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The loadModel() function initializes the TensorFlow.js model by loading it from the model.json file. This function must be called before performing any predictions.

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Function signature

async function loadModel()
This is an asynchronous function that returns a Promise. The model is loaded from cnn_model/model.json and stored in the global model variable.

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Parameters

This function takes no parameters.

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Return value

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model
tf.LayersModel
Returns a Promise that resolves when the model is successfully loaded. The loaded model is stored in the global model variable.

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How it works

The function performs the following steps:
  1. Logs “Loading Model” to the console
  2. Loads the TensorFlow.js model from cnn_model/model.json using tf.loadLayersModel()
  3. Logs “Loaded Model” to the console
  4. Updates the UI to indicate the model has loaded
  5. Hides the loading progress bar

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Code example

// Load the model when the page initializes
loadModel();

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Implementation

Here’s the complete implementation from the source code: 
async function loadModel(){
    console.log("Loading Model")
    model = await tf.loadLayersModel('cnn_model/model.json')
    console.log("Loaded Model")

    loadingmodel.innerHTML = "Loaded ML Model"
    progressbar.style.display = "none"
}

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Usage in HTML

The function is automatically called when the page loads: 
<script>
    loadModel()
</script>

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UI integration

The function updates two HTML elements:
  • loadingmodel - Text element that displays “Loaded ML Model” when complete
  • progressbar - Progress indicator that is hidden after loading
Ensure the model file exists at cnn_model/model.json before calling this function. The model file should be in the same directory structure as your HTML file.

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Best practices

  • Call this function once when your application initializes
  • Wait for the model to load before enabling prediction functionality
  • The global model variable must be initialized before calling loadModel()
var model = null

// Then call loadModel()
loadModel()

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