Changed PcaModel c'tor to take an orthonormal basis

Adjusted all files that use it (hopefully).

This is a breaking change: If you're currently using the PcaModel constructor and giving it a PCA basis matrix, your code will (probably silently) break: The function now expects an orthonormal basis matrix, whereas before, it expected a rescaled basis matrix. However it makes more sense for the function to take an orthonormal basis matrix.

include/eos/morphablemodel/PcaModel.hpp

@@ -66,13 +66,13 @@ public:
 	 * be arranged.
 	 *
 	 * @param[in] mean The mean used to build the PCA model.
-	 * @param[in] pca_basis The PCA basis (eigenvectors), normalised (multiplied by the eigenvalues).
+	 * @param[in] orthonormal_pca_basis An orthonormal PCA basis (eigenvectors).
 	 * @param[in] eigenvalues The eigenvalues used to build the PCA model.
 	 * @param[in] triangle_list An index list of how to assemble the mesh.
 	 */
-	PcaModel(Eigen::VectorXf mean, Eigen::MatrixXf pca_basis, Eigen::VectorXf eigenvalues, std::vector<std::array<int, 3>> triangle_list) : mean(mean), rescaled_pca_basis(pca_basis), eigenvalues(eigenvalues), triangle_list(triangle_list)
+	PcaModel(Eigen::VectorXf mean, Eigen::MatrixXf orthonormal_pca_basis, Eigen::VectorXf eigenvalues, std::vector<std::array<int, 3>> triangle_list) : mean(mean), orthonormal_pca_basis(orthonormal_pca_basis), eigenvalues(eigenvalues), triangle_list(triangle_list)
 	{
-		orthonormal_pca_basis = normalise_pca_basis(rescaled_pca_basis, eigenvalues);
+		rescaled_pca_basis = rescale_pca_basis(orthonormal_pca_basis, eigenvalues);
 	};
 
 	/**

include/eos/morphablemodel/io/cvssp.hpp

@@ -151,14 +151,12 @@ inline MorphableModel load_scm_model(boost::filesystem::path model_filename, boo
 		eigenvalues_shape.at<float>(i, 0) = static_cast<float>(var);
 	}
 
-	// We read the unnormalised basis from the file. Now let's normalise it and store the normalised basis separately.
 	// Todo: We should change these to read into an Eigen matrix directly, and not into a cv::Mat first.
 	using RowMajorMatrixXf = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
 	Eigen::Map<RowMajorMatrixXf> orthonormal_pca_basis_shape_(orthonormal_pca_basis_shape.ptr<float>(), orthonormal_pca_basis_shape.rows, orthonormal_pca_basis_shape.cols);
 	Eigen::Map<RowMajorMatrixXf> eigenvalues_shape_(eigenvalues_shape.ptr<float>(), eigenvalues_shape.rows, eigenvalues_shape.cols);
 	Eigen::Map<RowMajorMatrixXf> mean_shape_(mean_shape.ptr<float>(), mean_shape.rows, mean_shape.cols);
-	Eigen::MatrixXf rescaled_pca_basis_shape_ = rescale_pca_basis(orthonormal_pca_basis_shape_, eigenvalues_shape_);
-	PcaModel shape_model(mean_shape_, rescaled_pca_basis_shape_, eigenvalues_shape_, triangle_list);
+	PcaModel shape_model(mean_shape_, orthonormal_pca_basis_shape_, eigenvalues_shape_, triangle_list);
 
 	// Reading the color model
 	// Read number of rows and columns of projection matrix
@@ -205,12 +203,11 @@ inline MorphableModel load_scm_model(boost::filesystem::path model_filename, boo
 		eigenvalues_color.at<float>(i, 0) = static_cast<float>(var);
 	}
 
-	// We read the unnormalised basis from the file. Now let's normalise it and store the normalised basis separately.
+	// Todo: We should change these to read into an Eigen matrix directly, and not into a cv::Mat first.
 	Eigen::Map<RowMajorMatrixXf> orthonormal_pca_basis_color_(orthonormal_pca_basis_color.ptr<float>(), orthonormal_pca_basis_color.rows, orthonormal_pca_basis_color.cols);
 	Eigen::Map<RowMajorMatrixXf> eigenvalues_color_(eigenvalues_color.ptr<float>(), eigenvalues_color.rows, eigenvalues_color.cols);
 	Eigen::Map<RowMajorMatrixXf> mean_color_(mean_color.ptr<float>(), mean_color.rows, mean_color.cols);
-	Eigen::MatrixXf rescaled_pca_basis_color_ = rescale_pca_basis(orthonormal_pca_basis_color_, eigenvalues_color_);
-	PcaModel color_model(mean_color_, rescaled_pca_basis_color_, eigenvalues_color_, triangle_list);
+	PcaModel color_model(mean_color_, orthonormal_pca_basis_color_, eigenvalues_color_, triangle_list);
 
 	model_file.close();
 

python/generate-python-bindings.cpp

@@ -88,7 +88,7 @@ PYBIND11_PLUGIN(eos) {
 
 	py::class_<morphablemodel::PcaModel>(morphablemodel_module, "PcaModel", "Class representing a PcaModel with a mean, eigenvectors and eigenvalues, as well as a list of triangles to build a mesh.")
 		.def(py::init<>(), "Creates an empty model.")
-		.def(py::init<Eigen::VectorXf, Eigen::MatrixXf, Eigen::VectorXf, std::vector<std::array<int, 3>>>(), "Construct a PCA model from given mean, normalised PCA basis, eigenvalues and triangle list.", py::arg("mean"), py::arg("pca_basis"), py::arg("eigenvalues"), py::arg("triangle_list"))
+		.def(py::init<Eigen::VectorXf, Eigen::MatrixXf, Eigen::VectorXf, std::vector<std::array<int, 3>>>(), "Construct a PCA model from given mean, orthonormal PCA basis, eigenvalues and triangle list.", py::arg("mean"), py::arg("orthonormal_pca_basis"), py::arg("eigenvalues"), py::arg("triangle_list"))
 		.def("get_num_principal_components", &morphablemodel::PcaModel::get_num_principal_components, "Returns the number of principal components in the model.")
 		.def("get_data_dimension", &morphablemodel::PcaModel::get_data_dimension, "Returns the dimension of the data, i.e. the number of shape dimensions.")
 		.def("get_triangle_list", &morphablemodel::PcaModel::get_triangle_list, "Returns a list of triangles on how to assemble the vertices into a mesh.")

utils/bfm-binary-to-cereal.cpp

@@ -177,9 +177,7 @@ int main(int argc, char *argv[])
 		triangle_list[i][2] = v2 - 1;
 	}
 
-	// We read the orthonormal basis from the file. Now let's rescale it and store the rescaled basis separately.
-	const auto rescaled_pca_basis_shape = morphablemodel::rescale_pca_basis(orthonormal_pca_basis_shape, eigenvalues_shape);
-	morphablemodel::PcaModel shape_model(mean_shape, rescaled_pca_basis_shape, eigenvalues_shape, triangle_list);
+	morphablemodel::PcaModel shape_model(mean_shape, orthonormal_pca_basis_shape, eigenvalues_shape, triangle_list);
 
 	// Reading the colour (albedo) model:
 	int num_vertices_color = 0;
@@ -225,9 +223,7 @@ int main(int argc, char *argv[])
 		eigenvalues_color(i) = value;
 	}
 
-	// We read the orthonormal basis from the file. Now let's rescale it and store the rescaled basis separately.
-	const auto rescaled_pca_basis_color = morphablemodel::rescale_pca_basis(orthonormal_pca_basis_color, eigenvalues_color);
-	morphablemodel::PcaModel color_model(mean_color, rescaled_pca_basis_color, eigenvalues_color, triangle_list);
+	morphablemodel::PcaModel color_model(mean_color, orthonormal_pca_basis_color, eigenvalues_color, triangle_list);
 
 	file.close();