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BUG: Add tests demonstration current behavior of histogram based median
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blowekamp authored and Leengit committed May 4, 2021
1 parent f3108c7 commit 55d0fdf
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Showing 3 changed files with 255 additions and 2 deletions.
1 change: 1 addition & 0 deletions Modules/Filtering/LabelMap/ITKKWStyleOverwrite.txt
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@@ -1,4 +1,5 @@
test/*\.cxx Namespace Disable
test/itkAttributePositionLabelMapFilterTest1.cxx Namespace Disable
test/itkShapeLabelMapFilterGTest.cxx Namespace Disable
test/itkStatisticsLabelMapFilterGTest.cxx Namespace Disable
test/itkShapeLabelObjectAccessorsTest1.cxx SemicolonSpace Disable
5 changes: 3 additions & 2 deletions Modules/Filtering/LabelMap/test/CMakeLists.txt
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Expand Up @@ -273,7 +273,7 @@ itk_add_test(NAME itkLabelImageToStatisticsLabelMapFilterTest1
COMMAND ITKLabelMapTestDriver
--compare DATA{${ITK_DATA_ROOT}/Input/Spots.png}
${ITK_TEST_OUTPUT_DIR}/Spots-labelimage-to-statisticslabel.png
itkLabelImageToStatisticsLabelMapFilterTest1 DATA{${ITK_DATA_ROOT}/Input/Spots.png} DATA{${ITK_DATA_ROOT}/Input/Spots.png} ${ITK_TEST_OUTPUT_DIR}/Spots-labelimage-to-statisticslabel.png 0 1 1 1 128)
itkLabelImageToStatisticsLabelMapFilterTest1 DATA{${ITK_DATA_ROOT}/Input/Spots.png} DATA{${ITK_DATA_ROOT}/Input/Spots.png} ${ITK_TEST_OUTPUT_DIR}/Spots-labelimage-to-statisticslabel.png 0 1 1 1 256)
itk_add_test(NAME itkLabelMapFilterTest
COMMAND ITKLabelMapTestDriver itkLabelMapFilterTest)
itk_add_test(NAME itkLabelMapMaskImageFilterTest-0-0-0
Expand Down Expand Up @@ -598,6 +598,7 @@ itk_add_test(NAME itkStatisticsUniqueLabelMapFilterTest2
1 100)

set(ITKLabelMapGTests
itkShapeLabelMapFilterGTest.cxx)
itkShapeLabelMapFilterGTest.cxx
itkStatisticsLabelMapFilterGTest.cxx)

CreateGoogleTestDriver(ITKLabelMap "${ITKLabelMap-Test_LIBRARIES}" "${ITKLabelMapGTests}")
251 changes: 251 additions & 0 deletions Modules/Filtering/LabelMap/test/itkStatisticsLabelMapFilterGTest.cxx
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@@ -0,0 +1,251 @@
/*=========================================================================
*
* Copyright NumFOCUS
*
* 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.
*
*=========================================================================*/

#include "itkGTest.h"

#include "itkImage.h"
#include "itkLabelImageToStatisticsLabelMapFilter.h"
#include "itkImageRegionIterator.h"
#include <algorithm>


namespace
{

class StatisticsLabelMapFixture : public ::testing::Test
{
public:
StatisticsLabelMapFixture() = default;
~StatisticsLabelMapFixture() override = default;

protected:
void
SetUp() override
{}
void
TearDown() override
{}

template <unsigned int D, typename TPixelType = unsigned short>
struct FixtureUtilities
{
static const unsigned int Dimension = D;

using PixelType = TPixelType;
using ImageType = itk::Image<PixelType, Dimension>;

using LabelPixelType = unsigned char;
using LabelImageType = itk::Image<LabelPixelType, Dimension>;

using LabelObjectType = itk::StatisticsLabelObject<LabelPixelType, Dimension>;
using StatisticsLabelMapType = itk::LabelMap<LabelObjectType>;


static typename ImageType::Pointer
CreateImage()
{
typename ImageType::Pointer image = ImageType::New();

typename ImageType::SizeType imageSize;
imageSize.Fill(25);
image->SetRegions(typename ImageType::RegionType(imageSize));
image->Allocate();
image->FillBuffer(0);

return image;
}

static typename ImageType::Pointer
CreateImageRandom(PixelType randMax = 500, unsigned int randSeed = 0)
{
typename ImageType::Pointer image = ImageType::New();

typename ImageType::SizeType imageSize;
imageSize.Fill(25);
image->SetRegions(typename ImageType::RegionType(imageSize));
image->Allocate();
image->FillBuffer(0);

srand(randSeed);

itk::ImageRegionIterator<ImageType> it(image, image->GetLargestPossibleRegion());
while (!it.IsAtEnd())
{
it.Set(rand() % randMax);
++it;
}
return image;
}


static typename LabelImageType::Pointer
CreateLabelImage()
{
auto image = LabelImageType::New();

typename LabelImageType::SizeType imageSize;
imageSize.Fill(25);
image->SetRegions(typename ImageType::RegionType(imageSize));
image->Allocate();
image->FillBuffer(0);

return image;
}


static typename LabelObjectType::ConstPointer
ComputeLabelObject(const LabelImageType * labelImage,
const ImageType * image,
const PixelType label = 1,
const size_t numberOfBins = 0)
{

auto l2s = itk::LabelImageToStatisticsLabelMapFilter<LabelImageType, ImageType>::New();
l2s->SetInput1(labelImage);
l2s->SetFeatureImage(image);
l2s->ComputeFeretDiameterOn();
l2s->ComputePerimeterOn();
// l2s->ComputeOrientedBoundingBoxOn();
l2s->ComputeHistogramOn();
if (numberOfBins != 0)
{
l2s->SetNumberOfBins(numberOfBins);
}
l2s->Update();
return l2s->GetOutput()->GetLabelObject(label);
}

static double
ComputeExactMedian(const LabelObjectType * labelObject, const ImageType * image)
{
std::vector<PixelType> values;
typename LabelObjectType::ConstIndexIterator it(labelObject);

while (!it.IsAtEnd())
{
const typename ImageType::IndexType & idx = it.GetIndex();
values.push_back(image->GetPixel(idx));
++it;
}

std::sort(values.begin(), values.end());

auto n1 = values.size() / 2;
if (values.size() % 2 == 0)
{
return 0.5 * (double(values[n1]) + double(values[n1 - 1]));
}
return values[n1];
}
};
};
} // namespace


TEST_F(StatisticsLabelMapFixture, 2D_zero)
{
using Utils = FixtureUtilities<2, unsigned char>;

auto image = Utils::CreateImage();
auto labelImage = Utils ::CreateLabelImage();

Utils::LabelPixelType label = 1;
labelImage->FillBuffer(label);


Utils::LabelObjectType::ConstPointer labelObject = Utils::ComputeLabelObject(labelImage, image, 1, 1 << 8);

EXPECT_NEAR(0.0, labelObject->GetMinimum(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetMaximum(), 1e-12);
EXPECT_NEAR(Utils::ComputeExactMedian(labelObject, image), labelObject->GetMedian(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetSum(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetVariance(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetStandardDeviation(), 1e-12);

if (::testing::Test::HasFailure())
{
labelObject->Print(std::cout);
}
}


TEST_F(StatisticsLabelMapFixture, 2D_ones_with_outliers)
{
using Utils = FixtureUtilities<2, signed short>;

auto image = Utils::CreateImage();
Utils::PixelType value = 1;
image->FillBuffer(value);

// Test with outliers outside the label.
image->SetPixel({ 0, 0 }, 32000);
image->SetPixel({ 0, 1 }, -32000);


auto labelImage = Utils ::CreateLabelImage();
Utils::LabelPixelType label = 1;
labelImage->FillBuffer(label);
labelImage->SetPixel({ 0, 0 }, 0);
labelImage->SetPixel({ 0, 1 }, 0);

Utils::LabelObjectType::ConstPointer labelObject = Utils::ComputeLabelObject(labelImage, image, label, 1 << 16);

EXPECT_NEAR(value, labelObject->GetMinimum(), 1e-12);
EXPECT_NEAR(value, labelObject->GetMaximum(), 1e-12);
EXPECT_NEAR(Utils::ComputeExactMedian(labelObject, image), labelObject->GetMedian(), 0.5);
EXPECT_NEAR(25 * 25 - 2, labelObject->GetSum(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetVariance(), 1e-12);
EXPECT_NEAR(0.0, labelObject->GetStandardDeviation(), 1e-12);

if (::testing::Test::HasFailure())
{
labelObject->Print(std::cout);
}
}

TEST_F(StatisticsLabelMapFixture, 2D_rand_with_outliers)
{
using Utils = FixtureUtilities<2, signed short>;

auto image = Utils::CreateImageRandom(500, 0);
auto labelImage = Utils ::CreateLabelImage();

// Test with outliers outside the label.
image->SetPixel({ 0, 0 }, 32000);
image->SetPixel({ 0, 1 }, -2000);
// Set min/max in label
image->SetPixel({ 0, 2 }, 0);
image->SetPixel({ 0, 3 }, 500);

Utils::LabelPixelType label = 1;
labelImage->FillBuffer(label);
labelImage->SetPixel({ 0, 0 }, 0);
labelImage->SetPixel({ 0, 1 }, 0);


Utils::LabelObjectType::ConstPointer labelObject = Utils::ComputeLabelObject(labelImage, image, label, 1 << 16);

EXPECT_NEAR(0.0, labelObject->GetMinimum(), 1e-12);
EXPECT_NEAR(500.0, labelObject->GetMaximum(), 1e-12);
EXPECT_NEAR(Utils::ComputeExactMedian(labelObject, image), labelObject->GetMedian(), 0.5);

if (::testing::Test::HasFailure())
{
labelObject->Print(std::cout);
}
}

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