How about calling it "Mix (with) Undenoised" in Blender? I would think if a user selects a denoiser, he expects a denoised image by default. Hence name it something that explicitly states how it deviates from pure denoised image.
In LuxCore itself (the parameter Dade mentions) could just be "mix" for simplicity?
OpenImageDenoise
Re: OpenImageDenoise
For consistency's sake, I would call the property "amount".
This is how a simple lerp is called in the mix texture, mix material etc.
In Blender, lerps are called "fac" everywhere, which is probably short for "factor".
However we call it, I think (almost) every imagepipeline plugin should have this parameter, to make it easier to control the strength of it.
This is how a simple lerp is called in the mix texture, mix material etc.
In Blender, lerps are called "fac" everywhere, which is probably short for "factor".
However we call it, I think (almost) every imagepipeline plugin should have this parameter, to make it easier to control the strength of it.
Re: OpenImageDenoise
Yep, in Blender Fac. is Factor.
And "amount" could be fine if it has consistency with the rest of the UI, as long as the effect of this parameter is properly explained in the documentation there shouldn`t be any problem I think
And "amount" could be fine if it has consistency with the rest of the UI, as long as the effect of this parameter is properly explained in the documentation there shouldn`t be any problem I think
Re: OpenImageDenoise
Open Image Denoise v1.2.0
-Added neural network training code
-Added support for specifying user-trained models at runtime
-Slightly improved denoising quality (e.g. less ringing artifacts, less
blurriness in some cases)
-Improved denoising speed by about 7-38% (mostly depending on the compiler)
-Added OIDN_STATIC_RUNTIME CMake option (for Windows only)
-Added support for OpenImageIO to the example apps (disabled by default)
-Added check for minimum supported TBB version
-Find debug versions of TBB
-Added testing
https://github.com/OpenImageDenoise/oidn/releases
-Added neural network training code
-Added support for specifying user-trained models at runtime
-Slightly improved denoising quality (e.g. less ringing artifacts, less
blurriness in some cases)
-Improved denoising speed by about 7-38% (mostly depending on the compiler)
-Added OIDN_STATIC_RUNTIME CMake option (for Windows only)
-Added support for OpenImageIO to the example apps (disabled by default)
-Added check for minimum supported TBB version
-Find debug versions of TBB
-Added testing
https://github.com/OpenImageDenoise/oidn/releases
Actualy sorry for my google translate english :)