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com.amazonaws.services.textract.model.HumanLoopDataAttributes Maven / Gradle / Ivy

/*
 * Copyright 2018-2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 * 
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
 * the License. A copy of the License is located at
 * 
 * http://aws.amazon.com/apache2.0
 * 
 * or in the "license" file accompanying this file. This file 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.
 */
package com.amazonaws.services.textract.model;

import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;

/**
 * 

* Allows you to set attributes of the image. Currently, you can declare an image as free of personally identifiable * information and adult content. *

* * @see AWS * API Documentation */ @Generated("com.amazonaws:aws-java-sdk-code-generator") public class HumanLoopDataAttributes implements Serializable, Cloneable, StructuredPojo { /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

*/ private java.util.List contentClassifiers; /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

* * @return Sets whether the input image is free of personally identifiable information or adult content. * @see ContentClassifier */ public java.util.List getContentClassifiers() { return contentClassifiers; } /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

* * @param contentClassifiers * Sets whether the input image is free of personally identifiable information or adult content. * @see ContentClassifier */ public void setContentClassifiers(java.util.Collection contentClassifiers) { if (contentClassifiers == null) { this.contentClassifiers = null; return; } this.contentClassifiers = new java.util.ArrayList(contentClassifiers); } /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

*

* NOTE: This method appends the values to the existing list (if any). Use * {@link #setContentClassifiers(java.util.Collection)} or {@link #withContentClassifiers(java.util.Collection)} if * you want to override the existing values. *

* * @param contentClassifiers * Sets whether the input image is free of personally identifiable information or adult content. * @return Returns a reference to this object so that method calls can be chained together. * @see ContentClassifier */ public HumanLoopDataAttributes withContentClassifiers(String... contentClassifiers) { if (this.contentClassifiers == null) { setContentClassifiers(new java.util.ArrayList(contentClassifiers.length)); } for (String ele : contentClassifiers) { this.contentClassifiers.add(ele); } return this; } /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

* * @param contentClassifiers * Sets whether the input image is free of personally identifiable information or adult content. * @return Returns a reference to this object so that method calls can be chained together. * @see ContentClassifier */ public HumanLoopDataAttributes withContentClassifiers(java.util.Collection contentClassifiers) { setContentClassifiers(contentClassifiers); return this; } /** *

* Sets whether the input image is free of personally identifiable information or adult content. *

* * @param contentClassifiers * Sets whether the input image is free of personally identifiable information or adult content. * @return Returns a reference to this object so that method calls can be chained together. * @see ContentClassifier */ public HumanLoopDataAttributes withContentClassifiers(ContentClassifier... contentClassifiers) { java.util.ArrayList contentClassifiersCopy = new java.util.ArrayList(contentClassifiers.length); for (ContentClassifier value : contentClassifiers) { contentClassifiersCopy.add(value.toString()); } if (getContentClassifiers() == null) { setContentClassifiers(contentClassifiersCopy); } else { getContentClassifiers().addAll(contentClassifiersCopy); } return this; } /** * Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be * redacted from this string using a placeholder value. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getContentClassifiers() != null) sb.append("ContentClassifiers: ").append(getContentClassifiers()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof HumanLoopDataAttributes == false) return false; HumanLoopDataAttributes other = (HumanLoopDataAttributes) obj; if (other.getContentClassifiers() == null ^ this.getContentClassifiers() == null) return false; if (other.getContentClassifiers() != null && other.getContentClassifiers().equals(this.getContentClassifiers()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getContentClassifiers() == null) ? 0 : getContentClassifiers().hashCode()); return hashCode; } @Override public HumanLoopDataAttributes clone() { try { return (HumanLoopDataAttributes) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } @com.amazonaws.annotation.SdkInternalApi @Override public void marshall(ProtocolMarshaller protocolMarshaller) { com.amazonaws.services.textract.model.transform.HumanLoopDataAttributesMarshaller.getInstance().marshall(this, protocolMarshaller); } }




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