Question

我正在使用magick软件包对R keras进行图像分类。当我开始训练图像时，它以100％的错误结束：

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

我阅读了magick软件包，似乎将图像转换为矩阵是img_matrix <- graying[0] 我不明白我在编码中做错了什么。如果有人可以帮助我。谢谢。

library(keras)
library(magick)
library(stringr)
library(pbapply)

# 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
            img_resized <- _image_resize(img, "50x50")
            ## Set to grayscale (normalized to max)
            grayimg <- image_data(img_resized, channel="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)
      }
}

# Takes approx. 15min
trainData <- extract_feature("train/", width, height)

R magick名称属性的长度必须相同

0 个答案: