_path = test_utils.get_test_data_path(
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