Added a test for min_gesture_confidence
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					@ -224,6 +224,24 @@ class GestureRecognizerTest(parameterized.TestCase):
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      self._assert_actual_result_approximately_matches_expected_result(
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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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					        recognition_result, expected_recognition_result)
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					  def test_recognize_succeeds_with_min_gesture_confidence(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,
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					                                        min_gesture_confidence=2)
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					    with _GestureRecognizer.create_from_options(options) as recognizer:
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					      # Performs hand gesture recognition on the input.
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					      recognition_result = recognizer.recognize(self.test_image)
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					      expected_result = _get_expected_gesture_recognition_result(
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					          _THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX)
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					      # Only contains one top scoring gesture.
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					      self.assertLen(recognition_result.gestures[0].classifications, 1)
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					      # Actual gesture with top score matches expected gesture.
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					      actual_top_gesture = recognition_result.gestures[0].classifications[0]
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					      expected_top_gesture = expected_result.gestures[0].classifications[0]
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					      self.assertEqual(actual_top_gesture.index, expected_top_gesture.index)
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					      self.assertEqual(actual_top_gesture.label, expected_top_gesture.label)
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  def test_recognize_succeeds_with_num_hands(self):
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					  def test_recognize_succeeds_with_num_hands(self):
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    # Creates gesture recognizer.
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					    # Creates gesture recognizer.
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    base_options = _BaseOptions(model_asset_path=self.model_path)
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					    base_options = _BaseOptions(model_asset_path=self.model_path)
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					@ -30,7 +30,7 @@ class ImageProcessingOptions:
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  Attributes:
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					  Attributes:
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    region_of_interest: The optional region-of-interest to crop from the image.
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					    region_of_interest: The optional region-of-interest to crop from the image.
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      If not specified, the full image is used. Coordinates must be in [0,1]
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					      If not specified, the full image is used. Coordinates must be in [0,1]
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      with 'left' < 'right' and 'top' < bottom.
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					      with 'x_center' < 'width' and 'y_center' < height.
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    rotation_degress: The rotation to apply to the image (or cropped
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					    rotation_degress: The rotation to apply to the image (or cropped
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      region-of-interest), in degrees clockwise. The rotation must be a
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					      region-of-interest), in degrees clockwise. The rotation must be a
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      multiple (positive or negative) of 90°.
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					      multiple (positive or negative) of 90°.
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					@ -118,10 +118,10 @@ class GestureRecognizerOptions:
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  base_options: _BaseOptions
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					  base_options: _BaseOptions
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  running_mode: _RunningMode = _RunningMode.IMAGE
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					  running_mode: _RunningMode = _RunningMode.IMAGE
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  num_hands: Optional[int] = 1
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					  num_hands: Optional[int] = 1
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  min_hand_detection_confidence: Optional[int] = 0.5
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					  min_hand_detection_confidence: Optional[float] = 0.5
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  min_hand_presence_confidence: Optional[int] = 0.5
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					  min_hand_presence_confidence: Optional[float] = 0.5
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  min_tracking_confidence: Optional[int] = 0.5
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					  min_tracking_confidence: Optional[float] = 0.5
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  min_gesture_confidence: Optional[int] = -1
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					  min_gesture_confidence: Optional[float] = -1
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  result_callback: Optional[
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					  result_callback: Optional[
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      Callable[[GestureRecognitionResult, image_module.Image,
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					      Callable[[GestureRecognitionResult, image_module.Image,
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                int], None]] = None
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					                int], None]] = None
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