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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
using System;
using itk.simple;
namespace itk.simple.examples {
class IterationUpdate : Command {
private ImageRegistrationMethod m_Method;
public IterationUpdate(ImageRegistrationMethod m) {
m_Method=m;
}
public override void Execute() {
VectorDouble pos = m_Method.GetOptimizerPosition();
Console.WriteLine("{0:3} = {1:10.5} : [{2}, {3}]",
m_Method.GetOptimizerIteration(),
m_Method.GetMetricValue(),
pos[0], pos[1]);
}
}
class ImageRegistrationMethod1 {
static void Main(string[] args) {
if ( args.Length < 3 )
{
Console.WriteLine("Usage: %s <fixedImageFilter> <movingImageFile> <outputTransformFile>\n", "ImageRegistrationMethod1");
return;
}
ImageFileReader reader = new ImageFileReader();
reader.SetOutputPixelType( PixelIDValueEnum.sitkFloat32 );
reader.SetFileName(args[0]);
Image fixedImage = reader.Execute();
reader.SetFileName(args[1]);
Image movingImage = reader.Execute();
ImageRegistrationMethod R = new ImageRegistrationMethod();
R.SetMetricAsMeanSquares();
double maxStep = 4.0;
double minStep = 0.01;
uint numberOfIterations = 200;
double relaxationFactor = 0.5;
R.SetOptimizerAsRegularStepGradientDescent( maxStep,
minStep,
numberOfIterations,
relaxationFactor );
R.SetInitialTransform( new TranslationTransform( fixedImage.GetDimension() ) );
R.SetInterpolator( InterpolatorEnum.sitkLinear );
IterationUpdate cmd = new IterationUpdate(R);
R.AddCommand(EventEnum.sitkIterationEvent, cmd);
Transform outTx = R.Execute( fixedImage, movingImage );
// System.out.println("-------");
// System.out.println(outTx.toString());
// System.out.format("Optimizer stop condition: %s\n", R.getOptimizerStopConditionDescription());
// System.out.format(" Iteration: %d\n", R.getOptimizerIteration());
// System.out.format(" Metric value: %f\n", R.getMetricValue());
outTx.WriteTransform(args[2]);
}
}
}
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