Index (anchor-plugin-onnx 1.0.2 API)

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C

close() - Method in class org.anchoranalysis.plugin.onnx.model.OnnxModel
createModelPool(ConcurrencyPlan, Logger) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel

D

decode(List<OnnxTensor>, ImageInferenceContext) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN
decode(List<OnnxTensor>, ImageInferenceContext) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text.DecodeEAST
DecodeEAST - Class in org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text: Extracts text from a RGB image by using the EAST deep neural network model and the ONNX Runtime.
DecodeEAST() - Constructor for class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text.DecodeEAST
DecodeMaskRCNN - Class in org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn: Decodes the inference output from a Mask-RCNN implementation.
DecodeMaskRCNN() - Constructor for class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN
deriveInput(Stack, Optional<double[]>) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel

E

expectedOutputs() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN
expectedOutputs() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text.DecodeEAST

G

getInputName() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: The name of the input in the ONNX model.
getInterpolator() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: The interpolator to use for scaling images.
getMinConfidence() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: Only proposals outputted from the model with a score greater or equal to this threshold are considered.
getMinConfidence() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text.DecodeEAST: Proposed bounding boxes below this confidence interval are removed from consideration.
getMinMaskValue() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: Only voxels with a value greater or equal to this threshold are considered as part of the mask.
getModelPath() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: Relative-path to the model file in ONNX form, relative to the models/ directory in the Anchor distribution.

I

inputName() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel
isIncludeBatchDimension() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: If true, a 4-dimensional tensor is created (with the first dimension describing a batch-size of 1), instead of the usual 3-dimensional tensor describing channel, height, width.
isInterleaveChannels() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: If true, the channels are placed as the final position of the tensor (**after** width/height) instead of **before** width/height.
isReadFromResources() - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: When true, rather than reading modelPath from the file-system, it is read from Java resources on the class-path.

O

OnnxModel - Class in org.anchoranalysis.plugin.onnx.model: A model that can be used for inference using the ONNX Runtime's Java API.
OnnxModel(OrtSession) - Constructor for class org.anchoranalysis.plugin.onnx.model.OnnxModel
org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn - package org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn: Decodes the outputted tensors from a Mask R-CNN implementation.
org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text - package org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text: Decodes the outputted tensors from text-segmentation models.
org.anchoranalysis.plugin.onnx.bean.object.segment.stack - package org.anchoranalysis.plugin.onnx.bean.object.segment.stack: Segmenting a Stack using the ONNX Runtime to produce an ObjectCollection.
org.anchoranalysis.plugin.onnx.model - package org.anchoranalysis.plugin.onnx.model: Non-bean classes for running an inference model with the ONNX Runtime.

P

performInference(OnnxTensor, String, List<String>, CheckedFunction<List<OnnxTensor>, S, OperationFailedException>) - Method in class org.anchoranalysis.plugin.onnx.model.OnnxModel

S

SegmentObjectsFromONNXModel - Class in org.anchoranalysis.plugin.onnx.bean.object.segment.stack: Performs instance-segmentation using the ONNX Runtime and an .onnx model file.
SegmentObjectsFromONNXModel() - Constructor for class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel
setIncludeBatchDimension(boolean) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: If true, a 4-dimensional tensor is created (with the first dimension describing a batch-size of 1), instead of the usual 3-dimensional tensor describing channel, height, width.
setInputName(String) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: The name of the input in the ONNX model.
setInterleaveChannels(boolean) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: If true, the channels are placed as the final position of the tensor (**after** width/height) instead of **before** width/height.
setInterpolator(Interpolator) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: The interpolator to use for scaling images.
setMinConfidence(double) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.text.DecodeEAST: Proposed bounding boxes below this confidence interval are removed from consideration.
setMinConfidence(float) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: Only proposals outputted from the model with a score greater or equal to this threshold are considered.
setMinMaskValue(float) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.decode.instance.maskrcnn.DecodeMaskRCNN: Only voxels with a value greater or equal to this threshold are considered as part of the mask.
setModelPath(String) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: Relative-path to the model file in ONNX form, relative to the models/ directory in the Anchor distribution.
setReadFromResources(boolean) - Method in class org.anchoranalysis.plugin.onnx.bean.object.segment.stack.SegmentObjectsFromONNXModel: When true, rather than reading modelPath from the file-system, it is read from Java resources on the class-path.

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