The MedLEA package provides morphological and structural features of471 medicinal plant leaves and 1099 leaf images of 31 species and 29-45images per species.
You could install the stable version on CRAN:
install.packages("MedLEA")You can install the development version fromGitHub with:
# install.packages("devtools")devtools::install_github("SMART-Research/MedLEA")
library(MedLEA)data("medlea")head(medlea)#> ID Sinhala_Name Family_Name#> 1 1 Tel kaduru (???? ?????) EUPHORBIACEAE#> 2 2 Telhiriya (?????????) / Mayura manikkam (???? ?????????) RHAMNACEAE#> 3 3 Thakkali SOLANACEAE#> 4 4 Thala PEDALIACEAE#> 5 5 Thana hal POACEAE#> 6 6 Thebu (????) / Koltan (???????) ZINGIBERACEAE#> Scientific_Name Shape Arrangements Bipinnately_compound#> 1 Sapium insigne Round Simple False#> 2 Colubrina asiatica var. asiatica Round Simple False#> 3 Lycopersicon esculentum Diamond Compound False#> 4 Sesamum indicum Diamond Simple False#> 5 Setaria italica Diamond Simple False#> 6 Costus speciosus Round Simple False#> Pinnately_compound Palmately_compound Edges Uniform_background Red_Margin#> 1 False False Smooth True False#> 2 False False Toothed True False#> 3 True False Lobed True False#> 4 False False Smooth True False#> 5 False False Smooth True False#> 6 False False Smooth True False#> Shaded_margin White_Shading Red_Shading White_line Green_leaf Red_leaf#> 1 False False False False True False#> 2 False False False False True False#> 3 False False False False True False#> 4 False True False False True False#> 5 False False False False True False#> 6 False False False False True False#> Veins Arrangement_on_the_stem Leaf_Apices Leaf_Base#> 1 Pinnate Whorled Acute Obtuse#> 2 Pinnate Alternate Acute Acuate#> 3 Pinnate Opposite Obtuse Cordate#> 4 Pinnate Whorled Acute Cuneate#> 5 Parallel Opposite Acute Gradually tapering#> 6 Parallel Alternate Acute Obtuselibrary(ggplot2)library(wordcloud2)library(magrittr)library(patchwork)library(dplyr)library(tm)#unique(medlea$Family_Name)text1<- medlea$Family_Namedocs<-Corpus(VectorSource(text1))docs<- docs%>%tm_map(stripWhitespace)dtm<-TermDocumentMatrix(docs)matrix<-as.matrix(dtm)words<-sort(rowSums(matrix),decreasing =TRUE)df<-data.frame(word =names(words),freq = words)p1<-wordcloud2(data = df,size =0.9,color ='random-dark',shape ='pentagon')p1
medlea<-filter(medlea, Arrangements=="Simple")d11<-as.data.frame(table(medlea$Shape))names(d11)<-c('Shape_of_the_leaf','No_of_leaves')p2<-ggplot(d11,aes(x=reorder(Shape_of_the_leaf, No_of_leaves),y=No_of_leaves))+labs(y="Number of leaves",x="Shape of the leaf")+geom_bar(stat ="identity",width =0.6)+ggtitle("Composition of the Sample by the Shape Label")+coord_flip()d11<-as.data.frame(table(medlea$Edges))names(d11)<-c('Edges','No_of_leaves')#d11 <- d11 %>% mutate(Percentage = round(No_of_leaves*100/sum(No_of_leaves),0))#ggplot(d11, aes(x= reorder(Shape_of_the_leaf, Percentage), y=Percentage)) + labs(y="Percentage", x="Shape of the leaf") + geom_bar(stat = "identity", width = 0.5) + geom_label(aes(label = paste0(Percentage, "%")), nudge_y = -3, size = 3.25, label.padding = unit(0.175,"lines")) + ggtitle("Composition of the Sample by the Shape Label") + coord_flip()p3<-ggplot(d11,aes(x=reorder(Edges, No_of_leaves),y=No_of_leaves))+labs(y="Number of leaves",x="Edge type of the leaf")+geom_bar(stat ="identity",width =0.6)+ggtitle("Composition of the Sample by the Edge Type")+coord_flip()p2+ p3+plot_layout(ncol =1)
medlea<-filter(medlea, Shape!="Scale-like shaped")d29<-as.data.frame(table(medlea$Shape,medlea$Edges))names(d29)<-c('Shape','Edges','No_of_leaves')d29$Edges<-factor(d29$Edges,levels =c("Smooth","Toothed","Lobed","Crenate"))ggplot(d29,aes(fill = Edges,x=Shape ,y=No_of_leaves))+labs(y="Number of leaves",x="Shape of the leaf")+geom_bar(stat ="identity",width =0.5,position =position_dodge())+coord_flip()+ggtitle("Composition of the sample by Shape Label and Edge type")+scale_fill_brewer(palette ="Set1")
load_images()[1]"The repository of leaf images of medicinal plants in Sri Lanka is collected by following the image acquisition steps that we identified."[1]"The repository contains 1099 leaf images of 31 species and 29-45 images per species.These have simple arrangement. The photographs were taken from the device, Huawei nova 3i. The closest photographs were captured on a white background."[1]"All the leaf images are in a google drive folder that anyone can access. You can download the images directly from the drive."[1]"The shareable link: https://drive.google.com/drive/folders/1W3ap8UhBCIVN5U_UUVSZeTh7VG4Jqbev?usp=sharing"