VSR - Mesh Culling & Mesh Expansion: Remainder Theory from maths : Tessellation (c)RS
*****
VSR Virtual Screen Resolution & Upscaling Display Vectors ML (c)Rupert S
VSR - Mesh Culling & Mesh Expansion: Remainder Theory from maths : Tessellation
..
VSR Virtual Screen Resolution; But we use the original game resolution as our BASE & upscale in ML
Right, The original example is a Font, The font is represented in F32 floats in high precision,
When we use a lower precision output 800x600 for example; We have the font presented in a lower precision maths...
We however know what the original looked like; Or rather the exact higher precision maths used in the original.
Font Example:
Original example : 32bit Vector font + Font Hinting
Intermediary result recording : 8Bit
Machine learning processing & Identified subject 8Bit font
Output result : Identified subject 8Bit font,
Then we present the output as a formula presenting identified curves & shapes from the original font..
We can present a FP64 version by interpolating our known curves & lines with the font hinting.
Vectors are the same; We can identify if we were presenting a curve, ellipse or line...
Upscaling from a representative precision of 8Bit to our idealised F32 or F64
original media { Recorded data value in 8Bit };
Identified subject = { Recall { High resolution Original Identified subject or vector };
Present high quality version { Presentation of idealised & interpolated output value in f32 or f64 };
We present an interpolated version of the Original higher quality Understanding or Value.
..
Mesh Culling & Mesh Expansion: Remainder Theory from maths : Tessellation :
Production Rules for programs like Font creation & Blender represent created Polygon shapes with a higher precision set of points,
We can capitalise on the use of rules based polygon drawing & Upscale Precision or Downscale it, depending on processing requirements..
If we use rules to create our vectors from Curves, Polygons & Lines, Example Exact values for Curves & Lines,
Interpolation & Tessellation of results, Based on rules, Non random data precision expansion..
We know the Mesh shader stored polygon point matrix from point A to point B,..
We can interpret the expansion & reduction of points from A to B, As expanding or reducing Polygon Precision,
We can scale quality higher or lower..
Such a process as Mesh shading & VSR can then upscale or reduce polygon count, We use a dynamic process to scale our output precision,
The terms are, That we know the initial polygon dataset was drawn with rules..
If rules, Rather than freeform drawing are used, Upscaling the polygon count should be easy!
Tessellation of points with rules, Is far faster than random polygon point to point expansion & also more precise!
As with fonts, We can use Font Hinting, Font Hinting is where we know the curves that we used to produce the letter,..
By these rules, We can re-create the initial drawing..
Reducing or expanding polygon count, So called Mesh Culling & Mesh Expansion..
We use a process called R : Remainder in division & multiplication to represent the remaining calculation, ..
When we reduce precision for the result, This process is mainly used to reduce complexity in school maths, ..
So we can do more maths to our required remainder precision, 4 decimal points for example with Pi..
We can however Re-Expand our precision, If we calculate from remainder, ..
We can expand our precision with full calculations or reduce it with the remainder,..
Mesh Culling & Mesh Expansion, A fast & correct method.
RS
*
What is Trigonomic compression & curvature?
It is when we use base maths to explain things; a curve is the sum of the Hight or width to a central point...
The Hight point does not need to be in the centre; with the example shown below we are mapping the origin angles from A to B with centric point H (for simplicity)
H
A c B
A to B as a line is 7
C to H 2
A to C 3
B to C 4
We can set the curve angle from A to H & H to B, So we can curve how we like but arrive at point A, H , B..
The solve is a lot more complex than Vector points! but is highly compressed!
We can also supply Hight & Depth along with Right & Left for off-centric values in 3D that arrive at point A, B, C..
So:
Displacement in 3D & curvature, 3D coordinates & curve.
R H R
A c B
L D L
Modern hardware is very good at maths; So we can use base maths to store & show data.
RS
*
Machine learning upscale all the older titles we make compatible, The same goes for PS4 in our testing.. If the upscale works on PS4Pro (with more power) and maybe PS4 itself if the ML is cost effective GPU & CPU wise.
Now you may be asking .. How on earth do we manage this ?
The upscaling requires only around 4MB to around 512MB of ram..
If we have RAM we do not need to use tight SiMD expressions & we can use loose ..
Higher performance Machine Learning Image expansion expressions.
We can also Colour LUT SDR to HDR 12Bit if a modeset is not totally available
(that changes the game with VASA HDR 4K/8K Mode) is not totally available.
Colour lock Dynamic range SDR Colour and contrast assessed & Mapped in LUT + Light to dark Mapped Gama.
Example LUT Profiled LED 16 Hours 6 Hours interpolation Matrix: https://is.gd/16hProfiledLUT4LED
Auto function; Improve image quality https://is.gd/MonitorOptimiserAutoICC
The machine learning is to adapt the mode set range to optimum for our performance range:
VESA HDR 4K/8K 8Bit to 12Bit Dolby Vision + compression.. Dynamic Frame Rare Refresh etcetera.
Important that we use Display information & LUT Color Table & Dynamic Range of colors & Contrast/Brightness through HDMI & DVI,
VESA Standards information & LED Light output curve assessment (LAB)
We have a rule, that rule is: Economy with resources.
Effective work is what we are about.
We can still scope SiMD & FPU Maths precision outside of understanding the SDK they used..
For precise representation of our desired output virtualisation,
Either:
Original resolution x upscale + SiMD+FPU Vector Scope (the code run by the application or game)
Original resolution x upscale + SiMD+FPU Vector Scope; Into Virtual resolution
To Vector Scope: To understand the maths processes run by the program..
In order to improve precision of the output; We Know that the SiMD+FPU is a lot higher precision..
Than the output Display Resolution,
We can therefore promote the resolutions of all elements in Float values to vector quality.
Vector scope (the code run by the application or game)
We can then Machine Learn from Scope & that equals superior results,
But we can also directly apply those results though SiMD+FPU maths.
GBuffers are indeed a source of SiMD, Float results & we use all the details that we need.
Example method 3D Shaped screens & surfaces, Vector Scope:
Sample the 3D image of the surface & prove the following postulate:
Surface area N +- (Height + Contour Array bFloat16 = (Layer Surface requirement + Layer-N2)
contoured displays & dimples in wafers handled though VectorScope Maths.
(c)Rupert S / DukeThrust
https://is.gd/ProcessorLasso
Linear Bounding Volume Hierarchy &
Elliptic Bounding Volume Hierarchy for SVM Processor Feature:
SVM Can be emulated in SiMD pure 32Bit Single or 64Bit Double Precision,
& is for high complexity rendering such as non regular windows.
https://www.phoronix.com/scan.php?page=news_item&px=RADV-LBVH-Lands
SVM Can be emulated in SiMD pure 32Bit Single or 64Bit Double Precision..
Is useful for creating non Circle curves such as elliptoids & oblong wave boxes.
In VSR & VSR Variable Lighting we can define spaces with eliptoids SVM,
Therefore shape around trees & grasses & animals &or people & Whales.
https://www.youtube.com/watch?v=UojqzrPtR70
(c)RS
*****
Digital Signal Compression VESA Standard with Vector Prediction
1 plus 2 or rather Np1 + Np2 = Npr | N = Vector | Pixel 1 & Pixel 2
Pixel 2 is a vector direction from Np2 compared to Np1 from 8 locations , Ir rather 8 pixel squares surrounding Np1,
Processing the input Vector (lowering processing latency)
Obviously we take advantage of the fact that we have the keyboard & mouse or Input vector in low latency input mode & are processing the input Vector & therefore..
We can KNOW the Motion vector
Processing External input Vectors (lowering processing latency)
Obviously we take advantage of the fact that we have the Server or Input vector (Video for example with Predict; In low latency input mode & are processing the input Vector & therefore..
We can KNOW the Motion vector,
The 2 point motion Vector Frame
The 2 point motion & frame vector does have a clear advantage in that the DATA path is 100% 3D!
Indeed we do have a completely 3D Frame with:
Input Vector & 2 dislocated view point, The result is a 3D Frame with mathematically provable 3D Isometric Data, Also visible & processable,
Including by visual goggles & Red,Blue/Greed Differentiation (Classic Red & Green/Blue Glasses),
A simple SiMD Threaded examination of tells in the frame allows 3D Rendering,
Even with a single frame & we may provide 2+ different viewpoint frames...
Directly rendering that output To 3D Glass
https://www.youtube.com/watch?v=97JIldpUGE4
*****
High precision FFT Examples : https://is.gd/ProcessorLasso in the SiMD Folder...
Advanced FFT & 3D Audio functions for CPU & GPU https://gpuopen.com/true-audio-next/
https://www.kfr.dev/
*****
MadGamer mentioned DSR or VSR now on the subject of his words on Mortal Kombat
This got me thinking of a good way to do older PS & XBox games & PC for that matter!
As we know the resolution is locked on older SDK; So how do we manage to make a difference ?
UDV_ML
https://www.youtube.com/watch?v=OCkwpoux6ZM
GTA Proof of concept : Enhancing Photorealism Enhancement : (c)RS
VSR Virtual Screen Resolution & Upscaling Display Vectors ML
The work is literally amazing isn't it! >
https://www.youtube.com/watch?v=P1IcaBn3ej0
https://arxiv.org/pdf/2105.04619.pdf
https://github.com/intel-isl/PhotorealismEnhancement
https://arxiv.org/abs/2105.04619
****
Inference on any device with a C99 compiler
https://pypi.org/project/emlearn/
to run without activating C99; Installs under Python 3.10+
https://github.com/emlearn/emlearn-micropython
https://github.com/emlearn/emlearn-micropython/releases
git clone https://github.com/emlearn/emlearn-micropython
With EmLearn you can compile really tight models of tensors & random forest & Gaussian Matrix,
These are very good for:
A1: Anti-Aliasing ( Gaussian, Tensor error diffusion, forested Random spread )
A2: sharpening & Shaping ( Tensor Edge detect with enhance, Gaussian estimation & line fill, Random forest A to B to D: E to B to F X + )
A3: Line & Curve estimation fills & Tessellation ( forested Random spread (Dither fills) & A1 & A2 & Differentiation in 3D Space : 1:2:3{ A B C : E B F }
A4: HDR & WCG, Combinations of dithering in colour space & light/Shadow differentiation in 3D Space : 1:2:3{ A B C : E B F }
https://science.n-helix.com/2019/06/vulkan-stack.html
https://science.n-helix.com/2022/04/vecsr.html
https://science.n-helix.com/2016/04/3d-desktop-virtualization.html
VSR https://drive.google.com/file/d/1hewfYqLmY0z-Am800LMR-6H-P5J0Sr0N/view?usp=drive_link
VecSR https://drive.google.com/file/d/1WDvpD9a6TttMTmIz_sRYWaQT3RExBuSq/view?usp=drive_link
https://science.n-helix.com/2022/10/ml.html
https://science.n-helix.com/2021/03/brain-bit-precision-int32-fp32-int16.html
https://science.n-helix.com/2022/09/audio-presentation-play.html
Innate Compression, Decompression
https://science.n-helix.com/2022/03/ice-ssrtp.html
https://science.n-helix.com/2022/09/ovccans.html
https://science.n-helix.com/2023/02/smart-compression.html
ML tensor + ONNX Learner libraries & files
Model examples in models folder
https://is.gd/DictionarySortJS
https://is.gd/UpscaleWinDL
https://is.gd/HPC_HIP_CUDA
https://is.gd/UpscalerUSB_ROM
https://is.gd/OpenStreamingCodecs
https://drive.google.com/file/d/1li5MDf5FFPMEdpsgX6OEpn79aWZE19PW/view?usp=drive_link
https://is.gd/HuffBrotliAE
****
ML Progress statement 2021 : RS
9:02 You know FSR Virtual Screen Resolution with Dynamic letterboxing & Machine Learning..
Requires some core function,
For example Vulkan DirectML..
Such a feature is a survival trate of core function:
Core function list ML:
Adaptable Tessellation
Adaptable Sharpening
Adaptable Image Enhancement
Adaptable Resolution improvements : Vertex,Polygons,Textures & Shaders
Core function is essential for adaptation of each game engine,
Core ML function is essential for progress & improvement..
Machine learning is in essence : Cognition, Brain function & Development..
Therefore required for improvement to be made.
(c)Rupert S
https://www.youtube.com/watch?v=fzu9oT2JaK8
****
RSR APK Vrc:Lrc:Hrc : Advanced direct RAM Cached Pipe (c)RS
APK Formatic RSR App upscaling & in frame buffer Texture supersampling at the sub pixel level..
Injected into the frame buffer from alternate middle buffer (c)RS
Virtual Screen Buffer : Low latency High precision Frame Cache : Output HDMI Render layer and DSC Compression link with VRR Direct to screen.
****
Are you now using Tragicomic curvatures ..
Using ARC,SIN,TAN instead of polygons for curves?
You only need to map distance along the curve for a polygon point..
That point can be perfect; For there is no such thing as a limit to a curve except that defined by bit precision..
Being 16Bit or 32Bit SiMD can represent a perfection in 16K HDR..
Even more so a Float unit 186Bit! or divisions thereof for Multiplication & fraction boosted Threading.
Curvature modelling is a plan in which we need no points of a polygon
& thus we can compress the data..
A: b16Float for example because we need lower precision sub pixel rendering..
We use this for glTF
What is Trigonomic compression & curvature?
it is when we use base maths to explain things; a curve is the sum of the Hight or width to a central point...
The Hight point does not need to be in the centre; with the example shown below we are mapping the origin angles from A to B with centric point H (for simplicity)
H
A c B
A to B as a line is 7
Present high quality version { Presentation of idealised & interpolated output value in f32 or f64 };
We present an interpolated version of the Original higher quality Understanding or Value.
..
Mesh Culling & Mesh Expansion: Remainder Theory from maths : Tessellation :
Production Rules for programs like Font creation & Blender represent created Polygon shapes with a higher precision set of points,
We can capitalise on the use of rules based polygon drawing & Upscale Precision or Downscale it, depending on processing requirements..
If we use rules to create our vectors from Curves, Polygons & Lines, Example Exact values for Curves & Lines,
Interpolation & Tessellation of results, Based on rules, Non random data precision expansion..
We know the Mesh shader stored polygon point matrix from point A to point B,..
We can interpret the expansion & reduction of points from A to B, As expanding or reducing Polygon Precision,
We can scale quality higher or lower..
Such a process as Mesh shading & VSR can then upscale or reduce polygon count, We use a dynamic process to scale our output precision,
The terms are, That we know the initial polygon dataset was drawn with rules..
If rules, Rather than freeform drawing are used, Upscaling the polygon count should be easy!
Tessellation of points with rules, Is far faster than random polygon point to point expansion & also more precise!
As with fonts, We can use Font Hinting, Font Hinting is where we know the curves that we used to produce the letter,..
By these rules, We can re-create the initial drawing..
Reducing or expanding polygon count, So called Mesh Culling & Mesh Expansion..
We use a process called R : Remainder in division & multiplication to represent the remaining calculation, ..
When we reduce precision for the result, This process is mainly used to reduce complexity in school maths, ..
So we can do more maths to our required remainder precision, 4 decimal points for example with Pi..
We can however Re-Expand our precision, If we calculate from remainder, ..
We can expand our precision with full calculations or reduce it with the remainder,..
Mesh Culling & Mesh Expansion, A fast & correct method.
RS
*
What is Trigonomic compression & curvature?
It is when we use base maths to explain things; a curve is the sum of the Hight or width to a central point...
The Hight point does not need to be in the centre; with the example shown below we are mapping the origin angles from A to B with centric point H (for simplicity)
H
A c B
A to B as a line is 7
C to H 2
A to C 3
B to C 4
We can set the curve angle from A to H & H to B, So we can curve how we like but arrive at point A, H , B..
The solve is a lot more complex than Vector points! but is highly compressed!
We can also supply Hight & Depth along with Right & Left for off-centric values in 3D that arrive at point A, B, C..
So:
Displacement in 3D & curvature, 3D coordinates & curve.
R H R
A c B
L D L
Modern hardware is very good at maths; So we can use base maths to store & show data.
RS
*
Machine learning upscale all the older titles we make compatible, The same goes for PS4 in our testing.. If the upscale works on PS4Pro (with more power) and maybe PS4 itself if the ML is cost effective GPU & CPU wise.
Now you may be asking .. How on earth do we manage this ?
The upscaling requires only around 4MB to around 512MB of ram..
If we have RAM we do not need to use tight SiMD expressions & we can use loose ..
Higher performance Machine Learning Image expansion expressions.
We can also Colour LUT SDR to HDR 12Bit if a modeset is not totally available
(that changes the game with VASA HDR 4K/8K Mode) is not totally available.
Colour lock Dynamic range SDR Colour and contrast assessed & Mapped in LUT + Light to dark Mapped Gama.
Example LUT Profiled LED 16 Hours 6 Hours interpolation Matrix: https://is.gd/16hProfiledLUT4LED
Auto function; Improve image quality https://is.gd/MonitorOptimiserAutoICC
The machine learning is to adapt the mode set range to optimum for our performance range:
VESA HDR 4K/8K 8Bit to 12Bit Dolby Vision + compression.. Dynamic Frame Rare Refresh etcetera.
Important that we use Display information & LUT Color Table & Dynamic Range of colors & Contrast/Brightness through HDMI & DVI,
VESA Standards information & LED Light output curve assessment (LAB)
We have a rule, that rule is: Economy with resources.
Effective work is what we are about.
We can still scope SiMD & FPU Maths precision outside of understanding the SDK they used..
For precise representation of our desired output virtualisation,
Either:
Original resolution x upscale + SiMD+FPU Vector Scope (the code run by the application or game)
Original resolution x upscale + SiMD+FPU Vector Scope; Into Virtual resolution
To Vector Scope: To understand the maths processes run by the program..
In order to improve precision of the output; We Know that the SiMD+FPU is a lot higher precision..
Than the output Display Resolution,
We can therefore promote the resolutions of all elements in Float values to vector quality.
Vector scope (the code run by the application or game)
We can then Machine Learn from Scope & that equals superior results,
But we can also directly apply those results though SiMD+FPU maths.
GBuffers are indeed a source of SiMD, Float results & we use all the details that we need.
Example method 3D Shaped screens & surfaces, Vector Scope:
Sample the 3D image of the surface & prove the following postulate:
Surface area N +- (Height + Contour Array bFloat16 = (Layer Surface requirement + Layer-N2)
contoured displays & dimples in wafers handled though VectorScope Maths.
(c)Rupert S / DukeThrust
https://is.gd/ProcessorLasso
Linear Bounding Volume Hierarchy &
Elliptic Bounding Volume Hierarchy for SVM Processor Feature:
SVM Can be emulated in SiMD pure 32Bit Single or 64Bit Double Precision,
& is for high complexity rendering such as non regular windows.
https://www.phoronix.com/scan.php?page=news_item&px=RADV-LBVH-Lands
SVM Can be emulated in SiMD pure 32Bit Single or 64Bit Double Precision..
Is useful for creating non Circle curves such as elliptoids & oblong wave boxes.
In VSR & VSR Variable Lighting we can define spaces with eliptoids SVM,
Therefore shape around trees & grasses & animals &or people & Whales.
https://www.youtube.com/watch?v=UojqzrPtR70
(c)RS
*****
FSR_DL 2 Motion vector+ with DSC:
Digital Signal Compression VESA Standard with Vector Prediction
1 plus 2 or rather Np1 + Np2 = Npr | N = Vector | Pixel 1 & Pixel 2
Pixel 2 is a vector direction from Np2 compared to Np1 from 8 locations , Ir rather 8 pixel squares surrounding Np1,
Processing the input Vector (lowering processing latency)
Obviously we take advantage of the fact that we have the keyboard & mouse or Input vector in low latency input mode & are processing the input Vector & therefore..
We can KNOW the Motion vector
Processing External input Vectors (lowering processing latency)
Obviously we take advantage of the fact that we have the Server or Input vector (Video for example with Predict; In low latency input mode & are processing the input Vector & therefore..
We can KNOW the Motion vector,
The 2 point motion Vector Frame
The 2 point motion & frame vector does have a clear advantage in that the DATA path is 100% 3D!
Indeed we do have a completely 3D Frame with:
Input Vector & 2 dislocated view point, The result is a 3D Frame with mathematically provable 3D Isometric Data, Also visible & processable,
Including by visual goggles & Red,Blue/Greed Differentiation (Classic Red & Green/Blue Glasses),
A simple SiMD Threaded examination of tells in the frame allows 3D Rendering,
Even with a single frame & we may provide 2+ different viewpoint frames...
Directly rendering that output To 3D Glass
https://www.youtube.com/watch?v=97JIldpUGE4
*****
High precision FFT Examples : https://is.gd/ProcessorLasso in the SiMD Folder...
Advanced FFT & 3D Audio functions for CPU & GPU https://gpuopen.com/true-audio-next/
https://www.kfr.dev/
*****
VSR Virtual Screen Resolution & Upscaling Display Vectors ML (c)RS
MadGamer mentioned DSR or VSR now on the subject of his words on Mortal Kombat
This got me thinking of a good way to do older PS & XBox games & PC for that matter!
As we know the resolution is locked on older SDK; So how do we manage to make a difference ?
UDV_ML
https://www.youtube.com/watch?v=OCkwpoux6ZM
GTA Proof of concept : Enhancing Photorealism Enhancement : (c)RS
VSR Virtual Screen Resolution & Upscaling Display Vectors ML
The work is literally amazing isn't it! >
https://www.youtube.com/watch?v=P1IcaBn3ej0
https://arxiv.org/pdf/2105.04619.pdf
https://github.com/intel-isl/PhotorealismEnhancement
https://arxiv.org/abs/2105.04619
****
Future minimal VSR : fm-VSR : RS
Inference on any device with a C99 compiler
https://pypi.org/project/emlearn/
to run without activating C99; Installs under Python 3.10+
https://github.com/emlearn/emlearn-micropython
https://github.com/emlearn/emlearn-micropython/releases
git clone https://github.com/emlearn/emlearn-micropython
With EmLearn you can compile really tight models of tensors & random forest & Gaussian Matrix,
These are very good for:
A1: Anti-Aliasing ( Gaussian, Tensor error diffusion, forested Random spread )
A2: sharpening & Shaping ( Tensor Edge detect with enhance, Gaussian estimation & line fill, Random forest A to B to D: E to B to F X + )
A3: Line & Curve estimation fills & Tessellation ( forested Random spread (Dither fills) & A1 & A2 & Differentiation in 3D Space : 1:2:3{ A B C : E B F }
A4: HDR & WCG, Combinations of dithering in colour space & light/Shadow differentiation in 3D Space : 1:2:3{ A B C : E B F }
https://science.n-helix.com/2019/06/vulkan-stack.html
https://science.n-helix.com/2022/04/vecsr.html
https://science.n-helix.com/2016/04/3d-desktop-virtualization.html
VSR https://drive.google.com/file/d/1hewfYqLmY0z-Am800LMR-6H-P5J0Sr0N/view?usp=drive_link
VecSR https://drive.google.com/file/d/1WDvpD9a6TttMTmIz_sRYWaQT3RExBuSq/view?usp=drive_link
https://science.n-helix.com/2022/10/ml.html
https://science.n-helix.com/2021/03/brain-bit-precision-int32-fp32-int16.html
https://science.n-helix.com/2022/09/audio-presentation-play.html
Innate Compression, Decompression
https://science.n-helix.com/2022/03/ice-ssrtp.html
https://science.n-helix.com/2022/09/ovccans.html
https://science.n-helix.com/2023/02/smart-compression.html
ML tensor + ONNX Learner libraries & files
Model examples in models folder
https://is.gd/DictionarySortJS
https://is.gd/UpscaleWinDL
https://is.gd/HPC_HIP_CUDA
https://is.gd/UpscalerUSB_ROM
https://is.gd/OpenStreamingCodecs
https://drive.google.com/file/d/1li5MDf5FFPMEdpsgX6OEpn79aWZE19PW/view?usp=drive_link
https://is.gd/HuffBrotliAE
****
ML Progress statement 2021 : RS
9:02 You know FSR Virtual Screen Resolution with Dynamic letterboxing & Machine Learning..
Requires some core function,
For example Vulkan DirectML..
Such a feature is a survival trate of core function:
Core function list ML:
Adaptable Tessellation
Adaptable Sharpening
Adaptable Image Enhancement
Adaptable Resolution improvements : Vertex,Polygons,Textures & Shaders
Core function is essential for adaptation of each game engine,
Core ML function is essential for progress & improvement..
Machine learning is in essence : Cognition, Brain function & Development..
Therefore required for improvement to be made.
(c)Rupert S
https://www.youtube.com/watch?v=fzu9oT2JaK8
****
RSR APK Vrc:Lrc:Hrc : Advanced direct RAM Cached Pipe (c)RS
APK Formatic RSR App upscaling & in frame buffer Texture supersampling at the sub pixel level..
Injected into the frame buffer from alternate middle buffer (c)RS
Virtual Screen Buffer : Low latency High precision Frame Cache : Output HDMI Render layer and DSC Compression link with VRR Direct to screen.
****
Triganomic curvatures in glTF : (c)RS
Are you now using Tragicomic curvatures ..
Using ARC,SIN,TAN instead of polygons for curves?
You only need to map distance along the curve for a polygon point..
That point can be perfect; For there is no such thing as a limit to a curve except that defined by bit precision..
Being 16Bit or 32Bit SiMD can represent a perfection in 16K HDR..
Even more so a Float unit 186Bit! or divisions thereof for Multiplication & fraction boosted Threading.
Curvature modelling is a plan in which we need no points of a polygon
& thus we can compress the data..
A: b16Float for example because we need lower precision sub pixel rendering..
We use this for glTF
What is Trigonomic compression & curvature?
it is when we use base maths to explain things; a curve is the sum of the Hight or width to a central point...
The Hight point does not need to be in the centre; with the example shown below we are mapping the origin angles from A to B with centric point H (for simplicity)
H
A c B
A to B as a line is 7
C to H 2
A to C 3
B to C 4
We can set the curve angle from A to H & H to B, So we can curve how we like but arrive at point A, H , B..
The solve is a lot more complex than Vector points! but is highly compressed!
We can also supply Hight & Depth along with Right & Left for off-centric values in 3D that arrive at point A, B, C..
So:
Displacement in 3D & curvature, 3D coordinates & curve.
R H R
A c B
L D L
Modern hardware is very good at maths; So we can use base maths to store & show data.
The concept:
Traditional Polygonal Meshes: Typically, curves in 3D models are represented by collections of polygons (triangles, squares, etc.). The more polygons used, the smoother the curve appears. However, this approach can increase file size and processing complexity.
Trigonomic Curvatures: This method defines a curve using mathematical functions based on trigonometric relationships. By specifying a central point and angles from that point to various locations on the curve, the entire curve can be described with minimal data.
Advantages of Trigonomic Curvatures:
Compression: This method can significantly reduce the amount of data needed to represent a curve compared to traditional polygon meshes. This leads to smaller file sizes and potentially faster rendering.
Precision: Trigonometric functions can represent curves with high precision, limited only by the bit-depth used (e.g., 16-bit, 32-bit floats).
Flexibility: You can define complex curves with just a few parameters, allowing for greater control over the shape.
Challenges of Trigonomic Curvatures:
Complexity: Implementing and manipulating trigonometric curvatures can be more mathematically complex compared to simple polygon meshes.
Hardware Support: While modern hardware can handle trigonometric functions efficiently, not all rendering engines may natively support this specific method for curve representation.
glTF Compatibility: The document mentions using this technique with glTF, a common 3D model format. However, current glTF specifications don't directly support trigonometric curvatures. There might be workarounds or extensions to achieve this functionality.
(c)Rupert S
https://www.youtube.com/watch?v=rf4yxkB3t4o
High precision FFT Examples : https://is.gd/ProcessorLasso in the SiMD Folder...
Advanced FFT & 3D Audio functions for CPU & GPU https://gpuopen.com/true-audio-next/
https://www.kfr.dev/
****
Deep Colour Mode : Colour range of (Channel x 3) versus (Channel x 4) in mode set,
In a GPU Graphics card bios & Textures or Images & Video : Rupert S 2021-08-04
bt709 in 10Bit,12Bit,14Bit,16Bit per channel mode is a limited colour range HDR...
In 8Bit (8Bitx 4 : 8,8,8,8) somewhat limited,
However 8x4 is a lot better than 8x3!So what is 8x3 RGB & 8x4?
RGBA (A = Alpha) or RGBX (X= Black to White or light to dark)
Firstly using RGBX multiplies 8,8,8 by 8 so 8 Bits more colour or rather shade,
Most monitors have 4x8 on for example VGA port or HDMI or Displayport.
Specifying 8,8,8,8 in the DAC; Digital Converter & hence the port makes colour range 8 x the total amount...
24Bit becomes 32Bit, Internally inside the game engine & GPU this may be the case..
However most mode sets avoid the 4th Channel 8,8,8,(8:Missing)
On older cards (2008 or older) this may not even be used; However most cards have the channel..
So we should set the display mode to 8,8,8,8 & not 8,8,8
However HDMI & DVI standards imply Digital 8x4 & 10x4 & 12x4 & 14x4 & 16x4
We should mode scan the Display port socket & cable to the Monitor or TV..
Therefore using all the channels is particularly important to; Colour Depth & Deep Colour (TV supported format)
Probe the specification & examine if we can send data to the monitor in a colour profile LUT..
For example bt709,bt2020,stmpe2084 & Dolby Vision HDR..
Also in mode settings are FreeSync(AMD) & GSync(NVidia) & within these standards; A Range of LUT profiles..
Additionally the LED LUT profile for the Specific LED/QLED/DLQLED Type..
Setting the profile adds to the colour range on display on the Monitor or TV
But firstly Set 4x8,4x10,4x12,4x14,4x16 and not 3x8 because actual colour depth is reduced by one channel..
Not setting the alpha or Black channel & so a total of 24Bit & not 32Bit or 30Bit not 40BitReduces colour depth.
smpte2084/PQ ((Usually 10Bitx3 & Sometimes DeepColour : 10x4)
(Can be 16Bitx4 for ultra Deep Colour HDR)
bt709 (Usually 8Bitx3 & Sometimes DeepColour : 8x4)
*
Examples of Colour LUT & Depth
bt709 (Usually 8Bitx3 & Sometimes DeepColour : 8x4)
bt709: (PS5) Need for Speed Heat Gameplay | Ultra High Realistic Graphics [4K HDR]
https://www.youtube.com/watch?v=HFpaPteNSZw
bt709: GTA 5 Enhanced Rainy Weather And Lighting | Maxed Out Setting Gameplay With Ray Tracing On RTX 3080
Beautiful game
https://www.youtube.com/watch?v=S2XUZfhDlI0
bt709: WRC 9 | Next Gen Real Life Graphics | Citroen C3 R5 Gameplay | Rally Germany [PS5 4K 60FPS]
Good looking game, Higher overall contrast would make this look sweet in SDR
https://www.youtube.com/watch?v=MZssbtMXdAQ
smpte2084/PQ ((Usually 10Bitx3 & Sometimes DeepColour : 10x4)(Can be 16Bitx4 for ultra Deep Colour HDR)
(4K HDR) GT SPORT PS5 | GR1 A+ LAST TO 1ST?
Presented in 2084/PQ
https://www.youtube.com/watch?v=Qakvs7fCvm4
4K HDR (PS5) DRIVECLUB - AUDI TT RS Gameplay | Ultra High Realistic Graphics
Awesome rain, realistic if flat roads & beautiful terrain Presented in smpte2084/PQ
https://www.youtube.com/watch?v=oXNg8zv5JKQ
WRC 9 (PS5) HDR Heavy Rain Gameplay (4K 60FPS)
Presented in smpte2084/PQ
https://www.youtube.com/watch?v=6cTIq-8LfsU
https://www.youtube.com/watch?v=I7xYvdy3Akg
WRC 9 (PS5) HDR Scenic
https://www.youtube.com/watch?v=2i5vwcABIhU
https://www.youtube.com/watch?v=FU6DWmsLb54
Need for Speed Heat - PS5 Gameplay [HDR] Presented in smpte2084/PQ
https://www.youtube.com/watch?v=nxZrH4PBOI8
****
PlayStation 4 Pro & XBox One FSR Performance 60FPS Quality mode default recommendations
Ultra Q & Quality Setting FSR 60FPS Average Data-Rate 54FPS to 62FPS Performance Mode for consoles :
PlayStation 4 Pro & XBox One : Can FSR Save The AMD RX 580 and Old GPUs | 1080p, 1440p, and 4k Comparison
Additional settings advice:
HDR 10Bit Textures at 1024x1024 Compressed
1000:1 Contrast optimized at full resolution
Colour Definition Mastered at full resolution
LetterBox 1440 into 4K VSR & Rendered at 4K
Back Buffer 128MB to 512MB
DMA Blit & Shadow Copy
Shaders rendered with 3D Information into the VSR Frame with Polygon information
DukeThrust : Computational BOOM Exploroligist @ PSN @ Windows
Deeper explain VSR
https://www.youtube.com/watch?v=KXDfhoT2voA
Performance Examination > Speed VSR
https://www.youtube.com/watch?v=I72Nj8aqWdQ
A to C 3
B to C 4
We can set the curve angle from A to H & H to B, So we can curve how we like but arrive at point A, H , B..
The solve is a lot more complex than Vector points! but is highly compressed!
We can also supply Hight & Depth along with Right & Left for off-centric values in 3D that arrive at point A, B, C..
So:
Displacement in 3D & curvature, 3D coordinates & curve.
R H R
A c B
L D L
Modern hardware is very good at maths; So we can use base maths to store & show data.
The concept:
Traditional Polygonal Meshes: Typically, curves in 3D models are represented by collections of polygons (triangles, squares, etc.). The more polygons used, the smoother the curve appears. However, this approach can increase file size and processing complexity.
Trigonomic Curvatures: This method defines a curve using mathematical functions based on trigonometric relationships. By specifying a central point and angles from that point to various locations on the curve, the entire curve can be described with minimal data.
Advantages of Trigonomic Curvatures:
Compression: This method can significantly reduce the amount of data needed to represent a curve compared to traditional polygon meshes. This leads to smaller file sizes and potentially faster rendering.
Precision: Trigonometric functions can represent curves with high precision, limited only by the bit-depth used (e.g., 16-bit, 32-bit floats).
Flexibility: You can define complex curves with just a few parameters, allowing for greater control over the shape.
Challenges of Trigonomic Curvatures:
Complexity: Implementing and manipulating trigonometric curvatures can be more mathematically complex compared to simple polygon meshes.
Hardware Support: While modern hardware can handle trigonometric functions efficiently, not all rendering engines may natively support this specific method for curve representation.
glTF Compatibility: The document mentions using this technique with glTF, a common 3D model format. However, current glTF specifications don't directly support trigonometric curvatures. There might be workarounds or extensions to achieve this functionality.
(c)Rupert S
https://www.youtube.com/watch?v=rf4yxkB3t4o
High precision FFT Examples : https://is.gd/ProcessorLasso in the SiMD Folder...
Advanced FFT & 3D Audio functions for CPU & GPU https://gpuopen.com/true-audio-next/
https://www.kfr.dev/
****
Proposed VESA & DVB Standard with Video Codecs (MP4+VP9+AV1++) :
Deep Colour Mode : Colour range of (Channel x 3) versus (Channel x 4) in mode set,
In a GPU Graphics card bios & Textures or Images & Video : Rupert S 2021-08-04
bt709 in 10Bit,12Bit,14Bit,16Bit per channel mode is a limited colour range HDR...
In 8Bit (8Bitx 4 : 8,8,8,8) somewhat limited,
However 8x4 is a lot better than 8x3!So what is 8x3 RGB & 8x4?
RGBA (A = Alpha) or RGBX (X= Black to White or light to dark)
Firstly using RGBX multiplies 8,8,8 by 8 so 8 Bits more colour or rather shade,
Most monitors have 4x8 on for example VGA port or HDMI or Displayport.
Specifying 8,8,8,8 in the DAC; Digital Converter & hence the port makes colour range 8 x the total amount...
24Bit becomes 32Bit, Internally inside the game engine & GPU this may be the case..
However most mode sets avoid the 4th Channel 8,8,8,(8:Missing)
On older cards (2008 or older) this may not even be used; However most cards have the channel..
So we should set the display mode to 8,8,8,8 & not 8,8,8
However HDMI & DVI standards imply Digital 8x4 & 10x4 & 12x4 & 14x4 & 16x4
We should mode scan the Display port socket & cable to the Monitor or TV..
Therefore using all the channels is particularly important to; Colour Depth & Deep Colour (TV supported format)
Probe the specification & examine if we can send data to the monitor in a colour profile LUT..
For example bt709,bt2020,stmpe2084 & Dolby Vision HDR..
Also in mode settings are FreeSync(AMD) & GSync(NVidia) & within these standards; A Range of LUT profiles..
Additionally the LED LUT profile for the Specific LED/QLED/DLQLED Type..
Setting the profile adds to the colour range on display on the Monitor or TV
But firstly Set 4x8,4x10,4x12,4x14,4x16 and not 3x8 because actual colour depth is reduced by one channel..
Not setting the alpha or Black channel & so a total of 24Bit & not 32Bit or 30Bit not 40BitReduces colour depth.
smpte2084/PQ ((Usually 10Bitx3 & Sometimes DeepColour : 10x4)
(Can be 16Bitx4 for ultra Deep Colour HDR)
bt709 (Usually 8Bitx3 & Sometimes DeepColour : 8x4)
*
Examples of Colour LUT & Depth
bt709 (Usually 8Bitx3 & Sometimes DeepColour : 8x4)
bt709: (PS5) Need for Speed Heat Gameplay | Ultra High Realistic Graphics [4K HDR]
https://www.youtube.com/watch?v=HFpaPteNSZw
bt709: GTA 5 Enhanced Rainy Weather And Lighting | Maxed Out Setting Gameplay With Ray Tracing On RTX 3080
Beautiful game
https://www.youtube.com/watch?v=S2XUZfhDlI0
bt709: WRC 9 | Next Gen Real Life Graphics | Citroen C3 R5 Gameplay | Rally Germany [PS5 4K 60FPS]
Good looking game, Higher overall contrast would make this look sweet in SDR
https://www.youtube.com/watch?v=MZssbtMXdAQ
smpte2084/PQ ((Usually 10Bitx3 & Sometimes DeepColour : 10x4)(Can be 16Bitx4 for ultra Deep Colour HDR)
(4K HDR) GT SPORT PS5 | GR1 A+ LAST TO 1ST?
Presented in 2084/PQ
https://www.youtube.com/watch?v=Qakvs7fCvm4
4K HDR (PS5) DRIVECLUB - AUDI TT RS Gameplay | Ultra High Realistic Graphics
Awesome rain, realistic if flat roads & beautiful terrain Presented in smpte2084/PQ
https://www.youtube.com/watch?v=oXNg8zv5JKQ
WRC 9 (PS5) HDR Heavy Rain Gameplay (4K 60FPS)
Presented in smpte2084/PQ
https://www.youtube.com/watch?v=6cTIq-8LfsU
https://www.youtube.com/watch?v=I7xYvdy3Akg
WRC 9 (PS5) HDR Scenic
https://www.youtube.com/watch?v=2i5vwcABIhU
https://www.youtube.com/watch?v=FU6DWmsLb54
Need for Speed Heat - PS5 Gameplay [HDR] Presented in smpte2084/PQ
https://www.youtube.com/watch?v=nxZrH4PBOI8
****
PlayStation 4 Pro & XBox One FSR Performance 60FPS Quality mode default recommendations
Ultra Q & Quality Setting FSR 60FPS Average Data-Rate 54FPS to 62FPS Performance Mode for consoles :
PlayStation 4 Pro & XBox One : Can FSR Save The AMD RX 580 and Old GPUs | 1080p, 1440p, and 4k Comparison
Additional settings advice:
HDR 10Bit Textures at 1024x1024 Compressed
1000:1 Contrast optimized at full resolution
Colour Definition Mastered at full resolution
LetterBox 1440 into 4K VSR & Rendered at 4K
Back Buffer 128MB to 512MB
DMA Blit & Shadow Copy
Shaders rendered with 3D Information into the VSR Frame with Polygon information
DukeThrust : Computational BOOM Exploroligist @ PSN @ Windows
Deeper explain VSR
https://www.youtube.com/watch?v=KXDfhoT2voA
Performance Examination > Speed VSR
https://www.youtube.com/watch?v=I72Nj8aqWdQ
****
5K Height 2880 Width 5120 :
{primaries:BT709, transfer:LINEAR_HDR (slope 0.3333, SDR white point 240.0000 nits), matrix:RGB, range:FULL} :
Display bounds=[0,0 2560x1440], workarea=[0,0 2560x1410], scale=2, rotation=0, panel_rotation=0 external.
Display: Scaled: [0,0 2560x1440] Scale: 2.00 Actual: [0,0 5120x2880]
HEVC - Dolby Vision support TRUE
HEVC - HDR10 support true
HDCP 2.2 support true
HEVC - 4K support true
Color space (WCG/no-alpha,WCG/alpha,HDR/no-alpha,HDR/alpha)
{primaries:BT709, transfer:LINEAR_HDR (slope 0.3333, SDR white point 240.0000 nits), matrix:RGB, range:FULL}
Buffer format (WCG/no-alpha,WCG/alpha,HDR/no-alpha,HDR/alpha) RGBA_F16
SDR white level in nits 240 (300, 400, 500, 600, 800, 1000)
Bits per color component 10 > 12 Dolby Vision
Bits per pixel RGB 30 > 40 : Alpha Black 36 > 48
Color Profiles relevant to web formats & video : primaries:BT709, transfer:IEC61966_2_1
Texture format : RGBA_F16 : BT709
Compression of HDMI Display cable transfer : HDCP 2.2 support
https://bit.ly/DJ_EQ
https://bit.ly/VESA_BT
*************************
https://science.n-helix.com/2022/10/ml.html
ML tensor + ONNX Learner libraries & files
Model examples in models folder
https://is.gd/DictionarySortJS
https://is.gd/UpscaleWinDL
https://is.gd/HPC_HIP_CUDA
https://is.gd/UpscalerUSB_ROM
https://is.gd/OpenStreamingCodecs
The perfect Proposal RS
VSR : FSR & HDR Settings : RS
5K Height 2880 Width 5120 :
{primaries:BT709, transfer:LINEAR_HDR (slope 0.3333, SDR white point 240.0000 nits), matrix:RGB, range:FULL} :
Display bounds=[0,0 2560x1440], workarea=[0,0 2560x1410], scale=2, rotation=0, panel_rotation=0 external.
Display: Scaled: [0,0 2560x1440] Scale: 2.00 Actual: [0,0 5120x2880]
HEVC - Dolby Vision support TRUE
HEVC - HDR10 support true
HDCP 2.2 support true
HEVC - 4K support true
Color space (WCG/no-alpha,WCG/alpha,HDR/no-alpha,HDR/alpha)
{primaries:BT709, transfer:LINEAR_HDR (slope 0.3333, SDR white point 240.0000 nits), matrix:RGB, range:FULL}
Buffer format (WCG/no-alpha,WCG/alpha,HDR/no-alpha,HDR/alpha) RGBA_F16
SDR white level in nits 240 (300, 400, 500, 600, 800, 1000)
Bits per color component 10 > 12 Dolby Vision
Bits per pixel RGB 30 > 40 : Alpha Black 36 > 48
Color Profiles relevant to web formats & video : primaries:BT709, transfer:IEC61966_2_1
Texture format : RGBA_F16 : BT709
Compression of HDMI Display cable transfer : HDCP 2.2 support
https://bit.ly/DJ_EQ
https://bit.ly/VESA_BT
*************************
https://science.n-helix.com/2022/10/ml.html
ML tensor + ONNX Learner libraries & files
Model examples in models folder
https://is.gd/DictionarySortJS
https://is.gd/UpscaleWinDL
https://is.gd/HPC_HIP_CUDA
https://is.gd/UpscalerUSB_ROM
https://is.gd/OpenStreamingCodecs
The perfect Proposal RS
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