MovementBasedSegmenter

Last updated 3 months ago
MovementBasedSegmenter's turn to locate and classify fruits.
Let's create an initialization function for the MBS watcher.
const initializeMBS = () => {};
Once again, retrieve the elements we'll be working with, along with the bounding rect of the element defining the watcher's contour.
const initializeMBS = () => {
  const mbsElement = document.getElementsByClassName('mbs')[0];
  const mbsBounds = mbsElement.getBoundingClientRect();
};
Just like NeuralNetworkClassifier (and all watchers, for that matter), MBS also has its classification trigger on the onClassification callback.
However, MovementBasedSegmenter has a secondary callback, triggered prior to onClassification, named onLocation. This is because MBS first determines the location of an object and then it classifies it. onLocation is generally used to create a loading animation for a located, not yet classified object.
For the sake of simplicity, we will focus on onClassification in this guide.
const initializeMBS = () => {
  const mbsElement = document.getElementsByClassName('mbs')[0];
  const mbsBounds = mbsElement.getBoundingClientRect();
​
  const onClassification = (classifiedObjects) => classifiedObjects.forEach((classifiedObject) => {
    handleObjectClassified(classifiedObject, '#FFFFFF');
  });
​
  const onLocation = (locatedObjects) => {
    // This step fires before onClassification!
    console.log(locatedObjects);
  };
​
  const mbsFruitsWatcher = {
    name: 'MovementBasedSegmenter',
    shape: lampix.helpers.rectangle(
      mbsBounds.left,
      mbsBounds.top,
      mbsBounds.width,
      mbsBounds.height
    ),
    params: {
      neural_network_name: 'fruits'
    },
    onLocation,
    onClassification
  };
};
Let's also add the utility mentioned above to add DOM elements for each classified object (remember to import it):
// handleObjectClassified.js
const handleObjectClassified = (obj, color) => {
  const el = document.createElement('div');
  el.classList.add('mbs-object');
  el.style.borderColor = color;
  el.style.left = `${obj.centerPoint.posX - 25}px`;
  el.style.top = `${obj.centerPoint.posY - 25}px`;
  el.textContent = obj.classTag;
​
  document.body.appendChild(el);
};
​
export default handleObjectClassified;
All that's left is telling Lampix about this watcher too, by adding the following to the end of the initializeMBS function.
  // ...
  lampix.watchers.add(mbsFruitsWatcher);
Now, initializeMBS should look like this:
const initializeMBS = () => {
  const mbsElement = document.getElementsByClassName('mbs')[0];
  const mbsBounds = mbsElement.getBoundingClientRect();
​
  const onClassification = (classifiedObjects) => classifiedObjects.forEach((classifiedObject) => {
    handleObjectClassified(classifiedObject, '#FFFFFF');
  });
​
  const onLocation = (locatedObjects) => {
    // This step fires before onClassification!
    console.log(locatedObjects);
  };
​
  const mbsFruitsWatcher = {
    name: 'MovementBasedSegmenter',
    shape: lampix.helpers.rectangle(
      mbsBounds.left,
      mbsBounds.top,
      mbsBounds.width,
      mbsBounds.height
    ),
    params: {
      neural_network_name: 'fruits'
    },
    onLocation,
    onClassification
  };
​
  lampix.watchers.add(mbsFruitsWatcher);
};
NeuralNetworkClassifier
Final Step