How to use @tensorflow/tfjs-automl - 2 common examples
To help you get started, we’ve selected a few @tensorflow/tfjs-automl examples, based on popular ways it is used in public projects.
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tensorflow / tfjs / tfjs-automl / demo / img_classification / index.js View on Github 
async function run() {
const model = await automl.loadImageClassification(MODEL_URL);
const image = document.getElementById('daisy');
const predictions = await model.classify(image);
// Show the resulting object on the page.
const pre = document.createElement('pre');
pre.textContent = JSON.stringify(predictions, null, 2);
document.body.append(pre);
}async function run() {
const model = await automl.loadObjectDetection(MODEL_URL);
const image = document.getElementById('salad');
// These are the default options.
const options = {score: 0.5, iou: 0.5, topk: 20};
const predictions = await model.detect(image, options);
// Show the resulting object on the page.
const pre = document.createElement('pre');
pre.textContent = JSON.stringify(predictions, null, 2);
document.body.append(pre);
drawBoxes(predictions);
}@tensorflow/tfjs-automl
This packages provides a set of APIs to load and run models produced by AutoML Edge.
Apache-2.0
Latest version published 3 years ago