Fixes the typos in tasks internal files.
PiperOrigin-RevId: 526063515
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@ -47,11 +47,11 @@ class AudioRecord(object):
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raise sd_error
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if channels <= 0:
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raise ValueError('channels must be postive.')
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raise ValueError('channels must be positive.')
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if sampling_rate <= 0:
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raise ValueError('sampling_rate must be postive.')
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raise ValueError('sampling_rate must be positive.')
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if buffer_size <= 0:
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raise ValueError('buffer_size must be postive.')
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raise ValueError('buffer_size must be positive.')
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self._audio_buffer = []
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self._buffer_size = buffer_size
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@ -47,7 +47,7 @@ _TEST_DATA_DIR = 'mediapipe/tasks/testdata/audio'
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_TWO_HEADS_WAV_16K_MONO = 'two_heads_16000_hz_mono.wav'
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_TWO_HEADS_WAV_44K_MONO = 'two_heads_44100_hz_mono.wav'
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_YAMNET_NUM_OF_SAMPLES = 15600
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_MILLSECONDS_PER_SECOND = 1000
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_MILLISECONDS_PER_SECOND = 1000
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class AudioClassifierTest(parameterized.TestCase):
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@ -75,7 +75,7 @@ class AudioClassifierTest(parameterized.TestCase):
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end = min(start + (int)(step_size), len(buffer))
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audio_data_list.append((_AudioData.create_from_array(
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buffer[start:end].astype(float) / np.iinfo(np.int16).max,
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sample_rate), (int)(start / sample_rate * _MILLSECONDS_PER_SECOND)))
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sample_rate), (int)(start / sample_rate * _MILLISECONDS_PER_SECOND)))
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start = end
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return audio_data_list
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@ -45,7 +45,7 @@ _SPEECH_WAV_48K_MONO = 'speech_48000_hz_mono.wav'
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_TWO_HEADS_WAV_16K_MONO = 'two_heads_16000_hz_mono.wav'
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_TEST_DATA_DIR = 'mediapipe/tasks/testdata/audio'
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_YAMNET_NUM_OF_SAMPLES = 15600
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_MILLSECONDS_PER_SECOND = 1000
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_MILLISECONDS_PER_SECOND = 1000
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# Tolerance for embedding vector coordinate values.
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_EPSILON = 3e-6
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@ -78,7 +78,7 @@ class AudioEmbedderTest(parameterized.TestCase):
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end = min(start + (int)(step_size), len(buffer))
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audio_data_list.append((_AudioData.create_from_array(
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buffer[start:end].astype(float) / np.iinfo(np.int16).max,
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sample_rate), (int)(start / sample_rate * _MILLSECONDS_PER_SECOND)))
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sample_rate), (int)(start / sample_rate * _MILLISECONDS_PER_SECOND)))
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start = end
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return audio_data_list
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@ -188,7 +188,7 @@ class BaseVisionTaskApi(object):
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# For 90° and 270° rotations, we need to swap width and height.
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# This is due to the internal behavior of ImageToTensorCalculator, which:
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# - first denormalizes the provided rect by multiplying the rect width or
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# height by the image width or height, repectively.
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# height by the image width or height, respectively.
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# - then rotates this by denormalized rect by the provided rotation, and
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# uses this for cropping,
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# - then finally rotates this back.
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@ -186,7 +186,7 @@ export abstract class VisionTaskRunner extends TaskRunner {
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// For 90° and 270° rotations, we need to swap width and height.
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// This is due to the internal behavior of ImageToTensorCalculator, which:
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// - first denormalizes the provided rect by multiplying the rect width or
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// height by the image width or height, repectively.
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// height by the image width or height, respectively.
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// - then rotates this by denormalized rect by the provided rotation, and
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// uses this for cropping,
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// - then finally rotates this back.
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@ -117,12 +117,12 @@ describe('ImageClassifier', () => {
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classifcations.setHeadIndex(1);
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classifcations.setHeadName('headName');
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const classificationList = new ClassificationList();
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const clasification = new Classification();
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clasification.setIndex(1);
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clasification.setScore(0.2);
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clasification.setDisplayName('displayName');
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clasification.setLabel('categoryName');
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classificationList.addClassification(clasification);
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const classification = new Classification();
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classification.setIndex(1);
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classification.setScore(0.2);
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classification.setDisplayName('displayName');
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classification.setLabel('categoryName');
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classificationList.addClassification(classification);
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classifcations.setClassificationList(classificationList);
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classificationResult.addClassifications(classifcations);
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