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Update ml5 glossary #84

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merged 8 commits into from
Jun 22, 2024
+143 −237
Merged

Update ml5 glossary #84

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fc32fbf
Update ml5-glossary.md
alanvww Jun 15, 2024
55d5d22
Merge branch 'ml5js:main' into alan-ml5glossary
alanvww Jun 17, 2024
f3a1ba8
Update ml5-glossary.md
alanvww Jun 17, 2024
65cb7e2
Merge remote-tracking branch 'upstream/main' into alan-ml5glossary
alanvww Jun 20, 2024
ea4b294
Removed `Promise`
alanvww Jun 20, 2024
9615257
Update ml5-glossary.md
alanvww Jun 20, 2024
144c681
Merge branch 'ml5js:main' into alan-ml5glossary
alanvww Jun 21, 2024
ec35177
Add Runtime section
alanvww Jun 22, 2024
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58 changes: 36 additions & 22 deletions docs/learning/ml5-glossary.md
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ const classifier = ml5.imageClassifier("MobileNet", (err, model) => {
});

// Make a prediction with the selected image and pass a callback function with two arguments
classifier.predict(image, (err, results) => {
classifier.classify(image, (err, results) => {
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// Check for errors. If no errors, then do something with the results
});
```
Expand Down Expand Up @@ -72,10 +72,17 @@ function gotResult(error, results) {
if (error) {
console.error(error);
} else {
// The results are in an array ordered by confidence.
// The results are in an array ordered by confidence, print in console
console.log(results);
createDiv(`Label: ${results[0].label}`);
createDiv(`Confidence: ${nf(results[0].confidence, 0, 2)}`);

// Display the results on the canvas
fill(255);
stroke(0);
textSize(18);
label = "Label: " + results[0].label;
confidence = "Confidence: " + nf(results[0].confidence, 0, 2);
text(label, 10, 360);
text(confidence, 10, 380);
}
}
```
Expand Down Expand Up @@ -116,14 +123,14 @@ for (let i = 0; i < poses.length; i++) {
let point = poses[i].pose.keypoints[k];

// get the position of each keypoint
let x = point.position.x;
let y = point.position.y;
let x = point.x;
let y = point.y;

// get the confidence score of each keypoint
let score = point.score;

// get the name of each keypoint
let partName = point.part;
let partName = point.name;

// draw an ellipse at each keypoint
fill(0, 255, 0);
Expand All @@ -145,14 +152,14 @@ for (let i = 0; i < poses.length; i++) {
let point = poses[i].pose.keypoints[k];

// get the position of each keypoint
let x = point.position.x;
let y = point.position.y;
let x = point.x;
let y = point.y;

// get the confidence score of each keypoint
let score = point.score;

// get the name of each keypoint
let partName = point.part;
let partName = point.name;

// only draw an ellipse at each keypoint if the confidence score is higher than 0.5
if (score > 0.5) {
Expand Down Expand Up @@ -681,7 +688,7 @@ With Promises, the image classification example can be used in the following way
// No callback needs to be passed to use Promises.
ml5
.imageClassifier("MobileNet")
.then((classifier) => classifier.predict(image))
.then((classifier) => classifier.classify(image))
.then((results) => {
// Do something with the results
});
Expand Down Expand Up @@ -872,7 +879,7 @@ const classifier = ml5.imageClassifier("MobileNet", (err, model) => {
});

// Make a prediction with the selected image and pass a callback function with two arguments
classifier.predict(image, (err, results) => {
classifier.classify(image, (err, results) => {
// Check for errors. If no errors, then do something with the results
});
```
Expand Down Expand Up @@ -963,7 +970,7 @@ With Promises, the image classification example can be used in the following way
// No callback needs to be passed to use Promises.
ml5
.imageClassifier("MobileNet")
.then((classifier) => classifier.predict(image))
.then((classifier) => classifier.classify(image))
.then((results) => {
// Do something with the results
});
Expand Down Expand Up @@ -1007,10 +1014,17 @@ function gotResult(error, results) {
if (error) {
console.error(error);
} else {
// The results are in an array ordered by confidence.
// The results are in an array ordered by confidence, print in console
console.log(results);
createDiv(`Label: ${results[0].label}`);
createDiv(`Confidence: ${nf(results[0].confidence, 0, 2)}`);

// Display the results on the canvas
fill(255);
stroke(0);
textSize(18);
label = "Label: " + results[0].label;
confidence = "Confidence: " + nf(results[0].confidence, 0, 2);
text(label, 10, 360);
text(confidence, 10, 380);
}
}
```
Expand Down Expand Up @@ -1051,14 +1065,14 @@ for (let i = 0; i < poses.length; i++) {
let point = poses[i].pose.keypoints[k];

// get the position of each keypoint
let x = point.position.x;
let y = point.position.y;
let x = point.x;
let y = point.y;

// get the confidence score of each keypoint
let score = point.score;

// get the name of each keypoint
let partName = point.part;
let partName = point.name;

// draw an ellipse at each keypoint
fill(0, 255, 0);
Expand All @@ -1080,14 +1094,14 @@ for (let i = 0; i < poses.length; i++) {
let point = poses[i].pose.keypoints[k];

// get the position of each keypoint
let x = point.position.x;
let y = point.position.y;
let x = point.x;
let y = point.y;

// get the confidence score of each keypoint
let score = point.score;

// get the name of each keypoint
let partName = point.part;
let partName = point.name;

// only draw an ellipse at each keypoint if the confidence score is higher than 0.5
if (score > 0.5) {
Expand Down