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ReverseEngineering: [skip ci] improve segmentation based on point clouds

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This commit is contained in:
wmayer
2020-03-03 00:10:48 +01:00
committed by Bernd Hahnebach
parent 625bfd4b9e
commit 4b77f9f3ac
3 changed files with 150 additions and 13 deletions
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75
src/Mod/ReverseEngineering/App/AppReverseEngineering.cpp
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@@ -725,27 +725,92 @@ Mesh.show(m)
}
#endif
#if defined(HAVE_PCL_SAMPLE_CONSENSUS)
/*
import ReverseEngineering as reen
import Points
import Part
p = App.ActiveDocument.Points.Points
data = p.Points
n = reen.normalEstimation(p, 10)
model = reen.sampleConsensus(SacModel="Plane", Points=p)
indices = model["Model"]
param = model["Parameters"]
plane = Part.Plane()
plane.Axis = param[0:3]
plane.Position = -plane.Axis * param[3]
np = Points.Points()
np.addPoints([data[i] for i in indices])
Points.show(np)
# sort in descending order
indices = list(indices)
indices.sort(reverse=True)
# remove points of segment
for i in indices:
del data[i]
del n[i]
p = Points.Points()
p.addPoints(data)
model = reen.sampleConsensus(SacModel="Cylinder", Points=p, Normals=n)
indices = model["Model"]
np = Points.Points()
np.addPoints([data[i] for i in indices])
Points.show(np)
*/
Py::Object sampleConsensus(const Py::Tuple& args, const Py::Dict& kwds)
{
PyObject *pts;
PyObject *vec = nullptr;
const char* sacModelType = nullptr;
static char* kwds_sample[] = {"Points", NULL};
if (!PyArg_ParseTupleAndKeywords(args.ptr(), kwds.ptr(), "O!", kwds_sample,
&(Points::PointsPy::Type), &pts))
static char* kwds_sample[] = {"SacModel", "Points", "Normals", NULL};
if (!PyArg_ParseTupleAndKeywords(args.ptr(), kwds.ptr(), "sO!|O", kwds_sample,
&sacModelType, &(Points::PointsPy::Type), &pts, &vec))
throw Py::Exception();
Points::PointKernel* points = static_cast<Points::PointsPy*>(pts)->getPointKernelPtr();
std::vector<Base::Vector3d> normals;
if (vec) {
Py::Sequence list(vec);
normals.reserve(list.size());
for (Py::Sequence::iterator it = list.begin(); it != list.end(); ++it) {
Base::Vector3d v = Py::Vector(*it).toVector();
normals.push_back(v);
}
}
SampleConsensus::SacModel sacModel = SampleConsensus::SACMODEL_PLANE;
if (sacModelType) {
if (strcmp(sacModelType, "Cylinder") == 0)
sacModel = SampleConsensus::SACMODEL_CYLINDER;
else if (strcmp(sacModelType, "Sphere") == 0)
sacModel = SampleConsensus::SACMODEL_SPHERE;
else if (strcmp(sacModelType, "Cone") == 0)
sacModel = SampleConsensus::SACMODEL_CONE;
}
std::vector<float> parameters;
SampleConsensus sample(*points);
double probability = sample.perform(parameters);
SampleConsensus sample(sacModel, *points, normals);
std::vector<int> model;
double probability = sample.perform(parameters, model);
Py::Dict dict;
Py::Tuple tuple(parameters.size());
for (std::size_t i = 0; i < parameters.size(); i++)
tuple.setItem(i, Py::Float(parameters[i]));
Py::Tuple data(model.size());
for (std::size_t i = 0; i < model.size(); i++)
data.setItem(i, Py::Long(model[i]));
dict.setItem(Py::String("Probability"), Py::Float(probability));
dict.setItem(Py::String("Parameters"), tuple);
dict.setItem(Py::String("Model"), data);
return dict;
}