Классификация изображений R keras с помощью Magick

Question

Я пытаюсь перекодировать сверточную сеть с помощью пакета Magick R, но когда я выполнил сценарий trainData <- extract_feature("/run/media/rico/078622bc-841f-48e6-8bf5-0058f14a09fa/dogvscat/dogs-vs-cats/train/", width, height), он останавливается с ошибкой, которую я не могу объяснить:

Error in names(feature_matrix) <- paste0("pixel", c(1:img_size)) : 
'names' attribute [2500] must be the same length as the vector [0]

Вот код:

rm(list=ls())
library(keras)
library(stringr)
library(pbapply)
library(magick)

image_dir <- "/run/media/rico/078622bc-841f-48e6-8bf5-0058f14a09fa/dogvscat/dogs-vs-cats/train/"
# Set image size
width <- 50
height <- 50

extract_feature <- function(dir_path, width, height, labelsExist = T) {
  img_size <- width * height
  ## List images in path
  images_names <- list.files(dir_path)

  if(labelsExist){
    ## Select only cats or dogs images
    catdog <- str_extract(images_names, "^(cat|dog)")
    # Set cat == 0 and dog == 1
    key <- c("cat" = 0, "dog" = 1)
    y <- key[catdog]
  }

  print(paste("Start processing", length(images_names), "images"))
  ## This function will resize an image, turn it into greyscale
  feature_list <- pblapply(images_names, function(imgname) {
    ## Read image

    img <- image_read(file.path(dir_path, imgname))
    ## Resize image - use Magick
    img_resized <-image_resize(img, "50x50")
    ## Set to grayscale (normalized to max)

    grayimg <- image_data(img_resized, channels ="gray",frame=1)
    ## Get the image as a matrix
    img_matrix <- grayimg[0]
    ## Coerce to a vector (row-wise)
    img_vector <- as.vector(t(img_matrix))
    return(img_vector)
  })
  ## bind the list of vector into matrix
  feature_matrix <- do.call(rbind, feature_list)
  feature_matrix <- as.data.frame(feature_matrix)
  ## Set names
  names(feature_matrix) <- paste0("pixel", c(1:img_size))

  if(labelsExist){
    return(list(X = feature_matrix, y = y))
  }else{
    return(feature_matrix)
  }
}

trainData <- extract_feature("/run/media/rico/078622bc-841f-48e6-8bf5-0058f14a09fa/dogvscat/dogs-vs-cats/train/", width, height)

trainData достиг 100%, а затем ошибка, описанная выше. Есть ли у вас какие-либо идеи ? Спасибо.