Index
C D E G I O P S
All Classes All Packages
All Classes All Packages
All Classes All Packages
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
modelPathfrom 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
Stackusing the ONNX Runtime to produce anObjectCollection. - 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
.onnxmodel 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
modelPathfrom the file-system, it is read from Java resources on the class-path.
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