com.ibm.watson.developer_cloud.visual_recognition.v3.model

Class CreateClassifierOptions

java.lang.Object

com.ibm.watson.developer_cloud.service.model.GenericModel

com.ibm.watson.developer_cloud.visual_recognition.v3.model.CreateClassifierOptions

All Implemented Interfaces:

ObjectModel

public class CreateClassifierOptions
extends GenericModel

The createClassifier options.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CreateClassifierOptions.Builder Builder.

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	name() Gets the name.
java.io.InputStream	negativeExamples() Gets the negativeExamples.
java.lang.String	negativeExamplesFilename() Gets the negativeExamplesFilename.
CreateClassifierOptions.Builder	newBuilder() New builder.
java.util.Map<java.lang.String,java.io.InputStream>	positiveExamples() Gets the positiveExamples.
java.util.Map<java.lang.String,java.lang.String>	positiveExamplesFilename() Gets the positiveExamplesFilename.

Methods inherited from class com.ibm.watson.developer_cloud.service.model.GenericModel

equals, hashCode, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

newBuilder

public CreateClassifierOptions.Builder newBuilder()

New builder.

Returns:

a CreateClassifierOptions builder

name

public java.lang.String name()

Gets the name. The name of the new classifier. Encode special characters in UTF-8.

Returns:

the name

positiveExamples

public java.util.Map<java.lang.String,java.io.InputStream> positiveExamples()

Gets the positiveExamples. 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**. 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.

Returns:

the positiveExamples

positiveExamplesFilename

public java.util.Map<java.lang.String,java.lang.String> positiveExamplesFilename()

Gets the positiveExamplesFilename. The filename for positiveExamples.

Returns:

the positiveExamplesFilename

negativeExamples

public java.io.InputStream negativeExamples()

Gets the 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.

Returns:

the negativeExamples

negativeExamplesFilename

public java.lang.String negativeExamplesFilename()

Gets the negativeExamplesFilename. The filename for negativeExamples.

Returns:

the negativeExamplesFilename