public static final class ImageSegmentationPredictionResult.Builder extends GeneratedMessageV3.Builder<ImageSegmentationPredictionResult.Builder> implements ImageSegmentationPredictionResultOrBuilder
Prediction output format for Image Segmentation.
Protobuf type
google.cloud.aiplatform.v1.schema.predict.prediction.ImageSegmentationPredictionResult
Inherited Members
com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)
com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)
com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)
Static Methods
public static final Descriptors.Descriptor getDescriptor()
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Methods
public ImageSegmentationPredictionResult.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
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public ImageSegmentationPredictionResult build()
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public ImageSegmentationPredictionResult buildPartial()
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public ImageSegmentationPredictionResult.Builder clear()
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public ImageSegmentationPredictionResult.Builder clearCategoryMask()
A PNG image where each pixel in the mask represents the category in which
the pixel in the original image was predicted to belong to. The size of
this image will be the same as the original image. The mapping between the
AnntoationSpec and the color can be found in model's metadata. The model
will choose the most likely category and if none of the categories reach
the confidence threshold, the pixel will be marked as background.
string category_mask = 1;
Returns
public ImageSegmentationPredictionResult.Builder clearConfidenceMask()
A one channel image which is encoded as an 8bit lossless PNG. The size of
the image will be the same as the original image. For a specific pixel,
darker color means less confidence in correctness of the cateogry in the
categoryMask for the corresponding pixel. Black means no confidence and
white means complete confidence.
string confidence_mask = 2;
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public ImageSegmentationPredictionResult.Builder clearField(Descriptors.FieldDescriptor field)
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public ImageSegmentationPredictionResult.Builder clearOneof(Descriptors.OneofDescriptor oneof)
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public ImageSegmentationPredictionResult.Builder clone()
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public String getCategoryMask()
A PNG image where each pixel in the mask represents the category in which
the pixel in the original image was predicted to belong to. The size of
this image will be the same as the original image. The mapping between the
AnntoationSpec and the color can be found in model's metadata. The model
will choose the most likely category and if none of the categories reach
the confidence threshold, the pixel will be marked as background.
string category_mask = 1;
Returns
Type | Description |
String | The categoryMask.
|
public ByteString getCategoryMaskBytes()
A PNG image where each pixel in the mask represents the category in which
the pixel in the original image was predicted to belong to. The size of
this image will be the same as the original image. The mapping between the
AnntoationSpec and the color can be found in model's metadata. The model
will choose the most likely category and if none of the categories reach
the confidence threshold, the pixel will be marked as background.
string category_mask = 1;
Returns
Type | Description |
ByteString | The bytes for categoryMask.
|
public String getConfidenceMask()
A one channel image which is encoded as an 8bit lossless PNG. The size of
the image will be the same as the original image. For a specific pixel,
darker color means less confidence in correctness of the cateogry in the
categoryMask for the corresponding pixel. Black means no confidence and
white means complete confidence.
string confidence_mask = 2;
Returns
Type | Description |
String | The confidenceMask.
|
public ByteString getConfidenceMaskBytes()
A one channel image which is encoded as an 8bit lossless PNG. The size of
the image will be the same as the original image. For a specific pixel,
darker color means less confidence in correctness of the cateogry in the
categoryMask for the corresponding pixel. Black means no confidence and
white means complete confidence.
string confidence_mask = 2;
Returns
Type | Description |
ByteString | The bytes for confidenceMask.
|
public ImageSegmentationPredictionResult getDefaultInstanceForType()
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public Descriptors.Descriptor getDescriptorForType()
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protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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public ImageSegmentationPredictionResult.Builder mergeFrom(ImageSegmentationPredictionResult other)
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public ImageSegmentationPredictionResult.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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Exceptions
public ImageSegmentationPredictionResult.Builder mergeFrom(Message other)
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public final ImageSegmentationPredictionResult.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
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public ImageSegmentationPredictionResult.Builder setCategoryMask(String value)
A PNG image where each pixel in the mask represents the category in which
the pixel in the original image was predicted to belong to. The size of
this image will be the same as the original image. The mapping between the
AnntoationSpec and the color can be found in model's metadata. The model
will choose the most likely category and if none of the categories reach
the confidence threshold, the pixel will be marked as background.
string category_mask = 1;
Parameter
Name | Description |
value | String
The categoryMask to set.
|
Returns
public ImageSegmentationPredictionResult.Builder setCategoryMaskBytes(ByteString value)
A PNG image where each pixel in the mask represents the category in which
the pixel in the original image was predicted to belong to. The size of
this image will be the same as the original image. The mapping between the
AnntoationSpec and the color can be found in model's metadata. The model
will choose the most likely category and if none of the categories reach
the confidence threshold, the pixel will be marked as background.
string category_mask = 1;
Parameter
Name | Description |
value | ByteString
The bytes for categoryMask to set.
|
Returns
public ImageSegmentationPredictionResult.Builder setConfidenceMask(String value)
A one channel image which is encoded as an 8bit lossless PNG. The size of
the image will be the same as the original image. For a specific pixel,
darker color means less confidence in correctness of the cateogry in the
categoryMask for the corresponding pixel. Black means no confidence and
white means complete confidence.
string confidence_mask = 2;
Parameter
Name | Description |
value | String
The confidenceMask to set.
|
Returns
public ImageSegmentationPredictionResult.Builder setConfidenceMaskBytes(ByteString value)
A one channel image which is encoded as an 8bit lossless PNG. The size of
the image will be the same as the original image. For a specific pixel,
darker color means less confidence in correctness of the cateogry in the
categoryMask for the corresponding pixel. Black means no confidence and
white means complete confidence.
string confidence_mask = 2;
Parameter
Name | Description |
value | ByteString
The bytes for confidenceMask to set.
|
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public ImageSegmentationPredictionResult.Builder setField(Descriptors.FieldDescriptor field, Object value)
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public ImageSegmentationPredictionResult.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
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public final ImageSegmentationPredictionResult.Builder setUnknownFields(UnknownFieldSet unknownFields)
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