Tensor outputTensor = mModule.forward(om(inputTensor)).toTensor()Īfter that, the code processes the output, finding classes with the highest scores. The module has a get_classes method that returns List, which can be called using method nMethod(methodName): Result class names are packaged inside the TorchScript model and initialized just after initial module initialization. The logic happens in TextClassificattionActivity. Language Processing ExampleĪnother example is natural language processing, based on an LSTM model, trained on a reddit comments dataset. It uses the aforementioned TensorImageUtils.imageYUV420CenterCropToFloat32Tensor method to convert in YUV420 format to input tensor.Īfter getting predicted scores from the model it finds top K classes with the highest scores and shows on the UI. Where the analyzeImage method process the camera output,. setImageReaderMode(_LATEST_IMAGE)įinal ImageAnalysis imageAnalysis = new ImageAnalysis(imageAnalysisConfig) ĬameraX.bindToLifecycle(this, preview, imageAnalysis) tOnPreviewOutputUpdateListener(output -> tSurfaceTexture(output.getSurfaceTexture())) įinal ImageAnalysisConfig imageAnalysisConfig = Final PreviewConfig previewConfig = new PreviewConfig.Builder().build() įinal Preview preview = new Preview(previewConfig)

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