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chapter-10

Chapter 10 - AI in the Browser with TensorFlow.js and ml5.js

Note: All images in this directory, unless specified otherwise, are licensed under CC BY-NC 4.0.

Figure List

Figure number Description
10-1 The Bach music harmonizer doodle from Google
10-2 Screenshot of DeepTraffic training a car with reinforcement learning using ConvNetJS
10-3 Benchmarking data for ResNet-50 on different JavaScript machine learning libraries on CPU
10-4 Benchmarking data for ResNet-50 on different JavaScript machine learning libraries on GPU
10-5 A high-level overview of the TensorFlow.js and ml5.js ecosystem
10-6 Class prediction output in the browser
10-7 Training live in the browser with Teachable Machine
10-8 Predictions by our model on a webcam feed within a browser
10-9 GPU utilization shown in the Google Chrome profiler view
10-10 The top predicted classes with the probability of each class
10-11 Keypoints drawn using PoseNet on a picture of former President Obama in a snowball fight
10-12 Example of input and output pairs on pix2pix
10-13 A flowchart for a GAN
10-14 Sketch-to-image example
10-15 We can create colored blueprints (left) and pix2pix will convert them to realistic-looking human faces (right)
10-16 Training pairs for pix2pix: a B&W image and its original color image
10-17 Pix2Pix: Edges to Pikachu by Yining Shi, built on ml5.js
10-18 Inference time for MobileNetV1 in Chrome on different devices
10-19 Inference time in different browsers on iPhone X
10-20 Inference time in different browsers on an i7 @ 2.6 GHz macOS 10.14 machine
10-21 Control an orchestra by waving your arms on the Semi-Conductor demonstrator
10-22 LeNet model visualized inside TensorSpace
10-23 Metacar environment for training with reinforcement learning
10-24 Screenshot of GAN Lab