loadImage：Machine Learning 載入影像轉換

載入影像資料。

使用方式

  loadImage(vars)

引數

vars

輸入變數名稱和輸出變數名稱的字元向量具名清單。 請注意，輸入變數必須為相同類型。 輸入與輸出變數之間的一對一對應，可以使用具名字元向量。

詳細資料

loadImage 會從路徑載入影像。

值

定義轉換的 maml 物件。

作者

Microsoft Corporation Microsoft Technical Support

範例

 train <- data.frame(Path = c(system.file("help/figures/RevolutionAnalyticslogo.png", package = "MicrosoftML")), Label = c(TRUE), stringsAsFactors = FALSE)

 # Loads the images from variable Path, resizes the images to 1x1 pixels and trains a neural net.
 model <- rxNeuralNet(
     Label ~ Features,
     data = train,
     mlTransforms = list(
         loadImage(vars = list(Features = "Path")),
         resizeImage(vars = "Features", width = 1, height = 1, resizing = "Aniso"),
         extractPixels(vars = "Features")
         ),
     mlTransformVars = "Path",
     numHiddenNodes = 1,
     numIterations = 1)

 # Featurizes the images from variable Path using the default model, and trains a linear model on the result.
 model <- rxFastLinear(
     Label ~ Features,
     data = train,
     mlTransforms = list(
         loadImage(vars = list(Features = "Path")),
         resizeImage(vars = "Features", width = 224, height = 224), # If dnnModel == "AlexNet", the image has to be resized to 227x227.
         extractPixels(vars = "Features"),
         featurizeImage(var = "Features")
         ),
     mlTransformVars = "Path")