Split of one folder (with images) into two and move images to the new folder

user_13260249 0
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I have one folder, called train, which contains two subfolders hot_dog and not_hot_dog. Out of the first folder train I would like to randomly select images from both subfolders hot_dog and not_hot_dog and put them into a new folder, called validation. This validation folder has again two subfolders, called hot_dog and not_hot_dog. The amount of randomly selected images should be approx. 20% of the original amount of images. Those images which were randomly selected and saved under the new folder validation, should be deleted in the original folder train.

Current folder structure looks like this:

current folder structure

The end result of the folder structure should look like this:

target folder structure

r directory split
3 Answers

Here is a base R approach that may work for you. It is not what I would call elegant, but it's relatively easy to understand.

Be sure to replace ~/Stack Overflow/ with whatever directory your train directory is located in.

In short, we use dir.create to make the new directories (if they do not exist already). Then we use list.files to make a list of the files in each of the two training directories. Then we use sample to take a sample of those files. Lastly we use file.copy to place them into their new home.

setwd("~/Stack Overflow/")
sample.fraction <- 0.2
train.true.dir <- "train/hot_dog"
train.false.dir <- "train/not_hot_dog"
valid.true.dir <- "validation/hot_dog"
valid.false.dir <- "validation/not_hot_dog"
sapply(c("validation",valid.true.dir,valid.false.dir),function(x){dir.create(x,showWarnings = FALSE)})
true.files <- list.files(train.true.dir)
false.files <- list.files(train.false.dir)
true.sample <- sample(true.files,size = ceiling(length(true.files) * sample.fraction))
false.sample <- sample(false.files,size = ceiling(length(false.files) * sample.fraction))
sapply(true.sample,function(x){file.copy(paste(train.true.dir,x,sep="/"),paste(valid.true.dir,x,sep="/"))})
sapply(false.sample,function(x){file.copy(paste(train.false.dir,x,sep="/"),paste(valid.false.dir,x,sep="/"))})

If you wanted to remove those files afterwards, you could use these two lines.

Please make a backup first.

sapply(true.sample,function(x){file.remove(paste(train.true.dir,x,sep="/"))})
sapply(false.sample,function(x){file.remove(paste(train.false.dir,x,sep="/"))})
user_130953260

At first, set the current working directory to the path where the folder train is located by setwd(). Then run the following code:

# setwd("path/to/folder/train")
path1 <- file.path("train", c("hot_dog", "not_hot_dog"))
path2 <- file.path("validation", c("hot_dog", "not_hot_dog"))
dir.create("validation")
lapply(path2, dir.create)
Map(function(x, y){
  file <- dir(x) ; n <- length(file)
  file_selected <- file.path(x, sample(file, ceiling(n * 0.2)))
  file.copy(file_selected, y)
  file.remove(file_selected)
}, path1, path2)
user_100689850

This is the final code which I then used:

path2 <- file.path(here(), "data/hot-dog-not-hot-dog/validation", c("hot_dog", "not_hot_dog"))
dir.create(file.path(here(), "data/hot-dog-not-hot-dog/validation"))
lapply(path2, dir.create)
Map(function(x, y){
  file <- dir(x) ; n <- length(file)
  file_selected <- file.path(x, sample(file, ceiling(n * 0.2)))
  file.copy(file_selected, y)
  file.remove(file_selected)
}, path1, path2)```
user_132602490
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