Matthieu Brucher's blog

Yes, because Cover Trees are sometimes too slow. In fact, I asked myself this question, not for the build time, but for the search time if the data has a structure. Imagine, what would happen if your data was more a less a regular grid? When I tried that, starting with a point at (0,0), then (1,0)… the first node (0,0) had references to all the last points (9,9), (9,8)… And I figured, it would be slower than a tree search. So I decided to give kd-trees a shot for this kind of search on a regular grid.
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I had to port a simplex/Nelder-Mead optimizer that I already have in Python in C++. As for the Python version, I tried to be as generic as possible but as efficient as possible, so the state is no longer a dictionary, but a simple structure.

I could have used the Numerical Recipes version, but the licence cost is not worth it, and the code is not generic enough, not explained enough. And also there are some design decisions that are questionable (one method = one responsibility).

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I’ve looked on github for a good C++ implementation of Cover Trees for nearest-neighbors search, but I didn’t find one. I may have overlooked some repositories, but in the end, implementing it myself wasn’t that difficult.
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A few years ago, I mentioned that the registry pattern was my favorite pattern in Python. Well, it may also be my favorite C++ pattern.
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Just after the 0.1 release, I’ve worked to add some few tricks and fix a few bugs (see QtMosaic on Github). The most important change is a better image search.
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During SuperComputing 2011, I stumbled across a paper on parallel random number generation. And it brought back some memories of a blog post I wanted to do here on oversampling in my Interactive Raytracer.

Random numbers are important in a raytracer because one needs oversampling to have anti-aliasing, and to have a more realistic rendering, we need to add some jitter inside the oversampling. I won’t talk about this here, it is not my point (yet). So I’ve decided to resurrect IRT from the dead, at least long enough to test parallel random number generators. It is now on Github, and I’ve also changed the matrix library to Eigen. Some optimizations later, it is slightly faster than before, although it is still very far from Bikker’s work.

The Python wrappers are still working BTW.

Let’s hope I find some time to finish this before getting back at VSTs

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I’m pleased to announce the 1.0 version of QtSimpleEQ, a plugin with one low-pass, two peak and one high pass second-order filters. Nothing fancy in the algorithms, it’s mainly another show case for Qt VST plugins.

The code is available under the GPL2 on github and on Sourceforge.

The plugin can be download on the Sourceforge project page.

The plugin was tested with Tracktion 3 (Windows XP).

Snapshot:

QtSimpleEQ UI

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Just for fun, I’m pleased to announce a working version of QtMosaic.
It allows to create a mosaics database and then generate a photomosaic from this database.

For instance, here is an original image:

Original photo

The used database is freely available on the Internet, and the photomosaic is generated with 18×24 thumbnails:

Rendered photomosaic

The code is available on GitHub, as usual, and it has been tested on Windows and Linux.

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Today, I wanted to announce my new plugin, a 4-bands EQ, but when I started a test with pyVST, I encountered strange things:

• The first is my fault, as the code of the EQ disappeared from my Git repository, so I have to code it again. Mainly it is just plugin the correct actions between the filters and the GUI.
• The second is an error at the end of the test. I’ve updated my Qt version from 4.7.1 to 4.7.4, and since this update (or perhaps since I updated to Python 2.7 for pyVST), I found that even a recompiled QtSimpleOverdrive has the same behavior. It did not when I released it. It seems that Qt is complaining about events that are bounced between different threads, but the actual error message is more cryptic, and impossible to debug the application at this point.

I hope to fix these mistakes this month, I really hope I can get QtVST to work again.

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It has been a while since my last post here, but I’m back! I had access to the French version of this book, thanks to the publisher.

CUDA is now in the trend, and there are several books, one of them I’ve also reviewed.
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