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Opify ImgLib2 Algorithm
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‎.github/workflows/build-main.yml

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@@ -16,7 +16,7 @@ jobs:
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- name: Set up Java
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uses: actions/setup-java@v3
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with:
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java-version: '8'
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java-version: '11'
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distribution: 'zulu'
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cache: 'maven'
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- name: Set up CI environment

‎.github/workflows/build-pr.yml

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@@ -14,7 +14,7 @@ jobs:
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- name: Set up Java
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uses: actions/setup-java@v3
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with:
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java-version: '8'
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java-version: '11'
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distribution: 'zulu'
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cache: 'maven'
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- name: Set up CI environment

‎pom.xml

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@@ -206,6 +206,22 @@ Jean-Yves Tinevez and Michael Zinsmaier.</license.copyrightOwners>
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<imglib2-roi.version>0.15.0</imglib2-roi.version>
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<imglib2-cache.version>1.0.0-beta-18</imglib2-cache.version>
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<sc.fiji.bigdataviewer-core.version>10.4.16</sc.fiji.bigdataviewer-core.version>
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<!--
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NB: Older versions of OpenJDK 11 have a bug in the javadoc tool,
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which causes errors like:
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[ERROR] javadoc: error - The code being documented uses packages
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in the unnamed module, but the packages defined in
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https://github.com/scijava/scijava/apidocs/ are in named modules.
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The most recent version of OpenJDK 11 known to have this problem
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is 11.0.8; the oldest version known to have fixed it is 11.0.17.
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Therefore, we set the minimum build JDK version to 11.0.17 here.
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-->
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<scijava.jvm.build.version>[11.0.17,)</scijava.jvm.build.version>
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<scijava.jvm.version>8</scijava.jvm.version>
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<scijava.parse.ops>true</scijava.parse.ops>
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</properties>
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<repositories>
@@ -281,4 +297,39 @@ Jean-Yves Tinevez and Michael Zinsmaier.</license.copyrightOwners>
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<scope>test</scope>
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</dependency>
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</dependencies>
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<!-- TODO: Remove relevant sections once upstream -->
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<build>
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<plugins>
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<plugin>
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<artifactId>maven-compiler-plugin</artifactId>
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<configuration>
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<annotationProcessorPaths>
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<path>
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<groupId>org.scijava</groupId>
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<artifactId>scijava-ops-indexer</artifactId>
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<version>1.0.0</version>
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</path>
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</annotationProcessorPaths>
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<fork>true</fork>
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<compilerArgs>
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<arg>-Ascijava.ops.parse=${scijava.parse.ops}</arg>
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<arg>-Ascijava.ops.opVersion=${project.version}</arg>
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</compilerArgs>
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</configuration>
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</plugin>
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<plugin>
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<artifactId>maven-javadoc-plugin</artifactId>
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<configuration>
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<tags>
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<tag>
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<name>implNote</name>
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<placement>a</placement>
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<head>Implementation Note:</head>
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</tag>
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</tags>
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</configuration>
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</plugin>
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</plugins>
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</build>
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</project>

‎src/main/java/net/imglib2/algorithm/binary/Thresholder.java

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@@ -70,6 +70,7 @@ public class Thresholder
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* the number of threads to use for thresholding.
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* @return a new {@link Img} of type {@link BitType} and of same dimension
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* that the source image.
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* @implNote op name='threshold.apply'
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*/
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public static final < T extends Type< T > & Comparable< T >> Img< BitType > threshold( final Img< T > source, final T threshold, final boolean above, final int numThreads )
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{

‎src/main/java/net/imglib2/algorithm/componenttree/mser/MserTree.java

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@@ -105,7 +105,8 @@ public final class MserTree< T extends Type< T > > implements ComponentForest< M
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* {@link #buildMserTree(RandomAccessibleInterval, RealType, long, long, double, double, ImgFactory, boolean)}
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* using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
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* input image size.
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*
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*
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* @implNote op name='create.mserTree',type=Function
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* @param input
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* the input image.
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* @param delta
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* {@link #buildMserTree(RandomAccessibleInterval, RealType, long, long, double, double, ImgFactory, boolean)}
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* using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
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* input image size.
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*
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*
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* @implNote op name='create.mserTree',type=Function
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* @param input
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* the input image.
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* @param delta
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/**
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* Build a MSER tree from an input image.
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*
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*
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* @implNote op name='create.mserTree',type=Function
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* @param input
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* the input image.
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* @param delta
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* {@link #buildMserTree(RandomAccessibleInterval, ComputeDelta, long, long, double, double, ImgFactory, Type, Comparator)}
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* using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
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* input image size.
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*
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*
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* @implNote op name='create.mserTree',type=Function
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* @param input
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* the input image.
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* @param computeDelta
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/**
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* Build a MSER tree from an input image.
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*
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*
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* @implNote op name='create.mserTree',type=Function
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* @param input
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* the input image.
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* @param computeDelta

‎src/main/java/net/imglib2/algorithm/componenttree/pixellist/PixelListComponentTree.java

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@@ -74,6 +74,7 @@ public final class PixelListComponentTree< T extends Type< T > > implements Comp
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* using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
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* input image size.
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*
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* @implNote op name='create.pixelListComponentTree',type=Function
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* @param input
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* the input image.
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* @param type
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/**
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* Build a component tree from an input image.
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*
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* @implNote op name='create.pixelListComponentTree',type=Function
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* @param input
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* the input image.
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* @param type
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* using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
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* input image size.
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*
125+
* @implNote op name='create.pixelListComponentTree',type=Function
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* @param input
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* the input image.
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* @param maxValue
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138141
/**
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* Build a component tree from an input image.
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*
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* @implNote op name='create.pixelListComponentTree',type=Function
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* @param input
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* the input image.
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* @param maxValue

‎src/main/java/net/imglib2/algorithm/convolution/fast_gauss/FastGauss.java

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@@ -88,11 +88,23 @@ public class FastGauss
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return new LineConvolution<>( new FastGaussConvolverRealType( sigma ), direction );
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}
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91+
/**
92+
* @param sigmas the standard deviations of the Gaussian blur (in each dimension)
93+
* @param input the input data to blur
94+
* @param output the preallocated output buffer
95+
* @implNote op name='filter.gauss', type=Computer
96+
*/
9197
public static void convolve( final double[] sigmas, final RandomAccessible< ? extends RealType< ? > > input, final RandomAccessibleInterval< ? extends RealType< ? > > output )
9298
{
9399
convolution( sigmas ).process( input, output );
94100
}
95101

102+
/**
103+
* @param sigma the standard deviation of the Gaussian blur (in all dimensions)
104+
* @param input the input data to blur
105+
* @param output the preallocated output buffer
106+
* @implNote op name='filter.gauss', type=Computer
107+
*/
96108
public static void convolve( final double sigma, final RandomAccessible< ? extends RealType< ? > > input, final RandomAccessibleInterval< ? extends RealType< ? > > output )
97109
{
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convolution( sigma ).process( input, output );

‎src/main/java/net/imglib2/algorithm/convolution/kernel/Kernel1D.java

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@@ -56,6 +56,8 @@ public class Kernel1D
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* @param halfKernel
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* the upper half (starting at the center pixel) of the symmetric
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* convolution kernel.
59+
* @return a {@link Kernel1D} used for one dimensional convolutions
60+
* @implNote op name='create.kernel1DSymmetric'
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*/
6062
public static Kernel1D symmetric( final double... halfKernel )
6163
{
@@ -68,6 +70,9 @@ public static Kernel1D symmetric( final double... halfKernel )
6870
/**
6971
* Similar to {@link #symmetric(double[])} but creates an array of
7072
* one-dimensional convolution kernels.
73+
* @param halfKernels the upper halves (starting at the center pixel) of the symmetric convolution kernels
74+
* @return an array of {@link Kernel1D}s used for one dimensional convolutions
75+
* @implNote op name='create.kernel1DSymmetric'
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*/
7277
public static Kernel1D[] symmetric( final double[][] halfKernels )
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{
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8287
* @param originIndex
8388
* the index of the array element which is the origin of the
8489
* kernel
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* @return an asymmetric {@link Kernel1D} used for one dimensional convolutions
91+
* @implNote op name='create.kernel1DAsymmetric'
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*/
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public static Kernel1D asymmetric( final double[] fullKernel, final int originIndex )
8794
{
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/**
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* Creates a one-dimensional asymmetric convolution kernel, where the origin
96103
* of the kernel is in the middle.
104+
* @param kernel the raw data of the symmetric convolution kernel
105+
* @return a {@link Kernel1D} used for one dimensional convolutions
106+
* @implNote op name='create.kernel1DCentralAsymmetric'
97107
*/
98108
public static Kernel1D centralAsymmetric( final double... kernel )
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{
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103113
/**
104114
* Similar to {@link #asymmetric(double[], int)} but creates an array of
105115
* one-dimensional convolution kernels.
116+
* @param fullKernels
117+
* arrays containing the values of each kernel
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* @param originIndices
119+
* the indices of the array elements at the origin of each
120+
* kernel
121+
* @return an array of {@link Kernel1D}s used for one dimensional convolutions
122+
* @implNote op name='create.kernel1DAsymmetric'
106123
*/
107124
public static Kernel1D[] asymmetric( final double[][] fullKernels, final int[] originIndices )
108125
{
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113130
/**
114131
* Similar to {@link #centralAsymmetric(double...)} but creates an array of
115132
* one-dimensional convolution kernels.
133+
* @param kernels the upper halves (starting at the center pixel) of the symmetric convolution kernels
134+
* @return an array of {@link Kernel1D}s used for one dimensional convolutions
135+
* @implNote op name='create.kernel1DCentralAsymmetric'
116136
*/
117137
public static Kernel1D[] centralAsymmetric( final double[][] kernels )
118138
{

‎src/main/java/net/imglib2/algorithm/convolution/kernel/SeparableKernelConvolution.java

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* the required source interval.
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* @param target
116116
* target image.
117+
* @implNote op name='filter.convolve', type=Computer
117118
*/
118119
public static void convolve( final Kernel1D[] kernels,
119120
final RandomAccessible< ? extends NumericType< ? > > source,

‎src/main/java/net/imglib2/algorithm/dog/DifferenceOfGaussian.java

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*/
6161
public class DifferenceOfGaussian
6262
{
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/**
64+
* Compute the difference of Gaussian for the input. Input convolved with
65+
* Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian
66+
* of sigmaLarger (where {@code sigmaLarger > sigmaSmaller}).
67+
* <p>
68+
* Creates an appropriate temporary image and calls
69+
* {@link #DoG(double[], double[], RandomAccessible, RandomAccessible, RandomAccessibleInterval, ExecutorService)}
70+
* .
71+
* </p>
72+
* This method differs from
73+
* {@link #DoG(double[], double[], RandomAccessible, RandomAccessibleInterval, ExecutorService)}
74+
* only in that its parameter order is tailored to an Op. The output comes
75+
* last, and the primary input (the input image) comes first.
76+
*
77+
* @implNote op name="filter.DoG", type=Computer
78+
* @param input
79+
* the input image extended to infinity (or at least covering the
80+
* same interval as the dog result image, plus borders for
81+
* convolution).
82+
* @param sigmaSmaller
83+
* stddev (in every dimension) of smaller Gaussian.
84+
* @param sigmaLarger
85+
* stddev (in every dimension) of larger Gaussian.
86+
* @param service
87+
* service providing threads for multi-threading
88+
* @param dog
89+
* the Difference-of-Gaussian result image.
90+
*/
91+
public static < I extends NumericType< I >, T extends NumericType< T > & NativeType< T > > void DoG(
92+
final RandomAccessible< I > input,
93+
final double[] sigmaSmaller,
94+
final double[] sigmaLarger,
95+
final ExecutorService service,
96+
final RandomAccessibleInterval< T > dog)
97+
{
98+
DoG( sigmaSmaller, sigmaLarger, input, dog, service );
99+
}
100+
63101
/**
64102
* Compute the difference of Gaussian for the input. Input convolved with
65103
* Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian
@@ -97,6 +135,44 @@ public static < I extends NumericType< I >, T extends NumericType< T > & NativeT
97135
DoG( sigmaSmaller, sigmaLarger, input, Views.translate( g1, translation ), dog, service );
98136
}
99137

138+
/**
139+
* Compute the difference of Gaussian for the input. Input convolved with
140+
* Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian
141+
* of sigmaLarger (where sigmaLarger &gt; sigmaSmaller).
142+
* </p>
143+
* This method differs from
144+
* {@link #DoG(double[], double[], RandomAccessible, RandomAccessible, RandomAccessibleInterval, ExecutorService)}
145+
* only in that its parameter order is tailored to an Op. The output comes
146+
* last, and the primary input (the input image) comes first.
147+
*
148+
* @implNote op name="filter.DoG", type=Computer
149+
* @param input
150+
* the input image extended to infinity (or at least covering the
151+
* same interval as the dog result image, plus borders for
152+
* convolution).
153+
* @param sigmaSmaller
154+
* stddev (in every dimension) of smaller Gaussian.
155+
* @param sigmaLarger
156+
* stddev (in every dimension) of larger Gaussian.
157+
* @param tmp
158+
* temporary image, must at least cover the same interval as the
159+
* dog result image.
160+
* @param service
161+
* how many threads to use for the computation.
162+
* @param dog
163+
* the Difference-of-Gaussian result image.
164+
*/
165+
public static < I extends NumericType< I >, T extends NumericType< T > & NativeType< T > > void DoG(
166+
final RandomAccessible< I > input,
167+
final double[] sigmaSmaller,
168+
final double[] sigmaLarger,
169+
final RandomAccessible< T > tmp,
170+
final ExecutorService service,
171+
final RandomAccessibleInterval< T > dog)
172+
{
173+
DoG(sigmaSmaller, sigmaLarger, input, tmp, dog, service);
174+
}
175+
100176
/**
101177
* Compute the difference of Gaussian for the input. Input convolved with
102178
* Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian

‎src/main/java/net/imglib2/algorithm/edge/SubpixelEdgelDetection.java

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Original file line numberDiff line numberDiff line change
@@ -73,7 +73,8 @@ public class SubpixelEdgelDetection
7373
* <p>
7474
* Note: The input image type must be a signed type! Otherwise gradient
7575
* computation will not work.
76-
*
76+
*
77+
* @implNote op name='image.subpixelEdgels', type=Function
7778
* @param input
7879
* input image
7980
* @param factory

‎src/main/java/net/imglib2/algorithm/fill/FloodFill.java

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@@ -90,6 +90,7 @@ public class FloodFill
9090
* input pixel type
9191
* @param <U>
9292
* fill label type
93+
* @implNote op name='image.floodFill', type=Computer2
9394
*/
9495
public static < T extends Type< T >, U extends Type< U > > void fill(
9596
final RandomAccessible< T > source,
@@ -138,6 +139,7 @@ public static < T extends Type< T >, U extends Type< U > > void fill(
138139
* input pixel type
139140
* @param <U>
140141
* fill label type
142+
* @implNote op name='image.floodFill', type=Computer2
141143
*/
142144
public static < T, U extends Type< U > > void fill(
143145
final RandomAccessible< T > source,
@@ -180,6 +182,7 @@ public static < T, U extends Type< U > > void fill(
180182
* input pixel type
181183
* @param <U>
182184
* fill label type
185+
* @implNote op name='image.floodFill', type=Computer2
183186
*/
184187
public static < T, U > void fill(
185188
final RandomAccessible< T > source,

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