public class DecodeEAST extends DecodeInstanceSegmentation<ai.onnxruntime.OnnxTensor>
Each object-mask represented rotated-bounding box and is associated with a confidence score.
Particular thanks to Adrian Rosebrock whose tutorial was useful in applying this model
Constructor and Description |
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DecodeEAST() |
Modifier and Type | Method and Description |
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List<LabelledWithConfidence<MultiScaleObject>> |
decode(List<ai.onnxruntime.OnnxTensor> inferenceOutput,
ImageInferenceContext context)
Decodes the output tensors from inference into
ObjectMask s with confidence and
labels. |
List<String> |
expectedOutputs()
Ordered names of the tensors we are interested in processing, as outputted from inference.
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double |
getMinConfidence()
Proposed bounding boxes below this confidence interval are removed from consideration.
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void |
setMinConfidence(double minConfidence)
Proposed bounding boxes below this confidence interval are removed from consideration.
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checkMisconfigured, describeBean, describeChildren, duplicateBean, fields, findFieldsOfClass, getBeanName, getLocalPath, localise, toString
public List<LabelledWithConfidence<MultiScaleObject>> decode(List<ai.onnxruntime.OnnxTensor> inferenceOutput, ImageInferenceContext context) throws OperationFailedException
DecodeInstanceSegmentation
ObjectMask
s with confidence and
labels.
The created ObjectMask
s should match unscaledDimensions
in size.
decode
in class DecodeInstanceSegmentation<ai.onnxruntime.OnnxTensor>
inferenceOutput
- the tensors that are the result of the inference.context
- the context in which the inference is occurring.unscaledDimensions
in size.OperationFailedException
- if it cannot be decoded successfully.public List<String> expectedOutputs()
DecodeInstanceSegmentation
expectedOutputs
in class DecodeInstanceSegmentation<ai.onnxruntime.OnnxTensor>
public double getMinConfidence()
public void setMinConfidence(double minConfidence)
Copyright © 2010–2023 Owen Feehan, ETH Zurich, University of Zurich, Hoffmann-La Roche. All rights reserved.