4-Classification/4-Applied/solution/index.html - main - githubmirror/ML-For-Beginners

4-Classification/4-Applied/solution/index.html
97 строк3 KB
Avarayr
Fix and refactor Applied Classification README (#498)
02 янв 2022, 02:46
02 янв 2022, 02:46065cfe9
<!DOCTYPE html>
<html>
    <header>
        <title>Cuisine Matcher</title>
    </header>
    <body>
        <h1>Check your refrigerator. What can you create?</h1>
        <div id="wrapper">
            <div class="boxCont">
                <input type="checkbox" value="4" class="checkbox">
                <label>apple</label>
            </div>
        
            <div class="boxCont">
                <input type="checkbox" value="247" class="checkbox">
                <label>pear</label>
            </div>
        
            <div class="boxCont">
                <input type="checkbox" value="77" class="checkbox">
                <label>cherry</label>
            </div>

            <div class="boxCont">
                <input type="checkbox" value="126" class="checkbox">
                <label>fenugreek</label>
            </div>

            <div class="boxCont">
                <input type="checkbox" value="302" class="checkbox">
                <label>sake</label>
            </div>

            <div class="boxCont">
                <input type="checkbox" value="327" class="checkbox">
                <label>soy sauce</label>
            </div>

            <div class="boxCont">
                <input type="checkbox" value="112" class="checkbox">
                <label>cumin</label>
            </div>
        </div>
        <div style="padding-top:10px">
            <button onClick="startInference()">What kind of cuisine can you make?</button>
        </div>      
        <!-- import ONNXRuntime Web from CDN -->
        <script src="https://cdn.jsdelivr.net/npm/onnxruntime-web@1.9.0/dist/ort.min.js"></script>
        <script>
        const ingredients = Array(380).fill(0);
        
        const checks = [...document.querySelectorAll('.checkbox')];
        
        checks.forEach(check => {
            check.addEventListener('change', function() {
                // toggle the state of the ingredient
                // based on the checkbox's value (1 or 0)
                ingredients[check.value] = check.checked ? 1 : 0;
            });
        });

        function testCheckboxes() {
            // validate if at least one checkbox is checked
            return checks.some(check => check.checked);
        }

        async function startInference() {

            let atLeastOneChecked = testCheckboxes()

            if (!atLeastOneChecked) {
                alert('Please select at least one ingredient.');
                return;
            }
            try {
                // create a new session and load the model.
                
                const session = await ort.InferenceSession.create('./model.onnx');

                const input = new ort.Tensor(new Float32Array(ingredients), [1, 380]);
                const feeds = { float_input: input };

                // feed inputs and run
                const results = await session.run(feeds);

                // read from results
                alert('You can enjoy ' + results.label.data[0] + ' cuisine today!')

            } catch (e) {
                console.log(`failed to inference ONNX model`);
                console.error(e);
            }
        }
               
    </script>
    </body>
</html>