The CUDA library is always available as a singleton, so it does not make sense for it to be passed in. Instead we can simply grab it from the singleton and use it as it is, which makes the code easier to maintain and automates certain code.
Changes applied:
* Moved utility files to /util/.
* Removed unused #includes.
* Removed unused ::ffmpeg::tools function.
* Removed unused variables.
* Fixed missing parentheses in the version macro.
* Fixed missing override on virtual function overrides and removed unnecessary virtual keyword from them.
* Disabled additional warning for ATL headers on MSVC only.
* Replaced direct printf parameters with their macro equivalent.
* Replaced C-style casts with C++-style casts.
* Applied clang-format again after an earlier change to the CMake file broke the integration for it.
Load additional functions from CUDA and add new enumerations to support them:
* cuDevicePrimaryCtxSetFlags allows us to sched scheduling mode for the GPU.
* cuCtxgetStreamPriorityRange allows us to check which priority levels are supported.
* cuStreamCreateWithPriority allows us to create streams with non-default priority.
The scheduler mode is now set to yield so that other threads can do work when we hit an eventual stalling problem. Streams can also now be created with higher priority and different flags, if necessary. In most cases this should allow CUDA resources to execute even while the GPU is under heavy load.
With this, GCC 8 and above should now be able to compile the project both in obs-studio and as a standalone install. Some features are currently still not fully supported and require extra work, but the majority of things are supported and work out of the box. Exact feature parity can be looked up here on the wiki: https://github.com/Xaymar/obs-StreamFX/wiki/Platform-Feature-Parity
Related: #119#98#30
Ever wished you had a professional camera operator to highlight and follow the action, ensuring the audience never misses a beat? Thanks to NVIDIA, you can now do this at home for free! The new NVIDIA AR SDK unlocks augmented reality features, including motion tracking for faces.
This allows me to provide you with an automated zoom and cropping solution for your video camera to transform your streams into a slick, polished broadcast, where you’ll always be the star of the show. Don’t forget - everything is customizable so the possibilities are endless. You can even recreate that Futurama squinting meme if you wanted to (with some scripting)!
The filter requires compatible Nvidia RTX hardware and the Nvidia AR SDK Runtime to be installed ahead of time. This filter is considered "stable" and shouldn't change much from version to version.
Due to the 'nvcuda' library being part of the driver, it falls in a clause of the GPL which allows us to load and interface with system drivers. Since we can't rely on Nvidias headers here (incompatible license), most of this was pulled from FFmpeg and other things were found out via testing.
