tm

im_det.js

// More API functions here:
// https://github.com/googlecreativelab/teachablemachine-community/tree/master/libraries/image

let model, webcam, labelContainer, maxPredictions;

// Load the image model and setup the webcam
async function init() {

    const URL = "https://teachablemachine.withgoogle.com/models/uSXPV8Y2/";
    const modelURL = URL + 'model.json';
    const metadataURL = URL + 'metadata.json';
    model = await tmImage.load(modelURL, metadataURL);

    // load the model, weights, and metadata
    // load files from a file picker or from local hard drive
    // Note: the pose library adds "tmImage" object to your window (window.tmImage)
    const uploadModel = document.getElementById('uploaded-model');
    const uploadWeights = document.getElementById('uploaded-weights');
    const uploadMetadata = document.getElementById('uploaded-metadata');
    //model = await tmImage.loadFromFiles(uploadModel.files[0], uploadWeights.files[0], uploadMetadata.files[0]);


    maxPredictions = model.getTotalClasses();

    // Convenience function to setup a webcam
    const flip = true; // whether to flip the webcam
    webcam = new tmImage.Webcam(400, 400, flip); // width, height, flip
    await webcam.setup(); // request access to the webcam
    await webcam.play();
    window.requestAnimationFrame(loop);

    // append elements to the DOM
    document.getElementById("webcam-container").appendChild(webcam.canvas);
    labelContainer = document.getElementById("label-container");
    for (let i = 0; i < maxPredictions; i++) { // and class labels
        labelContainer.appendChild(document.createElement("div"));
    }
}

async function loop() {
    webcam.update(); // update the webcam frame
    await predict();
    window.requestAnimationFrame(loop);
}

// run the webcam image through the image model
async function predict() {
    // predict can take in an image, video or canvas html element
    const prediction = await model.predict(webcam.canvas);
    for (let i = 0; i < maxPredictions; i++) {
        // show name with percentage of confidence prediction
        const classPrediction =
            prediction[i].className + ": " + (prediction[i].probability.toFixed(4) * 100).toFixed(2) + '%';
        labelContainer.childNodes[i].innerHTML = classPrediction;
    }
}