NeuralNetworkClassifier: Buttons
The easiest way
npm install @lampix/core @lampix/dom
import lampixDOM from '@lampix/dom';
// Behind the scenes, this will draw a button with a scaling animation
const x = window.innerWidth / 2;
const y = window.innerHeight / 2;
const callback = () => {
console.log('Button activated!');
};
// Minimum necessary
lampixDOM.buttons.generate(x - 100, y, callback)
.then((firstButton) => console.log('Button ready to be used'));
// A little configuration goes a long way
const options = {
label: 'Generic button',
labelPosition: 'top',
scaleFactor: 1.2, // base animation is a simple scale animation to provide action feedback
animationDuration: 350 // enables a circle-filling style loader and syncs the scaling animation to this value as well
};
lampixDOM.buttons.generate(x + 100, y, callback, options)
.then((secondButton) => console.log('Another button ready to be used'));
Hooking up your own button using the button preset
npm install @lampix/core
import lampix from '@lampix/core';
// Assuming there is an element with an ID of 'superb-btn`
const btn = document.getElementById('superb-btn');
const btnBounds = btn.getBoundingClientRect();
const x = btnBounds.left;
const y = btnBounds.top;
const callback = () => {
console.log('Button activated!');
};
// Use the button preset
// This automatically takes care of creating the proper watcher data structure for you
// It also specifies the correct watcher to load and the correct neural network to use with it
const buttonWatcher = lampix.presets.button(x, y, callback);
// Remember: .watchers.add always returns an array of registered watchers
// of the same length as the number of arguments passed to it
lampix.watchers.add(buttonWatcher)
.then((listOfButtons) => {
console.log('Button ready to be used');
console.log(listOfButtons[0]);
});
Hooking up your own button creating the watcher data structure yourself
import lampix from '@lampix/core';
// Assuming there is an element with an ID of 'superb-btn`
const btn = document.getElementById('superb-btn');
const btnBounds = btn.getBoundingClientRect();
const x = btnBounds.left;
const y = btnBounds.top;
const callback = () => {
console.log('Button activated!');
};
const buttonWatcher = {
name: 'NeuralNetworkClassifier',
shape: {
type: 'rectangle',
data: {
posX: x,
posY: y,
width: 50,
height: 50
}
},
onClassification: callback,
params: {
neural_network_name: 'fingers'
}
};
// Remember: .watchers.add always returns an array of registered watchers
// of the same length as the number of arguments passed to it
lampix.watchers.add(buttonWatcher)
.then((listOfButtons) => {
console.log('Button ready to be used');
console.log(listOfButtons[0]);
});
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