All Classes and Interfaces
Class
Description
Wrapper for a deep learning model in a pipeline using OpenCV.
Class to deal with script auto-completions.
A single completion.
Functional interface to extract a token from a string needed to determine
a completion.
Helper class for working with Bioimage Model Zoo model specs, and attempting to
replicating the processing within QuPath.
Convert OpenCV Mats into blobs (tensors) for use with a deep learning framework.
Simple plugin to attempt a very fast cell counting based upon (smoothed) peak detection.
Plugin to calculate coherence features for image tiles.
Helper class for creating a JSON-serializable way to generate a
ColorModel.Simple builder to create a
ColorModel.Helper class to the display of a single channel (band) in a
ColorModel.Data structure to hold cooccurrence matrices for computation of Haralick features.
Deprecated.
Deprecated.
v0.6.0, to be replaced by
DelaunayTools.SubdivisionClass for constructing and using density maps.
Builder for an
ImageServer representing a density map or for DensityMaps.DensityMapParameters.Class for storing parameters to build a
ImageServer representing a density map.Density map types.
Plugin to create new annotations by expanding the size of existing annotations.
Line cap to use for annotation expansion.
General interface for implementing a deep learning model in a pipeline using OpenCV.
Builder to create a
DnnModel from DnnModelParams.Parameters to build a
DnnModel.Builder for
DnnModelParams.Helper class for building new DnnModels.
Initial implementation of a patch-based
ObjectClassifier using an OpenCV-compatible DNN.Helper class to represent input and output shapes associated with
PredictionFunction.Tools for working with OpenCV's DNN module.
Helper class to summarize a DNN layer.
A simple superpixel-generating command based upon applying ImageJ's watershed transform to the
absolute values of a Difference-of-Gaussians filtered image.
Code for estimating stain vectors automatically from an image, or to launch an editor for visually/interactively modifying stain vectors.
Functional interface for scripting languages that are runnable (e.g.
Interface for extracting features from PathObjects for the purpose of object classification.
Helper class for extracting features from objects, used along with ObjectClassifiers.
Create a preprocessor for an image or training matrix.
Builder to create a custom
FeaturePreprocessor.Plugin to create new annotations by expanding the size of existing annotations.
Plugin to identify/remove detections from the convex hull of all detections.
Category class for enhanced Groovy scripting with OpenCV.
Static methods for computing Haralick texture features.
Helper class for computing Haralick features given a cooccurrence matrix.
Plugin for calculating Haralick texture features, within or around detections or tiles.
Helper class for filtering ImageJ images.
Helper class for working with ImageJ.
Store QuPath-related information within the properties of ImageJ objects.
Collection of static methods to help with using ImageJ with QuPath.
Request pixels from an image, potentially applying further transforms.
An
ImageServer that wraps an ImageData.Class to generate a
PixelProcessor when using ImageJ for the primary image representation.ImageServer that uses ImageJ's image-reading capabilities.
Builder for ImageServers that use ImageJ to read images.
An operation that may be applied to a
Mat.Create and use
ImageOp and ImageDataOp objects.Channel and color operations.
Core operations.
Filtering operations.
Machine learning operations.
Normalization operations.
Abstract
ImageOp to simplify the process of handling padding.Thresholding operations.
A functional interface for supplying an image region for processing.
Plugin for calculating intensity-based features, including Haralick textures, within or around detections or tiles.
Methods to help with requesting interpolated values.
Interface that can generate a 'lazy' value from an object.
Initial test implementation of Local Binary Patterns.
Calculate local binary pattern features.
Methods to normalize the local image intensity within an image, to have (approximately) zero mean and unit variance.
Helper class to store local normalization parameters.
Local normalization type.
2D or 3D Gaussian scale.
A functional interface for supplying a mask corresponding to an image.
Value extracted from an object's measurement list.
Create
PixelProcessor instances that make measurements from objects.Interface for calculating one custom measurement from an image, using
Parameters.Functions for calculating measurements from an array of pixels.
Methods to create custom measurements.
Implementation of morphological reconstruction for ImageJ.
Implementation of 2D morphological reconstruction, using 8-connectivity & a hybrid method.
Calculate pixel-based features in both 2D and 3D.
Helper class for storing and computing pixel features from Hessian matrices.
Hessian matrix values for 2D images.
Hessian matrix values for 3D images (z-stacks).
Image features, dependent on Gaussian scale.
Helper-class for computing pixel-features at a specified scale.
Helper map implementation that provides access to
MultiscaleFeatures.Hessian if needed.Class to help with simple feature normalization, by adding an offset and then multiplying by a scaling factor.
Read .npy and .npz files from NumPy.
Experimental class to generate object measurements.
Cell compartments.
Requested intensity measurements.
Standard measurements that may be computed from shapes.
QuPath wrappers for OpenCV classifiers, which are instances of StatModel.
Classifier based on
Boost.Classifier based on
DTrees.Clusterer based on
EM.Classifier based on
LogisticRegression.Classifier based on
NormalBayesClassifier.Wrapper class for a
StatModel, which standardizes how training may be performed and
parameters can be set.Classifier based on
RTrees.Classifier based on
SVM.Classifier based on
SVMSGD.Wrapper for an OpenCV Net, including essential metadata about how it should be used.
Helper class to build an
OpenCVDnn.Enum representing different classes of
Model supported by OpenCV.A
DnnModelBuilder implementation that uses OpenCV's DNN module
to build a Net.An
ObjectClassifier that uses an OpenCVClassifiers.OpenCVStatModel for classification.Initial implementation of a patch-based
ObjectClassifier using an OpenCV-compatible DNN.Class to generate a
PixelProcessor when using OpenCV for the primary image representation.Collection of static methods to help with using OpenCV from Java.
Class representing the indices of a pixel and its value.
Helper classes for combining OpenCV's JSON serialization with Gson's.
TypeAdapter that helps include OpenCV-based objects within a Java object being serialized to JSON.
TypeAdapterFactory that helps make OpenCV's serialization methods more compatible with custom JSON/Gson serialization.
A functional interface for handling the output of a
Processor.Parameters for use with a
PixelProcessor.Builder class for
Parameters.Parameters required to build a classifier that operates on an image patch.
Builder class to create
PatchClassifierParams.Helper class to create or access different
LazyValue instances.Helper class to compute area-based measurements for regions of interest based on pixel classification.
Static methods and classes for working with pixel classifiers.
Helper methods for working with pixel classification.
Options when creating objects from a pixel classifier.
Very simple wrapper that allows some non-ImageJ-oriented QuPath commands to access ImageProcessor pixel values.
A class for tiled image processing.
Builder class for a
PixelProcessorUtility functions to help with the
PixelProcessor class.Alternative implementation of
WatershedCellDetection that automatically applies 1 or 3 intensity thresholds to classify cells.Simple command to detect regions with positive staining.
Prediction function, typically used with a deep learning framework.
Helper class for preprocessing input for machine learning algorithms using OpenCV Mats.
Helper class to apply PCA projection.
Static methods to enable existing code for watershed transforms and morphological reconstruction
to be applied to OpenCV images.
A generic processor designed to work with
Parameters and provide an output.Collection of static methods that are useful for scripting.
Plugin to create new annotations by expanding the size of existing annotations.
Collection of static methods to help work with ROIs, binary & labelled images in ImageJ.
Default attributes that can be set when running scripts.
Interface for classes that implement auto-completion (e.g.
Abstract class to represent languages supported by the script editor.
Class that stores key information that is useful for running scripts.
Builder class for
ScriptParameters.Add shape measurements
Collection of static methods to threshold images, either with single global thresholds or
using the pixel values of a second image.
Very basic global thresholding command to identify tissue regions.
An implementation of SLIC superpixels, as described at http://ivrl.epfl.ch/research/superpixels
Plugin to supplement the measurements for detection objects with the weighted sum of measurements
from nearby objects, using weights derived from a 2D Gaussian function.
Plugin to create new annotations by expanding the size of existing annotations.
Experimental plugin to help with the quantification of subcellular structures.
Implementation of the 3D binary thinning algorithm of
Lee et al.
ImageWriter implementation to write TIFF images using ImageJ.
Plugin to merge classified tiles into annotation objects.
Simple plugin to create square tiles, which may later have measurements added.
Static methods used by the TMA dearrayer plugin.
Plugin for automatically dearraying tissue microarrays (TMAs).
Implementation of 2D watershed transform for ImageJ.
Implementation of 2D watershed transform.
Default command for cell detection within QuPath, assuming either a nuclear or cytoplasmic staining.
Cell detection that takes into consideration membrane staining.
ImageWriter implementation to write zipped TIFF images using ImageJ.
DelaunayTools.