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initial work on post processor that highlights cracks forming in mate…
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…rials
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@dicengine
dicengine committed Apr 29, 2021
1 parent c17c292 commit 77ab7aa
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Showing 4 changed files with 281 additions and 18 deletions.
229 changes: 222 additions & 7 deletions src/core/DICe_PostProcessor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,11 @@
#include <Teuchos_LAPACK.hpp>
#include <Teuchos_SerialDenseMatrix.hpp>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/imgproc.hpp>

#include <fstream>

namespace DICe {
Expand Down Expand Up @@ -230,6 +235,216 @@ Post_Processor::initialize_neighborhood(const scalar_t & neighborhood_radius){
DEBUG_MSG("Post_Processor::initialize_neighborhood(): end");
}

Crack_Locator_Post_Processor::Crack_Locator_Post_Processor(const Teuchos::RCP<Teuchos::ParameterList> & params) :
Post_Processor(post_process_crack_locator){
window_size_ = 25;
ref_img_ = Teuchos::null;
// no new fields added since the post processor writes output files instead
DEBUG_MSG("Enabling post processor Crack_Locator_Post_Processor with no new associated fields:");
set_params(params);
}

void
Crack_Locator_Post_Processor::set_params(const Teuchos::RCP<Teuchos::ParameterList> & params){
window_size_ = params->get<int_t>(crack_locator_window_size,25);
DEBUG_MSG("Crack_Locator_Post_Processor set_params(): using window size " << window_size_);
}

void
Crack_Locator_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("Crack_Locator_Post_Processor execute() begin");
assert(ref_img!=Teuchos::null);
assert(def_img!=Teuchos::null);
if(ref_img_==Teuchos::null) ref_img_ = Teuchos::rcp(new DICe::Image(ref_img)); // deep copy the reference image in case it gets modified or swapped later
assert(ref_img_!=Teuchos::null);
// get the image width and height:
const int_t width = ref_img_->width();
const int_t height = ref_img_->height();

// create opencv mat images, start with 16 bit then equalize the histogram
cv::Mat ref = cv::Mat(height,width,CV_32FC1,cv::Scalar(0));
cv::Mat def = cv::Mat(height,width,CV_32FC1,cv::Scalar(0));
cv::Mat map = cv::Mat(height,width,CV_32FC1,cv::Scalar(0));
// for(int_t y=0;y<height;++y){
// for(int_t x=0;x<width;++x){
// ref.at<float>(y,x) = 0.0f;
// def.at<float>(y,x) = 0.0f;
// def.at<float>(y,x) = 0.0f;
// }
// }


// ensure only in serial for now TODO enable parallel post processor for this
const int_t num_procs = mesh_->get_comm()->get_size();
TEUCHOS_TEST_FOR_EXCEPTION(num_procs!=1,std::runtime_error,"Plotly_Contour_Post_Processor only works in serial");

// gather the current coordinates of the subsets with sigma>=0 or all valid points
Teuchos::RCP<MultiField> coords_x = mesh_->get_field(DICe::field_enums::SUBSET_COORDINATES_X_FS);
Teuchos::RCP<MultiField> coords_y = mesh_->get_field(DICe::field_enums::SUBSET_COORDINATES_Y_FS);
Teuchos::RCP<MultiField> disp_x = mesh_->get_field(DICe::field_enums::SUBSET_DISPLACEMENT_X_FS);
Teuchos::RCP<MultiField> disp_y = mesh_->get_field(DICe::field_enums::SUBSET_DISPLACEMENT_Y_FS);
Teuchos::RCP<MultiField> sigma = mesh_->get_field(DICe::field_enums::SIGMA_FS);

// count the number of valid points
int_t num_valid_pts = 0;
for(int_t i=0;i<local_num_points_;++i)
if(sigma->local_value(i)>=0.0)
num_valid_pts++;
std::vector<int_t> local_ids(num_valid_pts,0);

// create neighborhood lists using nanoflann:
DEBUG_MSG("creating the point cloud using nanoflann");
point_cloud_ = Teuchos::rcp(new Point_Cloud_2D<scalar_t>());
point_cloud_->pts.resize(num_valid_pts);
int_t current_pt = 0;
for(int_t i=0;i<local_num_points_;++i){
if(sigma->local_value(i)<0.0) continue;
point_cloud_->pts[current_pt].x = coords_x->local_value(i) + disp_x->local_value(i);
point_cloud_->pts[current_pt].y = coords_y->local_value(i) + disp_y->local_value(i);
local_ids[current_pt++] = i;
}
DEBUG_MSG("building the kd-tree");
Teuchos::RCP<kd_tree_2d_t> kd_tree = Teuchos::rcp(new kd_tree_2d_t(2 /*dim*/, *point_cloud_.get(), nanoflann::KDTreeSingleIndexAdaptorParams(10 /* max leaf */) ) );
kd_tree->buildIndex();
DEBUG_MSG("kd-tree completed");

const int_t N = 3;
int *IPIV = new int[N+1];
int LWORK = N*N;
int INFO = 0;
double *WORK = new double[LWORK];
double *GWORK = new double[10*N];
int *IWORK = new int[LWORK];
// Note, LAPACK does not allow templating on long int or scalar_t...must use int and double
Teuchos::LAPACK<int,double> lapack;
std::vector<std::pair<size_t,scalar_t> > ret_matches;
nanoflann::SearchParams params;
params.sorted = true; // sort by distance in ascending order
const double neigh_rad_sq = window_size_*window_size_;
scalar_t query_pt[2];
// initialize value storage vector of vectors
// iterate each pixel and find the closest displacement using least squares
for(int_t y=0;y<height;++y){
for(int_t x=0;x<width;++x){
query_pt[0] = x;
query_pt[1] = y;
kd_tree->radiusSearch(&query_pt[0],neigh_rad_sq,ret_matches,params);
const int_t num_neigh = ret_matches.size();
if(num_neigh<=3) continue;
// set up the X_t matrices
Teuchos::SerialDenseMatrix<int_t,double> X_t(N,num_neigh, true);
Teuchos::SerialDenseMatrix<int_t,double> X_t_X(N,N,true);
for(int_t i=0;i<num_neigh;++i){
X_t(0,i) = 1.0;
X_t(1,i) = point_cloud_->pts[ret_matches[i].first].x - x;//coords_x->local_value(local_ids[ret_matches[i].first]) - x;
X_t(2,i) = point_cloud_->pts[ret_matches[i].first].y - y;//coords_y->local_value(local_ids[ret_matches[i].first]) - y;
}
// set up X^T*X
for(int_t k=0;k<N;++k){
for(int_t m=0;m<N;++m){
for(int_t j=0;j<num_neigh;++j){
X_t_X(k,m) += X_t(k,j)*X_t(m,j);
}
}
}
// Invert X^T*X
// TODO: remove for performance?
// compute the 1-norm of H:
std::vector<double> colTotals(X_t_X.numCols(),0.0);
for(int_t i=0;i<X_t_X.numCols();++i){
for(int_t j=0;j<X_t_X.numRows();++j){
colTotals[i]+=std::abs(X_t_X(j,i));
}
}
double anorm = 0.0;
for(int_t i=0;i<X_t_X.numCols();++i){
if(colTotals[i] > anorm) anorm = colTotals[i];
}
lapack.GETRF(X_t_X.numRows(),X_t_X.numCols(),X_t_X.values(),X_t_X.numRows(),IPIV,&INFO);
double rcond=0.0; // reciporical condition number
lapack.GECON('1',X_t_X.numRows(),X_t_X.values(),X_t_X.numRows(),anorm,&rcond,GWORK,IWORK,&INFO);
if(rcond < 1.0E-12) continue;
lapack.GETRI(X_t_X.numRows(),X_t_X.values(),X_t_X.numRows(),IPIV,WORK,LWORK,&INFO);

Teuchos::ArrayRCP<double> u(num_neigh,0.0);
Teuchos::ArrayRCP<double> v(num_neigh,0.0);
for(int_t j=0;j<num_neigh;++j){
u[j] = -1.0*disp_x->local_value(local_ids[ret_matches[j].first]);
v[j] = -1.0*disp_y->local_value(local_ids[ret_matches[j].first]);
}
// compute X^T*u
Teuchos::ArrayRCP<double> X_t_u(N,0.0);
Teuchos::ArrayRCP<double> X_t_v(N,0.0);
for(int_t k=0;k<N;++k)
for(int_t j=0;j<num_neigh;++j){
X_t_u[k] += X_t(k,j)*u[j];
X_t_v[k] += X_t(k,j)*v[j];
}

// compute the coeffs
Teuchos::ArrayRCP<double> coeffs_u(N,0.0);
Teuchos::ArrayRCP<double> coeffs_v(N,0.0);
for(int_t k=0;k<N;++k)
for(int_t j=0;j<N;++j){
coeffs_u[k] += X_t_X(k,j)*X_t_u[j];
coeffs_v[k] += X_t_X(k,j)*X_t_v[j];
}

const scalar_t x_loc = x + coeffs_u[0];
const scalar_t y_loc = y + coeffs_v[0];
if(x_loc>=0&&x_loc<width&&y_loc>=0&&y_loc<height){
ref.at<float>(y,x) = (*ref_img_)(x,y);
def.at<float>(y,x) = (*def_img)(x,y);
map.at<float>(y,x) = ref_img_->interpolate_keys_fourth(x_loc,y_loc);
}
} // end y loop
} // end x loop

// TODO write the output json file
delete [] WORK;
delete [] GWORK;
delete [] IWORK;
delete [] IPIV;

ref.convertTo(ref,CV_8UC1);
def.convertTo(def,CV_8UC1);
map.convertTo(map,CV_8UC1);
cv::equalizeHist(ref,ref);
cv::equalizeHist(def,def);
cv::equalizeHist(map,map);
std::stringstream filenameR;
filenameR << "ref_" << current_frame_id_ << ".png";
cv::imwrite(filenameR.str(),ref);
std::stringstream filenameD;
filenameD << "def_" << current_frame_id_ << ".png";
cv::imwrite(filenameD.str(),def);
std::stringstream filenameM;
filenameM << "map_" << current_frame_id_ << ".png";
cv::imwrite(filenameM.str(),map);

for(int_t y=0;y<height;++y){
for(int_t x=0;x<width;++x){
if(def.at<uchar>(y,x)<map.at<uchar>(y,x)){
def.at<uchar>(y,x) = map.at<uchar>(y,x) - def.at<uchar>(y,x);
}else{
def.at<uchar>(y,x) = 0.0f;
}
}
}
// cv::absdiff(def,map,def);
std::stringstream filenameDiff;
filenameDiff << "diff_" << current_frame_id_ << ".png";
cv::imwrite(filenameDiff.str(),def);

// set a threshold on how far away the nearest subset can be
// do a diff using the displacement value
// threshold the diff
// output a json file with a heatmap?


DEBUG_MSG("Crack_Locator_Post_Processor execute() end");
}

Plotly_Contour_Post_Processor::Plotly_Contour_Post_Processor(const Teuchos::RCP<Teuchos::ParameterList> & params) :
Post_Processor(post_process_plotly_contour){
// no new fields added since the post processor writes output files instead
Expand All @@ -244,7 +459,7 @@ Plotly_Contour_Post_Processor::set_params(const Teuchos::RCP<Teuchos::ParameterL
}

void
Plotly_Contour_Post_Processor::execute(){
Plotly_Contour_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("Plotly_Contour_Post_Processor execute() begin");

// ensure only in serial for now TODO enable parallel post processor for this
Expand Down Expand Up @@ -493,7 +708,7 @@ Plotly_Contour_Post_Processor::execute(){
} // end gy loop
} // end gx loop

// TODO write the output json file
// write the output json file
delete [] WORK;
delete [] GWORK;
delete [] IWORK;
Expand Down Expand Up @@ -658,7 +873,7 @@ VSG_Strain_Post_Processor::pre_execution_tasks(){
}

void
VSG_Strain_Post_Processor::execute(){
VSG_Strain_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("VSG_Strain_Post_Processor execute() begin");
if(!neighborhood_initialized_) pre_execution_tasks();

Expand Down Expand Up @@ -934,7 +1149,7 @@ NLVC_Strain_Post_Processor::compute_kernel(const scalar_t & dx,


void
NLVC_Strain_Post_Processor::execute(){
NLVC_Strain_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("NLVC_Strain_Post_Processor execute() begin");
if(!neighborhood_initialized_) pre_execution_tasks();

Expand Down Expand Up @@ -1074,7 +1289,7 @@ Altitude_Post_Processor::Altitude_Post_Processor(const Teuchos::RCP<Teuchos::Par
}

void
Altitude_Post_Processor::execute(){
Altitude_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("Altitude_Post_Processor::execute(): begin");

// Teuchos::RCP<DICe::MultiField> ground_level_rcp = mesh_->get_field(DICe::field_enums::GROUND_LEVEL_FS);
Expand Down Expand Up @@ -1234,7 +1449,7 @@ Uncertainty_Post_Processor::Uncertainty_Post_Processor(const Teuchos::RCP<Teucho
}

void
Uncertainty_Post_Processor::execute(){
Uncertainty_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("Uncertainty_Post_Processor::execute(): begin");

Teuchos::RCP<DICe::MultiField> sigma_rcp = mesh_->get_field(DICe::field_enums::SIGMA_FS);
Expand Down Expand Up @@ -1586,7 +1801,7 @@ Live_Plot_Post_Processor::pre_execution_tasks(){
}

void
Live_Plot_Post_Processor::execute(){
Live_Plot_Post_Processor::execute(Teuchos::RCP<Image> ref_img, Teuchos::RCP<Image> def_img){
DEBUG_MSG("Live_Plot_Post_Processor execute() begin");
if(!neighborhood_initialized_) pre_execution_tasks();

Expand Down
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