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InpaintingTwoStep.cpp
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InpaintingTwoStep.cpp
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/*=========================================================================
*
* Copyright David Doria 2012 [email protected]
*
* 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.
*
*=========================================================================*/
// Custom
#include "Helpers/Helpers.h"
// Pixel descriptors
#include "PixelDescriptors/ImagePatchPixelDescriptor.h"
// Visitors
#include "Visitors/NearestNeighborsDefaultVisitor.hpp"
// Descriptor visitors
#include "Visitors/DescriptorVisitors/ImagePatchDescriptorVisitor.hpp"
// Inpainting visitors
#include "Visitors/InpaintingVisitor.hpp"
#include "Visitors/AcceptanceVisitors/DefaultAcceptanceVisitor.hpp"
// Nearest neighbors functions
#include "NearestNeighbor/LinearSearchBestProperty.hpp"
#include "NearestNeighbor/LinearSearchKNNProperty.hpp"
#include "NearestNeighbor/TwoStepNearestNeighbor.hpp"
// Initializers
#include "Initializers/InitializeFromMaskImage.hpp"
#include "Initializers/InitializePriority.hpp"
// Inpainters
#include "Inpainters/MaskImagePatchInpainter.hpp"
#include "Inpainters/HoleListPatchInpainter.hpp"
// Difference functions
#include "DifferenceFunctions/ImagePatchDifference.hpp"
#include "DifferenceFunctions/SumAbsolutePixelDifference.hpp"
#include "DifferenceFunctions/SumSquaredPixelDifference.hpp"
// Utilities
#include "Utilities/PatchHelpers.h"
// Inpainting
#include "Algorithms/InpaintingAlgorithm.hpp"
// Priority
#include "Priority/PriorityRandom.h"
// ITK
#include "itkImageFileReader.h"
// Boost
#include <boost/graph/grid_graph.hpp>
#include <boost/property_map/property_map.hpp>
#include <boost/graph/detail/d_ary_heap.hpp>
// Run with: Data/trashcan.png Data/trashcan.mask 15 filled.png
int main(int argc, char *argv[])
{
// Verify arguments
if(argc != 5)
{
std::cerr << "Required arguments: image.png imageMask.mask patchHalfWidth output.png" << std::endl;
std::cerr << "Input arguments: ";
for(int i = 1; i < argc; ++i)
{
std::cerr << argv[i] << " ";
}
return EXIT_FAILURE;
}
// Parse arguments
std::string imageFilename = argv[1];
std::string maskFilename = argv[2];
std::stringstream ssPatchHalfWidth;
ssPatchHalfWidth << argv[3];
unsigned int patchHalfWidth = 0;
ssPatchHalfWidth >> patchHalfWidth;
std::string outputFilename = argv[4];
// Output arguments
std::cout << "Reading image: " << imageFilename << std::endl;
std::cout << "Reading mask: " << maskFilename << std::endl;
std::cout << "Patch half width: " << patchHalfWidth << std::endl;
std::cout << "Output: " << outputFilename << std::endl;
typedef itk::VectorImage<float, 2> FloatVectorImageType;
typedef FloatVectorImageType ImageType;
typedef itk::ImageFileReader<ImageType> ImageReaderType;
ImageReaderType::Pointer imageReader = ImageReaderType::New();
imageReader->SetFileName(imageFilename);
imageReader->Update();
ImageType::Pointer image = ImageType::New();
ITKHelpers::DeepCopy(imageReader->GetOutput(), image.GetPointer());
Mask::Pointer mask = Mask::New();
mask->Read(maskFilename);
std::cout << "hole pixels: " << mask->CountHolePixels() << std::endl;
std::cout << "valid pixels: " << mask->CountValidPixels() << std::endl;
bool compatibleMask = PatchHelpers::CheckSurroundingRegionsOfAllHolePixels(mask, patchHalfWidth);
if(!compatibleMask)
{
throw std::runtime_error("The mask is not compatible!");
}
typedef ImagePatchPixelDescriptor<ImageType> ImagePatchPixelDescriptorType;
// Create the graph
typedef boost::grid_graph<2> VertexListGraphType;
boost::array<std::size_t, 2> graphSideLengths = { { imageReader->GetOutput()->GetLargestPossibleRegion().GetSize()[0],
imageReader->GetOutput()->GetLargestPossibleRegion().GetSize()[1] } };
VertexListGraphType graph(graphSideLengths);
typedef boost::graph_traits<VertexListGraphType>::vertex_descriptor VertexDescriptorType;
// Get the index map
typedef boost::property_map<VertexListGraphType, boost::vertex_index_t>::const_type IndexMapType;
IndexMapType indexMap(get(boost::vertex_index, graph));
// Create the priority map
typedef boost::vector_property_map<float, IndexMapType> PriorityMapType;
PriorityMapType priorityMap(num_vertices(graph), indexMap);
// Create the boundary status map. A node is on the current boundary if this property is true.
// This property helps the boundaryNodeQueue because we can mark here if a node has become no longer
// part of the boundary, so when the queue is popped we can check this property to see if it should
// actually be processed.
typedef boost::vector_property_map<bool, IndexMapType> BoundaryStatusMapType;
BoundaryStatusMapType boundaryStatusMap(num_vertices(graph), indexMap);
// Create the descriptor map. This is where the data for each pixel is stored.
typedef boost::vector_property_map<ImagePatchPixelDescriptorType, IndexMapType> ImagePatchDescriptorMapType;
ImagePatchDescriptorMapType imagePatchDescriptorMap(num_vertices(graph), indexMap);
// Create the patch inpainter. The inpainter needs to know the status of each pixel to determine if they should be inpainted.
typedef MaskImagePatchInpainter InpainterType;
InpainterType patchInpainter(patchHalfWidth, mask);
// Create the priority function
typedef PriorityRandom PriorityType;
PriorityType priorityFunction;
// Create the boundary node queue. The priority of each node is used to order the queue.
typedef boost::vector_property_map<std::size_t, IndexMapType> IndexInHeapMap;
IndexInHeapMap index_in_heap(indexMap);
// Create the priority compare functor
typedef std::less<float> PriorityCompareType;
PriorityCompareType lessThanFunctor;
typedef boost::d_ary_heap_indirect<VertexDescriptorType, 4, IndexInHeapMap, PriorityMapType, PriorityCompareType>
BoundaryNodeQueueType;
BoundaryNodeQueueType boundaryNodeQueue(priorityMap, index_in_heap, lessThanFunctor);
// Create the descriptor visitor
typedef ImagePatchDescriptorVisitor<VertexListGraphType, ImageType, ImagePatchDescriptorMapType>
ImagePatchDescriptorVisitorType;
ImagePatchDescriptorVisitorType imagePatchDescriptorVisitor(image, mask, imagePatchDescriptorMap, patchHalfWidth);
typedef DefaultAcceptanceVisitor<VertexListGraphType> AcceptanceVisitorType;
AcceptanceVisitorType acceptanceVisitor;
// Create the inpainting visitor
typedef InpaintingVisitor<VertexListGraphType, ImageType, BoundaryNodeQueueType,
ImagePatchDescriptorVisitorType, AcceptanceVisitorType, PriorityType,
PriorityMapType, BoundaryStatusMapType>
InpaintingVisitorType;
InpaintingVisitorType inpaintingVisitor(image, mask, boundaryNodeQueue,
imagePatchDescriptorVisitor, acceptanceVisitor, priorityMap,
&priorityFunction, patchHalfWidth,
boundaryStatusMap, outputFilename);
InitializePriority(mask, boundaryNodeQueue, priorityMap, &priorityFunction, boundaryStatusMap);
// Initialize the boundary node queue from the user provided mask image.
InitializeFromMaskImage<InpaintingVisitorType, VertexDescriptorType>(mask, &inpaintingVisitor);
std::cout << "PatchBasedInpaintingNonInteractive: There are " << boundaryNodeQueue.size()
<< " nodes in the boundaryNodeQueue" << std::endl;
typedef ImagePatchDifference<ImagePatchPixelDescriptorType, SumAbsolutePixelDifference<ImageType::PixelType> > PatchDifferenceType;
// Create the neighbor finder
typedef LinearSearchKNNProperty<ImagePatchDescriptorMapType, PatchDifferenceType> KNNSearchType;
unsigned int numberOfKNN = 1000;
KNNSearchType linearSearchKNN(imagePatchDescriptorMap, numberOfKNN);
typedef LinearSearchBestHistogram<ImagePatchDescriptorMapType> BestSearchType;
BestSearchType linearSearchBest(imagePatchDescriptorMap);
// typedef NearestNeighborsDefaultVisitor NNVisitorType;
// NNVisitorType defaultNNVisitor; // This is required, but not used here.
// TwoStepNearestNeighbor<KNNSearchType, BestSearchType, NNVisitorType> twoStepNearestNeighbor(linearSearchKNN, linearSearchBest, defaultNNVisitor);
TwoStepNearestNeighbor<KNNSearchType, BestSearchType> twoStepNearestNeighbor(linearSearchKNN, linearSearchBest);
// Perform the inpainting
InpaintingAlgorithm(graph, inpaintingVisitor, &boundaryStatusMap, &boundaryNodeQueue, twoStepNearestNeighbor, patchInpainter);
return EXIT_SUCCESS;
}