Searched refs:labelProbArray (Results 1 – 4 of 4) sorted by relevance
30 private byte[][] labelProbArray = null; field in ImageClassifierQuantizedMobileNet39 labelProbArray = new byte[1][getNumLabels()]; in ImageClassifierQuantizedMobileNet()80 return labelProbArray[0][labelIndex]; in getProbability()85 labelProbArray[0][labelIndex] = value.byteValue(); in setProbability()90 return (labelProbArray[0][labelIndex] & 0xff) / 255.0f; in getNormalizedProbability()95 tflite.run(imgData, labelProbArray); in runInference()
33 private float[][] labelProbArray = null; field in ImageClassifierFloatMobileNet42 labelProbArray = new float[1][getNumLabels()]; in ImageClassifierFloatMobileNet()82 return labelProbArray[0][labelIndex]; in getProbability()87 labelProbArray[0][labelIndex] = value.floatValue(); in setProbability()92 return labelProbArray[0][labelIndex]; in getNormalizedProbability()97 tflite.run(imgData, labelProbArray); in runInference()
38 private float[][] labelProbArray = null; field in ImageClassifierFloatInception47 labelProbArray = new float[1][getNumLabels()]; in ImageClassifierFloatInception()87 return labelProbArray[0][labelIndex]; in getProbability()92 labelProbArray[0][labelIndex] = value.floatValue(); in setProbability()103 tflite.run(imgData, labelProbArray); in runInference()
53 private float[][] labelProbArray = null; field in OvicClassifier107 labelProbArray = new float[1][labelList.size()]; in OvicClassifier()120 tflite.run(imgData, labelProbArray); in classifyByteBuffer()125 labelProbArray[0][i] = (inferenceOutputArray[0][i] & 0xff) / 255.0f; in classifyByteBuffer()136 return labelProbArray; in getlabelProbArray()198 sortedLabels.add(new AbstractMap.SimpleEntry<>(i, labelProbArray[0][i])); in computeTopKLabels()