how to Recreate boundary from array of junctions in imagej - fiji? - imagej

I am detecting and storing the boundary of a sandpile to an array and then save it as a text file for later use. the way i stored the boundary as text file is by using the wand tool, then getting the properties of the selection which gives me a table. Then converting table to array and finally storing it as text file.
after doing so i noticed that the above mentioned table only has the (X,Y) coordinates of the "junctions" on the boundary and not every pixel of the boundary.
Now when i say later use, i want to smooth out the boundary with various methods and redraw it but i am stuck at how to go from junctions to complete boundary. Below is my attempt to do it but i am seeing heavy ram usage just after the output is printed.
Thanks for any help and your time.
X=newArray(1,5,5,10);
Y=newArray(3,3,8,8);
c=newArray("c1","c2");
//answer should be g=(1,2,3,4,5,5,5,5,5,5,6,7,8,9,10, --x part
// 3,3,3,3,3,4,5,6,7,8,8,8,8,8,8) --y part
//f=slide(a,2,c);Array.print(f);
g=cmpltarray(X,Y);Array.print(g);
function cmpltarray(Tx,Ty){
for (i = 0; i < Tx.length-1; i++) {
if(Tx[i]==Tx[i+1] && Ty[i]!=Ty[i+1])
{
l=abs(Ty[i]-Ty[i+1])-1;tempy=newArray(l);tempx=newArray(l);
for (j = 0; j < l; j++) {
tempy[j]=Ty[i]+j+1;tempx[j]=Tx[i];
}
Tx=slide(Tx,(i+1),tempx);Ty=slide(Ty,(i+1),tempy);i=i+l;
}
if(Ty[i]==Ty[i+1] && Tx[i]!=Tx[i+1])
{
l=abs(Tx[i]-Tx[i+1])-1;tempy=newArray(l);tempx=newArray(l);
for (j = 0; j < l; j++) {
tempx[j]=Tx[i]+j+1;tempy[j]=Ty[i];
}
Tx=slide(Tx,(i+1),tempx);Ty=slide(Ty,(i+1),tempy);i=i+l;
}
}
return Array.concat(Tx,Ty);
}
function slide(array,n,data){
array=Array.concat(Array.slice(array,0,n),data,Array.slice(array,n,array.length));
return array;
}

Related

Autodiff for Jacobian derivative with respect to individual joint angles

I am trying to compute $\partial{J}{q_i}$ in drake C++ for manipulator and as per my search, the best approach seems to be using autodiff function. I was not able to fully understand autodiff approach from the resources that I found, so I apologize if my approach is not clear enough. I have used my understanding from some already asked questions mentioned on the forum regarding auto diff as well as https://drake.mit.edu/doxygen_cxx/classdrake_1_1multibody_1_1_multibody_plant.html as reference.
As I want to calculate $\partial{J}{q_i}$, the return type will be a tensor i.e. 3 * 7 * 7(or 6 * 7 * 7 depending on the spatial jacobian). I can think of using std::vectorEigen::MatrixXd to allocate the output or alternatively just doing one $q_i$ at a time and computing the respective jacobian for the auto diff. In either case, I was struggling to pass it in the initializing the jacobian function.
I did the following to initialize autodiff
std::unique_ptr<multibody::MultibodyPlant<AutoDiffXd>> mplant_autodiff = systems::System<double>::ToAutoDiffXd(mplant);
std::unique_ptr<systems::Context<AutoDiffXd>> mContext_autodiff = mplant_autodiff->CreateDefaultContext();
mContext_autodiff->SetTimeStateAndParametersFrom(*mContext);
const multibody::Frame<AutoDiffXd>* mFrame_EE_autodiff = &mplant_autodiff->GetBodyByName(mEE_link).body_frame();
const multibody::Frame<AutoDiffXd>* mWorld_Frame_autodiff = &(mplant_autodiff->world_frame());
//Initialize the q as autodiff vector
drake::AutoDiffVecXd q_autodiff = drake::math::InitializeAutoDiff(mq_robot);
MatrixX<AutoDiffXd> mJacobian_autodiff; // Linear Jacobian matrix.
mplant_autodiff->SetPositions(context_autodiff.get(), q_autodiff);
mplant_autodiff->CalcJacobianTranslationalVelocity(*mContext_autodiff,
multibody::JacobianWrtVariable::kQDot,
*mFrame_EE_autodiff,
Eigen::Vector3d::Zero(),
*mWorld_Frame_autodiff,
*mWorld_Frame_autodiff,
&mJacobian_autodiff
);
However, as far as I understand, InitializeAutoDiff initializes to the identity matrix, whereas I want to $\partial{J}{q_i}$, so is there is a better way to do it. In addition, I get error messages when I try to call the jacobian matrix. Is there a way to address this problem both for $\partial{J}{q_i}$ for each q_i and changing q_i in a for loop or directly getting the result in a tensor. My apologies if I am doing something total tangent to the correct approach. I thank you in anticipation.
However, as far as I understand, InitializeAutoDiff initializes to the identity matrix, whereas I want to $\partial{J}{q_i}$, so is there is a better way to do it
That is correct. When you call InitializeAutoDiff and compute mJacobian_autodiff, you get a matrix of AutoDiffXd. Each AutoDiffXd has a value() function that stores the double value, and a derivatives() storing the gradient as an Eigen::VectorXd. We have
mJacobian(i, j).value() = J(i, j)
mJacobian_autodiff(i, j).derivatives()(k) = ∂J(i, j)/∂q(k)
So if you want to create a std::vecot<Eigen::MatrixXd> such that the k'th entry of this vector stores the matrix ∂J/∂q(k), then here is a code
std::vector<Eigen::MatrixXd> dJdq(q_autodiff.rows());
for (int i = 0; i < q_autodiff.rows(); ++i) {
dJdq[i].resize(mJacobian_autodiff.rows(), mJacobian_autodiff.cols());
}
for (int i = 0; i < q_autodiff.rows(); ++i) {
// dJidq stores the gradient of the ∂J.col(i)/∂q, namely dJidq(j, k) = ∂J(j, i)/∂q(k)
auto dJidq = ExtractGradient(mJacobian_autodiff.col(i));
for (int j = 0; j < static_cast<int>(dJdq.size()); ++j) {
dJdq[j].col(i) = dJidq.col(j);
}
}
Compute ∂J/∂q(i) for a single i
If you do not want to compute ∂J/∂q(i) for all i, but only for one specific i, you can change the initialization of q_autodiff from InitializeAutoDiff to this
AutoDiffVecXd q_autodiff(q.rows());
for (int k = 0; k < q_autodiff.rows(); ++k) {
q_autodiff(k).value() = q(k)
q_autodiff(k).derivatives() = Vector1d::Zero();
if (k == i) {
q_autodiff(k).derivatives()(0) = 1;
}
}
namely q_autodiff stores the gradient ∂q/∂q(i), which is 0 for all k != i and 1 when k == i. And then you can compute mJacobian_autodiff using your current code. Now mJacobian_autodiff(m, n).derivatives() store the gradient of ∂J(m, m)/∂q(i) for that specific i. You can extract this gradient as
Eigen::Matrix dJdqi(mJacobian_autodiff.rows(), mJacobian_autodiff.cols());
for (int m = 0; m < dJdqi.rows(); ++m) {
for (int n = 0; n < dJdqi.cols(); ++n) {
dJdqi(m, n) = mJacobian_autodiff(m, n).derivatives()(0);
}
}

How to export a profile of a calibrated image with an imagej macro

i wrote a little macro, that locates spheres on a spatially calibrated (Dicom-) image. Once found, it draws lots! of lines and saves the brightness profiles along these lines to a csv file. So far, this works nice and fast. This is the piece of code, that extracts the profiles and saves them:
for (i=0; i < 360; i++){
run("Clear Results");
angle = i*2*PI/360;
makeLine(xm,ym,(xm+(length*sin(angle))), (ym-(length*cos(angle))));
profile = getProfile();
for (j=0; j<profile.length; j++) {
setResult("Value", j, profile[j]);
}
updateResults;
saveAs("Results",path + "\\angle_"+i+".csv");
}
My problem is, that the actual scale is not exported. I get something like this:
1,3070.070
2,3069.000
3,3069.986
4,3053.646
but i want
0.4395 3070
0.8789 3070
1.3184 3070
1.7578 069.8994
And so on. I tried to modify this line a little:
setResult("Value", j*xscale, profile[j]);
but this does not work. I also tried to plot the profiles and then read and save them.
for (i=0; i < 360; i++){
run("Clear Results");
angle = i*2*PI/360;
makeLine(xm,ym,(xm+(length*sin(angle))), (ym-(length*cos(angle))));
run ("Plot Profile");
Plot.getValues(xplot,yplot);
for (j=0; j< xplot.length; j++){
print (xplot[j],yplot [j]);
}
selectWindow("Log");
saveAs("Text",path + "\\angle_"+i+".csv");
print("\\Clear");
selectWindow("04");
}
(Sorry, the window switching is still experimental and the profiles are not closing..)
This works in principle but it is of course PAINFULLY slow. So my question is.... How do i extract not online line numbers but the correct scale in a profile?
Thank you all very much!
The first column is just a non editable line number. The code must be changed like this:
for (i=0; i < 360; i++){
run("Clear Results");
angle = i*2*PI/360;
makeLine(xm,ym,(xm+(length*sin(angle))), (ym-(length*cos(angle))));
profile = getProfile();
for (j=0; j<profile.length; j++) {
setResult("xvalues", j, j*dx);
setResult("yvalues", j, profile[j]);
}
updateResults;
saveAs("Results",path + "\\angle_"+i+".csv");
}

ID3D11DeviceContext::DrawIndexed() Failed

my program is Directx Program that draws a container cube within it smaller cubes....these smaller cubes fall by time i hope you understand what i mean...
The program isn't complete yet ...it should draws the container only ....but it draws nothing ...only the background color is visible... i only included what i think is needed ...
this is the routines that initialize the program
bool Game::init(HINSTANCE hinst,HWND _hw){
Directx11 ::init(hinst , _hw);
return LoadContent();}
Directx11::init()
bool Directx11::init(HINSTANCE hinst,HWND hw){
_hinst=hinst;_hwnd=hw;
RECT rc;
GetClientRect(_hwnd,&rc);
height= rc.bottom - rc.top;
width = rc.right - rc.left;
UINT flags=0;
#ifdef _DEBUG
flags |=D3D11_CREATE_DEVICE_DEBUG;
#endif
HR(D3D11CreateDevice(0,_driverType,0,flags,0,0,D3D11_SDK_VERSION,&d3dDevice,&_featureLevel,&d3dDeviceContext));
if (d3dDevice == 0 || d3dDeviceContext == 0)
return 0;
DXGI_SWAP_CHAIN_DESC sdesc;
ZeroMemory(&sdesc,sizeof(DXGI_SWAP_CHAIN_DESC));
sdesc.Windowed=true;
sdesc.BufferCount=1;
sdesc.BufferDesc.Format=DXGI_FORMAT_R8G8B8A8_UNORM;
sdesc.BufferDesc.Height=height;
sdesc.BufferDesc.Width=width;
sdesc.BufferDesc.Scaling=DXGI_MODE_SCALING_UNSPECIFIED;
sdesc.BufferDesc.ScanlineOrdering=DXGI_MODE_SCANLINE_ORDER_UNSPECIFIED;
sdesc.OutputWindow=_hwnd;
sdesc.BufferDesc.RefreshRate.Denominator=1;
sdesc.BufferDesc.RefreshRate.Numerator=60;
sdesc.Flags=0;
sdesc.BufferUsage = DXGI_USAGE_RENDER_TARGET_OUTPUT;
if (m4xMsaaEnable)
{
sdesc.SampleDesc.Count=4;
sdesc.SampleDesc.Quality=m4xMsaaQuality-1;
}
else
{
sdesc.SampleDesc.Count=1;
sdesc.SampleDesc.Quality=0;
}
IDXGIDevice *Device=0;
HR(d3dDevice->QueryInterface(__uuidof(IDXGIDevice),reinterpret_cast <void**> (&Device)));
IDXGIAdapter*Ad=0;
HR(Device->GetParent(__uuidof(IDXGIAdapter),reinterpret_cast <void**> (&Ad)));
IDXGIFactory* fac=0;
HR(Ad->GetParent(__uuidof(IDXGIFactory),reinterpret_cast <void**> (&fac)));
fac->CreateSwapChain(d3dDevice,&sdesc,&swapchain);
ReleaseCOM(Device);
ReleaseCOM(Ad);
ReleaseCOM(fac);
ID3D11Texture2D *back = 0;
HR(swapchain->GetBuffer(0,__uuidof(ID3D11Texture2D),reinterpret_cast <void**> (&back)));
HR(d3dDevice->CreateRenderTargetView(back,0,&RenderTarget));
D3D11_TEXTURE2D_DESC Tdesc;
ZeroMemory(&Tdesc,sizeof(D3D11_TEXTURE2D_DESC));
Tdesc.BindFlags = D3D11_BIND_DEPTH_STENCIL;
Tdesc.ArraySize = 1;
Tdesc.Format= DXGI_FORMAT_D24_UNORM_S8_UINT;
Tdesc.Height= height;
Tdesc.Width = width;
Tdesc.Usage = D3D11_USAGE_DEFAULT;
Tdesc.MipLevels=1;
if (m4xMsaaEnable)
{
Tdesc.SampleDesc.Count=4;
Tdesc.SampleDesc.Quality=m4xMsaaQuality-1;
}
else
{
Tdesc.SampleDesc.Count=1;
Tdesc.SampleDesc.Quality=0;
}
HR(d3dDevice->CreateTexture2D(&Tdesc,0,&depthview));
HR(d3dDevice->CreateDepthStencilView(depthview,0,&depth));
d3dDeviceContext->OMSetRenderTargets(1,&RenderTarget,depth);
D3D11_VIEWPORT vp;
vp.TopLeftX=0.0f;
vp.TopLeftY=0.0f;
vp.Width = static_cast <float> (width);
vp.Height= static_cast <float> (height);
vp.MinDepth = 0.0f;
vp.MaxDepth = 1.0f;
d3dDeviceContext -> RSSetViewports(1,&vp);
return true;
SetBuild() Prepare the matrices inside the container for the smaller cubes ....i didnt program it to draw the smaller cubes yet
and this the function that draws the scene
void Game::Render(){
d3dDeviceContext->ClearRenderTargetView(RenderTarget,reinterpret_cast <const float*> (&Colors::LightSteelBlue));
d3dDeviceContext->ClearDepthStencilView(depth,D3D11_CLEAR_DEPTH | D3D11_CLEAR_STENCIL,1.0f,0);
d3dDeviceContext-> IASetInputLayout(_layout);
d3dDeviceContext-> IASetPrimitiveTopology(D3D10_PRIMITIVE_TOPOLOGY_TRIANGLELIST);
d3dDeviceContext->IASetIndexBuffer(indices,DXGI_FORMAT_R32_UINT,0);
UINT strides=sizeof(Vertex),off=0;
d3dDeviceContext->IASetVertexBuffers(0,1,&vertices,&strides,&off);
D3DX11_TECHNIQUE_DESC des;
Tech->GetDesc(&des);
Floor * Lookup; /*is a variable to Lookup inside the matrices structure (Floor Contains XMMATRX Piese[9])*/
std::vector<XMFLOAT4X4> filled; // saves the matrices of the smaller cubes
XMMATRIX V=XMLoadFloat4x4(&View),P = XMLoadFloat4x4(&Proj);
XMMATRIX vp = V * P;XMMATRIX wvp;
for (UINT i = 0; i < des.Passes; i++)
{
d3dDeviceContext->RSSetState(BuildRast);
wvp = XMLoadFloat4x4(&(B.Memory[0].Pieces[0])) * vp; // Loading The Matrix at translation(0,0,0)
HR(ShadeMat->SetMatrix(reinterpret_cast<float*> ( &wvp)));
HR(Tech->GetPassByIndex(i)->Apply(0,d3dDeviceContext));
d3dDeviceContext->DrawIndexed(build_ind_count,build_ind_index,build_vers_index);
d3dDeviceContext->RSSetState(PieseRast);
UINT r1=B.GetSize(),r2=filled.size();
for (UINT j = 0; j < r1; j++)
{
Lookup = &B.Memory[j];
for (UINT r = 0; r < Lookup->filledindeces.size(); r++)
{
filled.push_back(Lookup->Pieces[Lookup->filledindeces[r]]);
}
}
for (UINT j = 0; j < r2; j++)
{
ShadeMat->SetMatrix( reinterpret_cast<const float*> (&filled[i]));
Tech->GetPassByIndex(i)->Apply(0,d3dDeviceContext);
d3dDeviceContext->DrawIndexed(piese_ind_count,piese_ind_index,piese_vers_index);
}
}
HR(swapchain->Present(0,0));}
thanks in Advance
One bug in your program appears to be that you're using i, the index of the current pass, as an index into the filled vector, when you should apparently be using j.
Another apparent bug is that in the loop where you are supposed to be iterating over the elements of filled, you're not iterating over all of them. The value r2 is set to the size of filled before you append anything to it during that pass. During the first pass this means that nothing will be drawn by this loop. If your technique only has one pass then this means that the second DrawIndexed call in your code will never be executed.
It also appears you should be only adding matrices to filled once, regardless of the number of the passes the technique has. You should consider if your code is actually meant to work with techniques with multiple passes.

Getting vector which holding certain point

I've a vector of points from a grey section of an image and written like this:
std::vector<Point> vectorg;
for(i = 0; i <= hei - 1; i++) {
for(j = 0; j <= wid - 1; j++) {
if(mask(i,j) == 128) {
vectorg.push_back(Point(j,i));
}
}
}
Knowing what coordinates stored in certain cell is possible by:
cout << vectorg[0].x;
cout << vectorg[0].y;
The question is now the other way around, is it possible to know which cell holds certain coordinates?
Thanks a lot, I'm new here also with opencv programming, I'll be in your care.
Just do the following:
#include <algorithm>
// ...
Point p(searchedX, searchedY);
std::vector<Point>::iterator element = std::find(vectorg.begin(), vectorg.end(), p);
if (element != vectorg.end()) {
cout << (*element).x << endl;
cout << (*element).y << endl;
} else {
cout << "The point is not in the vector" << endl;
}
It may be overkill, but a way to do it (without doing a greedy exhaustive search) would be to build a FLANN index that will store the position of your points.
The feature matrix is made of the coordinates of your points.
Since OpenCV knows how to convert a vector to a matrix, you should be able to use your current vector as is.
Then, if you want only one point, just ask for the 1 nearest neighbour in the query (k parameter).
The bonus is, if you decide later that you need to have also the closest points in the neighborhood, just raise the value of k.
Sorry for the late response, and thanks for the answers, they inspired me indirectly.
I found an easy way to do it. This is by making another Mat which holds the numbers where the coordinates were saved.
std::vector<Point> vectorg;
cv::Mat_<int> Index =Mat_<int>::zeros(hei,wid);
for(i = 0; i <= hei - 1; i++) {
for(j = 0; j <= wid - 1; j++) {
if(mask(i,j) == 128) {
vectorg.push_back(Point(j,i));
Index(vector[count])=count;
count++;
}
}
}
This way I can know which cell holds certain coordinates by simply:
cout<<Index(36,362); //as example
Thanks a lot, I'll be in your care next time.

Checking if removing an edge in a graph will result in the graph splitting

I have a graph structure where I am removing edges one by one until some conditions are met. My brain has totally stopped and i can't find an efficient way to detect if removing an edge will result in my graph splitting in two or more graphs.
The bruteforce solution would be to do an bfs until one can reach all the nodes from a random node, but that will take too much time with large graphs...
Any ideas?
Edit: After a bit of search it seems what I am trying to do is very similar to the fleury's algorithm, where I need to find if an edge is a "bridge" or not.
Edges that make a graph disconnected when removed are called 'bridges'. You can find them in O(|V|+|E|) with a single depth-first search over the whole graph. A related algorithm finds all 'articulation points' (nodes that, if removed, makes the graph disconnected) follows. Any edge between two articulation-points is a bridge (you can test that in a second pass over all edges).
//
// g: graph; v: current vertex id;
// r_p: parents (r/w); r_a: ascents (r/w); r_ap: art. points, bool array (r/w)
// n_v: bfs order-of-visit
//
void dfs_art_i(graph *g, int v, int *r_p, int *r_v, int *r_a, int *r_ap, int *n_v) {
int i;
r_v[v] = *n_v;
r_a[v] = *n_v;
(*n_v) ++;
// printf("entering %d (nv = %d)\n", v, *n_v);
for (i=0; i<g->vertices[v].n_edges; i++) {
int w = g->vertices[v].edges[i].target;
// printf("\t evaluating %d->%d: ", v, w);
if (r_v[w] == -1) {
// printf("...\n");
// This is the first time we find this vertex
r_p[w] = v;
dfs_art_i(g, w, r_p, r_v, r_a, r_ap, n_v);
// printf("\n\t ... back in %d->%d", v, w);
if (r_a[w] >= r_v[v]) {
// printf(" - a[%d] %d >= v[%d] %d", w, r_a[w], v, r_v[v]);
// Articulation point found
r_ap[i] = 1;
}
if (r_a[w] < r_a[v]) {
// printf(" - a[%d] %d < a[%d] %d", w, r_a[w], v, r_a[v]);
r_a[v] = r_a[w];
}
// printf("\n");
}
else {
// printf("back");
// We have already found this vertex before
if (r_v[w] < r_a[v]) {
// printf(" - updating ascent to %d", r_v[w]);
r_a[v] = r_v[w];
}
// printf("\n");
}
}
}
int dfs_art(graph *g, int root, int *r_p, int *r_v, int *r_a, int *r_ap) {
int i, n_visited = 0, n_root_children = 0;
for (i=0; i<g->n_vertices; i++) {
r_p[i] = r_v[i] = r_a[i] = -1;
r_ap[i] = 0;
}
dfs_art_i(g, root, r_p, r_v, r_a, r_ap, &n_visitados);
// the root can only be an AP if it has more than 1 child
for (i=0; i<g->n_vertices; i++) {
if (r_p[i] == root) {
n_root_children ++;
}
}
r_ap[root] = n_root_children > 1 ? 1 : 0;
return 1;
}
If you remove the link between vertices A and B, can't you just check that you can still reach A from B after the edge removal? That's a little better than getting to all nodes from a random node.
How do you choose the edges to be removed?
Can you tell more about your problem domain?
Just how large Is your graph? maybe BFS is just fine!
After you wrote that you are trying to find out whether an edge is a bridge or not, I suggest
you remove edges in decreasing order of their betweenness measure.
Essentially, betweenness is a measure of an edges (or vertices) centrality in a graph.
Edges with higher value of betweenness have greater potential of being a bridge in a graph.
Look it up on the web, the algorithm is called 'Girvan-Newman algorithm'.

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