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Comment by antimatter15 | Hacker News Reader

Hey HN!

We're really excited to finally share this with you all! This is the first of a series of demos that we're working to release this week, and we're hoping you'll keep us to that promise :)

Sorry if it doesn't work on your computer! There's still a few glitches and browser compatibility problems that we need to iron out, and we're collecting some telemetry data with LogRocket (https://logrocket.com/) to help us do so (so you all know what kind of data is being collected).

We'll open source the library under an MIT license once we finish writing up the API docs, and fixing these bugs.

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Just wanted to note, I ran the kitten demo in Chrome on my Nexus 6P (Android O Beta) and it worked perfectly.

Extremely impressed. Keep it up!

It's quite unreal. I remember when the paper and initial implementations came out less than 2 years ago, you had to go through this really long setup process that only worked on certain operating system and was a huge fuss. A few services came out online that would do it for you, but they were slow and limited, with huge queues.

Now, as you mention, you can run it in a few seconds on your phone, or in my case, on my Chromebook, right in the browser, with zero installation. Truly amazing.

It really had trouble with the portraits in my experience.

I'm not sure if it's working with my browser or not. It says "Compiling network", then shows a lot of flashing rectangles, then stops and displays a single grey rectangle. Is that what it's supposed to do?

Dude what it did was paint , as in recognizing thats its a picture of 2 cubs and then paint it like the way humans can, its freaking amazing

This looks awesome!

It looks like it (like keras-js) is only for inference (running already-trained models) and not for training. Is this correct?

Are the operations or memory required for training very different?

Yes, you are correct! Training benefits much more from available memory through batching and, since in many cases you only need to train once, it usually makes sense to train on beefy GPUs.

TensorFire is useful in situations where you want to perform inference, but you don't want to ship user-supplied data to your servers, either because you would run out of bandwidth, you would run out of compute power, or your users want to keep their data private.

This is great! Keep up the good work! A link to your github repo would be great. I don't know if it was intentional but I did find your library on npm: https://www.npmjs.com/package/tensorfire

Very nice work, folks. Impressive, and very well-put-together demo. That's the easiest neural style transfer demo I've ever used - and the most fun. (Other than a minute of worrying that my poor 2013 MBP was about to melt down, but that's not your fault. :-)

The download link failed, as others have noted.

Thanks so much for sharing this!

If I upload a 6MB image from my Canon, the site/browser (chrome) crashes. Example images work fine.

Do you have benchmark number like FLOPS compared to GPU / CPU?

Works fine in Chrome on my Google Pixel, Android 7.1.2.

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