Created
May 22, 2019 12:49
-
-
Save mohdsanadzakirizvi/2c210c52e08bc3559716ff11d20e684e to your computer and use it in GitHub Desktop.
Ml5.js demo video classification using webcam input.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| <!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/[email protected]/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> |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 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); | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment