googleapis/lib/vision/v1.dart

// This is a generated file (see the discoveryapis_generator project).

library googleapis.vision.v1;

import 'dart:core' as core;
import 'dart:async' as async;
import 'dart:convert' as convert;

import 'package:_discoveryapis_commons/_discoveryapis_commons.dart' as commons;
import 'package:http/http.dart' as http;

export 'package:_discoveryapis_commons/_discoveryapis_commons.dart'
    show ApiRequestError, DetailedApiRequestError;

const core.String USER_AGENT = 'dart-api-client vision/v1';

/// Integrates Google Vision features, including image labeling, face, logo, and
/// landmark detection, optical character recognition (OCR), and detection of
/// explicit content, into applications.
class VisionApi {
  /// View and manage your data across Google Cloud Platform services
  static const CloudPlatformScope =
      "https://www.googleapis.com/auth/cloud-platform";

  /// Apply machine learning models to understand and label images
  static const CloudVisionScope =
      "https://www.googleapis.com/auth/cloud-vision";

  final commons.ApiRequester _requester;

  ImagesResourceApi get images => new ImagesResourceApi(_requester);

  VisionApi(http.Client client,
      {core.String rootUrl: "https://vision.googleapis.com/",
      core.String servicePath: ""})
      : _requester =
            new commons.ApiRequester(client, rootUrl, servicePath, USER_AGENT);
}

class ImagesResourceApi {
  final commons.ApiRequester _requester;

  ImagesResourceApi(commons.ApiRequester client) : _requester = client;

  /// Run image detection and annotation for a batch of images.
  ///
  /// [request] - The metadata request object.
  ///
  /// Request parameters:
  ///
  /// [$fields] - Selector specifying which fields to include in a partial
  /// response.
  ///
  /// Completes with a [BatchAnnotateImagesResponse].
  ///
  /// Completes with a [commons.ApiRequestError] if the API endpoint returned an
  /// error.
  ///
  /// If the used [http.Client] completes with an error when making a REST call,
  /// this method will complete with the same error.
  async.Future<BatchAnnotateImagesResponse> annotate(
      BatchAnnotateImagesRequest request,
      {core.String $fields}) {
    var _url = null;
    var _queryParams = new core.Map();
    var _uploadMedia = null;
    var _uploadOptions = null;
    var _downloadOptions = commons.DownloadOptions.Metadata;
    var _body = null;

    if (request != null) {
      _body = convert.JSON.encode((request).toJson());
    }
    if ($fields != null) {
      _queryParams["fields"] = [$fields];
    }

    _url = 'v1/images:annotate';

    var _response = _requester.request(_url, "POST",
        body: _body,
        queryParams: _queryParams,
        uploadOptions: _uploadOptions,
        uploadMedia: _uploadMedia,
        downloadOptions: _downloadOptions);
    return _response
        .then((data) => new BatchAnnotateImagesResponse.fromJson(data));
  }
}

/// Request for performing Google Cloud Vision API tasks over a user-provided
/// image, with user-requested features.
class AnnotateImageRequest {
  /// Requested features.
  core.List<Feature> features;

  /// The image to be processed.
  Image image;

  /// Additional context that may accompany the image.
  ImageContext imageContext;

  AnnotateImageRequest();

  AnnotateImageRequest.fromJson(core.Map _json) {
    if (_json.containsKey("features")) {
      features = _json["features"]
          .map((value) => new Feature.fromJson(value))
          .toList();
    }
    if (_json.containsKey("image")) {
      image = new Image.fromJson(_json["image"]);
    }
    if (_json.containsKey("imageContext")) {
      imageContext = new ImageContext.fromJson(_json["imageContext"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (features != null) {
      _json["features"] = features.map((value) => (value).toJson()).toList();
    }
    if (image != null) {
      _json["image"] = (image).toJson();
    }
    if (imageContext != null) {
      _json["imageContext"] = (imageContext).toJson();
    }
    return _json;
  }
}

/// Response to an image annotation request.
class AnnotateImageResponse {
  /// If present, crop hints have completed successfully.
  CropHintsAnnotation cropHintsAnnotation;

  /// If set, represents the error message for the operation.
  /// Note that filled-in image annotations are guaranteed to be
  /// correct, even when `error` is set.
  Status error;

  /// If present, face detection has completed successfully.
  core.List<FaceAnnotation> faceAnnotations;

  /// If present, text (OCR) detection or document (OCR) text detection has
  /// completed successfully.
  /// This annotation provides the structural hierarchy for the OCR detected
  /// text.
  TextAnnotation fullTextAnnotation;

  /// If present, image properties were extracted successfully.
  ImageProperties imagePropertiesAnnotation;

  /// If present, label detection has completed successfully.
  core.List<EntityAnnotation> labelAnnotations;

  /// If present, landmark detection has completed successfully.
  core.List<EntityAnnotation> landmarkAnnotations;

  /// If present, logo detection has completed successfully.
  core.List<EntityAnnotation> logoAnnotations;

  /// If present, safe-search annotation has completed successfully.
  SafeSearchAnnotation safeSearchAnnotation;

  /// If present, text (OCR) detection has completed successfully.
  core.List<EntityAnnotation> textAnnotations;

  /// If present, web detection has completed successfully.
  WebDetection webDetection;

  AnnotateImageResponse();

  AnnotateImageResponse.fromJson(core.Map _json) {
    if (_json.containsKey("cropHintsAnnotation")) {
      cropHintsAnnotation =
          new CropHintsAnnotation.fromJson(_json["cropHintsAnnotation"]);
    }
    if (_json.containsKey("error")) {
      error = new Status.fromJson(_json["error"]);
    }
    if (_json.containsKey("faceAnnotations")) {
      faceAnnotations = _json["faceAnnotations"]
          .map((value) => new FaceAnnotation.fromJson(value))
          .toList();
    }
    if (_json.containsKey("fullTextAnnotation")) {
      fullTextAnnotation =
          new TextAnnotation.fromJson(_json["fullTextAnnotation"]);
    }
    if (_json.containsKey("imagePropertiesAnnotation")) {
      imagePropertiesAnnotation =
          new ImageProperties.fromJson(_json["imagePropertiesAnnotation"]);
    }
    if (_json.containsKey("labelAnnotations")) {
      labelAnnotations = _json["labelAnnotations"]
          .map((value) => new EntityAnnotation.fromJson(value))
          .toList();
    }
    if (_json.containsKey("landmarkAnnotations")) {
      landmarkAnnotations = _json["landmarkAnnotations"]
          .map((value) => new EntityAnnotation.fromJson(value))
          .toList();
    }
    if (_json.containsKey("logoAnnotations")) {
      logoAnnotations = _json["logoAnnotations"]
          .map((value) => new EntityAnnotation.fromJson(value))
          .toList();
    }
    if (_json.containsKey("safeSearchAnnotation")) {
      safeSearchAnnotation =
          new SafeSearchAnnotation.fromJson(_json["safeSearchAnnotation"]);
    }
    if (_json.containsKey("textAnnotations")) {
      textAnnotations = _json["textAnnotations"]
          .map((value) => new EntityAnnotation.fromJson(value))
          .toList();
    }
    if (_json.containsKey("webDetection")) {
      webDetection = new WebDetection.fromJson(_json["webDetection"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (cropHintsAnnotation != null) {
      _json["cropHintsAnnotation"] = (cropHintsAnnotation).toJson();
    }
    if (error != null) {
      _json["error"] = (error).toJson();
    }
    if (faceAnnotations != null) {
      _json["faceAnnotations"] =
          faceAnnotations.map((value) => (value).toJson()).toList();
    }
    if (fullTextAnnotation != null) {
      _json["fullTextAnnotation"] = (fullTextAnnotation).toJson();
    }
    if (imagePropertiesAnnotation != null) {
      _json["imagePropertiesAnnotation"] = (imagePropertiesAnnotation).toJson();
    }
    if (labelAnnotations != null) {
      _json["labelAnnotations"] =
          labelAnnotations.map((value) => (value).toJson()).toList();
    }
    if (landmarkAnnotations != null) {
      _json["landmarkAnnotations"] =
          landmarkAnnotations.map((value) => (value).toJson()).toList();
    }
    if (logoAnnotations != null) {
      _json["logoAnnotations"] =
          logoAnnotations.map((value) => (value).toJson()).toList();
    }
    if (safeSearchAnnotation != null) {
      _json["safeSearchAnnotation"] = (safeSearchAnnotation).toJson();
    }
    if (textAnnotations != null) {
      _json["textAnnotations"] =
          textAnnotations.map((value) => (value).toJson()).toList();
    }
    if (webDetection != null) {
      _json["webDetection"] = (webDetection).toJson();
    }
    return _json;
  }
}

/// Multiple image annotation requests are batched into a single service call.
class BatchAnnotateImagesRequest {
  /// Individual image annotation requests for this batch.
  core.List<AnnotateImageRequest> requests;

  BatchAnnotateImagesRequest();

  BatchAnnotateImagesRequest.fromJson(core.Map _json) {
    if (_json.containsKey("requests")) {
      requests = _json["requests"]
          .map((value) => new AnnotateImageRequest.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (requests != null) {
      _json["requests"] = requests.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Response to a batch image annotation request.
class BatchAnnotateImagesResponse {
  /// Individual responses to image annotation requests within the batch.
  core.List<AnnotateImageResponse> responses;

  BatchAnnotateImagesResponse();

  BatchAnnotateImagesResponse.fromJson(core.Map _json) {
    if (_json.containsKey("responses")) {
      responses = _json["responses"]
          .map((value) => new AnnotateImageResponse.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (responses != null) {
      _json["responses"] = responses.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Logical element on the page.
class Block {
  /// Detected block type (text, image etc) for this block.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown block type.
  /// - "TEXT" : Regular text block.
  /// - "TABLE" : Table block.
  /// - "PICTURE" : Image block.
  /// - "RULER" : Horizontal/vertical line box.
  /// - "BARCODE" : Barcode block.
  core.String blockType;

  /// The bounding box for the block.
  /// The vertices are in the order of top-left, top-right, bottom-right,
  /// bottom-left. When a rotation of the bounding box is detected the rotation
  /// is represented as around the top-left corner as defined when the text is
  /// read in the 'natural' orientation.
  /// For example:
  ///
  /// * when the text is horizontal it might look like:
  ///
  ///         0----1
  ///         |    |
  ///         3----2
  ///
  /// * when it's rotated 180 degrees around the top-left corner it becomes:
  ///
  ///         2----3
  ///         |    |
  ///         1----0
  ///
  ///   and the vertice order will still be (0, 1, 2, 3).
  BoundingPoly boundingBox;

  /// Confidence of the OCR results on the block. Range [0, 1].
  core.double confidence;

  /// List of paragraphs in this block (if this blocks is of type text).
  core.List<Paragraph> paragraphs;

  /// Additional information detected for the block.
  TextProperty property;

  Block();

  Block.fromJson(core.Map _json) {
    if (_json.containsKey("blockType")) {
      blockType = _json["blockType"];
    }
    if (_json.containsKey("boundingBox")) {
      boundingBox = new BoundingPoly.fromJson(_json["boundingBox"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("paragraphs")) {
      paragraphs = _json["paragraphs"]
          .map((value) => new Paragraph.fromJson(value))
          .toList();
    }
    if (_json.containsKey("property")) {
      property = new TextProperty.fromJson(_json["property"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (blockType != null) {
      _json["blockType"] = blockType;
    }
    if (boundingBox != null) {
      _json["boundingBox"] = (boundingBox).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (paragraphs != null) {
      _json["paragraphs"] =
          paragraphs.map((value) => (value).toJson()).toList();
    }
    if (property != null) {
      _json["property"] = (property).toJson();
    }
    return _json;
  }
}

/// A bounding polygon for the detected image annotation.
class BoundingPoly {
  /// The bounding polygon vertices.
  core.List<Vertex> vertices;

  BoundingPoly();

  BoundingPoly.fromJson(core.Map _json) {
    if (_json.containsKey("vertices")) {
      vertices =
          _json["vertices"].map((value) => new Vertex.fromJson(value)).toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (vertices != null) {
      _json["vertices"] = vertices.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Represents a color in the RGBA color space. This representation is designed
/// for simplicity of conversion to/from color representations in various
/// languages over compactness; for example, the fields of this representation
/// can be trivially provided to the constructor of "java.awt.Color" in Java; it
/// can also be trivially provided to UIColor's "+colorWithRed:green:blue:alpha"
/// method in iOS; and, with just a little work, it can be easily formatted into
/// a CSS "rgba()" string in JavaScript, as well. Here are some examples:
///
/// Example (Java):
///
///      import com.google.type.Color;
///
///      // ...
///      public static java.awt.Color fromProto(Color protocolor) {
///        float alpha = protocolor.hasAlpha()
///            ? protocolor.getAlpha().getValue()
///            : 1.0;
///
///        return new java.awt.Color(
///            protocolor.getRed(),
///            protocolor.getGreen(),
///            protocolor.getBlue(),
///            alpha);
///      }
///
///      public static Color toProto(java.awt.Color color) {
///        float red = (float) color.getRed();
///        float green = (float) color.getGreen();
///        float blue = (float) color.getBlue();
///        float denominator = 255.0;
///        Color.Builder resultBuilder =
///            Color
///                .newBuilder()
///                .setRed(red / denominator)
///                .setGreen(green / denominator)
///                .setBlue(blue / denominator);
///        int alpha = color.getAlpha();
///        if (alpha != 255) {
///          result.setAlpha(
///              FloatValue
///                  .newBuilder()
///                  .setValue(((float) alpha) / denominator)
///                  .build());
///        }
///        return resultBuilder.build();
///      }
///      // ...
///
/// Example (iOS / Obj-C):
///
///      // ...
///      static UIColor* fromProto(Color* protocolor) {
///         float red = [protocolor red];
///         float green = [protocolor green];
///         float blue = [protocolor blue];
///         FloatValue* alpha_wrapper = [protocolor alpha];
///         float alpha = 1.0;
///         if (alpha_wrapper != nil) {
///           alpha = [alpha_wrapper value];
///         }
/// return [UIColor colorWithRed:red green:green blue:blue alpha:alpha];
///      }
///
///      static Color* toProto(UIColor* color) {
///          CGFloat red, green, blue, alpha;
///          if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) {
///            return nil;
///          }
///          Color* result = [Color alloc] init];
///          [result setRed:red];
///          [result setGreen:green];
///          [result setBlue:blue];
///          if (alpha <= 0.9999) {
///            [result setAlpha:floatWrapperWithValue(alpha)];
///          }
///          [result autorelease];
///          return result;
///     }
///     // ...
///
///  Example (JavaScript):
///
///     // ...
///
///     var protoToCssColor = function(rgb_color) {
///        var redFrac = rgb_color.red || 0.0;
///        var greenFrac = rgb_color.green || 0.0;
///        var blueFrac = rgb_color.blue || 0.0;
///        var red = Math.floor(redFrac * 255);
///        var green = Math.floor(greenFrac * 255);
///        var blue = Math.floor(blueFrac * 255);
///
///        if (!('alpha' in rgb_color)) {
///           return rgbToCssColor_(red, green, blue);
///        }
///
///        var alphaFrac = rgb_color.alpha.value || 0.0;
///        var rgbParams = [red, green, blue].join(',');
///        return ['rgba(', rgbParams, ',', alphaFrac, ')'].join('');
///     };
///
///     var rgbToCssColor_ = function(red, green, blue) {
///       var rgbNumber = new Number((red << 16) | (green << 8) | blue);
///       var hexString = rgbNumber.toString(16);
///       var missingZeros = 6 - hexString.length;
///       var resultBuilder = ['#'];
///       for (var i = 0; i < missingZeros; i++) {
///          resultBuilder.push('0');
///       }
///       resultBuilder.push(hexString);
///       return resultBuilder.join('');
///     };
///
///     // ...
class Color {
  /// The fraction of this color that should be applied to the pixel. That is,
  /// the final pixel color is defined by the equation:
  ///
  ///   pixel color = alpha * (this color) + (1.0 - alpha) * (background color)
  ///
  /// This means that a value of 1.0 corresponds to a solid color, whereas
  /// a value of 0.0 corresponds to a completely transparent color. This
  /// uses a wrapper message rather than a simple float scalar so that it is
  /// possible to distinguish between a default value and the value being unset.
  /// If omitted, this color object is to be rendered as a solid color
  /// (as if the alpha value had been explicitly given with a value of 1.0).
  core.double alpha;

  /// The amount of blue in the color as a value in the interval [0, 1].
  core.double blue;

  /// The amount of green in the color as a value in the interval [0, 1].
  core.double green;

  /// The amount of red in the color as a value in the interval [0, 1].
  core.double red;

  Color();

  Color.fromJson(core.Map _json) {
    if (_json.containsKey("alpha")) {
      alpha = _json["alpha"];
    }
    if (_json.containsKey("blue")) {
      blue = _json["blue"];
    }
    if (_json.containsKey("green")) {
      green = _json["green"];
    }
    if (_json.containsKey("red")) {
      red = _json["red"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (alpha != null) {
      _json["alpha"] = alpha;
    }
    if (blue != null) {
      _json["blue"] = blue;
    }
    if (green != null) {
      _json["green"] = green;
    }
    if (red != null) {
      _json["red"] = red;
    }
    return _json;
  }
}

/// Color information consists of RGB channels, score, and the fraction of
/// the image that the color occupies in the image.
class ColorInfo {
  /// RGB components of the color.
  Color color;

  /// The fraction of pixels the color occupies in the image.
  /// Value in range [0, 1].
  core.double pixelFraction;

  /// Image-specific score for this color. Value in range [0, 1].
  core.double score;

  ColorInfo();

  ColorInfo.fromJson(core.Map _json) {
    if (_json.containsKey("color")) {
      color = new Color.fromJson(_json["color"]);
    }
    if (_json.containsKey("pixelFraction")) {
      pixelFraction = _json["pixelFraction"];
    }
    if (_json.containsKey("score")) {
      score = _json["score"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (color != null) {
      _json["color"] = (color).toJson();
    }
    if (pixelFraction != null) {
      _json["pixelFraction"] = pixelFraction;
    }
    if (score != null) {
      _json["score"] = score;
    }
    return _json;
  }
}

/// Single crop hint that is used to generate a new crop when serving an image.
class CropHint {
  /// The bounding polygon for the crop region. The coordinates of the bounding
  /// box are in the original image's scale, as returned in `ImageParams`.
  BoundingPoly boundingPoly;

  /// Confidence of this being a salient region.  Range [0, 1].
  core.double confidence;

  /// Fraction of importance of this salient region with respect to the original
  /// image.
  core.double importanceFraction;

  CropHint();

  CropHint.fromJson(core.Map _json) {
    if (_json.containsKey("boundingPoly")) {
      boundingPoly = new BoundingPoly.fromJson(_json["boundingPoly"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("importanceFraction")) {
      importanceFraction = _json["importanceFraction"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (boundingPoly != null) {
      _json["boundingPoly"] = (boundingPoly).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (importanceFraction != null) {
      _json["importanceFraction"] = importanceFraction;
    }
    return _json;
  }
}

/// Set of crop hints that are used to generate new crops when serving images.
class CropHintsAnnotation {
  /// Crop hint results.
  core.List<CropHint> cropHints;

  CropHintsAnnotation();

  CropHintsAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("cropHints")) {
      cropHints = _json["cropHints"]
          .map((value) => new CropHint.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (cropHints != null) {
      _json["cropHints"] = cropHints.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Parameters for crop hints annotation request.
class CropHintsParams {
  /// Aspect ratios in floats, representing the ratio of the width to the height
  /// of the image. For example, if the desired aspect ratio is 4/3, the
  /// corresponding float value should be 1.33333.  If not specified, the
  /// best possible crop is returned. The number of provided aspect ratios is
  /// limited to a maximum of 16; any aspect ratios provided after the 16th are
  /// ignored.
  core.List<core.double> aspectRatios;

  CropHintsParams();

  CropHintsParams.fromJson(core.Map _json) {
    if (_json.containsKey("aspectRatios")) {
      aspectRatios = _json["aspectRatios"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (aspectRatios != null) {
      _json["aspectRatios"] = aspectRatios;
    }
    return _json;
  }
}

/// Detected start or end of a structural component.
class DetectedBreak {
  /// True if break prepends the element.
  core.bool isPrefix;

  /// Detected break type.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown break label type.
  /// - "SPACE" : Regular space.
  /// - "SURE_SPACE" : Sure space (very wide).
  /// - "EOL_SURE_SPACE" : Line-wrapping break.
  /// - "HYPHEN" : End-line hyphen that is not present in text; does not
  /// co-occur with
  /// `SPACE`, `LEADER_SPACE`, or `LINE_BREAK`.
  /// - "LINE_BREAK" : Line break that ends a paragraph.
  core.String type;

  DetectedBreak();

  DetectedBreak.fromJson(core.Map _json) {
    if (_json.containsKey("isPrefix")) {
      isPrefix = _json["isPrefix"];
    }
    if (_json.containsKey("type")) {
      type = _json["type"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (isPrefix != null) {
      _json["isPrefix"] = isPrefix;
    }
    if (type != null) {
      _json["type"] = type;
    }
    return _json;
  }
}

/// Detected language for a structural component.
class DetectedLanguage {
  /// Confidence of detected language. Range [0, 1].
  core.double confidence;

  /// The BCP-47 language code, such as "en-US" or "sr-Latn". For more
  /// information, see
  /// http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
  core.String languageCode;

  DetectedLanguage();

  DetectedLanguage.fromJson(core.Map _json) {
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("languageCode")) {
      languageCode = _json["languageCode"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (languageCode != null) {
      _json["languageCode"] = languageCode;
    }
    return _json;
  }
}

/// Set of dominant colors and their corresponding scores.
class DominantColorsAnnotation {
  /// RGB color values with their score and pixel fraction.
  core.List<ColorInfo> colors;

  DominantColorsAnnotation();

  DominantColorsAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("colors")) {
      colors = _json["colors"]
          .map((value) => new ColorInfo.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (colors != null) {
      _json["colors"] = colors.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Set of detected entity features.
class EntityAnnotation {
  /// Image region to which this entity belongs. Not produced
  /// for `LABEL_DETECTION` features.
  BoundingPoly boundingPoly;

  /// **Deprecated. Use `score` instead.**
  /// The accuracy of the entity detection in an image.
  /// For example, for an image in which the "Eiffel Tower" entity is detected,
  /// this field represents the confidence that there is a tower in the query
  /// image. Range [0, 1].
  core.double confidence;

  /// Entity textual description, expressed in its `locale` language.
  core.String description;

  /// The language code for the locale in which the entity textual
  /// `description` is expressed.
  core.String locale;

  /// The location information for the detected entity. Multiple
  /// `LocationInfo` elements can be present because one location may
  /// indicate the location of the scene in the image, and another location
  /// may indicate the location of the place where the image was taken.
  /// Location information is usually present for landmarks.
  core.List<LocationInfo> locations;

  /// Opaque entity ID. Some IDs may be available in
  /// [Google Knowledge Graph Search
  /// API](https://developers.google.com/knowledge-graph/).
  core.String mid;

  /// Some entities may have optional user-supplied `Property` (name/value)
  /// fields, such a score or string that qualifies the entity.
  core.List<Property> properties;

  /// Overall score of the result. Range [0, 1].
  core.double score;

  /// The relevancy of the ICA (Image Content Annotation) label to the
  /// image. For example, the relevancy of "tower" is likely higher to an image
  /// containing the detected "Eiffel Tower" than to an image containing a
  /// detected distant towering building, even though the confidence that
  /// there is a tower in each image may be the same. Range [0, 1].
  core.double topicality;

  EntityAnnotation();

  EntityAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("boundingPoly")) {
      boundingPoly = new BoundingPoly.fromJson(_json["boundingPoly"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("description")) {
      description = _json["description"];
    }
    if (_json.containsKey("locale")) {
      locale = _json["locale"];
    }
    if (_json.containsKey("locations")) {
      locations = _json["locations"]
          .map((value) => new LocationInfo.fromJson(value))
          .toList();
    }
    if (_json.containsKey("mid")) {
      mid = _json["mid"];
    }
    if (_json.containsKey("properties")) {
      properties = _json["properties"]
          .map((value) => new Property.fromJson(value))
          .toList();
    }
    if (_json.containsKey("score")) {
      score = _json["score"];
    }
    if (_json.containsKey("topicality")) {
      topicality = _json["topicality"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (boundingPoly != null) {
      _json["boundingPoly"] = (boundingPoly).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (description != null) {
      _json["description"] = description;
    }
    if (locale != null) {
      _json["locale"] = locale;
    }
    if (locations != null) {
      _json["locations"] = locations.map((value) => (value).toJson()).toList();
    }
    if (mid != null) {
      _json["mid"] = mid;
    }
    if (properties != null) {
      _json["properties"] =
          properties.map((value) => (value).toJson()).toList();
    }
    if (score != null) {
      _json["score"] = score;
    }
    if (topicality != null) {
      _json["topicality"] = topicality;
    }
    return _json;
  }
}

/// A face annotation object contains the results of face detection.
class FaceAnnotation {
  /// Anger likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String angerLikelihood;

  /// Blurred likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String blurredLikelihood;

  /// The bounding polygon around the face. The coordinates of the bounding box
  /// are in the original image's scale, as returned in `ImageParams`.
  /// The bounding box is computed to "frame" the face in accordance with human
  /// expectations. It is based on the landmarker results.
  /// Note that one or more x and/or y coordinates may not be generated in the
  /// `BoundingPoly` (the polygon will be unbounded) if only a partial face
  /// appears in the image to be annotated.
  BoundingPoly boundingPoly;

  /// Detection confidence. Range [0, 1].
  core.double detectionConfidence;

  /// The `fd_bounding_poly` bounding polygon is tighter than the
  /// `boundingPoly`, and encloses only the skin part of the face. Typically, it
  /// is used to eliminate the face from any image analysis that detects the
  /// "amount of skin" visible in an image. It is not based on the
  /// landmarker results, only on the initial face detection, hence
  /// the <code>fd</code> (face detection) prefix.
  BoundingPoly fdBoundingPoly;

  /// Headwear likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String headwearLikelihood;

  /// Joy likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String joyLikelihood;

  /// Face landmarking confidence. Range [0, 1].
  core.double landmarkingConfidence;

  /// Detected face landmarks.
  core.List<Landmark> landmarks;

  /// Yaw angle, which indicates the leftward/rightward angle that the face is
  /// pointing relative to the vertical plane perpendicular to the image. Range
  /// [-180,180].
  core.double panAngle;

  /// Roll angle, which indicates the amount of clockwise/anti-clockwise
  /// rotation
  /// of the face relative to the image vertical about the axis perpendicular to
  /// the face. Range [-180,180].
  core.double rollAngle;

  /// Sorrow likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String sorrowLikelihood;

  /// Surprise likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String surpriseLikelihood;

  /// Pitch angle, which indicates the upwards/downwards angle that the face is
  /// pointing relative to the image's horizontal plane. Range [-180,180].
  core.double tiltAngle;

  /// Under-exposed likelihood.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String underExposedLikelihood;

  FaceAnnotation();

  FaceAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("angerLikelihood")) {
      angerLikelihood = _json["angerLikelihood"];
    }
    if (_json.containsKey("blurredLikelihood")) {
      blurredLikelihood = _json["blurredLikelihood"];
    }
    if (_json.containsKey("boundingPoly")) {
      boundingPoly = new BoundingPoly.fromJson(_json["boundingPoly"]);
    }
    if (_json.containsKey("detectionConfidence")) {
      detectionConfidence = _json["detectionConfidence"];
    }
    if (_json.containsKey("fdBoundingPoly")) {
      fdBoundingPoly = new BoundingPoly.fromJson(_json["fdBoundingPoly"]);
    }
    if (_json.containsKey("headwearLikelihood")) {
      headwearLikelihood = _json["headwearLikelihood"];
    }
    if (_json.containsKey("joyLikelihood")) {
      joyLikelihood = _json["joyLikelihood"];
    }
    if (_json.containsKey("landmarkingConfidence")) {
      landmarkingConfidence = _json["landmarkingConfidence"];
    }
    if (_json.containsKey("landmarks")) {
      landmarks = _json["landmarks"]
          .map((value) => new Landmark.fromJson(value))
          .toList();
    }
    if (_json.containsKey("panAngle")) {
      panAngle = _json["panAngle"];
    }
    if (_json.containsKey("rollAngle")) {
      rollAngle = _json["rollAngle"];
    }
    if (_json.containsKey("sorrowLikelihood")) {
      sorrowLikelihood = _json["sorrowLikelihood"];
    }
    if (_json.containsKey("surpriseLikelihood")) {
      surpriseLikelihood = _json["surpriseLikelihood"];
    }
    if (_json.containsKey("tiltAngle")) {
      tiltAngle = _json["tiltAngle"];
    }
    if (_json.containsKey("underExposedLikelihood")) {
      underExposedLikelihood = _json["underExposedLikelihood"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (angerLikelihood != null) {
      _json["angerLikelihood"] = angerLikelihood;
    }
    if (blurredLikelihood != null) {
      _json["blurredLikelihood"] = blurredLikelihood;
    }
    if (boundingPoly != null) {
      _json["boundingPoly"] = (boundingPoly).toJson();
    }
    if (detectionConfidence != null) {
      _json["detectionConfidence"] = detectionConfidence;
    }
    if (fdBoundingPoly != null) {
      _json["fdBoundingPoly"] = (fdBoundingPoly).toJson();
    }
    if (headwearLikelihood != null) {
      _json["headwearLikelihood"] = headwearLikelihood;
    }
    if (joyLikelihood != null) {
      _json["joyLikelihood"] = joyLikelihood;
    }
    if (landmarkingConfidence != null) {
      _json["landmarkingConfidence"] = landmarkingConfidence;
    }
    if (landmarks != null) {
      _json["landmarks"] = landmarks.map((value) => (value).toJson()).toList();
    }
    if (panAngle != null) {
      _json["panAngle"] = panAngle;
    }
    if (rollAngle != null) {
      _json["rollAngle"] = rollAngle;
    }
    if (sorrowLikelihood != null) {
      _json["sorrowLikelihood"] = sorrowLikelihood;
    }
    if (surpriseLikelihood != null) {
      _json["surpriseLikelihood"] = surpriseLikelihood;
    }
    if (tiltAngle != null) {
      _json["tiltAngle"] = tiltAngle;
    }
    if (underExposedLikelihood != null) {
      _json["underExposedLikelihood"] = underExposedLikelihood;
    }
    return _json;
  }
}

/// The type of Google Cloud Vision API detection to perform, and the maximum
/// number of results to return for that type. Multiple `Feature` objects can
/// be specified in the `features` list.
class Feature {
  /// Maximum number of results of this type. Does not apply to
  /// `TEXT_DETECTION`, `DOCUMENT_TEXT_DETECTION`, or `CROP_HINTS`.
  core.int maxResults;

  /// Model to use for the feature.
  /// Supported values: "builtin/stable" (the default if unset) and
  /// "builtin/latest".
  core.String model;

  /// The feature type.
  /// Possible string values are:
  /// - "TYPE_UNSPECIFIED" : Unspecified feature type.
  /// - "FACE_DETECTION" : Run face detection.
  /// - "LANDMARK_DETECTION" : Run landmark detection.
  /// - "LOGO_DETECTION" : Run logo detection.
  /// - "LABEL_DETECTION" : Run label detection.
  /// - "TEXT_DETECTION" : Run text detection / optical character recognition
  /// (OCR). Text detection
  /// is optimized for areas of text within a larger image; if the image is
  /// a document, use `DOCUMENT_TEXT_DETECTION` instead.
  /// - "DOCUMENT_TEXT_DETECTION" : Run dense text document OCR. Takes
  /// precedence when both
  /// `DOCUMENT_TEXT_DETECTION` and `TEXT_DETECTION` are present.
  /// - "SAFE_SEARCH_DETECTION" : Run Safe Search to detect potentially unsafe
  /// or undesirable content.
  /// - "IMAGE_PROPERTIES" : Compute a set of image properties, such as the
  /// image's dominant colors.
  /// - "CROP_HINTS" : Run crop hints.
  /// - "WEB_DETECTION" : Run web detection.
  core.String type;

  Feature();

  Feature.fromJson(core.Map _json) {
    if (_json.containsKey("maxResults")) {
      maxResults = _json["maxResults"];
    }
    if (_json.containsKey("model")) {
      model = _json["model"];
    }
    if (_json.containsKey("type")) {
      type = _json["type"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (maxResults != null) {
      _json["maxResults"] = maxResults;
    }
    if (model != null) {
      _json["model"] = model;
    }
    if (type != null) {
      _json["type"] = type;
    }
    return _json;
  }
}

/// Client image to perform Google Cloud Vision API tasks over.
class Image {
  /// Image content, represented as a stream of bytes.
  /// Note: As with all `bytes` fields, protobuffers use a pure binary
  /// representation, whereas JSON representations use base64.
  core.String content;
  core.List<core.int> get contentAsBytes {
    return convert.BASE64.decode(content);
  }

  void set contentAsBytes(core.List<core.int> _bytes) {
    content =
        convert.BASE64.encode(_bytes).replaceAll("/", "_").replaceAll("+", "-");
  }

  /// Google Cloud Storage image location, or publicly-accessible image
  /// URL. If both `content` and `source` are provided for an image, `content`
  /// takes precedence and is used to perform the image annotation request.
  ImageSource source;

  Image();

  Image.fromJson(core.Map _json) {
    if (_json.containsKey("content")) {
      content = _json["content"];
    }
    if (_json.containsKey("source")) {
      source = new ImageSource.fromJson(_json["source"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (content != null) {
      _json["content"] = content;
    }
    if (source != null) {
      _json["source"] = (source).toJson();
    }
    return _json;
  }
}

/// Image context and/or feature-specific parameters.
class ImageContext {
  /// Parameters for crop hints annotation request.
  CropHintsParams cropHintsParams;

  /// List of languages to use for TEXT_DETECTION. In most cases, an empty value
  /// yields the best results since it enables automatic language detection. For
  /// languages based on the Latin alphabet, setting `language_hints` is not
  /// needed. In rare cases, when the language of the text in the image is
  /// known,
  /// setting a hint will help get better results (although it will be a
  /// significant hindrance if the hint is wrong). Text detection returns an
  /// error if one or more of the specified languages is not one of the
  /// [supported languages](/vision/docs/languages).
  core.List<core.String> languageHints;

  /// lat/long rectangle that specifies the location of the image.
  LatLongRect latLongRect;

  /// Parameters for web detection.
  WebDetectionParams webDetectionParams;

  ImageContext();

  ImageContext.fromJson(core.Map _json) {
    if (_json.containsKey("cropHintsParams")) {
      cropHintsParams = new CropHintsParams.fromJson(_json["cropHintsParams"]);
    }
    if (_json.containsKey("languageHints")) {
      languageHints = _json["languageHints"];
    }
    if (_json.containsKey("latLongRect")) {
      latLongRect = new LatLongRect.fromJson(_json["latLongRect"]);
    }
    if (_json.containsKey("webDetectionParams")) {
      webDetectionParams =
          new WebDetectionParams.fromJson(_json["webDetectionParams"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (cropHintsParams != null) {
      _json["cropHintsParams"] = (cropHintsParams).toJson();
    }
    if (languageHints != null) {
      _json["languageHints"] = languageHints;
    }
    if (latLongRect != null) {
      _json["latLongRect"] = (latLongRect).toJson();
    }
    if (webDetectionParams != null) {
      _json["webDetectionParams"] = (webDetectionParams).toJson();
    }
    return _json;
  }
}

/// Stores image properties, such as dominant colors.
class ImageProperties {
  /// If present, dominant colors completed successfully.
  DominantColorsAnnotation dominantColors;

  ImageProperties();

  ImageProperties.fromJson(core.Map _json) {
    if (_json.containsKey("dominantColors")) {
      dominantColors =
          new DominantColorsAnnotation.fromJson(_json["dominantColors"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (dominantColors != null) {
      _json["dominantColors"] = (dominantColors).toJson();
    }
    return _json;
  }
}

/// External image source (Google Cloud Storage or web URL image location).
class ImageSource {
  /// **Use `image_uri` instead.**
  ///
  /// The Google Cloud Storage  URI of the form
  /// `gs://bucket_name/object_name`. Object versioning is not supported. See
  /// [Google Cloud Storage Request
  /// URIs](https://cloud.google.com/storage/docs/reference-uris) for more info.
  core.String gcsImageUri;

  /// The URI of the source image. Can be either:
  ///
  /// 1. A Google Cloud Storage URI of the form
  /// `gs://bucket_name/object_name`. Object versioning is not supported. See
  ///    [Google Cloud Storage Request
  ///    URIs](https://cloud.google.com/storage/docs/reference-uris) for more
  ///    info.
  ///
  /// 2. A publicly-accessible image HTTP/HTTPS URL. When fetching images from
  ///    HTTP/HTTPS URLs, Google cannot guarantee that the request will be
  ///    completed. Your request may fail if the specified host denies the
  /// request (e.g. due to request throttling or DOS prevention), or if Google
  ///    throttles requests to the site for abuse prevention. You should not
  ///    depend on externally-hosted images for production applications.
  ///
  /// When both `gcs_image_uri` and `image_uri` are specified, `image_uri` takes
  /// precedence.
  core.String imageUri;

  ImageSource();

  ImageSource.fromJson(core.Map _json) {
    if (_json.containsKey("gcsImageUri")) {
      gcsImageUri = _json["gcsImageUri"];
    }
    if (_json.containsKey("imageUri")) {
      imageUri = _json["imageUri"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (gcsImageUri != null) {
      _json["gcsImageUri"] = gcsImageUri;
    }
    if (imageUri != null) {
      _json["imageUri"] = imageUri;
    }
    return _json;
  }
}

/// A face-specific landmark (for example, a face feature).
class Landmark {
  /// Face landmark position.
  Position position;

  /// Face landmark type.
  /// Possible string values are:
  /// - "UNKNOWN_LANDMARK" : Unknown face landmark detected. Should not be
  /// filled.
  /// - "LEFT_EYE" : Left eye.
  /// - "RIGHT_EYE" : Right eye.
  /// - "LEFT_OF_LEFT_EYEBROW" : Left of left eyebrow.
  /// - "RIGHT_OF_LEFT_EYEBROW" : Right of left eyebrow.
  /// - "LEFT_OF_RIGHT_EYEBROW" : Left of right eyebrow.
  /// - "RIGHT_OF_RIGHT_EYEBROW" : Right of right eyebrow.
  /// - "MIDPOINT_BETWEEN_EYES" : Midpoint between eyes.
  /// - "NOSE_TIP" : Nose tip.
  /// - "UPPER_LIP" : Upper lip.
  /// - "LOWER_LIP" : Lower lip.
  /// - "MOUTH_LEFT" : Mouth left.
  /// - "MOUTH_RIGHT" : Mouth right.
  /// - "MOUTH_CENTER" : Mouth center.
  /// - "NOSE_BOTTOM_RIGHT" : Nose, bottom right.
  /// - "NOSE_BOTTOM_LEFT" : Nose, bottom left.
  /// - "NOSE_BOTTOM_CENTER" : Nose, bottom center.
  /// - "LEFT_EYE_TOP_BOUNDARY" : Left eye, top boundary.
  /// - "LEFT_EYE_RIGHT_CORNER" : Left eye, right corner.
  /// - "LEFT_EYE_BOTTOM_BOUNDARY" : Left eye, bottom boundary.
  /// - "LEFT_EYE_LEFT_CORNER" : Left eye, left corner.
  /// - "RIGHT_EYE_TOP_BOUNDARY" : Right eye, top boundary.
  /// - "RIGHT_EYE_RIGHT_CORNER" : Right eye, right corner.
  /// - "RIGHT_EYE_BOTTOM_BOUNDARY" : Right eye, bottom boundary.
  /// - "RIGHT_EYE_LEFT_CORNER" : Right eye, left corner.
  /// - "LEFT_EYEBROW_UPPER_MIDPOINT" : Left eyebrow, upper midpoint.
  /// - "RIGHT_EYEBROW_UPPER_MIDPOINT" : Right eyebrow, upper midpoint.
  /// - "LEFT_EAR_TRAGION" : Left ear tragion.
  /// - "RIGHT_EAR_TRAGION" : Right ear tragion.
  /// - "LEFT_EYE_PUPIL" : Left eye pupil.
  /// - "RIGHT_EYE_PUPIL" : Right eye pupil.
  /// - "FOREHEAD_GLABELLA" : Forehead glabella.
  /// - "CHIN_GNATHION" : Chin gnathion.
  /// - "CHIN_LEFT_GONION" : Chin left gonion.
  /// - "CHIN_RIGHT_GONION" : Chin right gonion.
  core.String type;

  Landmark();

  Landmark.fromJson(core.Map _json) {
    if (_json.containsKey("position")) {
      position = new Position.fromJson(_json["position"]);
    }
    if (_json.containsKey("type")) {
      type = _json["type"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (position != null) {
      _json["position"] = (position).toJson();
    }
    if (type != null) {
      _json["type"] = type;
    }
    return _json;
  }
}

/// An object representing a latitude/longitude pair. This is expressed as a
/// pair
/// of doubles representing degrees latitude and degrees longitude. Unless
/// specified otherwise, this must conform to the
/// <a href="http://www.unoosa.org/pdf/icg/2012/template/WGS_84.pdf">WGS84
/// standard</a>. Values must be within normalized ranges.
class LatLng {
  /// The latitude in degrees. It must be in the range [-90.0, +90.0].
  core.double latitude;

  /// The longitude in degrees. It must be in the range [-180.0, +180.0].
  core.double longitude;

  LatLng();

  LatLng.fromJson(core.Map _json) {
    if (_json.containsKey("latitude")) {
      latitude = _json["latitude"];
    }
    if (_json.containsKey("longitude")) {
      longitude = _json["longitude"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (latitude != null) {
      _json["latitude"] = latitude;
    }
    if (longitude != null) {
      _json["longitude"] = longitude;
    }
    return _json;
  }
}

/// Rectangle determined by min and max `LatLng` pairs.
class LatLongRect {
  /// Max lat/long pair.
  LatLng maxLatLng;

  /// Min lat/long pair.
  LatLng minLatLng;

  LatLongRect();

  LatLongRect.fromJson(core.Map _json) {
    if (_json.containsKey("maxLatLng")) {
      maxLatLng = new LatLng.fromJson(_json["maxLatLng"]);
    }
    if (_json.containsKey("minLatLng")) {
      minLatLng = new LatLng.fromJson(_json["minLatLng"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (maxLatLng != null) {
      _json["maxLatLng"] = (maxLatLng).toJson();
    }
    if (minLatLng != null) {
      _json["minLatLng"] = (minLatLng).toJson();
    }
    return _json;
  }
}

/// Detected entity location information.
class LocationInfo {
  /// lat/long location coordinates.
  LatLng latLng;

  LocationInfo();

  LocationInfo.fromJson(core.Map _json) {
    if (_json.containsKey("latLng")) {
      latLng = new LatLng.fromJson(_json["latLng"]);
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (latLng != null) {
      _json["latLng"] = (latLng).toJson();
    }
    return _json;
  }
}

/// Detected page from OCR.
class Page {
  /// List of blocks of text, images etc on this page.
  core.List<Block> blocks;

  /// Confidence of the OCR results on the page. Range [0, 1].
  core.double confidence;

  /// Page height in pixels.
  core.int height;

  /// Additional information detected on the page.
  TextProperty property;

  /// Page width in pixels.
  core.int width;

  Page();

  Page.fromJson(core.Map _json) {
    if (_json.containsKey("blocks")) {
      blocks =
          _json["blocks"].map((value) => new Block.fromJson(value)).toList();
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("height")) {
      height = _json["height"];
    }
    if (_json.containsKey("property")) {
      property = new TextProperty.fromJson(_json["property"]);
    }
    if (_json.containsKey("width")) {
      width = _json["width"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (blocks != null) {
      _json["blocks"] = blocks.map((value) => (value).toJson()).toList();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (height != null) {
      _json["height"] = height;
    }
    if (property != null) {
      _json["property"] = (property).toJson();
    }
    if (width != null) {
      _json["width"] = width;
    }
    return _json;
  }
}

/// Structural unit of text representing a number of words in certain order.
class Paragraph {
  /// The bounding box for the paragraph.
  /// The vertices are in the order of top-left, top-right, bottom-right,
  /// bottom-left. When a rotation of the bounding box is detected the rotation
  /// is represented as around the top-left corner as defined when the text is
  /// read in the 'natural' orientation.
  /// For example:
  ///   * when the text is horizontal it might look like:
  ///      0----1
  ///      |    |
  ///      3----2
  ///   * when it's rotated 180 degrees around the top-left corner it becomes:
  ///      2----3
  ///      |    |
  ///      1----0
  ///   and the vertice order will still be (0, 1, 2, 3).
  BoundingPoly boundingBox;

  /// Confidence of the OCR results for the paragraph. Range [0, 1].
  core.double confidence;

  /// Additional information detected for the paragraph.
  TextProperty property;

  /// List of words in this paragraph.
  core.List<Word> words;

  Paragraph();

  Paragraph.fromJson(core.Map _json) {
    if (_json.containsKey("boundingBox")) {
      boundingBox = new BoundingPoly.fromJson(_json["boundingBox"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("property")) {
      property = new TextProperty.fromJson(_json["property"]);
    }
    if (_json.containsKey("words")) {
      words = _json["words"].map((value) => new Word.fromJson(value)).toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (boundingBox != null) {
      _json["boundingBox"] = (boundingBox).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (property != null) {
      _json["property"] = (property).toJson();
    }
    if (words != null) {
      _json["words"] = words.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// A 3D position in the image, used primarily for Face detection landmarks.
/// A valid Position must have both x and y coordinates.
/// The position coordinates are in the same scale as the original image.
class Position {
  /// X coordinate.
  core.double x;

  /// Y coordinate.
  core.double y;

  /// Z coordinate (or depth).
  core.double z;

  Position();

  Position.fromJson(core.Map _json) {
    if (_json.containsKey("x")) {
      x = _json["x"];
    }
    if (_json.containsKey("y")) {
      y = _json["y"];
    }
    if (_json.containsKey("z")) {
      z = _json["z"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (x != null) {
      _json["x"] = x;
    }
    if (y != null) {
      _json["y"] = y;
    }
    if (z != null) {
      _json["z"] = z;
    }
    return _json;
  }
}

/// A `Property` consists of a user-supplied name/value pair.
class Property {
  /// Name of the property.
  core.String name;

  /// Value of numeric properties.
  core.String uint64Value;

  /// Value of the property.
  core.String value;

  Property();

  Property.fromJson(core.Map _json) {
    if (_json.containsKey("name")) {
      name = _json["name"];
    }
    if (_json.containsKey("uint64Value")) {
      uint64Value = _json["uint64Value"];
    }
    if (_json.containsKey("value")) {
      value = _json["value"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (name != null) {
      _json["name"] = name;
    }
    if (uint64Value != null) {
      _json["uint64Value"] = uint64Value;
    }
    if (value != null) {
      _json["value"] = value;
    }
    return _json;
  }
}

/// Set of features pertaining to the image, computed by computer vision
/// methods over safe-search verticals (for example, adult, spoof, medical,
/// violence).
class SafeSearchAnnotation {
  /// Represents the adult content likelihood for the image. Adult content may
  /// contain elements such as nudity, pornographic images or cartoons, or
  /// sexual activities.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String adult;

  /// Likelihood that this is a medical image.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String medical;

  /// Likelihood that the request image contains racy content. Racy content may
  /// include (but is not limited to) skimpy or sheer clothing, strategically
  /// covered nudity, lewd or provocative poses, or close-ups of sensitive
  /// body areas.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String racy;

  /// Spoof likelihood. The likelihood that an modification
  /// was made to the image's canonical version to make it appear
  /// funny or offensive.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String spoof;

  /// Likelihood that this image contains violent content.
  /// Possible string values are:
  /// - "UNKNOWN" : Unknown likelihood.
  /// - "VERY_UNLIKELY" : It is very unlikely that the image belongs to the
  /// specified vertical.
  /// - "UNLIKELY" : It is unlikely that the image belongs to the specified
  /// vertical.
  /// - "POSSIBLE" : It is possible that the image belongs to the specified
  /// vertical.
  /// - "LIKELY" : It is likely that the image belongs to the specified
  /// vertical.
  /// - "VERY_LIKELY" : It is very likely that the image belongs to the
  /// specified vertical.
  core.String violence;

  SafeSearchAnnotation();

  SafeSearchAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("adult")) {
      adult = _json["adult"];
    }
    if (_json.containsKey("medical")) {
      medical = _json["medical"];
    }
    if (_json.containsKey("racy")) {
      racy = _json["racy"];
    }
    if (_json.containsKey("spoof")) {
      spoof = _json["spoof"];
    }
    if (_json.containsKey("violence")) {
      violence = _json["violence"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (adult != null) {
      _json["adult"] = adult;
    }
    if (medical != null) {
      _json["medical"] = medical;
    }
    if (racy != null) {
      _json["racy"] = racy;
    }
    if (spoof != null) {
      _json["spoof"] = spoof;
    }
    if (violence != null) {
      _json["violence"] = violence;
    }
    return _json;
  }
}

/// The `Status` type defines a logical error model that is suitable for
/// different
/// programming environments, including REST APIs and RPC APIs. It is used by
/// [gRPC](https://github.com/grpc). The error model is designed to be:
///
/// - Simple to use and understand for most users
/// - Flexible enough to meet unexpected needs
///
/// # Overview
///
/// The `Status` message contains three pieces of data: error code, error
/// message,
/// and error details. The error code should be an enum value of
/// google.rpc.Code, but it may accept additional error codes if needed.  The
/// error message should be a developer-facing English message that helps
/// developers *understand* and *resolve* the error. If a localized user-facing
/// error message is needed, put the localized message in the error details or
/// localize it in the client. The optional error details may contain arbitrary
/// information about the error. There is a predefined set of error detail types
/// in the package `google.rpc` that can be used for common error conditions.
///
/// # Language mapping
///
/// The `Status` message is the logical representation of the error model, but
/// it
/// is not necessarily the actual wire format. When the `Status` message is
/// exposed in different client libraries and different wire protocols, it can
/// be
/// mapped differently. For example, it will likely be mapped to some exceptions
/// in Java, but more likely mapped to some error codes in C.
///
/// # Other uses
///
/// The error model and the `Status` message can be used in a variety of
/// environments, either with or without APIs, to provide a
/// consistent developer experience across different environments.
///
/// Example uses of this error model include:
///
/// - Partial errors. If a service needs to return partial errors to the client,
/// it may embed the `Status` in the normal response to indicate the partial
///     errors.
///
/// - Workflow errors. A typical workflow has multiple steps. Each step may
///     have a `Status` message for error reporting.
///
/// - Batch operations. If a client uses batch request and batch response, the
///     `Status` message should be used directly inside batch response, one for
///     each error sub-response.
///
/// - Asynchronous operations. If an API call embeds asynchronous operation
///     results in its response, the status of those operations should be
///     represented directly using the `Status` message.
///
/// - Logging. If some API errors are stored in logs, the message `Status` could
/// be used directly after any stripping needed for security/privacy reasons.
class Status {
  /// The status code, which should be an enum value of google.rpc.Code.
  core.int code;

  /// A list of messages that carry the error details.  There is a common set of
  /// message types for APIs to use.
  ///
  /// The values for Object must be JSON objects. It can consist of `num`,
  /// `String`, `bool` and `null` as well as `Map` and `List` values.
  core.List<core.Map<core.String, core.Object>> details;

  /// A developer-facing error message, which should be in English. Any
  /// user-facing error message should be localized and sent in the
  /// google.rpc.Status.details field, or localized by the client.
  core.String message;

  Status();

  Status.fromJson(core.Map _json) {
    if (_json.containsKey("code")) {
      code = _json["code"];
    }
    if (_json.containsKey("details")) {
      details = _json["details"];
    }
    if (_json.containsKey("message")) {
      message = _json["message"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (code != null) {
      _json["code"] = code;
    }
    if (details != null) {
      _json["details"] = details;
    }
    if (message != null) {
      _json["message"] = message;
    }
    return _json;
  }
}

/// A single symbol representation.
class Symbol {
  /// The bounding box for the symbol.
  /// The vertices are in the order of top-left, top-right, bottom-right,
  /// bottom-left. When a rotation of the bounding box is detected the rotation
  /// is represented as around the top-left corner as defined when the text is
  /// read in the 'natural' orientation.
  /// For example:
  ///   * when the text is horizontal it might look like:
  ///      0----1
  ///      |    |
  ///      3----2
  ///   * when it's rotated 180 degrees around the top-left corner it becomes:
  ///      2----3
  ///      |    |
  ///      1----0
  ///   and the vertice order will still be (0, 1, 2, 3).
  BoundingPoly boundingBox;

  /// Confidence of the OCR results for the symbol. Range [0, 1].
  core.double confidence;

  /// Additional information detected for the symbol.
  TextProperty property;

  /// The actual UTF-8 representation of the symbol.
  core.String text;

  Symbol();

  Symbol.fromJson(core.Map _json) {
    if (_json.containsKey("boundingBox")) {
      boundingBox = new BoundingPoly.fromJson(_json["boundingBox"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("property")) {
      property = new TextProperty.fromJson(_json["property"]);
    }
    if (_json.containsKey("text")) {
      text = _json["text"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (boundingBox != null) {
      _json["boundingBox"] = (boundingBox).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (property != null) {
      _json["property"] = (property).toJson();
    }
    if (text != null) {
      _json["text"] = text;
    }
    return _json;
  }
}

/// TextAnnotation contains a structured representation of OCR extracted text.
/// The hierarchy of an OCR extracted text structure is like this:
///     TextAnnotation -> Page -> Block -> Paragraph -> Word -> Symbol
/// Each structural component, starting from Page, may further have their own
/// properties. Properties describe detected languages, breaks etc.. Please
/// refer
/// to the TextAnnotation.TextProperty message definition below for more
/// detail.
class TextAnnotation {
  /// List of pages detected by OCR.
  core.List<Page> pages;

  /// UTF-8 text detected on the pages.
  core.String text;

  TextAnnotation();

  TextAnnotation.fromJson(core.Map _json) {
    if (_json.containsKey("pages")) {
      pages = _json["pages"].map((value) => new Page.fromJson(value)).toList();
    }
    if (_json.containsKey("text")) {
      text = _json["text"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (pages != null) {
      _json["pages"] = pages.map((value) => (value).toJson()).toList();
    }
    if (text != null) {
      _json["text"] = text;
    }
    return _json;
  }
}

/// Additional information detected on the structural component.
class TextProperty {
  /// Detected start or end of a text segment.
  DetectedBreak detectedBreak;

  /// A list of detected languages together with confidence.
  core.List<DetectedLanguage> detectedLanguages;

  TextProperty();

  TextProperty.fromJson(core.Map _json) {
    if (_json.containsKey("detectedBreak")) {
      detectedBreak = new DetectedBreak.fromJson(_json["detectedBreak"]);
    }
    if (_json.containsKey("detectedLanguages")) {
      detectedLanguages = _json["detectedLanguages"]
          .map((value) => new DetectedLanguage.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (detectedBreak != null) {
      _json["detectedBreak"] = (detectedBreak).toJson();
    }
    if (detectedLanguages != null) {
      _json["detectedLanguages"] =
          detectedLanguages.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// A vertex represents a 2D point in the image.
/// NOTE: the vertex coordinates are in the same scale as the original image.
class Vertex {
  /// X coordinate.
  core.int x;

  /// Y coordinate.
  core.int y;

  Vertex();

  Vertex.fromJson(core.Map _json) {
    if (_json.containsKey("x")) {
      x = _json["x"];
    }
    if (_json.containsKey("y")) {
      y = _json["y"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (x != null) {
      _json["x"] = x;
    }
    if (y != null) {
      _json["y"] = y;
    }
    return _json;
  }
}

/// Relevant information for the image from the Internet.
class WebDetection {
  /// Best guess text labels for the request image.
  core.List<WebLabel> bestGuessLabels;

  /// Fully matching images from the Internet.
  /// Can include resized copies of the query image.
  core.List<WebImage> fullMatchingImages;

  /// Web pages containing the matching images from the Internet.
  core.List<WebPage> pagesWithMatchingImages;

  /// Partial matching images from the Internet.
  /// Those images are similar enough to share some key-point features. For
  /// example an original image will likely have partial matching for its crops.
  core.List<WebImage> partialMatchingImages;

  /// The visually similar image results.
  core.List<WebImage> visuallySimilarImages;

  /// Deduced entities from similar images on the Internet.
  core.List<WebEntity> webEntities;

  WebDetection();

  WebDetection.fromJson(core.Map _json) {
    if (_json.containsKey("bestGuessLabels")) {
      bestGuessLabels = _json["bestGuessLabels"]
          .map((value) => new WebLabel.fromJson(value))
          .toList();
    }
    if (_json.containsKey("fullMatchingImages")) {
      fullMatchingImages = _json["fullMatchingImages"]
          .map((value) => new WebImage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("pagesWithMatchingImages")) {
      pagesWithMatchingImages = _json["pagesWithMatchingImages"]
          .map((value) => new WebPage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("partialMatchingImages")) {
      partialMatchingImages = _json["partialMatchingImages"]
          .map((value) => new WebImage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("visuallySimilarImages")) {
      visuallySimilarImages = _json["visuallySimilarImages"]
          .map((value) => new WebImage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("webEntities")) {
      webEntities = _json["webEntities"]
          .map((value) => new WebEntity.fromJson(value))
          .toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (bestGuessLabels != null) {
      _json["bestGuessLabels"] =
          bestGuessLabels.map((value) => (value).toJson()).toList();
    }
    if (fullMatchingImages != null) {
      _json["fullMatchingImages"] =
          fullMatchingImages.map((value) => (value).toJson()).toList();
    }
    if (pagesWithMatchingImages != null) {
      _json["pagesWithMatchingImages"] =
          pagesWithMatchingImages.map((value) => (value).toJson()).toList();
    }
    if (partialMatchingImages != null) {
      _json["partialMatchingImages"] =
          partialMatchingImages.map((value) => (value).toJson()).toList();
    }
    if (visuallySimilarImages != null) {
      _json["visuallySimilarImages"] =
          visuallySimilarImages.map((value) => (value).toJson()).toList();
    }
    if (webEntities != null) {
      _json["webEntities"] =
          webEntities.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}

/// Parameters for web detection request.
class WebDetectionParams {
  /// Whether to include results derived from the geo information in the image.
  core.bool includeGeoResults;

  WebDetectionParams();

  WebDetectionParams.fromJson(core.Map _json) {
    if (_json.containsKey("includeGeoResults")) {
      includeGeoResults = _json["includeGeoResults"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (includeGeoResults != null) {
      _json["includeGeoResults"] = includeGeoResults;
    }
    return _json;
  }
}

/// Entity deduced from similar images on the Internet.
class WebEntity {
  /// Canonical description of the entity, in English.
  core.String description;

  /// Opaque entity ID.
  core.String entityId;

  /// Overall relevancy score for the entity.
  /// Not normalized and not comparable across different image queries.
  core.double score;

  WebEntity();

  WebEntity.fromJson(core.Map _json) {
    if (_json.containsKey("description")) {
      description = _json["description"];
    }
    if (_json.containsKey("entityId")) {
      entityId = _json["entityId"];
    }
    if (_json.containsKey("score")) {
      score = _json["score"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (description != null) {
      _json["description"] = description;
    }
    if (entityId != null) {
      _json["entityId"] = entityId;
    }
    if (score != null) {
      _json["score"] = score;
    }
    return _json;
  }
}

/// Metadata for online images.
class WebImage {
  /// (Deprecated) Overall relevancy score for the image.
  core.double score;

  /// The result image URL.
  core.String url;

  WebImage();

  WebImage.fromJson(core.Map _json) {
    if (_json.containsKey("score")) {
      score = _json["score"];
    }
    if (_json.containsKey("url")) {
      url = _json["url"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (score != null) {
      _json["score"] = score;
    }
    if (url != null) {
      _json["url"] = url;
    }
    return _json;
  }
}

/// Label to provide extra metadata for the web detection.
class WebLabel {
  /// Label for extra metadata.
  core.String label;

  /// The BCP-47 language code for `label`, such as "en-US" or "sr-Latn".
  /// For more information, see
  /// http://www.unicode.org/reports/tr35/#Unicode_locale_identifier.
  core.String languageCode;

  WebLabel();

  WebLabel.fromJson(core.Map _json) {
    if (_json.containsKey("label")) {
      label = _json["label"];
    }
    if (_json.containsKey("languageCode")) {
      languageCode = _json["languageCode"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (label != null) {
      _json["label"] = label;
    }
    if (languageCode != null) {
      _json["languageCode"] = languageCode;
    }
    return _json;
  }
}

/// Metadata for web pages.
class WebPage {
  /// Fully matching images on the page.
  /// Can include resized copies of the query image.
  core.List<WebImage> fullMatchingImages;

  /// Title for the web page, may contain HTML markups.
  core.String pageTitle;

  /// Partial matching images on the page.
  /// Those images are similar enough to share some key-point features. For
  /// example an original image will likely have partial matching for its
  /// crops.
  core.List<WebImage> partialMatchingImages;

  /// (Deprecated) Overall relevancy score for the web page.
  core.double score;

  /// The result web page URL.
  core.String url;

  WebPage();

  WebPage.fromJson(core.Map _json) {
    if (_json.containsKey("fullMatchingImages")) {
      fullMatchingImages = _json["fullMatchingImages"]
          .map((value) => new WebImage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("pageTitle")) {
      pageTitle = _json["pageTitle"];
    }
    if (_json.containsKey("partialMatchingImages")) {
      partialMatchingImages = _json["partialMatchingImages"]
          .map((value) => new WebImage.fromJson(value))
          .toList();
    }
    if (_json.containsKey("score")) {
      score = _json["score"];
    }
    if (_json.containsKey("url")) {
      url = _json["url"];
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (fullMatchingImages != null) {
      _json["fullMatchingImages"] =
          fullMatchingImages.map((value) => (value).toJson()).toList();
    }
    if (pageTitle != null) {
      _json["pageTitle"] = pageTitle;
    }
    if (partialMatchingImages != null) {
      _json["partialMatchingImages"] =
          partialMatchingImages.map((value) => (value).toJson()).toList();
    }
    if (score != null) {
      _json["score"] = score;
    }
    if (url != null) {
      _json["url"] = url;
    }
    return _json;
  }
}

/// A word representation.
class Word {
  /// The bounding box for the word.
  /// The vertices are in the order of top-left, top-right, bottom-right,
  /// bottom-left. When a rotation of the bounding box is detected the rotation
  /// is represented as around the top-left corner as defined when the text is
  /// read in the 'natural' orientation.
  /// For example:
  ///   * when the text is horizontal it might look like:
  ///      0----1
  ///      |    |
  ///      3----2
  ///   * when it's rotated 180 degrees around the top-left corner it becomes:
  ///      2----3
  ///      |    |
  ///      1----0
  ///   and the vertice order will still be (0, 1, 2, 3).
  BoundingPoly boundingBox;

  /// Confidence of the OCR results for the word. Range [0, 1].
  core.double confidence;

  /// Additional information detected for the word.
  TextProperty property;

  /// List of symbols in the word.
  /// The order of the symbols follows the natural reading order.
  core.List<Symbol> symbols;

  Word();

  Word.fromJson(core.Map _json) {
    if (_json.containsKey("boundingBox")) {
      boundingBox = new BoundingPoly.fromJson(_json["boundingBox"]);
    }
    if (_json.containsKey("confidence")) {
      confidence = _json["confidence"];
    }
    if (_json.containsKey("property")) {
      property = new TextProperty.fromJson(_json["property"]);
    }
    if (_json.containsKey("symbols")) {
      symbols =
          _json["symbols"].map((value) => new Symbol.fromJson(value)).toList();
    }
  }

  core.Map<core.String, core.Object> toJson() {
    final core.Map<core.String, core.Object> _json =
        new core.Map<core.String, core.Object>();
    if (boundingBox != null) {
      _json["boundingBox"] = (boundingBox).toJson();
    }
    if (confidence != null) {
      _json["confidence"] = confidence;
    }
    if (property != null) {
      _json["property"] = (property).toJson();
    }
    if (symbols != null) {
      _json["symbols"] = symbols.map((value) => (value).toJson()).toList();
    }
    return _json;
  }
}