Deep convolutional networks have become a popular tool for image generation and restoration. Generally, their excellent performance is imputed to their ability to learn realistic image priors from a large number of example images. In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning. In order to do so, we show that a randomly-initialized neural network can be used as a handcrafted prior with excellent results in standard inverse problems such as denoising, super-resolution, and inpainting. Furthermore, the same prior can be used to invert deep neural representations to diagnose them, and to restore images based on flash-no flash input pairs. Apart from its diverse applications, our approach highlights the inductive bias captured by standard generator network architectures. It also bridges the gap between two very popular families of image restoration methods: learning-based methods using deep convolutional networks and learning-free methods based on handcrafted image priors such as self-similarity.
AI and deep-learning is not always necessary or helpful. In this case impressive results have been achieved without the use of any of the hyped technologies.
In this case you give the algorithms two inputs. A video base that you want to stylize and a base picture that resembles the style you want to achieve.
We introduce a new example-based approach to video stylization, with a focus on preserving the visual quality of the style, user controllability and applicability to arbitrary video. Our method gets as input one or more keyframes that the artist chooses to stylize with standard painting tools. It then automatically propagates the stylization to the rest of the sequence. To facilitate this while preserving visual quality, we developed a new type of guidance for state-of-art patch-based synthesis, that can be applied to any type of video content and does not require any additional information besides the video itself and a user-specified mask of the region to be stylized. We further show a temporal blending approach for interpolating style between keyframes that preserves texture coherence, contrast and high frequency details. We evaluate our method on various scenes from real production setting and provide a thorough comparison with prior art.
Apparently there also is a Windows demo available in which you are supposedly be able to create your own stylized short clips. But as I wanted to try it out it threw a lot of funky messages regarding the application to be specifically untrustworthy / possibly malicious. So be aware and cautious.
Maybe you want to give EasyEDA a try as it’s in-browser experience is better than anything I had come across so far. Granted I am not doing PCBs regularly but nevertheless – whenever I tried with the programs I’ve got recommended it wasn’t as straight forward as it is with this tool.
The image [..] is a visual/artistic experiment playing with simultanous contrast resulting from other experiments these days. An over-saturated colored grid overlayed on a grayscale image causes the grayscale cells to be perceived as having color. The processing needed to create the above image happened along with unrelated but significant code improvements In the last couple of weeks. I have been visiting mitch – a prolific GIMP contributors for collaboration – and lots of progress has been – and is still – being made on babl, GEGL and GIMP.
As people around me discuss what to go for in regards to manage their growing number of private GIT repositories I joined their discussion.
A couple of years ago I assessed how I would want to store my collection of almost 100 GIT private repositories and all those cloned mirrors I want to keep for archival and sentimental reasons.
An option was to pay for GitHub. Another option, which most seemed to prefer, was going for a local Gitlab set-up.
All seemed not desirable. Like chaining my workflows to GitHub as a provider or adopting a new hobby to operate and maintain a private GitLab server. And as it might have become easier to operate a GitLab server with the introduction of container management systems. But I’ve always seemed to have to update to a new version when I actually wanted to use it.
So this was when I had to make the call for my own set-up about 4 years ago. We were using a rather well working GitLab set-up for work back then. But it all seemed overkill to me also back then.
It runs with one command, the only dependency is two file system directories with (a) the settings of gogs and (b) your repositories.
It’ll deploy as literally a SINGLE BINARY without any other things to consider. With the provided dockerfile you are up and running in seconds.
It has never let me down. It’s running and providing it’s service. And that’s the end of it.
I am using it, as said, for 95 private repositories and a lot of additionally mirrored GIT repositories. Gogs will support you by keeping those mirrors in sync for you in the background. It’s even multi-user multi-organization.
Let me introduce you to a wonderful concept. We are using these movies as backdrop when on the stepper or spinning, essentially when doing sports or as a screensaver that plays whenever nothing else is playing on the screens around the house.
What is it you ask?
The thing I am talking about is: Walking Videos! Especially from people who walk through Tokyo / Japan. And there are lots of them!
Think of it as a relaxing walk around a neighborhood you might not know. Take in the sounds and sights and enjoy. That’s the idea of it.
If you want the immediate experience, try this:
Of course there are a couple of different such YouTube channels waiting for your subscription. The most prominent ones I know are:
In hearing distance of the place I am usually staying when in Tokyo is a train station. So if the wind is right and the window is open I hear all these train station chimes and sounds.
If you don’t know what it is, let Wikipedia educate you:
A train melody is a succession of musically expressive tones played when a train is arriving at or about to depart from a train station. As part of train passenger operations, a train melody includes a parade of single notes organized to follow each other rhythmically to form a lilting, singular musical thought.
In Japan, departing train melodies are arranged to invoke a relief feeling in a train passenger after sitting down and moving with the departing train. In contrast, arriving train melodies are configured to cause alertness, such as to help travelers shake off sleepiness experienced by morning commuters.
When you are writing code the patterns seem to repeat every once in a while. Not only the patterns but also the occasion you are going to apply certain code styles and methods while developing.
To support a developer with this creative work the tedious and repetitious tasks of typing out what is thought can be supported by machine learning.
Chances are your favourite IDE already supports an somehow AI driven code autocomplete feature. And if it does not, read on as there are ways to integrate products like TabNine into any editor you can think of…
Visual Studio IntelliCode is a set of AI-assisted capabilities that improve developer productivity with features like contextual IntelliSense, argument completion, code formatting, and style rule inference.
Of course there are some new contenders to the scene, like TabNine:
TL;DR: TabNine is an autocompleter that helps you write code faster. We’re adding a deep learning model which significantly improves suggestion quality. You can see videos below and you can sign up for it here.
Deep TabNine requires a lot of computing power: running the model on a laptop would not deliver the low latency that TabNine’s users have come to expect. So we are offering a service that will allow you to use TabNine’s servers for GPU-accelerated autocompletion. It’s called TabNine Cloud, …
Prickle-Prickle 5 Bureaucracy: The Apostle Zarathud’s Holyday. A hard nosed Hermit of Medieval Europe and Chaosphe Bible Banger (after his enlightenment, that is). Dubbed “Offender of The Faith”. Discovered the Five Commandments (The Pentabarf).
Expose your undies! Celebrate by wearing nothing but unmentionables in public, or at least by wearing your underwear, or somebody else’s, where people can see it so they can gawk at you. (This is a great day to apply for membership in the Lesser Disorder of Underwear Heads.)
Preserving old software is all about storing it and keeping it running.
With the most important part being the later one. The best way to keep things running is by emulating the old and obsolete hardware as accurate as possible.
In computing, an emulator is hardware or software that enables one computer system (called the host) to behave like another computer system (called the guest). An emulator typically enables the host system to run software or use peripheral devices designed for the guest system. Emulation refers to the ability of a computer program in an electronic device to emulate (or imitate) another program or device.
There are a lot of different types of emulators for all sorts of purposes.
There’s things like bochs which is effectively emulating the hardware of a PC on chip-level and can run virtually anywhere:
Bochs is a highly portable open source IA-32 (x86) PC emulator written in C++, that runs on most popular platforms. It includes emulation of the Intel x86 CPU, common I/O devices, and a custom BIOS. Bochs can be compiled to emulate many different x86 CPUs, from early 386 to the most recent x86-64 Intel and AMD processors which may even not reached the market yet.
Emulators of game consoles are alike that – they are emulating the whole system hardware and are able to run original and unchanged code by replicating the exact hardware. Sometimes more and sometimes less exactly.
Hardware emulation in itself an extremely interesting field of software engineering. There’s the hard way to emulate everything accurately (and slowly) by doing what the actual old hardware would have done but maybe in software (or even in replicated hardware).
In regards of old game console hardware there are even now specialized distributions of lots of hardware/system emulators available for specific and readily available hardware like the RaspberryPi. Some of them recently have gotten some nice updates.
The firecracker exploded. Apparently after 2 weeks of usage of the Chuwi Hi10 Air the eMMC flash is malfunctioning.
In a totally strange way: Every byte on the eMMC can be read, seemingly. Even Windows 10 boots. But after a while it will hang and blue screen. Apparently because it tries to write to the eMMC and when those writes fail and pile up in the caches at some point the system calls it quits.
Anyhow: It means that no byte that is right now on this eMMC can be deleted / overwritten but only be read.
The great chinese support is really helpful and offered to replace the device free of charge right away. That’s very nice! But I came to the conclusion that I cannot send the device in, because:
It contains a full set of synched private data that I cannot remove by all means because the freaking soldered-on eMMC flash is broken.
The recipient of this broken tablet in china would be able to read all my data and I could not do anything about it.
Only an extremely small fraction of data is on there unencrypted. Only that much I hadn’t yet switched on encryption on during the initial set-up I was still doing on the device. And that little piece of data already is what won’t let me send out the device.
Now, what can we learn from this? We can learn: Never ever ever work with anything, even during set-up, without full encryption.