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@Ilya_6483 [8547462020] warned (2 of 2).
• Action: Banned 🚷
the sender is an 4th 5th raspberry or jetson orin nano
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may be you think this is neglible, but maintainance cost is also better that way. you can enchant your lib with the update of other module
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just my advice 🎉. I dont have experience, just some observation of possible steps
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another more concrete example : obs studio — twitch
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hello guys! long time no see!
so i am developing a bit of realtime video streaming client. the rtp and encoding are already handled by the uvgrtp and libav
i have other implementation that is based entirely on gstreamer pipeline (gst.h), that is a lot of a heck easier
i want to show the raw frame buffer (packed rgb or planar yuv 4:2:0) to the user efficiently. i have implemented the qpixmap label thing but it involves a lot of data duplication and in general does not seem professional to me. i am planning to use the opengl widgets integration so my question is: is there some ready-to-use reatime-video-display widgets to put pixels on the screen efficiently from memory?
i tried to investigate the docs qvideowidget thing but i was not able to understand how to pass my own raw data pointer to qvideoframe.
maybe someone have done something simmiral in qt already and could provide some directions?
But yes - when you're learning these, writing test programs that use the STL algorithms available - benchmarking them to see how they work does help a lot to understand.
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Yes — I was doing a Qt 6 porting effort for Renderdoc a few weeks ago - and RenderDoc has its own string class (rdcstr) with cast operators between it and QString.
In Qt 6, QString went from being internally stored as UTF-8 to being stored as UTF-16, which made conversions more expensive, so I didn't want to make the conversions between QString and rdcstr implicit (plus, the compiler kept giving me ambiguous overload selection errors).
So — to make all of the conversions explicit, I needed to modify a *LOT* of code, and not something I could craft a regex to do. GenAI was a real big help here.
std::vector is your default choice except you have a good reason not to
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Ronald Rivest is also the very same "R" in RSA, btw.
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Nah, I suppose it isn’t that much worse than most textbooks but it’s a lot more fun when you can use it immediately (and experience what it is all about)
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I didn't find the "Introduction to Algorithms" book to be dry — though you do need to consume it in small chunks to really understand it.
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btw, already noted this a few times before, why people always think of embedded device as of something
in
out
cpu-realmode level :D
it's full system, from grub-loader to linux-kernel, drivers for devices at bus, and gnome(so you even can configure it with hands in UI !!!). tho it may start 1 APP full-screen...
I assume your qt runs at PC, maybe in your mini-linux-distributive with qt as in some embedded device. so access to qt you already have, you MUST not to tweak with mesa, etc. have to use simple approach — system starts your app fullscreen, etc.... just as normal app
cant imagine why you may think about opengl in encoding of stream-packet
so heavily recommend to use existing API. if license is fine — best way is too hook to obs studio. has already all you may need. (by hook I mean — just compile into your project .obj that you need. but I'm sure there're public API, docs, and headless version)
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should not think through implementation theory. will solve task but not efficient. best to use/hook into already polished API, check the docs. github libs (including heavily qt-oriented but the only main part of the gears are Gather(in any way, may be capture dx-surface every 1/4 sec)-Cache with delay-Encoding-Send-Decode-Show with preloaded timeline optionaly(in any way may draw img as texture, may use qt-widget))
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should not work with pixels/redo everything, should work with packed cadr-S (img at timeline). there're already open-source solutions
example — any popular web-video platform
I would contend that theoretic is what you need — to understand the time complexity and space complexity of different algorithms (Big-O in particular).
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About algorithms, which is really vital, STL gives you a bunch of good ones, but you can enhance your skills by dealing with related exercises or problems.
Benchmark each and do not expect better results just by knowing them.
CLRS, is mostly theoretic.
I would suggest learning them each by real projects.
It’s also very useful when you want to refactor or tweak the code
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This is how I use AI in my job (when I can). I will also use it to generate boilerplate application code.
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Get a copy of the CLRS (Thomas Cormet, Charles Liserson, Ronald Rivest, and Clifford Stein) book "Introduction to Algorithms" — it is a really good book for learning algorithms and data structures.
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@Ilya_6483 [8547462020] warned (1 of 2).
Due to: already deleted message once