As an OpenCASCADE newbie, I am reading the OpenCASCADE tutorial:
https://www.opencascade.com/doc/occt-7.4.0/overview/html/occt__tutorial.html
There are following two curious calls:
BRepLib::BuildCurves3d(threadingWire1);
BRepLib::BuildCurves3d(threadingWire2);
The tutorial explains the need for these two calls in this way:
Remember that these wires were built out of a surface and 2D curves. One important data item is missing as far as these wires are concerned: there is no information on the 3D curves. Fortunately, you do not need to compute this yourself, which can be a difficult task since the mathematics can be quite complex. When a shape contains all the necessary information except 3D curves, Open CASCADE Technology provides a tool to build them automatically. In the BRepLib tool package, you can use the BuildCurves3d method to compute 3D curves for all the edges of a shape.
which I did not find entirely clear.
Imagine that I have constructed some TopoDS_Shape object.
How can I, in general, figure out whether BRepLib::BuildCurves3d call is necessary or not?
With this code you can get the 3D curve of an edge (take from BRepExtrema_DistanceSS.cxx):
Standard_Real aFirst, aLast;
Handle(Geom_Curve) pCurv = BRep_Tool::Curve(E, aFirst, aLast);
If you have not created the 3D curves, pCurv will be a null handle. Using it will result in segmentation faults.
I have been excited about where the 3D curves are actually used. Therefore I have tried several algorithms. These are the algorithms I have tried where the 3D curves are not used:
Visualizing
Export to BREP
Export to STEP
Length Measurement
Checking Whether a Wire Is Closed or Ordered
The only algorithm I have found where the 3D curves are used are extrema/distance computations with BRepExtrema_DistShapeShape. You will not be able to use this class if you have not created the 3D curves.
Related
i have fairly large files with 3D scan points (200.000 ish) and try to make a TopoDS_Shape with BRepOffsetAPI_Sewing
gp_Pnt p1(0,0,100);
...
TopoDS_Edge e1 = BRepBuilderAPI_MakeEdge( p4, p1);
...
TopoDS_Wire w1 = BRepBuilderAPI_MakeWire(e1, e2, e3, e4);
...
TopoDS_Face f1 = BRepBuilderAPI_MakeFace(w1);
...
BRepOffsetAPI_Sewing sew(0.1);
sew.Add(f1);sew.Perform();TopoDS_Shape sewedShape = sew.SewedShape();
of corse with all the points in loops etc. above code is just a sample how I try to create things.
with 200.000 points it takes 20-30 second to produce the face.
my next approach was to save the produced shape after generated and load it later as a workaround.
BRepTools::Write(sewedShape, sFile);
but even that is slow.
I did similar things in Java3D and it was way faster. So I make something wrong.
only showing the points with
Handle_Graphic3d_ArrayOfPoints points3d = new Graphic3d_ArrayOfPoints(totPoints, true, false);
gp_Pnt pnt(x, y, z);
points3d->AddVertex(pnt, aColor); // adding 200.000 points
Handle(AIS_PointCloud) m_points = new AIS_PointCloud();
m_points->SetPoints(points3d);
m_occView->getContext()->Display(m_points, true);
is almost instant (less then a second)
my goal is to build 2 of those faces and find the intersection with OCBRepAlgoAPI_Section
Thanks for help in advance!
As far as I understand, your current approach is:
Create a TopoDS_Face per quad in Point Cloud.
To avoid unnecessary overhead on sewing operation, you would need reconsidering your workflow and create shared shapes from the scratch. E.g., instead of creating TopoDS_Vertex for the same point in Point Cloud multiple times, you should create a single one and reuse it in construction of connected edges / quads; the same applies to TopoDS_Edge construction. What sewing operation does for you is finding and repairing shared information between geometrically connected faces - which is a plenty of work that could be entirely avoided.
But as you have been already pointed out (by trying to dump produced shape into a file), mapping tessellation to B-Rep is counter-efficient approach in general. Just take a look at all these TopoDS_Vertex, TopoDS_Edge, TopoDS_Wire, TopoDS_Face to figure out how much more data structures are needed in B-Rep for mapping a very single triangle or quad. This structure is heavy not only from memory utilization point of view, but also for algorithms you might want to do with it like Boolean operations.
Possible alternatives:
Create a Poly_Triangulation from your point cloud and a single TopoDS_Face from it. You would be able to efficiently visualize it in 3D Viewer and perform some operations like computing surface area. Unfortunately, such geometry definition is not yet supported by all OCCT algorithms, so that you wouldn't be able performing Boolean operations.
Create an approximated B-Spline surface from your Point Clouds. This could be done with help of GeomPlate or SSP (Surface from Scattered Points) algorithms. Approximated surface would be a better fit to B-Rep geometry definition, but might loose some details of original surface and might be tricky to apply (you might need splitting a complex surface into several pieces).
Use OMF product (Mesh Framework) to perform Boolean operations on meshes. In case if Boolean operation on meshes is all you need, OMF could be helpful.
I am using GL_LINE_LOOP to draw a circle in C and openGL! Is it possible for me to fill the circle with colors?
If needed, this is the code I'm using:
const int circle_points=100;
const float cx=50+i, cy=50+x, r=50;
const float pi = 3.14159f;
int i = 50;
glColor3f(1, 1, 1);
glBegin(GL_LINE_LOOP);
for(i=0;i<circle_points;i++)
{
const float theta=(2*pi*i)/circle_points;
glVertex2f(cx+r*cos(theta),cy+r*sin(theta));
}
glEnd();
Lookup polygon triangulation!
I hope something here is somehow useful to someone, even though this question was asked in February. There are many answers, even though a lot of people would give none. I could witter forever, but I'll try to finish before then.
Some would even say, "You never would," or, "That's not appropriate for OpenGL," I'd like to say more than them about why. Converting polygons into the triangles that OpenGL likes so much is outside of OpenGL's job-spec, and is probably better done on the processor side anyway. Calculate that stage in advance, as few times as possible, rather than repeatedly sending such a chunky problem on every draw call.
Perhaps the original questioner drifted away from OpenGL since February, or perhaps they've become an expert. Perhaps I'll re-inspire them to look at it again, to hack away at some original 'imposters'. Or maybe they'll say it's not the tool for them after all, but that would be disappointing. Whatever graphics code you're writing, you know that OpenGL can speed it up!
Triangles for convex polygons are easy
Do you just want a circle? Make a triangle fan with the shared point at the circle's origin. GL_POLYGON was, for better or worse, deprecated then killed off entirely; it will not work with current or future implementations of OpenGL.
Triangles for concave polygons are hard
You'll want more general polygons later? Well, there are some tricks you could play with, for all manner of convex polygons, but concave ones will soon get difficult. It would be easy to start five different solutions without finishing a single one. Then it would be difficult, on finishing one, to make it quick, and nearly impossible to be sure that it's the quickest.
To achieve it in a future-proofed way you really want to stick with triangles -- so "polygon triangulation" is the subject you want to search for. OpenGL will always be great for drawing triangles. Triangle strips are popular because they reuse many vertices, and a whole mesh can be covered with only triangle strips, (perhaps including the odd lone triangle or pair of triangles). Drawing with only one primitive usually means the entire mesh can be rendered with a single draw call, which could improve performance. (Number of draw calls is one performance consideration, but not always the most important.)
Polygon triangulation gets more complex when you allow convex polygons or polygons with holes. (Finding algorithms for triangulating a general polygon, robustly yet quickly, is actually an area of ongoing research. Nonetheless, you can find some pretty good solutions out there that are probably fit for purpose.)
But is this what you want?
Is a filled polygon crucial to your final goals in OpenGL? Or did you simply choose what felt like it would be a simple early lesson?
Frustratingly, although drawing a filled polygon seems like a simple thing to do -- and indeed is one of the simplest things to do in many languages -- the solution in OpenGL is likely to be quite complicated. Of course, it can be done if we're clever enough -- but that could be a lot of effort, without being the best route to take towards your later goals.
Even in languages that implement filled polygons in a way that is simple to program with, you don't always know how much strain it puts on the CPU or GPU. If you send a sequence of vertices, to be linked and filled, once every animation frame, will it be slow? If a polygon doesn't change shape, perhaps you should do the difficult part of the calculation just once? You will be doing just that, if you triangulate a polygon once using the CPU, then repeatedly send those triangles to OpenGL for rendering.
OpenGL is very, very good at doing certain things, very quickly, taking advantage of hardware acceleration. It is worth appreciating what it is and is not optimal for, to decide your best route towards your final goals with OpenGL.
If you're looking for a simple early lesson, rotating brightly coloured tetrahedrons is ideal, and happens early in most tutorials.
If on the other hand, you're planning a project that you currently envision using filled polygons a great deal -- say, a stylized cartoon rendering engine for instance -- I still advise going to the tutorials, and even more so! Find a good one; stick with it to the end; you can then think better about OpenGL functions that are and aren't available to you. What can you take advantage of? What do you need or want to redo in software? And is it worth writing your own code for apparently simple things -- like drawing filled polygons -- that are 'missing from' (or at least inappropriate to) OpenGL?
Is there a higher level graphics library, free to use -- perhaps relying on OpenGL for rasterisation -- that can already do want you want? If so, how much freedom does it give you, to mess with the nuts and bolts of OpenGL itself?
OpenGL is very good at drawing points, lines, and triangles, and hardware accelerating certain common operations such as clipping, face culling, perspective divides, perspective texture accesses (very useful for lighting) and so on. It offers you a chance to write special programs called shaders, which operate at various stages of the rendering pipeline, maximising your chance to insert your own unique cleverness while still taking advantage of hardware acceleration.
A good tutorial is one that explains the rendering pipeline and puts you in a much better position to assess what the tool of OpenGL is best used for.
Here is one such tutorial that I found recently: Learning Modern 3D Graphics Programming
by Jason L. McKesson. It doesn't appear to be complete, but if you get far enough for that to annoy you, you'll be well placed to search for the rest.
Using imposters to fill polygons
Everything in computer graphics is an imposter, but the term often has a specialised meaning. Imposters display very different geometry from what they actually have -- only more so than usual! Of course, a 3D world is very different from the pixels representing it, but with imposters, the deception goes deeper than usual.
For instance, a rectangle that OpenGL actually constructs out of two triangles can appear to be a sphere if, in its fragment shader, you write a customised depth value to the depth coordinate, calculate your own normals for lighting and so on, and discard those fragments of the square that would fall outside the outline of the sphere. (Calculating the depth on those fragments would involve a square root of a negative number, which can be used to discard the fragment.) Imposters like that are sometimes called flat cards or billboards.
(The tutorial above includes a chapter on imposters, and examples doing just what I've described here. In fact, the rectangle itself is constructed only part way through the pipeline, from a single point. I warn that the scaling of their rectangle, to account for the way that perspective distorts a sphere into an ellipse in a wide FOV, is a non-robust fudge . The correct and robust answer is tricky to work out, using mathematics that would be slightly beyond the scope of the book. I'd say it is beyond the author's algebra skills to work it out but I could be wrong; he'd certainly understand a worked example. However, when you have the correct solution, it is computationally inexpensive; it involves only linear operations plus two square roots, to find the four limits of a horizontally- or vertically-translated sphere. To generalise that technique for other displacements requires one more square root, for a vector normalisation to find the correct rotation, and one application of that rotation matrix when you render the rectangle.)
So just to suggest an original solution that others aren't likely to provide, you could use an inequality (like x * x + y * y <= 1 for a circle or x * x - y * y <= 1 for a hyperbola) or a system of inequalities (like three straight line forms to bound a triangle) to decide how to discard a fragment. Note that if inequalities have more than linear order, they can encode perfect curves, and render them just as smoothly as your pixelated screen will allow -- with no limitation on the 'geometric detail' of the curve. You can also combine straight and curved edges in a single polygon, in this way.
For instance, a fragment shader (which would be written in GLSL) for a semi-circle might have something like this:
if (y < 0) discard;
float rSq = x * x + y * y;
if (1 < rSq) discard;
// We're inside the semi-circle; put further shader computations here
However, the polygons that are easy to draw, in this way, are very different from the ones that you're used to being easy. Converting a sequence of connected nodes into inequalities means yet more code to write, and deciding on the Boolean logic, to deal with combining those inequalities, could then get quite complex -- especially for concave polygons. Performing inequalities in a sensible order, so that some can be culled based on the results of others, is another ill-posed headache of a problem, if it needs to be general, even though it is easy to hard-code an optimal solution for a single case like a square.
I suggest using imposters mainly for its contrast with the triangulation method. Something like either one could be a route to pursue, depending on what you're hoping to achieve in the end, and the nature of your polygons.
Have fun...
P.S. have a related topic... Polygon triangulation into triangle strips for OpenGL ES
As long as the link lasts, it's a more detailed explanation of 'polygon triangulation' than mine. Those are the two words to search for if the link ever dies.
A line loop is just an outline.
To fill the middle as well, you want to use GL_POLYGON.
I am looking for some advice for a good way to detect either square or circular objects in an image. I currently have a canny edge algorithm running on the original greyscale and I can produce this output:
http://imgur.com/FAwowr1
Now I can see that there is a cubesat in this picture, but what is a good computationally efficient way that the program can see that aswell? I have looked at houghs transform but that seems to be very computation heavy. I have also looked at Harris corner detect, but I feel I would get to many false positives, for I am essentially looking to isolate pictures that contain said cube satellite.
Anyone have any thoughts on some good algorithms to pursue? I am very limited on space so I cannot use any large external libraries like opencv. (This is all in C btw)
Many Thanks!
I would into what is called mathematical morphology
Basically you operate on binary images, so you must find a clever way to threshold them first , the you do operations such as erosion and dilation with some well selected structuring element to extract areas of interest in your image.
I'm interested in different algorithms people use to visualise millions of particles in a box. I know you can use Cloud-In-Cell, adaptive mesh, Kernel smoothing, nearest grid point methods etc to reduce the load in memory but there is very little documentation on how to do these things online.
i.e. I have array with:
x,y,z
1,2,3
4,5,6
6,7,8
xi,yi,zi
for i = 100 million for example. I don't want a package like Mayavi/Paraview to do it, I want to code this myself then load the decomposed matrix into Mayavi (rather than on-the-fly rendering) My poor 8Gb Macbook explodes if I try and use the particle positions. Any tutorials would be appreciated.
Analysing and creating visualisations for complex multi-dimensional data is complex. The best visualisation almost always depends on what the data is, and what relationships exists within the data. Of course, you are probably wanting to create visualisation of the data to show and explore relationships. Ultimately, this comes down to trying different posibilities.
My advice is to think about the data, and try to find sensible ways to slice up the dimensions. 3D plots, like surface plots or voxel renderings may be what you want. Personally, I prefer trying to find 2D representations, because they are easier to understand and to communicate to other people. Contour plots are great because they show 3D information in a 2D form. You can show a sequence of contour plots side by side, or in a timelapse to add a fourth dimension. There are also creative ways to use colour to add dimensions, while keeping the visualisation comprehensible -- which is the most important thing.
I see you want to write the code yourself. I understand that. Doing so will take a non-trivial effort, and afterwards, you might not have an effective visualisation. My advice is this: use a tool to help you prototype visualisations first! I've used gnuplot with some success, although I'm sure there are other options.
Once you have a good handle on the data, and how to communicate what it means, then you will be well positioned to code a good visualisation.
UPDATE
I'll offer a suggestion for the data you have described. It sounds as though you want/need a point density map. These are popular in geographical information systems, but have other uses. I haven't used one before, but the basic idea is to use a function to enstimate the density in a 3D space. The density becomes the fourth dimension. Something relatively simple, like the equation below, may be good enough.
The point density map might be easier to slice, summarise and render than the raw particle data.
The data I have analysed has been of a different nature, so I have not used this particular method before. Hopefully it proves helpful.
PS. I've just seen your comment below, and I'm not sure that this information will help you with that. However, I am posting my update anyway, just in case it is useful information.
I have to make an application that recognizes inside an black and white image a piece of tetris given by the user. I read the image to analyze into an array.
How can I do something like this using C?
Assuming that you already loaded the images into arrays, what about using regular expressions?
You don't need exact shape matching but approximately, so why not give it a try!
Edit: I downloaded your doc file. You must identify a random pattern among random figures on a 2D array so regex isn't suitable for this problem, lets say that's the bad news. The good news is that your homework is not exactly image processing, and it's much easier.
It's your homework so I won't create the code for you but I can give you directions.
You need a routine that can create a new piece from the original pattern/piece rotated. (note: with piece I mean the 4x4 square - all the cells of it)
You need a routine that checks if a piece matches an area from the 2D image at position x,y - the matching area would have corners (x-2, y-2, x+1, y+1).
You search by checking every image position (x,y) for a match.
Since you must use parallelism you can create 4 threads and assign to each thread a different rotation to search.
You might not want to implement that from scratch (unless required, of course) ... I'd recommend looking for a suitable library. I've heard that OpenCV is good, but never done any work with machine vision myself so I haven't tested it.
Search for connected components (i.e. using depth-first search; you might want to avoid recursion if efficiency is an issue; use your own stack instead). The largest connected component should be your tetris piece. You can then further analyze it (using the shape, the size or some kind of border description)
Looking at the shapes given for tetris pieces in Wikipedia, called "I,J,L,O,S,T,Z", it seems that the ratios of the sides of the bounding box (easy to find given a binary image and C) reveal whether you have I (4:1) or O (1:1); the other shapes are 2:3.
To detect which of the remaining shapes you have (J,L,S,T, or Z), it looks like you could collect the length and position of the shape's edges that fall on the bounding box's edges. Thus, T would show 3 and 1 along the 3-sides, and 1 and 1 along the 2 sides. Keeping track of the positions helps distinguish J from L, S from Z.