mlnet-metadata.json 3.2 KB

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  1. [
  2. {
  3. "name": "ImageLoaderTransform",
  4. "schema": {
  5. "description": "Load images from files.",
  6. "attributes": [
  7. { "name": "ImageFolder", "type": "string", "description": "Folder where to search for images" }
  8. ]
  9. }
  10. },
  11. {
  12. "name": "ImageScalerTransform",
  13. "schema": {
  14. "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.",
  15. "attributes": [
  16. { "name": "Width" },
  17. { "name": "Height" },
  18. { "name": "Resizing", "type": "ImageResizingTransformer.ResizingKind" },
  19. { "name": "Anchor", "type": "ImageResizingTransformer.Anchor" }
  20. ]
  21. }
  22. },
  23. {
  24. "name": "ImagePixelExtractor",
  25. "schema": {
  26. "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.",
  27. "attributes": [
  28. { "name": "ColorsToExtract", "type": "ImagePixelExtractingTransformer.ColorBits" },
  29. { "name": "OrderOfExtraction", "type": "ImagePixelExtractingTransformer.ColorsOrder" },
  30. { "name": "Planes", "type": "uint8" },
  31. { "name": "OutputAsFloatArray", "type": "boolean" },
  32. { "name": "OffsetImage", "type": "float32" },
  33. { "name": "ScaleImage", "type": "float32" },
  34. { "name": "InterleavePixelColors", "type": "boolean" }
  35. ]
  36. }
  37. },
  38. {
  39. "name": "TensorFlowTransform",
  40. "schema": {
  41. "description": "Transforms the data using the TensorFlow model.",
  42. "attributes": [
  43. { "name": "IsFrozen", "type": "boolean" },
  44. { "name": "AddBatchDimensionInput", "type": "boolean" }
  45. ]
  46. }
  47. },
  48. {
  49. "name": "TextNormalizerTransform",
  50. "schema": {
  51. "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).",
  52. "attributes": [
  53. { "name": "CaseMode", "type": "TextNormalizingTransformer.CaseMode" },
  54. { "name": "KeepDiacritics", "type": "boolean" },
  55. { "name": "KeepPunctuations", "type": "boolean" },
  56. { "name": "KeepNumbers", "type": "boolean" }
  57. ]
  58. }
  59. },
  60. {
  61. "name": "CharToken",
  62. "schema": {
  63. "description": "Character-oriented tokenizer where text is considered a sequence of characters.",
  64. "attributes": [
  65. { "name": "UseMarkerChars", "type": "boolean" },
  66. { "name": "IsSeparatorStartEnd", "type": "boolean" }
  67. ]
  68. }
  69. },
  70. {
  71. "name": "ConcatTransform",
  72. "schema": {
  73. "category": "Tensor",
  74. "description": "Concatenates one or more columns of the same item type."
  75. }
  76. },
  77. {
  78. "name": "CopyTransform",
  79. "schema": {
  80. "category": "Tensor",
  81. "description": "Duplicates columns from the dataset."
  82. }
  83. },
  84. {
  85. "name": "SSAModel",
  86. "schema": {
  87. "attributes": [
  88. { "name": "UseMarkerChars", "type": "boolean" }
  89. ]
  90. }
  91. }
  92. ]