Created
May 22, 2019 12:49
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Ml5.js demo video classification using webcam input.
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| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <!-- title of the page --> | |
| <title>image_classification</title> | |
| <!-- load processing library--> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/p5.min.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.dom.min.js"></script> | |
| <!-- load ml5.js --> | |
| <script src="https://unpkg.com/ml5@0.1.1/dist/ml5.min.js"></script> | |
| <!-- load index.js --> | |
| <script src="index.js"></script> | |
| </head> | |
| <body> | |
| <!-- this is where the video will be shown --> | |
| <video id="video"></video> | |
| </body> | |
| </html> |
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| let mobilenet; | |
| let video; | |
| let label = ''; | |
| // when model is ready make predictions | |
| function modelReady() { | |
| console.log('Model is ready!!!'); | |
| mobilenet.predict(gotResults); | |
| } | |
| function gotResults(error, results) { | |
| if (error) { | |
| console.error(error); | |
| } else { | |
| label = results[0].className; | |
| // loop the inference by calling itself | |
| mobilenet.predict(gotResults); | |
| } | |
| } | |
| // setup function | |
| function setup() { | |
| createCanvas(640, 550); | |
| // ml5 to create video capture | |
| video = createCapture(VIDEO); | |
| video.hide(); | |
| background(0); | |
| // load the MobileNet and apply it on video feed | |
| mobilenet = ml5.imageClassifier('MobileNet', video, modelReady); | |
| } | |
| function draw() { | |
| background(0); | |
| // show video | |
| image(video, 0, 0); | |
| fill(255); | |
| textSize(32); | |
| // show prediction label | |
| text(label, 10, height - 20); | |
| } |
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