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ML-For-Beginners
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Fix and refactor Applied Classification README (#498) 

* Refactored the classify-4 README to use modern ES6 javascript syntax

* Fixed the nonworking onnxruntime version

* Applied the javascript refactoring to applied classify solution
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Avarayr 2022-01-01 15:46:51 -08:00 коммит произвёл GitHub
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60
4-Classification/4-Applied/README.md
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@ -219,57 +219,40 @@ You can use your model directly in a web app. This architecture also allows you
1. First, import the [Onnx Runtime](https://www.onnxruntime.ai/):
```html
<script src="https://cdn.jsdelivr.net/npm/onnxruntime-web@1.9.09/dist/ort.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/onnxruntime-web@1.9.0/dist/ort.min.js"></script>
```
> Onnx Runtime is used to enable running your Onnx models across a wide range of hardware platforms, including optimizations and an API to use.
1. Once the Runtime is in place, you can call it:
```javascript
```html
<script>
const ingredients = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
const ingredients = Array(380).fill(0);
const checks = [].slice.call(document.querySelectorAll('.checkbox'));
const checks = [...document.querySelectorAll('.checkbox')];
// use an async context to call onnxruntime functions.
function init() {
checks.forEach(function (checkbox, index) {
checkbox.onchange = function () {
if (this.checked) {
var index = checkbox.value;
if (index !== -1) {
ingredients[index] = 1;
}
console.log(ingredients)
}
else {
var index = checkbox.value;
if (index !== -1) {
ingredients[index] = 0;
}
console.log(ingredients)
}
}
})
}
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() {
for (var i = 0; i < checks.length; i++)
if (checks[i].type == "checkbox")
if (checks[i].checked)
return true;
return false;
// validate if at least one checkbox is checked
return checks.some(check => check.checked);
}
async function startInference() {
let checked = testCheckboxes()
let atLeastOneChecked = testCheckboxes()
if (checked) {
if (!atLeastOneChecked) {
alert('Please select at least one ingredient.');
return;
}
try {
// create a new session and load the model.
@ -279,19 +262,16 @@ You can use your model directly in a web app. This architecture also allows you
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: ${e}.`);
console.log(`failed to inference ONNX model`);
console.error(e);
}
}
else alert("Please check an ingredient")
}
init();
</script>
```

58
4-Classification/4-Applied/solution/index.html
Просмотреть файл

@ -47,49 +47,31 @@
<!-- 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 = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
const ingredients = Array(380).fill(0);
const checks = [].slice.call(document.querySelectorAll('.checkbox'));
const checks = [...document.querySelectorAll('.checkbox')];
// use an async context to call onnxruntime functions.
function init() {
checks.forEach(function (checkbox, index) {
checkbox.onchange = function () {
if (this.checked) {
var index = checkbox.value;
if (index !== -1) {
ingredients[index] = 1;
}
console.log(ingredients)
}
else {
var index = checkbox.value;
if (index !== -1) {
ingredients[index] = 0;
}
console.log(ingredients)
}
}
})
}
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() {
for (var i = 0; i < checks.length; i++)
if (checks[i].type == "checkbox")
if (checks[i].checked)
return true;
return false;
// validate if at least one checkbox is checked
return checks.some(check => check.checked);
}
async function startInference() {
let checked = testCheckboxes()
if (checked) {
let atLeastOneChecked = testCheckboxes()
if (!atLeastOneChecked) {
alert('Please select at least one ingredient.');
return;
}
try {
// create a new session and load the model.
@ -99,20 +81,16 @@
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: ${e}.`);
console.log(`failed to inference ONNX model`);
console.error(e);
}
}
else alert("Please check an ingredient")
}
init();
</script>
</body>