Stylistic tweaks to example codes

examples/bodyPose-blazePose-skeleton/sketch.js

@@ -26,15 +26,15 @@ function setup() {
 
   // Start detecting poses in the webcam video
   bodyPose.detectStart(video, gotPoses);
-  //get the skeleton connection information
+  // Get the skeleton connection information
   connections = bodyPose.getSkeleton();
 }
 
 function draw() {
   // Draw the webcam video
   image(video, 0, 0, width, height);
 
-  //draw the skeleton connections
+  // Draw the skeleton connections
   for (let i = 0; i < poses.length; i++) {
     let pose = poses[i];
     for (let j = 0; j < connections.length; j++) {

examples/bodyPose-skeleton/sketch.js

@@ -26,15 +26,15 @@ function setup() {
 
   // Start detecting poses in the webcam video
   bodyPose.detectStart(video, gotPoses);
-  //get the skeleton connection information
+  // Get the skeleton connection information
   connections = bodyPose.getSkeleton();
 }
 
 function draw() {
   // Draw the webcam video
   image(video, 0, 0, width, height);
 
-  //draw the skeleton connections
+  // Draw the skeleton connections
   for (let i = 0; i < poses.length; i++) {
     let pose = poses[i];
     for (let j = 0; j < connections.length; j++) {

examples/faceMesh-bounding-box/sketch.js

@@ -26,10 +26,10 @@ function setup() {
 }
 
 function draw() {
-  // draw the webcam video
+  // Draw the webcam video
   image(video, 0, 0, width, height);
 
-  // draw the faces' bounding boxes
+  // Draw the faces' bounding boxes
   for (let i = 0; i < faces.length; i++) {
     let face = faces[i];
     let x = face.box.xMin;
@@ -44,7 +44,7 @@ function draw() {
     rect(x, y, w, h);
     text(i, x, y - 10);
 
-    // draw the center of the face
+    // Draw the center of the face
     noStroke();
     fill(255, 0, 0);
     circle(centerX, centerY, 10);

examples/imageClassifier-single-image/sketch.js

@@ -27,9 +27,9 @@ function setup() {
   image(img, 0, 0, width, height);
 }
 
-// A function to run when we get any errors and the results
+// Callback function for when classification has finished
 function gotResult(results) {
-  // The results are in an array ordered by confidence, print in console
+  // The results are in an array ordered by confidence
   console.log(results);
 
   // Display the results on the canvas

examples/imageClassifier-teachable-machine/sketch.js

@@ -45,6 +45,6 @@ function draw() {
 
 // A function to run when we get the results
 function gotResult(results) {
-  // update label variable which is displayed on the canvas
+  // Update label variable which is displayed on the canvas
   label = results[0].label;
 }

examples/imageClassifier-webcam/sketch.js

@@ -31,17 +31,17 @@ function setup() {
 }
 
 function draw() {
-  //Each video frame is painted on the canvas
+  // Each video frame is painted on the canvas
   image(video, 0, 0);
 
-  //Printing class with the highest probability on the canvas
+  // Printing class with the highest probability on the canvas
   fill(255);
   textSize(32);
   text(label, 20, 50);
 }
 
-// A function to run when we get the results and any errors
+// Callback function for when classification has finished
 function gotResult(results) {
-  //update label variable which is displayed on the canvas
+  // Update label variable which is displayed on the canvas
   label = results[0].label;
 }

examples/sentiment/sketch.js

@@ -12,37 +12,37 @@ let inputBox;
 let sentimentResult;
 
 function preload() {
+  // Initialize the sentiment analysis model
   sentiment = ml5.sentiment("MovieReviews");
 }
 
 function setup() {
   noCanvas();
-  // initialize sentiment analysis model
 
-  // setup the html dom elements
+  // Setup the DOM elements
   inputBox = createInput("Today is the happiest day and is full of rainbows!");
   inputBox.attribute("size", "75");
   submitBtn = createButton("submit");
   sentimentResult = createP("Sentiment confidence:");
 
-  // predicting the sentiment when submit button is pressed
+  // Start predicting when the submit button is pressed
   submitBtn.mousePressed(getSentiment);
 }
 
 function getSentiment() {
-  // get the values from the input
+  // Use the value of the input box
   let text = inputBox.value();
 
-  // make the prediction
+  // Start making the prediction
   sentiment.predict(text, gotResult);
 }
 
 function gotResult(prediction) {
-  // display sentiment result on html page
+  // Display sentiment result via the DOM
   sentimentResult.html("Sentiment confidence: " + prediction.confidence);
 }
 
-// predicting the sentiment when 'Enter' key is pressed
+// Start predicting when the Enter key is pressed
 function keyPressed() {
   if (keyCode == ENTER) {
     getSentiment();