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| 1 | +{ |
| 2 | + "title": "Image Classification", |
| 3 | + "description": "This video covers image classification in ml5.js 1.0. I demonstrate both the default MobileNet model as well as how to train your own classifier with transfer leraning and teachable machine.", |
| 4 | + "videoId": "pbjR20eTLVs", |
| 5 | + "date": "2024-10-06", |
| 6 | + "languages": ["ml5.js", "JavaScript"], |
| 7 | + "topics": ["machine learning (ML)", "webcam", "image classification", "ml5.js", "MobileNet"], |
| 8 | + "canContribute": true, |
| 9 | + "timestamps": [ |
| 10 | + { "time": "0:00", "title": "Introduction" }, |
| 11 | + { "time": "2:30", "title": "What is MobileNet?" }, |
| 12 | + { "time": "4:53", "title": "What is ImageNet?" }, |
| 13 | + { "time": "10:32", "title": "ml5.js Classifier Code!" }, |
| 14 | + { "time": "21:19", "title": "Incorporating Live Video" }, |
| 15 | + { "time": "24:51", "title": "Training your own model" } |
| 16 | + ], |
| 17 | + "codeExamples": [ |
| 18 | + { |
| 19 | + "title": "Image Classification", |
| 20 | + "description": "Simple image classification using MobileNet.", |
| 21 | + "image": "simple.png", |
| 22 | + "urls": { "p5": "https://editor.p5js.org/codingtrain/sketches/A2W-0ayI5" } |
| 23 | + }, |
| 24 | + { |
| 25 | + "title": "Image Classification with Webcam", |
| 26 | + "description": "Continuous image classification with webcam feed.", |
| 27 | + "image": "webcam.png", |
| 28 | + "urls": { "p5": "https://editor.p5js.org/codingtrain/sketches/r9LjJqaw6" } |
| 29 | + }, |
| 30 | + { |
| 31 | + "title": "Image Classification - Drag and Drop", |
| 32 | + "description": "Drag and drop an image in the canvas to classify it.", |
| 33 | + "image": "drag.png", |
| 34 | + "urls": { "p5": "https://editor.p5js.org/codingtrain/sketches/v1sAlvSHR" } |
| 35 | + }, |
| 36 | + { |
| 37 | + "title": "Image Classification - Display label and confidence", |
| 38 | + "description": "Displays the label and confidence of the classification.", |
| 39 | + "image": "conf.png", |
| 40 | + "urls": { "p5": "https://editor.p5js.org/codingtrain/sketches/7zA6_MlIo" } |
| 41 | + }, |
| 42 | + { |
| 43 | + "title": "Image Classification - Tint", |
| 44 | + "description": "Tints the image with a color based on the confidence.", |
| 45 | + "image": "tint.png", |
| 46 | + "urls": { "p5": "https://editor.p5js.org/codingtrain/sketches/uHN5htRpC" } |
| 47 | + } |
| 48 | + ], |
| 49 | + "groupLinks": [ |
| 50 | + { |
| 51 | + "title": "References", |
| 52 | + "links": [ |
| 53 | + { |
| 54 | + "icon": "💻", |
| 55 | + "title": "ml5.js", |
| 56 | + "url": "https://ml5js.org/", |
| 57 | + "description": "ml5 page with documentation and supporting material." |
| 58 | + }, |
| 59 | + { |
| 60 | + "icon": "🏫", |
| 61 | + "title": "Introduction to Machine Learning for the Arts", |
| 62 | + "url": "https://github.com/ml5js/Intro-ML-Arts-IMA-F24", |
| 63 | + "description": "Syllabus for ITP IMA course on Machine Learning." |
| 64 | + }, |
| 65 | + { |
| 66 | + "icon": "📄", |
| 67 | + "title": "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications", |
| 68 | + "url": "https://arxiv.org/abs/1704.04861", |
| 69 | + "description": "Original paper on MobileNet." |
| 70 | + }, |
| 71 | + { |
| 72 | + "icon": "💻", |
| 73 | + "title": "Tensorflow.js port of MobileNet", |
| 74 | + "url": "https://github.com/tensorflow/tfjs-models/tree/master/mobilenet", |
| 75 | + "description": "Repository with the Tensorflow.js MobileNet model." |
| 76 | + }, |
| 77 | + { |
| 78 | + "icon": "💻", |
| 79 | + "title": "Image-Net", |
| 80 | + "url": "https://image-net.org/", |
| 81 | + "description": "ImageNet is an image database organized according to the WordNet hierarchy." |
| 82 | + }, |
| 83 | + { |
| 84 | + "icon": "🎤", |
| 85 | + "title": "How we teach computers to understand pictures", |
| 86 | + "url": "https://www.youtube.com/watch?v=40riCqvRoMs", |
| 87 | + "description": "Fei-Fei Li's TED talk on ImageNet." |
| 88 | + }, |
| 89 | + { |
| 90 | + "icon": "🌐", |
| 91 | + "title": "Excavating AI: The Politics of Images in Machine Learning Training Sets", |
| 92 | + "url": "https://excavating.ai/", |
| 93 | + "description": "About bias in ImageNet data set." |
| 94 | + }, |
| 95 | + { |
| 96 | + "icon": "🖼️", |
| 97 | + "title": "ml5 ImageClassifier", |
| 98 | + "url": "https://docs.ml5js.org/#/reference/image-classifier", |
| 99 | + "description": "ml5.js documentation on ImageClassifier." |
| 100 | + }, |
| 101 | + { |
| 102 | + "icon": "📱", |
| 103 | + "title": "Teachable Machine", |
| 104 | + "url": "https://teachablemachine.withgoogle.com/", |
| 105 | + "description": "Google's Teachable Machine." |
| 106 | + } |
| 107 | + ] |
| 108 | + } |
| 109 | + ], |
| 110 | + "credits": [ |
| 111 | + { "title": "Editing", "name": "Mathieu Blanchette" }, |
| 112 | + { "title": "Animations", "name": "Jason Heglund" } |
| 113 | + ] |
| 114 | +} |
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