/**
 * (C) Copyright IBM Corp. 2017, 2020.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
/// <reference types="node" />
import { IncomingHttpHeaders, OutgoingHttpHeaders } from 'http';
import { BaseService, UserOptions } from 'ibm-cloud-sdk-core';
/**
 * IBM Watson&trade; Visual Recognition is discontinued. Existing instances are supported until 1 December 2021, but as
 * of 7 January 2021, you can't create instances. Any instance that is provisioned on 1 December 2021 will be deleted.
 * {: deprecated}
 *
 * The IBM Watson Visual Recognition service uses deep learning algorithms to identify scenes and objects in images that
 * you upload to the service. You can create and train a custom classifier to identify subjects that suit your needs.
 */
declare class VisualRecognitionV3 extends BaseService {
    static DEFAULT_SERVICE_URL: string;
    static DEFAULT_SERVICE_NAME: string;
    /** Release date of the API version you want to use. Specify dates in YYYY-MM-DD format. The current version is
     *  `2018-03-19`.
     */
    version: string;
    /**
     * Construct a VisualRecognitionV3 object.
     *
     * @param {Object} options - Options for the service.
     * @param {string} options.version - Release date of the API version you want to use. Specify dates in YYYY-MM-DD
     * format. The current version is `2018-03-19`.
     * @param {string} [options.serviceUrl] - The base url to use when contacting the service (e.g. 'https://api.us-south.visual-recognition.watson.cloud.ibm.com'). The base url may differ between IBM Cloud regions.
     * @param {OutgoingHttpHeaders} [options.headers] - Default headers that shall be included with every request to the service.
     * @param {string} [options.serviceName] - The name of the service to configure
     * @param {Authenticator} [options.authenticator] - The Authenticator object used to authenticate requests to the service. Defaults to environment if not set
     * @constructor
     * @returns {VisualRecognitionV3}
     */
    constructor(options: UserOptions);
    /*************************
     * general
     ************************/
    /**
     * Classify images.
     *
     * Classify images with built-in or custom classifiers.
     *
     * @param {Object} [params] - The parameters to send to the service.
     * @param {NodeJS.ReadableStream|Buffer} [params.imagesFile] - An image file (.gif, .jpg, .png, .tif) or .zip file
     * with images. Maximum image size is 10 MB. Include no more than 20 images and limit the .zip file to 100 MB. Encode
     * the image and .zip file names in UTF-8 if they contain non-ASCII characters. The service assumes UTF-8 encoding if
     * it encounters non-ASCII characters.
     *
     * You can also include an image with the **url** parameter.
     * @param {string} [params.imagesFilename] - The filename for imagesFile.
     * @param {string} [params.imagesFileContentType] - The content type of imagesFile.
     * @param {string} [params.url] - The URL of an image (.gif, .jpg, .png, .tif) to analyze. The minimum recommended
     * pixel density is 32X32 pixels, but the service tends to perform better with images that are at least 224 x 224
     * pixels. The maximum image size is 10 MB.
     *
     * You can also include images with the **images_file** parameter.
     * @param {number} [params.threshold] - The minimum score a class must have to be displayed in the response. Set the
     * threshold to `0.0` to return all identified classes.
     * @param {string[]} [params.owners] - The categories of classifiers to apply. The **classifier_ids** parameter
     * overrides **owners**, so make sure that **classifier_ids** is empty.
     * - Use `IBM` to classify against the `default` general classifier. You get the same result if both
     * **classifier_ids** and **owners** parameters are empty.
     * - Use `me` to classify against all your custom classifiers. However, for better performance use **classifier_ids**
     * to specify the specific custom classifiers to apply.
     * - Use both `IBM` and `me` to analyze the image against both classifier categories.
     * @param {string[]} [params.classifierIds] - Which classifiers to apply. Overrides the **owners** parameter. You can
     * specify both custom and built-in classifier IDs. The built-in `default` classifier is used if both
     * **classifier_ids** and **owners** parameters are empty.
     *
     * The following built-in classifier IDs require no training:
     * - `default`: Returns classes from thousands of general tags.
     * - `food`: Enhances specificity and accuracy for images of food items.
     * - `explicit`: Evaluates whether the image might be pornographic.
     * @param {string} [params.acceptLanguage] - The desired language of parts of the response. See the response for
     * details.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.ClassifiedImages>>}
     */
    classify(params?: VisualRecognitionV3.ClassifyParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.ClassifiedImages>>;
    /*************************
     * custom
     ************************/
    /**
     * Create a classifier.
     *
     * Train a new multi-faceted classifier on the uploaded image data. Create your custom classifier with positive or
     * negative example training images. Include at least two sets of examples, either two positive example files or one
     * positive and one negative file. You can upload a maximum of 256 MB per call.
     *
     * **Tips when creating:**
     *
     * - If you set the **X-Watson-Learning-Opt-Out** header parameter to `true` when you create a classifier, the example
     * training images are not stored. Save your training images locally. For more information, see [Data
     * collection](#data-collection).
     *
     * - Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier and
     * class names). The service assumes UTF-8 encoding if it encounters non-ASCII characters.
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.name - The name of the new classifier. Encode special characters in UTF-8.
     * @param {Record<string, NodeJS.ReadableStream|Buffer>} params.positiveExamples - A dictionary that contains the
     * value for each classname. The value is a .zip file of images that depict the visual subject of a class in the new
     * classifier. You can include more than one positive example file in a call.
     *
     * Specify the parameter name by appending `_positive_examples` to the class name. For example,
     * `goldenretriever_positive_examples` creates the class **goldenretriever**. The string cannot contain the following
     * characters: ``$ * - { } \ | / ' " ` [ ]``.
     *
     * Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The
     * maximum number of images is 10,000 images or 100 MB per .zip file.
     *
     * Encode special characters in the file name in UTF-8.
     * @param {NodeJS.ReadableStream|Buffer} [params.negativeExamples] - A .zip file of images that do not depict the
     * visual subject of any of the classes of the new classifier. Must contain a minimum of 10 images.
     *
     * Encode special characters in the file name in UTF-8.
     * @param {string} [params.negativeExamplesFilename] - The filename for negativeExamples.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>}
     */
    createClassifier(params: VisualRecognitionV3.CreateClassifierParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>;
    /**
     * Retrieve a list of classifiers.
     *
     * @param {Object} [params] - The parameters to send to the service.
     * @param {boolean} [params.verbose] - Specify `true` to return details about the classifiers. Omit this parameter to
     * return a brief list of classifiers.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifiers>>}
     */
    listClassifiers(params?: VisualRecognitionV3.ListClassifiersParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifiers>>;
    /**
     * Retrieve classifier details.
     *
     * Retrieve information about a custom classifier.
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.classifierId - The ID of the classifier.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>}
     */
    getClassifier(params: VisualRecognitionV3.GetClassifierParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>;
    /**
     * Update a classifier.
     *
     * Update a custom classifier by adding new positive or negative classes or by adding new images to existing classes.
     * You must supply at least one set of positive or negative examples. For details, see [Updating custom
     * classifiers](https://cloud.ibm.com/docs/visual-recognition?topic=visual-recognition-customizing#updating-custom-classifiers).
     *
     * Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier and class
     * names). The service assumes UTF-8 encoding if it encounters non-ASCII characters.
     *
     * **Tips about retraining:**
     *
     * - You can't update the classifier if the **X-Watson-Learning-Opt-Out** header parameter was set to `true` when the
     * classifier was created. Training images are not stored in that case. Instead, create another classifier. For more
     * information, see [Data collection](#data-collection).
     *
     * - Don't make retraining calls on a classifier until the status is ready. When you submit retraining requests in
     * parallel, the last request overwrites the previous requests. The `retrained` property shows the last time the
     * classifier retraining finished.
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.classifierId - The ID of the classifier.
     * @param {Record<string, NodeJS.ReadableStream|Buffer>} [params.positiveExamples] - A dictionary that contains the
     * value for each classname. The value is a .zip file of images that depict the visual subject of a class in the
     * classifier. The positive examples create or update classes in the classifier. You can include more than one
     * positive example file in a call.
     *
     * Specify the parameter name by appending `_positive_examples` to the class name. For example,
     * `goldenretriever_positive_examples` creates the class `goldenretriever`. The string cannot contain the following
     * characters: ``$ * - { } \ | / ' " ` [ ]``.
     *
     * Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The
     * maximum number of images is 10,000 images or 100 MB per .zip file.
     *
     * Encode special characters in the file name in UTF-8.
     * @param {NodeJS.ReadableStream|Buffer} [params.negativeExamples] - A .zip file of images that do not depict the
     * visual subject of any of the classes of the new classifier. Must contain a minimum of 10 images.
     *
     * Encode special characters in the file name in UTF-8.
     * @param {string} [params.negativeExamplesFilename] - The filename for negativeExamples.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>}
     */
    updateClassifier(params: VisualRecognitionV3.UpdateClassifierParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Classifier>>;
    /**
     * Delete a classifier.
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.classifierId - The ID of the classifier.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Empty>>}
     */
    deleteClassifier(params: VisualRecognitionV3.DeleteClassifierParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Empty>>;
    /*************************
     * coreML
     ************************/
    /**
     * Retrieve a Core ML model of a classifier.
     *
     * Download a Core ML model file (.mlmodel) of a custom classifier that returns <tt>"core_ml_enabled": true</tt> in
     * the classifier details.
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.classifierId - The ID of the classifier.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<NodeJS.ReadableStream|Buffer>>}
     */
    getCoreMlModel(params: VisualRecognitionV3.GetCoreMlModelParams): Promise<VisualRecognitionV3.Response<NodeJS.ReadableStream | Buffer>>;
    /*************************
     * userData
     ************************/
    /**
     * Delete labeled data.
     *
     * Deletes all data associated with a specified customer ID. The method has no effect if no data is associated with
     * the customer ID.
     *
     * You associate a customer ID with data by passing the `X-Watson-Metadata` header with a request that passes data.
     * For more information about personal data and customer IDs, see [Information
     * security](https://cloud.ibm.com/docs/visual-recognition?topic=visual-recognition-information-security).
     *
     * @param {Object} params - The parameters to send to the service.
     * @param {string} params.customerId - The customer ID for which all data is to be deleted.
     * @param {OutgoingHttpHeaders} [params.headers] - Custom request headers
     * @returns {Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Empty>>}
     */
    deleteUserData(params: VisualRecognitionV3.DeleteUserDataParams): Promise<VisualRecognitionV3.Response<VisualRecognitionV3.Empty>>;
}
/*************************
 * interfaces
 ************************/
declare namespace VisualRecognitionV3 {
    /** Options for the `VisualRecognitionV3` constructor. */
    interface Options extends UserOptions {
        /** Release date of the API version you want to use. Specify dates in YYYY-MM-DD format. The current version is
         *  `2018-03-19`.
         */
        version: string;
    }
    /** An operation response. */
    interface Response<T = any> {
        result: T;
        status: number;
        statusText: string;
        headers: IncomingHttpHeaders;
    }
    /** The callback for a service request. */
    type Callback<T> = (error: any, response?: Response<T>) => void;
    /** The body of a service request that returns no response data. */
    interface Empty {
    }
    /** A standard JS object, defined to avoid the limitations of `Object` and `object` */
    interface JsonObject {
        [key: string]: any;
    }
    /*************************
     * request interfaces
     ************************/
    /** Parameters for the `classify` operation. */
    interface ClassifyParams {
        /** An image file (.gif, .jpg, .png, .tif) or .zip file with images. Maximum image size is 10 MB. Include no
         *  more than 20 images and limit the .zip file to 100 MB. Encode the image and .zip file names in UTF-8 if they
         *  contain non-ASCII characters. The service assumes UTF-8 encoding if it encounters non-ASCII characters.
         *
         *  You can also include an image with the **url** parameter.
         */
        imagesFile?: NodeJS.ReadableStream | Buffer;
        /** The filename for imagesFile. */
        imagesFilename?: string;
        /** The content type of imagesFile. */
        imagesFileContentType?: string;
        /** The URL of an image (.gif, .jpg, .png, .tif) to analyze. The minimum recommended pixel density is 32X32
         *  pixels, but the service tends to perform better with images that are at least 224 x 224 pixels. The maximum
         *  image size is 10 MB.
         *
         *  You can also include images with the **images_file** parameter.
         */
        url?: string;
        /** The minimum score a class must have to be displayed in the response. Set the threshold to `0.0` to return
         *  all identified classes.
         */
        threshold?: number;
        /** The categories of classifiers to apply. The **classifier_ids** parameter overrides **owners**, so make sure
         *  that **classifier_ids** is empty.
         *  - Use `IBM` to classify against the `default` general classifier. You get the same result if both
         *  **classifier_ids** and **owners** parameters are empty.
         *  - Use `me` to classify against all your custom classifiers. However, for better performance use
         *  **classifier_ids** to specify the specific custom classifiers to apply.
         *  - Use both `IBM` and `me` to analyze the image against both classifier categories.
         */
        owners?: string[];
        /** Which classifiers to apply. Overrides the **owners** parameter. You can specify both custom and built-in
         *  classifier IDs. The built-in `default` classifier is used if both **classifier_ids** and **owners** parameters
         *  are empty.
         *
         *  The following built-in classifier IDs require no training:
         *  - `default`: Returns classes from thousands of general tags.
         *  - `food`: Enhances specificity and accuracy for images of food items.
         *  - `explicit`: Evaluates whether the image might be pornographic.
         */
        classifierIds?: string[];
        /** The desired language of parts of the response. See the response for details. */
        acceptLanguage?: ClassifyConstants.AcceptLanguage | string;
        headers?: OutgoingHttpHeaders;
    }
    /** Constants for the `classify` operation. */
    namespace ClassifyConstants {
        /** The desired language of parts of the response. See the response for details. */
        enum AcceptLanguage {
            EN = "en",
            AR = "ar",
            DE = "de",
            ES = "es",
            FR = "fr",
            IT = "it",
            JA = "ja",
            KO = "ko",
            PT_BR = "pt-br",
            ZH_CN = "zh-cn",
            ZH_TW = "zh-tw"
        }
    }
    /** Parameters for the `createClassifier` operation. */
    interface CreateClassifierParams {
        /** The name of the new classifier. Encode special characters in UTF-8. */
        name: string;
        /** A dictionary that contains the value for each classname. The value is a .zip file of images that depict the
         *  visual subject of a class in the new classifier. You can include more than one positive example file in a call.
         *
         *  Specify the parameter name by appending `_positive_examples` to the class name. For example,
         *  `goldenretriever_positive_examples` creates the class **goldenretriever**. The string cannot contain the
         *  following characters: ``$ * - { } \ | / ' " ` [ ]``.
         *
         *  Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The
         *  maximum number of images is 10,000 images or 100 MB per .zip file.
         *
         *  Encode special characters in the file name in UTF-8.
         */
        positiveExamples: Record<string, NodeJS.ReadableStream | Buffer>;
        /** A .zip file of images that do not depict the visual subject of any of the classes of the new classifier.
         *  Must contain a minimum of 10 images.
         *
         *  Encode special characters in the file name in UTF-8.
         */
        negativeExamples?: NodeJS.ReadableStream | Buffer;
        /** The filename for negativeExamples. */
        negativeExamplesFilename?: string;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `listClassifiers` operation. */
    interface ListClassifiersParams {
        /** Specify `true` to return details about the classifiers. Omit this parameter to return a brief list of
         *  classifiers.
         */
        verbose?: boolean;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `getClassifier` operation. */
    interface GetClassifierParams {
        /** The ID of the classifier. */
        classifierId: string;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `updateClassifier` operation. */
    interface UpdateClassifierParams {
        /** The ID of the classifier. */
        classifierId: string;
        /** A dictionary that contains the value for each classname. The value is a .zip file of images that depict the
         *  visual subject of a class in the classifier. The positive examples create or update classes in the classifier.
         *  You can include more than one positive example file in a call.
         *
         *  Specify the parameter name by appending `_positive_examples` to the class name. For example,
         *  `goldenretriever_positive_examples` creates the class `goldenretriever`. The string cannot contain the following
         *  characters: ``$ * - { } \ | / ' " ` [ ]``.
         *
         *  Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The
         *  maximum number of images is 10,000 images or 100 MB per .zip file.
         *
         *  Encode special characters in the file name in UTF-8.
         */
        positiveExamples?: Record<string, NodeJS.ReadableStream | Buffer>;
        /** A .zip file of images that do not depict the visual subject of any of the classes of the new classifier.
         *  Must contain a minimum of 10 images.
         *
         *  Encode special characters in the file name in UTF-8.
         */
        negativeExamples?: NodeJS.ReadableStream | Buffer;
        /** The filename for negativeExamples. */
        negativeExamplesFilename?: string;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `deleteClassifier` operation. */
    interface DeleteClassifierParams {
        /** The ID of the classifier. */
        classifierId: string;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `getCoreMlModel` operation. */
    interface GetCoreMlModelParams {
        /** The ID of the classifier. */
        classifierId: string;
        headers?: OutgoingHttpHeaders;
    }
    /** Parameters for the `deleteUserData` operation. */
    interface DeleteUserDataParams {
        /** The customer ID for which all data is to be deleted. */
        customerId: string;
        headers?: OutgoingHttpHeaders;
    }
    /*************************
     * model interfaces
     ************************/
    /** A category within a classifier. */
    interface Class {
        /** The name of the class. */
        class: string;
    }
    /** Result of a class within a classifier. */
    interface ClassResult {
        /** Name of the class.
         *
         *  Class names are translated in the language defined by the **Accept-Language** request header for the build-in
         *  classifier IDs (`default`, `food`, and `explicit`). Class names of custom classifiers are not translated. The
         *  response might not be in the specified language when the requested language is not supported or when there is no
         *  translation for the class name.
         */
        class: string;
        /** Confidence score for the property in the range of 0 to 1. A higher score indicates greater likelihood that
         *  the class is depicted in the image. The default threshold for returning scores from a classifier is 0.5.
         */
        score: number;
        /** Knowledge graph of the property. For example, `/fruit/pome/apple/eating apple/Granny Smith`. Included only
         *  if identified.
         */
        type_hierarchy?: string;
    }
    /** Results for one image. */
    interface ClassifiedImage {
        /** Source of the image before any redirects. Not returned when the image is uploaded. */
        source_url?: string;
        /** Fully resolved URL of the image after redirects are followed. Not returned when the image is uploaded. */
        resolved_url?: string;
        /** Relative path of the image file if uploaded directly. Not returned when the image is passed by URL. */
        image?: string;
        /** Information about what might have caused a failure, such as an image that is too large. Not returned when
         *  there is no error.
         */
        error?: ErrorInfo;
        /** The classifiers. */
        classifiers: ClassifierResult[];
    }
    /** Results for all images. */
    interface ClassifiedImages {
        /** Number of custom classes identified in the images. */
        custom_classes?: number;
        /** Number of images processed for the API call. */
        images_processed?: number;
        /** Classified images. */
        images: ClassifiedImage[];
        /** Information about what might cause less than optimal output. For example, a request sent with a corrupt .zip
         *  file and a list of image URLs will still complete, but does not return the expected output. Not returned when
         *  there is no warning.
         */
        warnings?: WarningInfo[];
    }
    /** Information about a classifier. */
    interface Classifier {
        /** ID of a classifier identified in the image. */
        classifier_id: string;
        /** Name of the classifier. */
        name: string;
        /** Unique ID of the account who owns the classifier. Might not be returned by some requests. */
        owner?: string;
        /** Training status of classifier. */
        status?: string;
        /** Whether the classifier can be downloaded as a Core ML model after the training status is `ready`. */
        core_ml_enabled?: boolean;
        /** If classifier training has failed, this field might explain why. */
        explanation?: string;
        /** Date and time in Coordinated Universal Time (UTC) that the classifier was created. */
        created?: string;
        /** Classes that define a classifier. */
        classes?: Class[];
        /** Date and time in Coordinated Universal Time (UTC) that the classifier was updated. Might not be returned by
         *  some requests. Identical to `updated` and retained for backward compatibility.
         */
        retrained?: string;
        /** Date and time in Coordinated Universal Time (UTC) that the classifier was most recently updated. The field
         *  matches either `retrained` or `created`. Might not be returned by some requests.
         */
        updated?: string;
    }
    /** Classifier and score combination. */
    interface ClassifierResult {
        /** Name of the classifier. */
        name: string;
        /** ID of a classifier identified in the image. */
        classifier_id: string;
        /** Classes within the classifier. */
        classes: ClassResult[];
    }
    /** A container for the list of classifiers. */
    interface Classifiers {
        /** List of classifiers. */
        classifiers: Classifier[];
    }
    /** Information about what might have caused a failure, such as an image that is too large. Not returned when there is no error. */
    interface ErrorInfo {
        /** HTTP status code. */
        code: number;
        /** Human-readable error description. For example, `File size limit exceeded`. */
        description: string;
        /** Codified error string. For example, `limit_exceeded`. */
        error_id: string;
    }
    /** Information about something that went wrong. */
    interface WarningInfo {
        /** Codified warning string, such as `limit_reached`. */
        warning_id: string;
        /** Information about the error. */
        description: string;
    }
}
export = VisualRecognitionV3;