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This package contains Microsoft Azure SDK for MediaServices Management SDK. For documentation on how to use this package, please see https://aka.ms/azsdk/java/mgmt. This Swagger was generated by the API Framework. Package tag package-account-2023-01.
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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.

package com.azure.resourcemanager.mediaservices.models;

import com.azure.core.annotation.Fluent;
import com.azure.json.JsonReader;
import com.azure.json.JsonToken;
import com.azure.json.JsonWriter;
import java.io.IOException;
import java.util.Map;

/**
 * Describes all the settings to be used when analyzing a video in order to detect (and optionally redact) all the faces
 * present.
 */
@Fluent
public final class FaceDetectorPreset extends Preset {
    /*
     * The discriminator for derived types.
     */
    private String odataType = "#Microsoft.Media.FaceDetectorPreset";

    /*
     * Specifies the maximum resolution at which your video is analyzed. The default behavior is "SourceResolution,"
     * which will keep the input video at its original resolution when analyzed. Using "StandardDefinition" will resize
     * input videos to standard definition while preserving the appropriate aspect ratio. It will only resize if the
     * video is of higher resolution. For example, a 1920x1080 input would be scaled to 640x360 before processing.
     * Switching to "StandardDefinition" will reduce the time it takes to process high resolution video. It may also
     * reduce the cost of using this component (see
     * https://azure.microsoft.com/en-us/pricing/details/media-services/#analytics for details). However, faces that end
     * up being too small in the resized video may not be detected.
     */
    private AnalysisResolution resolution;

    /*
     * This mode provides the ability to choose between the following settings: 1) Analyze - For detection only.This
     * mode generates a metadata JSON file marking appearances of faces throughout the video.Where possible, appearances
     * of the same person are assigned the same ID. 2) Combined - Additionally redacts(blurs) detected faces. 3) Redact
     * - This enables a 2-pass process, allowing for selective redaction of a subset of detected faces.It takes in the
     * metadata file from a prior analyze pass, along with the source video, and a user-selected subset of IDs that
     * require redaction.
     */
    private FaceRedactorMode mode;

    /*
     * Blur type
     */
    private BlurType blurType;

    /*
     * Dictionary containing key value pairs for parameters not exposed in the preset itself
     */
    private Map experimentalOptions;

    /**
     * Creates an instance of FaceDetectorPreset class.
     */
    public FaceDetectorPreset() {
    }

    /**
     * Get the odataType property: The discriminator for derived types.
     * 
     * @return the odataType value.
     */
    @Override
    public String odataType() {
        return this.odataType;
    }

    /**
     * Get the resolution property: Specifies the maximum resolution at which your video is analyzed. The default
     * behavior is "SourceResolution," which will keep the input video at its original resolution when analyzed. Using
     * "StandardDefinition" will resize input videos to standard definition while preserving the appropriate aspect
     * ratio. It will only resize if the video is of higher resolution. For example, a 1920x1080 input would be scaled
     * to 640x360 before processing. Switching to "StandardDefinition" will reduce the time it takes to process high
     * resolution video. It may also reduce the cost of using this component (see
     * https://azure.microsoft.com/en-us/pricing/details/media-services/#analytics for details). However, faces that end
     * up being too small in the resized video may not be detected.
     * 
     * @return the resolution value.
     */
    public AnalysisResolution resolution() {
        return this.resolution;
    }

    /**
     * Set the resolution property: Specifies the maximum resolution at which your video is analyzed. The default
     * behavior is "SourceResolution," which will keep the input video at its original resolution when analyzed. Using
     * "StandardDefinition" will resize input videos to standard definition while preserving the appropriate aspect
     * ratio. It will only resize if the video is of higher resolution. For example, a 1920x1080 input would be scaled
     * to 640x360 before processing. Switching to "StandardDefinition" will reduce the time it takes to process high
     * resolution video. It may also reduce the cost of using this component (see
     * https://azure.microsoft.com/en-us/pricing/details/media-services/#analytics for details). However, faces that end
     * up being too small in the resized video may not be detected.
     * 
     * @param resolution the resolution value to set.
     * @return the FaceDetectorPreset object itself.
     */
    public FaceDetectorPreset withResolution(AnalysisResolution resolution) {
        this.resolution = resolution;
        return this;
    }

    /**
     * Get the mode property: This mode provides the ability to choose between the following settings: 1) Analyze - For
     * detection only.This mode generates a metadata JSON file marking appearances of faces throughout the video.Where
     * possible, appearances of the same person are assigned the same ID. 2) Combined - Additionally redacts(blurs)
     * detected faces. 3) Redact - This enables a 2-pass process, allowing for selective redaction of a subset of
     * detected faces.It takes in the metadata file from a prior analyze pass, along with the source video, and a
     * user-selected subset of IDs that require redaction.
     * 
     * @return the mode value.
     */
    public FaceRedactorMode mode() {
        return this.mode;
    }

    /**
     * Set the mode property: This mode provides the ability to choose between the following settings: 1) Analyze - For
     * detection only.This mode generates a metadata JSON file marking appearances of faces throughout the video.Where
     * possible, appearances of the same person are assigned the same ID. 2) Combined - Additionally redacts(blurs)
     * detected faces. 3) Redact - This enables a 2-pass process, allowing for selective redaction of a subset of
     * detected faces.It takes in the metadata file from a prior analyze pass, along with the source video, and a
     * user-selected subset of IDs that require redaction.
     * 
     * @param mode the mode value to set.
     * @return the FaceDetectorPreset object itself.
     */
    public FaceDetectorPreset withMode(FaceRedactorMode mode) {
        this.mode = mode;
        return this;
    }

    /**
     * Get the blurType property: Blur type.
     * 
     * @return the blurType value.
     */
    public BlurType blurType() {
        return this.blurType;
    }

    /**
     * Set the blurType property: Blur type.
     * 
     * @param blurType the blurType value to set.
     * @return the FaceDetectorPreset object itself.
     */
    public FaceDetectorPreset withBlurType(BlurType blurType) {
        this.blurType = blurType;
        return this;
    }

    /**
     * Get the experimentalOptions property: Dictionary containing key value pairs for parameters not exposed in the
     * preset itself.
     * 
     * @return the experimentalOptions value.
     */
    public Map experimentalOptions() {
        return this.experimentalOptions;
    }

    /**
     * Set the experimentalOptions property: Dictionary containing key value pairs for parameters not exposed in the
     * preset itself.
     * 
     * @param experimentalOptions the experimentalOptions value to set.
     * @return the FaceDetectorPreset object itself.
     */
    public FaceDetectorPreset withExperimentalOptions(Map experimentalOptions) {
        this.experimentalOptions = experimentalOptions;
        return this;
    }

    /**
     * Validates the instance.
     * 
     * @throws IllegalArgumentException thrown if the instance is not valid.
     */
    @Override
    public void validate() {
    }

    /**
     * {@inheritDoc}
     */
    @Override
    public JsonWriter toJson(JsonWriter jsonWriter) throws IOException {
        jsonWriter.writeStartObject();
        jsonWriter.writeStringField("@odata.type", this.odataType);
        jsonWriter.writeStringField("resolution", this.resolution == null ? null : this.resolution.toString());
        jsonWriter.writeStringField("mode", this.mode == null ? null : this.mode.toString());
        jsonWriter.writeStringField("blurType", this.blurType == null ? null : this.blurType.toString());
        jsonWriter.writeMapField("experimentalOptions", this.experimentalOptions,
            (writer, element) -> writer.writeString(element));
        return jsonWriter.writeEndObject();
    }

    /**
     * Reads an instance of FaceDetectorPreset from the JsonReader.
     * 
     * @param jsonReader The JsonReader being read.
     * @return An instance of FaceDetectorPreset if the JsonReader was pointing to an instance of it, or null if it was
     * pointing to JSON null.
     * @throws IOException If an error occurs while reading the FaceDetectorPreset.
     */
    public static FaceDetectorPreset fromJson(JsonReader jsonReader) throws IOException {
        return jsonReader.readObject(reader -> {
            FaceDetectorPreset deserializedFaceDetectorPreset = new FaceDetectorPreset();
            while (reader.nextToken() != JsonToken.END_OBJECT) {
                String fieldName = reader.getFieldName();
                reader.nextToken();

                if ("@odata.type".equals(fieldName)) {
                    deserializedFaceDetectorPreset.odataType = reader.getString();
                } else if ("resolution".equals(fieldName)) {
                    deserializedFaceDetectorPreset.resolution = AnalysisResolution.fromString(reader.getString());
                } else if ("mode".equals(fieldName)) {
                    deserializedFaceDetectorPreset.mode = FaceRedactorMode.fromString(reader.getString());
                } else if ("blurType".equals(fieldName)) {
                    deserializedFaceDetectorPreset.blurType = BlurType.fromString(reader.getString());
                } else if ("experimentalOptions".equals(fieldName)) {
                    Map experimentalOptions = reader.readMap(reader1 -> reader1.getString());
                    deserializedFaceDetectorPreset.experimentalOptions = experimentalOptions;
                } else {
                    reader.skipChildren();
                }
            }

            return deserializedFaceDetectorPreset;
        });
    }
}