mlnet-metadata.json

[
  {
    "name": "ImageLoaderTransform",
    "schema": {
      "description": "Load images from files.",
      "attributes": [
        { "name": "ImageFolder", "type": "string", "description": "Folder where to search for images" }
      ]
    }
  },
  {
    "name": "ImageScalerTransform",
    "schema": {
      "description": "Scales an image to specified dimensions using one of the three scale types: isotropic with padding, isotropic with cropping or anisotropic. In case of isotropic padding, transparent color is used to pad resulting image.",
      "attributes": [
        { "name": "Width" },
        { "name": "Height" },
        { "name": "Resizing", "type": "ImageResizingTransformer.ResizingKind" },
        { "name": "Anchor", "type": "ImageResizingTransformer.Anchor" }
      ]
    }
  },
  {
    "name": "ImagePixelExtractor",
    "schema": {
      "description": "Scales an image to specified dimensions using one of the three scale types: isotropic with padding, isotropic with cropping or anisotropic. In case of isotropic padding, transparent color is used to pad resulting image.",
      "attributes": [
        { "name": "ColorsToExtract", "type": "ImagePixelExtractingTransformer.ColorBits" },
        { "name": "OrderOfExtraction", "type": "ImagePixelExtractingTransformer.ColorsOrder" },
        { "name": "Planes", "type": "uint8" },
        { "name": "OutputAsFloatArray", "type": "boolean" },
        { "name": "OffsetImage", "type": "float32" },
        { "name": "ScaleImage", "type": "float32" },
        { "name": "InterleavePixelColors", "type": "boolean" }
      ]
    }
  },
  {
    "name": "TensorFlowTransform",
    "schema": {
      "description": "Transforms the data using the TensorFlow model.",
      "attributes": [
        { "name": "IsFrozen", "type": "boolean" },
        { "name": "AddBatchDimensionInput", "type": "boolean" }
      ]
    }
  },
  {
    "name": "TextNormalizerTransform",
    "schema": {
      "description": "A text normalization transform that allows normalizing text case, removing diacritical marks, punctuation marks and/or numbers. The transform operates on text input as well as vector of tokens/text (vector of ReadOnlyMemory).",
      "attributes": [
        { "name": "CaseMode", "type": "TextNormalizingTransformer.CaseMode" },
        { "name": "KeepDiacritics", "type": "boolean" },
        { "name": "KeepPunctuations", "type": "boolean" },
        { "name": "KeepNumbers", "type": "boolean" }
      ]
    }
  },
  {
    "name": "CharToken",
    "schema": {
      "description": "Character-oriented tokenizer where text is considered a sequence of characters.",
      "attributes": [
        { "name": "UseMarkerChars", "type": "boolean" },
        { "name": "IsSeparatorStartEnd", "type": "boolean" }
      ]
    }
  },
  {
    "name": "ConcatTransform",
    "schema": {
      "category": "Tensor",
      "description": "Concatenates one or more columns of the same item type."
    }
  },
  {
    "name": "CopyTransform",
    "schema": {
      "category": "Tensor",
      "description": "Duplicates columns from the dataset."
    }
  },
  {
    "name": "SSAModel",
    "schema": {
      "attributes": [
        { "name": "UseMarkerChars", "type": "boolean" }
      ]
    }
  }
]