Add Op annotations to relevant static methods

pom.xml

@@ -200,8 +200,8 @@ Jean-Yves Tinevez and Michael Zinsmaier.</license.copyrightOwners>
 
 		<!-- NB: Deploy releases to the SciJava Maven repository. -->
 		<releaseProfiles>sign,deploy-to-scijava</releaseProfiles>
-
 		<net.imglib2.imglib2.version>6.2.0</net.imglib2.imglib2.version>
+		<scijava.parse.ops>true</scijava.parse.ops>
 	</properties>
 
 	<repositories>
@@ -280,6 +280,24 @@ Jean-Yves Tinevez and Michael Zinsmaier.</license.copyrightOwners>
 
 	<build>
 		<plugins>
+			<plugin>
+				<artifactId>maven-compiler-plugin</artifactId>
+				<configuration>
+					<annotationProcessorPaths>
+						<path>
+							<groupId>org.scijava</groupId>
+							<artifactId>scijava-ops-indexer</artifactId>
+							<version>0-SNAPSHOT</version>
+						</path>
+					</annotationProcessorPaths>
+					<fork>true</fork>
+					<showWarnings>true</showWarnings>
+					<compilerArgs>
+						<arg>-Aparse.ops=${scijava.parse.ops}</arg>
+						<arg>-Aop.version=${project.version}</arg>
+					</compilerArgs>
+				</configuration>
+			</plugin>
 			<plugin>
 				<artifactId>maven-javadoc-plugin</artifactId>
 				<configuration>

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

@@ -59,6 +59,7 @@ public class Thresholder
 	 * Returns a new boolean {@link Img} generated by thresholding the values of
 	 * the source image.
 	 *
+	 * @implNote op name='threshold.value',type=Function
 	 * @param source
 	 *            the image to threshold.
 	 * @param threshold

src/main/java/net/imglib2/algorithm/componenttree/BuildComponentTree.java

@@ -86,7 +86,8 @@ public final class BuildComponentTree< T extends Type< T >, C extends PartialCom
 	 * {@link PartialComponent.Handler} which is responsible for building up the
 	 * tree structure. An implementations of {@link PartialComponent.Handler} is
 	 * provided for example by {@link PixelListComponentTree}.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildComponentTree',type=Function
 	 * @param input
 	 *            input image.
 	 * @param componentGenerator
@@ -110,7 +111,8 @@ public static < T extends Type< T >, C extends PartialComponent< T, C > > void b
 	 * {@link PartialComponent.Handler} which is responsible for building up the
 	 * tree structure. An implementations of {@link PartialComponent.Handler} is
 	 * provided for example by {@link PixelListComponentTree}.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildComponentTree',type=Function
 	 * @param input
 	 *            input image of a comparable value type.
 	 * @param componentGenerator

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

@@ -105,7 +105,8 @@ public final class MserTree< T extends Type< T > > implements ComponentForest< M
 	 * {@link #buildMserTree(RandomAccessibleInterval, RealType, long, long, double, double, ImgFactory, boolean)}
 	 * using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
 	 * input image size.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildMserTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param delta
@@ -133,7 +134,8 @@ public static < T extends RealType< T > > MserTree< T > buildMserTree( final Ran
 	 * {@link #buildMserTree(RandomAccessibleInterval, RealType, long, long, double, double, ImgFactory, boolean)}
 	 * using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
 	 * input image size.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildMserTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param delta
@@ -159,7 +161,8 @@ public static < T extends RealType< T > > MserTree< T > buildMserTree( final Ran
 
 	/**
 	 * Build a MSER tree from an input image.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildMserTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param delta
@@ -198,7 +201,8 @@ public static < T extends RealType< T > > MserTree< T > buildMserTree( final Ran
 	 * {@link #buildMserTree(RandomAccessibleInterval, ComputeDelta, long, long, double, double, ImgFactory, Type, Comparator)}
 	 * using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
 	 * input image size.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildMserTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param computeDelta
@@ -226,7 +230,8 @@ public static < T extends Type< T > > MserTree< T > buildMserTree( final RandomA
 
 	/**
 	 * Build a MSER tree from an input image.
-	 * 
+	 *
+	 * @implNote op name='componenttree.buildMserTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param computeDelta

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

@@ -74,6 +74,7 @@ public final class PixelListComponentTree< T extends Type< T > > implements Comp
 	 * using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
 	 * input image size.
 	 *
+	 * @implNote op name='componenttree.buildPixelListComponentTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param type
@@ -92,6 +93,7 @@ public static < T extends RealType< T > > PixelListComponentTree< T > buildCompo
 	/**
 	 * Build a component tree from an input image.
 	 *
+	 * @implNote op name='componenttree.buildPixelListComponentTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param type
@@ -120,6 +122,7 @@ public static < T extends RealType< T > > PixelListComponentTree< T > buildCompo
 	 * using an {@link ArrayImgFactory} or {@link CellImgFactory} depending on
 	 * input image size.
 	 *
+	 * @implNote op name='componenttree.buildPixelListComponentTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param maxValue
@@ -138,6 +141,7 @@ public static < T extends Type< T > > PixelListComponentTree< T > buildComponent
 	/**
 	 * Build a component tree from an input image.
 	 *
+	 * @implNote op name='componenttree.buildPixelListComponentTree',type=Function
 	 * @param input
 	 *            the input image.
 	 * @param maxValue

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

@@ -78,21 +78,33 @@ public class FastGauss
 		return Convolution.concat( steps );
 	}
 
+	/**
+	 * @implNote op name='convolve.fastGauss',type=Function
+	 */
 	public static Convolution< RealType< ? > > convolution( final double sigma )
 	{
 		return new MultiDimensionConvolution<>( k -> convolution( nCopies( k, sigma ) ) );
 	}
 
+	/**
+	 * @implNote op name='convolve.fastGauss',type=Function
+	 */
 	public static Convolution< RealType< ? > > convolution1d( final double sigma, final int direction )
 	{
 		return new LineConvolution<>( new FastGaussConvolverRealType( sigma ), direction );
 	}
 
+	/**
+	 * @implNote op name='convolve.fastGauss',type=Computer
+	 */
 	public static void convolve( final double[] sigmas, final RandomAccessible< ? extends RealType< ? > > input, final RandomAccessibleInterval< ? extends RealType< ? > > output )
 	{
 		convolution( sigmas ).process( input, output );
 	}
 
+	/**
+	 * @implNote op name='convolve.fastGauss',type=Computer
+	 */
 	public static void convolve( final double sigma, final RandomAccessible< ? extends RealType< ? > > input, final RandomAccessibleInterval< ? extends RealType< ? > > output )
 	{
 		convolution( sigma ).process( input, output );

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

@@ -53,9 +53,11 @@ public class Kernel1D
 	/**
 	 * Creates a one-dimensional symmetric convolution kernel.
 	 *
+	 * @implNote op name='create.kernel1DSymmetric',type=Function
 	 * @param halfKernel
 	 *            the upper half (starting at the center pixel) of the symmetric
 	 *            convolution kernel.
+	 * @return a {@link Kernel1D} used for one dimensional convolutions
 	 */
 	public static Kernel1D symmetric( final double... halfKernel )
 	{
@@ -68,6 +70,7 @@ public static Kernel1D symmetric( final double... halfKernel )
 	/**
 	 * Similar to {@link #symmetric(double[])} but creates an array of
 	 * one-dimensional convolution kernels.
+	 * @implNote op name='create.kernel1DSymmetric',type=Function
 	 */
 	public static Kernel1D[] symmetric( final double[][] halfKernels )
 	{
@@ -77,11 +80,13 @@ public static Kernel1D[] symmetric( final double[][] halfKernels )
 	/**
 	 * Creates a one-dimensional asymmetric convolution kernel.
 	 *
+	 * @implNote op name='create.kernel1DAsymmetric',type=Function
 	 * @param fullKernel
 	 *            an array containing the values of the kernel
 	 * @param originIndex
 	 *            the index of the array element which is the origin of the
 	 *            kernel
+	 * @return an asymmetric {@link Kernel1D} used for one dimensional convolutions
 	 */
 	public static Kernel1D asymmetric( final double[] fullKernel, final int originIndex )
 	{
@@ -94,6 +99,7 @@ public static Kernel1D asymmetric( final double[] fullKernel, final int originIn
 	/**
 	 * Creates a one-dimensional asymmetric convolution kernel, where the origin
 	 * of the kernel is in the middle.
+	 * @implNote op name='create.kernel1DCentralAsymmetric',type=Function
 	 */
 	public static Kernel1D centralAsymmetric( final double... kernel )
 	{
@@ -103,6 +109,7 @@ public static Kernel1D centralAsymmetric( final double... kernel )
 	/**
 	 * Similar to {@link #asymmetric(double[], int)} but creates an array of
 	 * one-dimensional convolution kernels.
+	 * @implNote op name='create.kernel1DAsymmetric',type=Function
 	 */
 	public static Kernel1D[] asymmetric( final double[][] fullKernels, final int[] originIndices )
 	{
@@ -113,6 +120,7 @@ public static Kernel1D[] asymmetric( final double[][] fullKernels, final int[] o
 	/**
 	 * Similar to {@link #centralAsymmetric(double...)} but creates an array of
 	 * one-dimensional convolution kernels.
+	 * @implNote op name='create.kernel1DCentralAsymmetric',type=Function
 	 */
 	public static Kernel1D[] centralAsymmetric( final double[][] kernels )
 	{

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

@@ -68,6 +68,9 @@ public class SeparableKernelConvolution
 	 * }
 	 * </pre>
 	 *
+	 * @param kernels the kernel(s) to use in the convolution
+	 * @return a {@link Convolution} object that can convolve an image
+	 * @implNote op name='filter.convolveSeparable',type=Function
 	 * @see Convolution
 	 */
 	public static Convolution< NumericType< ? > > convolution( final Kernel1D... kernels )
@@ -89,6 +92,10 @@ public class SeparableKernelConvolution
 	 * }
 	 * </pre>
 	 *
+	 * @param kernel the kernel to use in the convolution
+	 * @param direction the direction to use in the convolution
+	 * @return a {@link Convolution} object that can convolve an image
+	 * @implNote op name='filter.convolveSeparable',type=Function
 	 * @see Convolution
 	 */
 	public static Convolution< NumericType< ? > > convolution1d( final Kernel1D kernel, final int direction )
@@ -106,6 +113,7 @@ public class SeparableKernelConvolution
 	 * in their own precision. The source type S and target type T are either
 	 * both {@link RealType RealTypes} or both the same type.
 	 *
+	 * @implNote op name='filter.convolveSeparable',type=Computer
 	 * @param kernels
 	 *            an array containing kernels for every dimension.
 	 * @param source

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

@@ -60,6 +60,44 @@
  */
 public class DifferenceOfGaussian
 {
+	/**
+	 * Compute the difference of Gaussian for the input. Input convolved with
+	 * Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian
+	 * of sigmaLarger (where {@code sigmaLarger > sigmaSmaller}).
+	 * <p>
+	 * Creates an appropriate temporary image and calls
+	 * {@link #DoG(double[], double[], RandomAccessible, RandomAccessible, RandomAccessibleInterval, ExecutorService)}
+	 * .
+	 * </p>
+	 * This method differs from
+	 * {@link #DoG(double[], double[], RandomAccessible, RandomAccessibleInterval, ExecutorService)}
+	 * only in that its parameter order is tailored to an Op. The output comes
+	 * last, and the primary input (the input image) comes first.
+	 *
+	 * @implNote op name="filter.DoG", type=Computer
+	 * @param input
+	 *            the input image extended to infinity (or at least covering the
+	 *            same interval as the dog result image, plus borders for
+	 *            convolution).
+	 * @param sigmaSmaller
+	 *            stddev (in every dimension) of smaller Gaussian.
+	 * @param sigmaLarger
+	 *            stddev (in every dimension) of larger Gaussian.
+	 * @param service
+	 *            service providing threads for multi-threading
+	 * @param dog
+	 *            the Difference-of-Gaussian result image.
+	 */
+	public static < I extends NumericType< I >, T extends NumericType< T > & NativeType< T > > void DoG(
+			final RandomAccessible< I > input,
+			final double[] sigmaSmaller,
+			final double[] sigmaLarger,
+			final ExecutorService service,
+			final RandomAccessibleInterval< T > dog)
+	{
+		DoG( sigmaSmaller, sigmaLarger, input, dog, service );
+	}
+
 	/**
 	 * Compute the difference of Gaussian for the input. Input convolved with
 	 * 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
 		DoG( sigmaSmaller, sigmaLarger, input, Views.translate( g1, translation ), dog, service );
 	}
 
+	/**
+	 * Compute the difference of Gaussian for the input. Input convolved with
+	 * Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian
+	 * of sigmaLarger (where sigmaLarger &gt; sigmaSmaller).
+	 * </p>
+	 * This method differs from
+	 * {@link #DoG(double[], double[], RandomAccessible, RandomAccessible, RandomAccessibleInterval, ExecutorService)}
+	 * only in that its parameter order is tailored to an Op. The output comes
+	 * last, and the primary input (the input image) comes first.
+	 *
+	 * @implNote op name="filter.DoG", type=Computer
+	 * @param input
+	 *            the input image extended to infinity (or at least covering the
+	 *            same interval as the dog result image, plus borders for
+	 *            convolution).
+	 * @param sigmaSmaller
+	 *            stddev (in every dimension) of smaller Gaussian.
+	 * @param sigmaLarger
+	 *            stddev (in every dimension) of larger Gaussian.
+	 * @param tmp
+	 *            temporary image, must at least cover the same interval as the
+	 *            dog result image.
+	 * @param service
+	 *            how many threads to use for the computation.
+	 * @param dog
+	 *            the Difference-of-Gaussian result image.
+	 */
+	public static < I extends NumericType< I >, T extends NumericType< T > & NativeType< T > > void DoG(
+			final RandomAccessible< I > input,
+			final double[] sigmaSmaller,
+			final double[] sigmaLarger,
+			final RandomAccessible< T > tmp,
+			final ExecutorService service,
+			final RandomAccessibleInterval< T > dog)
+	{
+		DoG(sigmaSmaller, sigmaLarger, input, tmp, dog, service);
+	}
+
 	/**
 	 * Compute the difference of Gaussian for the input. Input convolved with
 	 * Gaussian of sigmaSmaller is subtracted from input convolved with Gaussian

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

@@ -73,7 +73,8 @@ public class SubpixelEdgelDetection
 	 * <p>
 	 * Note: The input image type must be a signed type! Otherwise gradient
 	 * computation will not work.
-	 * 
+	 *
+	 * @implNote op name='image.subpixelEdgels', type=Function
 	 * @param input
 	 *            input image
 	 * @param factory