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Jeya Balaji Balasubramanian
AI Researcher in Medicine. All opinions are my own.
Public
Edited
Nov 8, 2022
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Artificial Intelligence
Interactively Assessing Disentanglement in GANsAnalyzing the Design Space for Visualizing Neural Attention in Text ClassificationTensorsImage tensorsVisualization in Deep LearningInteractive Convolutional Neural NetworkMachine Learning in JS with TensorFlow.js (Part I)How to visualize timeline of a Wiki article?Simulation ResultsMachine learning in the browserRecommender systemsPython in Observable through PyodideArtificial intelligence systems Timelinebackground-position ScrubberDrawings to HumansahajBERT - Bubbles chartPretrained models (image classification)
Advanced pretrained models (object detection)
Robotics Perturbation: Broken Joint (Rotation)Multi-Agent Evaluation: Object Counting
Also listed in…
TensorFlow.js
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ssdMobileNetPath = "https://tfhub.dev/tensorflow/tfjs-model/ssd_mobilenet_v2/1/default/1"
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ssdMobileNet = tf.loadGraphModel(ssdMobileNetPath, {fromTFHub: true})
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ssdMobileNet.inputs[0].shape
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{
let count = 0;
cocoClasses.forEach(element => {
if (element === "-") {
count++;
}
});
return count;
}
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img = new Promise((resolve, reject) => {
const img = htl.html`<img/>`;
img.src = imgUrl;
img.crossOrigin = 'anonymous';
img.onload = () => resolve(img);
img.onerror = reject;
})
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imageTensor = tf.browser.fromPixels(img)
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imageTensor.shape
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ssdMobileNet.predict(imageTensor.expandDims()) // Oops!
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detections = ssdMobileNet.executeAsync(imageTensor.expandDims())
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detections[0].shape
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detections[1].shape
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boxes = detections[1].squeeze().array()
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detectionsTopClass = detections[0].topk()
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topIndices = detectionsTopClass.indices.data()
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topValues = detectionsTopClass.values.data()
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nmsSelections = tf.image.nonMaxSuppressionWithScoreAsync(
detections[1].squeeze(), // box coordinates
detectionsTopClass.values.squeeze(), // box object probabilities
detectionConstraintsNms.maxBoxes,
detectionConstraintsNms.iouThreshold,
detectionConstraintsNms.confidenceThreshold,
detectionConstraintsNms.softNMS
)
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selections = nmsSelections.selectedIndices.data()
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webcamContainer = createWebcamContainer()
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detectObjectsInWebcam(activateWebcam, webcamContainer, ssdMobileNet, cocoClasses, detectionConstraintsVideo)
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tf = require('@tensorflow/tfjs@4.0.0/dist/tf.min.js')
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