Handling metallic roughness maps colour channels

I’m trying to use a metalness/roughness workflow and I’m not sure how to translate the colour channels into the different metalness and roughness attributes. I’m not sure if there’s a standard on how to encode that information and I can’t find any online resources on how to treat the colour channels so I’m guessing that there is no standard.

I have had materials which have used only the R and B channels and having the B channel set as 0 and I have had materials that somehow use all the RGB channels and I’m confused as to why they would need a third channel to determine metallness and roughness.

My question is, how should I determine the format that the map is in and which channel corresponds to which attribute?

Update: I’ve already come to terms that I’ll probably have to compile new shaders for different materials but I’m trying to figure out a way of identifying the format that a map is in. It would appear that for one of the models I’m using, it stores its bump map in the R channel. I didn’t even know that was an option

Update 2: I imagine I’ll have to just delegate this to the asset pipeline and have the user select which channels to sample from. That or have a hardcoded format and make sure that any PBR materials imported follow that format

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APP REDESIGN – implement new brand colour or new layout/experience?

I’m trying to do a personal project as part of my portfolio. So one of the things I have been constantly asking myself is when looking at doing a complete redesign of the Mobile App including the core experience, layout, and even the primary brand colours, which route would you take?;

  1. Introduce the latest brand colours in the existing design/layout.
  2. Implement the new layout/experience and do an A/B and at the final stage introduce the brand colour.

The main reason for wanting to do the split implementation; to provide the users a sense of continuity between the existing app screens and newer app screens. So by all means, the users do not feel alienated when they are left to navigate an entirely new app (with changed experience, layout and brand colours)

Please do let me know the core reason on why you think either of the approaches work.

Thanks a lot in advance.

Document card hover colour change

Hi I have used office fabric ui document card i want to change colour on hover of document card ,

enter image description here

   const cardStyles: IDocumentCardStyles = {    root: { display: 'inline-block', marginRight: 20, borderRadius: 25, marginBottom: 20,width: 200,     backgroundColor:"#fbce07",    }     };       const  Documentcardstyle = {   root: { textAlign: "center" , borderRadius: 25, backgroundColor:"#fbce07" , color:"white" }    };     <DocumentCard styles={cardStyles} onClick={() =>this.ShowGrid(items.Template)}>   <DocumentCardTitle styles={Documentcardstyle} title={items.Template} />  <DocumentCardImage  styles={Documentcardstyle} height={100}imageFit={ImageFit.cover}  imageSrc={items.ImageLink ? items.ImageLink["Url"] : ''} />    <DocumentCardDetails> </DocumentCardDetails> </DocumentCard> 

Aesthetics must be either length 1 or the same as the data (1983): colour

tudo bem? Estou tentando fazer um gráfico de interação no R usando o pacote ggplot2, no entanto o seguinte erro está ocorrendo

Aesthetics should be the length 1 or the same as the data (1983): color.

Alguém pode me ajudar?

Data base: http://halweb.uc3m.es/esp/Personal/personas/durban/esp/web/cursos/Maringa/gam-markdown/index.html

Os dados estão na seção data.zip, a base dados é a leukemia.txt. Note: Eu estou utilizando as seguintes librarys:

library(nlme) library(ggplot2) library(GGally) library(splines) library(nlme) library(fields) library(lattice) require(ISLR) library(grid) library(dplyr) library(MASS) library(mgcv) library(latticeExtra) library(fields) 

Segue o código abaixo:

setwd("C:\Users\breni\Google Drive\Acadêmica\Mestrado\Splines") dados <- read.table("leukemia.txt", header=TRUE) dados$  treatment  <- factor(dados$  treatment) dados$  case  <- factor(dados$  case) head(dados) attach(dados)   interaction <- dados %>%   dplyr::select(height, age, case) %>%   group_by(case, age) %>%   summarise(Average = mean(height))  x11() ggplot(interaction, aes(x=age, y=Average, colour=treatment, group=case)) +    ggtitle("Evolução da altura em cm no tempo para cada individuo") +      geom_line()