Disease index counting error

[Ahasanul Hoque]

Hi,

I am trying to count the disease index using the command and pictures available in fieldimageR github. But always getting the attached error message. 

Could anyone help me to solve this problem?

Thanks

Ahasan

[fmatias]

Hi Ahasan,

Maybe you are using a old script ... It changes a bit to adapt to new packages.

Now you need to use the function EX<-imgLAB(EX)

Try to adapt this script: https://github.com/filipematias23/Phenomics-2025/blob/main/Script_EX3.R

################
### Parallel ###
################

# Required packages
library(parallel)
library(foreach)
library(doParallel)

# Images names (folder directory: "./soybean/")
pics<-list.files("./soybean/")

# Number of cores
n.core<-2

# Starting parallel
cl <- makeCluster(n.core, output = "")
registerDoParallel(cl)
EX.Table.Parallel <- foreach(i = 1:length(pics), .packages = c("stars","sf","terra","FIELDimageR"),
                             .combine = rbind) %dopar% {
                               EX3<-rast(paste("./soybean/",pics[i],sep = ""))
                               EX3<-imgLAB(EX3)
                               # Removing the background
                               EX3.R<- fieldMask(mosaic = EX3, index = "BGI",
                                                 cropValue = 0.7,
                                                 cropAbove = T)
                               # Counting the total number of seeds
                               EX.P.Total<-fieldCount(mosaic = EX3.R$mask,plot = T)
                               Total=EX.P.Total[EX.P.Total$area>15000,]
                               # Selecting green seeds
                               EX3.R2<- fieldMask(mosaic = EX3.R$newMosaic,
                                                  index = "BI",
                                                  cropValue = 130,
                                                  cropAbove = T)
                               # Counting the number of green seeds
                               EX.Green<-fieldCount(mosaic = EX3.R2$mask,plot = T)
                               Green=EX.Green[EX.Green$area>10800,]
                               data.frame(Total=dim(Total)[1],
                                          Green=dim(Green)[1],
                                          Percentage=round(dim(Green)[1]/dim(Total)[1],2))
                             }
stopCluster(cl)
rownames(EX.Table.Parallel)<-pics
EX.Table.Parallel

Hope it helps,

Filipe

[Ahasanul Hoque]

Hi  Filipe,

Thanks for your response. 

Actually I am trying to measure the diseased area of supplied files in fieldimaeR github (https://drive.google.com/file/d/1zgOZFd7KuTu4sERcG1wFoAWLCahIJIlu/view). but failed with the supplied error message (attached as figure). 

Could you please help me to solve this problem? I used imgLAB command but the same problem happened. 

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Regards

Ahasanul Hoque

     PhD (NDSU, USA)

Associate Professor

Dept. of Genetics & Plant Breeding

Bangladesh Agricultural University

Mymensingh-2202, Bangladesh

Mobile: +8801797601052

Skype: ahasan102

[fmatias]

Hi Ahasanul,

Now days the code is a bit different from the one you are using. Try this:

##############
### Script ###
##############

library(FIELDimageR)
library(FIELDimageR.Extra)
library(terra)
library(sf)
library(mapview)
library(leafsync)

######################
### Example Images ###
######################

# List and set working directory for images
pics <- list.files("./images/")

# Define vegetation indices to be calculated
index <- c("BGI", "VARI", "SCI")

# Read and process each image
EX.L1 <- rast(paste("./images/", pics[1], sep = ""))
EX.L1 <- imgLAB(EX.L1)
plot(EX.L1)
fieldView(EX.L1)

# Image SHP
EX.L.Shape <- ext(EX.L1) %>% as.polygons() %>% st_as_sf()

# Select one index to identify leaves and remove background
EX.L2 <- fieldMask(mosaic=EX.L1, index="BGI", cropValue=0.8, cropAbove=T)

# Select one index to identify damaged area in leaves
EX.L3 <- fieldMask(mosaic=EX.L2$newMosaic, index="VARI", cropValue=0.1, cropAbove=T)

# Calculate indices
EX.L4 <- fieldIndex(mosaic=EX.L2$newMosaic, index=index)
rgb<-fieldView(EX.L4)
VARI<-fieldView(EX.L4$VARI)
sync(rgb,VARI)

# Combine layers
EX.L5 <- rast(list(1-EX.L2$mask,1-EX.L3$mask, EX.L4))
names(EX.L5)[c(1,2)]<-c("area_total","area_seg")

# Extract additional field information
EX.L.Info <- fieldInfo_extra(mosaic=EX.L5, fieldShape=EX.L.Shape)
View(EX.L.Info)
as.matrix(EX.L.Info)

###################
### Many Images ###
###################

# List and set working directory for images
pics <- list.files("./images/")

# Define vegetation indices to be calculated
index <- c("BGI", "VARI", "SCI")

# Load required packages
library(parallel)
library(foreach)
library(doParallel)

# Set up parallel processing
n.core <- 2

cl <- makeCluster(n.core, output = "")
registerDoParallel(cl)

# Process images in parallel
system.time({
  EX.Table.Parallel <- foreach(i = 1:length(pics), .packages = c("stars", "sf", "terra", "FIELDimageR", "FIELDimageR.Extra"),
                               .combine = rbind) %dopar% {
                                 
                                 # Read and process each image
                                 EX.L1 <- rast(paste("./images/", pics[i], sep = ""))
                                 EX.L1 <- imgLAB(EX.L1)
                                 EX.L.Shape <- ext(EX.L1) %>% as.polygons() %>% st_as_sf()
                                 
                                 # Select one index to identify leaves and remove background
                                 EX.L2 <- fieldMask(mosaic=EX.L1, index="BGI", cropValue=0.8, cropAbove=T, plot=F)
                                 
                                 # Select one index to identify damaged area in leaves
                                 EX.L3 <- fieldMask(mosaic=EX.L2$newMosaic, index="VARI", cropValue=0.1, cropAbove=T, plot=F)
                                 
                                 # Calculate indices
                                 EX.L4 <- fieldIndex(mosaic=EX.L2$newMosaic, index=index, plot=F)
                                 
                                 # Combine layers
                                 EX.L5 <- rast(list(1-EX.L2$mask,1-EX.L3$mask, EX.L4))
                                 names(EX.L5)[c(1,2)]<-c("area_total","area_seg")
                                 
                                 # Extract additional field information
                                 EX.L.Info <- fieldInfo_extra(mosaic=EX.L5, fieldShape=EX.L.Shape)
                                 
                                 # Return combined information
                                 as.matrix(EX.L.Info)
                               }
})

EX.Table.Parallel

### END ###

[Ahasanul Hoque]

Hi  Filipe,

Thank you for providing the codes. It's working. 

I need little help in interpreting the data:

In commands:

 "# Select one index to identify leaves and remove background

EX.L2 <- fieldMask(mosaic=EX.L1, index="BGI", cropValue=0.8, cropAbove=T)

# Select one index to identify damaged area in leaves
EX.L3 <- fieldMask(mosaic=EX.L2$newMosaic, index="VARI", cropValue=0.1, cropAbove=T) "

Are the cropValue 0.8 and 0.1 always the same for all pictures?

After running, I get the attached result file. In this file which one is the disease index and which data should I used for GWAS?

Thanks

Ahasan

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