[
  {
    "metadataOutputVersion" : "3.0",
    "shortDescription" : "DeepLab is a state-of-art deep learning model for semantic image segmentation, where the goal is to assign semantic labels (e.g., person, dog, cat and so on) to every pixel in the input image.",
    "outputSchema" : [
      {
        "hasShapeFlexibility" : "0",
        "isOptional" : "0",
        "dataType" : "Int32",
        "formattedType" : "MultiArray (Int32 513 × 513)",
        "shortDescription" : "Array of integers of the same size as the input image, where each value represents the class of the corresponding pixel.",
        "shape" : "[513, 513]",
        "name" : "semanticPredictions",
        "type" : "MultiArray"
      }
    ],
    "storagePrecision" : "Float16",
    "modelParameters" : [

    ],
    "author" : "Original Paper: Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen. DeepLabV3+: Liang-Chieh Chen and Yukun Zhu and George Papandreou and Florian Schroff and Hartwig Adam.",
    "specificationVersion" : 3,
    "license" : "Please see https:\/\/github.com\/tensorflow\/tensorflow for license information, and https:\/\/github.com\/tensorflow\/models\/tree\/master\/research\/deeplab for the original source of the model.",
    "computePrecision" : "Float16",
    "isUpdatable" : "0",
    "availability" : {
      "macOS" : "10.14",
      "tvOS" : "12.0",
      "watchOS" : "5.0",
      "iOS" : "12.0",
      "macCatalyst" : "12.0"
    },
    "modelType" : {
      "name" : "MLModelType_neuralNetwork"
    },
    "inputSchema" : [
      {
        "height" : "513",
        "colorspace" : "RGB",
        "isOptional" : "0",
        "width" : "513",
        "isColor" : "1",
        "formattedType" : "Image (Color 513 × 513)",
        "hasSizeFlexibility" : "0",
        "type" : "Image",
        "shortDescription" : "Input image to be segmented",
        "name" : "image"
      }
    ],
    "userDefinedMetadata" : {

    },
    "generatedClassName" : "DeepLabV3FP16",
    "neuralNetworkLayerTypeHistogram" : {
      "PoolingAverage" : 1,
      "Concat" : 1,
      "UnaryThreshold" : 34,
      "Convolution" : 55,
      "ResizeBilinear" : 4,
      "PaddingConstant" : 1,
      "ReduceArgmax" : 1,
      "Add" : 13,
      "BatchNorm" : 55,
      "Multiply" : 1,
      "ActivationLinear" : 68,
      "ActivationReLU" : 37,
      "LoadConstant" : 2
    },
    "method" : "predict"
  }
]