Quickly Build a Snapchat Lens By Leveraging Fritz AI Studio’s Style Transfer Model

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Computer Vision — SnapML

The style transfer is one of the most creative applications of Convolutional Neural Networks. It allows you to retrieve the style of an image and use it to transform any given image.

It is an interesting technique that highlights the capacities and internal representations of neural networks. It can also be useful in certain scientific fields for augmenting or simulating image data.

The almost endless combinations of content and styles possible bring out unique and ever more creative results from neural network enthusiasts.

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Audio in Lens Studio

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Lens Studio allows you to import and add audio to your lenses. Adding audio to your lenses enhances the nature of the lenses by enabling the viewer more interaction. It can be added in behavior scripts as a response and even in animations.

Behavior scripts in lens studio enable you to make interactions in your lenses by defining a trigger type and a response for that trigger.

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Building an Image Recognition Model for Mobile using Depthwise Convolutions

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Deep Learning algorithms are excellent at solving very complex problems, including Image Recognition, Object Detection, Language Translation, Speech Recognition, and Synthesis, and include many more applications, such as Generative Models.

However, deep learning is extremely compute intensive—it’s generally only viable through acceleration by powerful general-purpose GPUs, especially from Nvidia. Unfortunately, mobile devices have very limited compute capacity; hence, most architectures that have been very successful on desktop computers and servers cannot be directly deployed to mobile devices.

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Snapchat, FaceApp, and the necessary lessons of data privacy with mobile machine learning

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If you’re even remotely plugged into the tech world, you’d have been hard-pressed to miss a couple viral summer trends, both involving AI-powered photo transformations.

Here’s the gist. Snapchat caught fire and soared past all Q2 estimates, in large part because of their rollout out of popular gender-swap and baby-face Lenses. And soon after, FaceApp took the internet by storm when its old-age filter went viral. This has led to millions of users, including prominent celebrities, showing off what they’d look like in 40 years or as members of a different gender.

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Image Classification on Android with TensorFlow Lite and CameraX

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TensorFlow Lite is the lightweight version of TensorFlow Mobile. It’s here to unleash the machine learning power on your smartphones while ensuring that the model binary size isn’t too big and there’s low latency. Additionally, it also supports hardware acceleration using the Neural Networks API and is destined to run 4X faster with GPU support.

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Body Segmentation in the Browser with TensorFlow.js

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Learning and implementing different AI-powered apps using the TensorFlow.js library empowers you to do so many amazing things with ML in the browser.

This tutorial is the latest in my series using TensorFlow.js for machine learning and implementing those models in React apps. Here, we’ll learn about another TensorFlow library that helps with body segmentation.

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