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Would you please expand on your VSLAM improvements? What other implementations are you comparing against and on what metrics/settings?


The latest NN based approaches still fall short of ORB-SLAM - which is considered the state of the art (in terms implementations). However, it still has only 70% success rate in loop closures.

We tend to measure our accuracy with loop closures and slam graph consistency over time.

Here’s the link of Matic self and exploring and building map on the fly: https://www.dropbox.com/s/e051nmb1ci0o8nu/Auto_Explore_Mehul...


Is that sped up ?


Yes. Its at 4x the speed.


Can you talk more about what models of geography you're referring to? In school in the US, I was always taught there were 7 continents, including the North and South Americas as 2 separate ones. As far as I remember, there was never even a mention of other models apart from maybe some historical understanding before lands had been fully explored by Europeans.


https://en.wikipedia.org/wiki/Continent#Number

This, like history, is one of those dogmatic aspects of state education where only one side get taught and implicitly assumed to be the only one. Geography books need one big asterisk in so many sections


Continents are not natural features, but human determined. Some of the models don't make logical sense.

If Americas are one continent, then Afro-Eurasia must be continent. And end up with the four continent model with continuous landmasses.

If isthmuses make continent, then get the six continent model with tectonic plates.

If can split into non-geographical regions, then Europe and Asia can be separate continents and get the seven continents in the US model.


https://en.wikipedia.org/wiki/Continent#Number

I was never really taught a different model either, but the entire distinctions always felt strange. Moreso with Eurasia.


Different models are taught in different countries. Like with many things, if you never left your country, you are highly unlikely to find out.


Is there such a tool for use with python? preferably matplotlib compatible. I often find myself needing to plot some data to get a quick idea of what it looks like, and my work is generally on a remote host. Having to open a new ssh session with X forwarding is not difficult but a more frictionless approach would be nice.


If you happen to use `iTerm2`, then https://github.com/daleroberts/itermplot works very well. I've used it before and can recommend it pretty highly.


Is iTerm2 GPU accelerated? Wasn't aware it could do that kind of thing. I didn't use it in years, admittedly, haven't had a Mac for a while.


You don't really need GPU acceleration for 2d graphics (and neither for simple 3D). The CPU is more than enough for that.


I understand, but without some kind of direct rendering going on, I can't see how this would work on a terminal emulator.


> without some kind of direct rendering going on, I can't see how this would work on a terminal emulator.

Nah.

You just dump the pixels one by one to the screen using a for loop. You can even do some cpu math with each pixel if you want, and at the end you call XPutImage with the raster (or whatever your toolkit offers). This runs at more than 30fps in fullhd on a 10 year old cpu.

Notice that xterm is blazingly fast and runs entirely on the cpu. Think about it, the plots that this iterm2 demo shows were already done in realtime in the late nineties using the first pentium cpus.

The GPU is not really needed for the basic stuff a terminal emulator does. Of course, if you want to do crazy stuff like scaling by enormous factors, or ultra-fast scroll without skipping tricks, you'll need GPU support.


I see. I'm not nearly qualified enough to talk about that, admittedly. Drawing the pixels isn't the problem, it's updating them fast enough, then?


I guess there is no problem? You only need the gpu to compute fancy 3d graphics in high resolution. For normal terminal stuff and low resolution plots, anything should work.


iTerm2 is GPU accelerated since 2018, yes. Other terminals on Mac that I know of (Kitty, Alacritty, Warp) are also GPU accelerated.


If you use euporie [1], you can draw plots in a Jupyter notebook in the terminal using matotlib and friends, and have them displayed using terminal graphics.

[1] https://github.com/joouha/euporie



There are [1, 2], and AFAICT they rely on gnuplot [3].

[1] https://github.com/nschloe/termplotlib [2] https://github.com/dkogan/gnuplotlib [3] http://www.gnuplot.info/


The last time I used gnuplot was around 25 years ago. And it is still around!


A few years ago, you had to recompile it to add sixel support on debian, so I provided https://github.com/csdvrx/sixel-gnuplot

Now it's included by default IIRC


Have a look at Uniplot - https://github.com/olavolav/uniplot


In this case, we could say that all functions e^ax are eigenfunctions of the derivative, with the eigenvalues being a.


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