WEBVTT

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Welcome back.

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We created those functions build analyzer load labels and load model.

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Now let's make use of those functions.

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Return back to the initialize function.

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Here the model byte buffer equals to load model.

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And we pass the model file name as a parameter.

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Then labels equals to load labels and pass the label file name.

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By the way those variables we create them in the first, uh, first video of this ViewModel class.

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Okay.

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Then we need the interpreter equals to the interpreter model byte buffer and pass null.

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Here we need the byte buffer and the options null.

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This is what we created before interpreter.

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The interpreter equals to the class interpreter which is from TensorFlow Lite interpreter class.

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And we pass the byte buffer that we created before state dot value equals to the response dot success.

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Make it as success and return unit.

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Pass the unit as parameter.

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We are updating the state here at the first uh the first step we are loading the The response and make

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the response as loading so the state equals to loading.

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When the load is finished, set the state as success val input tensor equals to interpreter dot get

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tensor.

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Input tensor equals to zero.

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Then we can make a log dot v to get the parameters and the shapes of the tensor.

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So the input tensor shape and the input tensor data type okay.

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This is good.

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And this is healthy because you need to check always for the correct shapes of your model.

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Close the try and catch by making the exception here and fail to initialize.

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Set the state to failure.

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So, um, this is what I'm gonna try to show you guys.

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When you start loading the model, set the state to loading.

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When you finished loading, set the state as success, and if you failed, go and set the state as failed.

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Okay.

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This is the initialize function of this.

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If this data the view model.

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And this is very important and we are following the clean architecture, the MVVM model architecture

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model for this application.