core: add PCABackProject() and PCAProject() functions

Signed-off-by: deadprogram <ron@hybridgroup.com>

ROADMAP.md

@@ -17,9 +17,9 @@ Your pull requests will be greatly appreciated!
     - [ ] **Operations on arrays - WORK STARTED**. The following functions still need implementation:
         - [X] [Mahalanobis](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga4493aee129179459cbfc6064f051aa7d)
         - [ ] [mulTransposed](https://docs.opencv.org/master/d2/de8/group__core__array.html#gadc4e49f8f7a155044e3be1b9e3b270ab)
-        - [ ] [PCABackProject](https://docs.opencv.org/master/d2/de8/group__core__array.html#gab26049f30ee8e94f7d69d82c124faafc)
+        - [X] [PCABackProject](https://docs.opencv.org/master/d2/de8/group__core__array.html#gab26049f30ee8e94f7d69d82c124faafc)
         - [X] [PCACompute](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga4e2073c7311f292a0648f04c37b73781)
-        - [ ] [PCAProject](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga6b9fbc7b3a99ebfd441bbec0a6bc4f88)
+        - [X] [PCAProject](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga6b9fbc7b3a99ebfd441bbec0a6bc4f88)
         - [ ] [PSNR](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga07aaf34ae31d226b1b847d8bcff3698f)
         - [X] [randn](https://docs.opencv.org/master/d2/de8/group__core__array.html#gaeff1f61e972d133a04ce3a5f81cf6808)
         - [X] [randShuffle](https://docs.opencv.org/master/d2/de8/group__core__array.html#ga6a789c8a5cb56c6dd62506179808f763)

core.cpp

@@ -516,10 +516,18 @@ void Mat_EigenNonSymmetric(Mat src, Mat eigenvalues, Mat eigenvectors) {
     cv::eigenNonSymmetric(*src, *eigenvalues, *eigenvectors);
 }
 
+void Mat_PCABackProject(Mat data, Mat mean, Mat eigenvectors, Mat result) {
+    cv::PCABackProject(*data, *mean, *eigenvectors, *result);
+}
+
 void Mat_PCACompute(Mat src, Mat mean, Mat eigenvectors, Mat eigenvalues, int maxComponents) {
     cv::PCACompute(*src, *mean, *eigenvectors, *eigenvalues, maxComponents);
 }
 
+void Mat_PCAProject(Mat data, Mat mean, Mat eigenvectors, Mat result) {
+    cv::PCAProject(*data, *mean, *eigenvectors, *result);
+}
+
 void Mat_Exp(Mat src, Mat dst) {
     cv::exp(*src, *dst);
 }

core.go

@@ -1196,6 +1196,14 @@ func EigenNonSymmetric(src Mat, eigenvalues *Mat, eigenvectors *Mat) {
 	C.Mat_EigenNonSymmetric(src.p, eigenvalues.p, eigenvectors.p)
 }
 
+// PCABackProject reconstructs vectors from their PC projections.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/d2/de8/group__core__array.html#gab26049f30ee8e94f7d69d82c124faafc
+func PCABackProject(data Mat, mean Mat, eigenvectors Mat, result *Mat) {
+	C.Mat_PCABackProject(data.p, mean.p, eigenvectors.p, result.p)
+}
+
 // PCACompute performs PCA.
 //
 // The computed eigenvalues are sorted from the largest to the smallest and the corresponding
@@ -1209,6 +1217,14 @@ func PCACompute(src Mat, mean *Mat, eigenvectors *Mat, eigenvalues *Mat, maxComp
 	C.Mat_PCACompute(src.p, mean.p, eigenvectors.p, eigenvalues.p, C.int(maxComponents))
 }
 
+// PCAProject projects vector(s) to the principal component subspace.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/d2/de8/group__core__array.html#ga6b9fbc7b3a99ebfd441bbec0a6bc4f88
+func PCAProject(data Mat, mean Mat, eigenvectors Mat, result *Mat) {
+	C.Mat_PCAProject(data.p, mean.p, eigenvectors.p, result.p)
+}
+
 // Exp calculates the exponent of every array element.
 //
 // For further details, please see:

core.h

@@ -382,7 +382,9 @@ void Mat_DFT(Mat m, Mat dst, int flags);
 void Mat_Divide(Mat src1, Mat src2, Mat dst);
 bool Mat_Eigen(Mat src, Mat eigenvalues, Mat eigenvectors);
 void Mat_EigenNonSymmetric(Mat src, Mat eigenvalues, Mat eigenvectors);
+void Mat_PCABackProject(Mat data, Mat mean, Mat eigenvectors, Mat result);
 void Mat_PCACompute(Mat src, Mat mean, Mat eigenvectors, Mat eigenvalues, int maxComponents);
+void Mat_PCAProject(Mat data, Mat mean, Mat eigenvectors, Mat result);
 void Mat_Exp(Mat src, Mat dst);
 void Mat_ExtractChannel(Mat src, Mat dst, int coi);
 void Mat_FindNonZero(Mat src, Mat idx);

core_test.go

@@ -2070,6 +2070,36 @@ func TestMatEigenNonSymmetric(t *testing.T) {
 	eigenvalues.Close()
 }
 
+func TestPCABackProject(t *testing.T) {
+	data := NewMatWithSize(3, 1, MatTypeCV32F)
+	defer data.Close()
+	data.SetFloatAt(0, 0, float32(-5))
+	data.SetFloatAt(1, 0, float32(0))
+	data.SetFloatAt(2, 0, float32(-10))
+
+	mean := NewMatWithSize(1, 4, MatTypeCV32F)
+	defer mean.Close()
+	mean.SetFloatAt(0, 0, float32(2))
+	mean.SetFloatAt(0, 1, float32(4))
+	mean.SetFloatAt(0, 2, float32(4))
+	mean.SetFloatAt(0, 3, float32(8))
+
+	vectors := NewMatWithSizeFromScalar(NewScalar(0, 0, 0, 0), 1, 4, MatTypeCV32F)
+	defer vectors.Close()
+	vectors.SetFloatAt(0, 0, float32(0.2))
+	vectors.SetFloatAt(0, 1, float32(0.4))
+	vectors.SetFloatAt(0, 2, float32(0.4))
+	vectors.SetFloatAt(0, 3, float32(0.8))
+
+	result := NewMat()
+	defer result.Close()
+
+	PCABackProject(data, mean, vectors, &result)
+	if result.Empty() {
+		t.Error("PCABackProject should not have empty result.")
+	}
+}
+
 func TestPCACompute(t *testing.T) {
 	src := NewMatWithSize(10, 10, MatTypeCV32F)
 	// Set some source data so the PCA is done on a non-zero matrix.
@@ -2093,6 +2123,45 @@ func TestPCACompute(t *testing.T) {
 	eigenvalues.Close()
 }
 
+func TestPCAProject(t *testing.T) {
+	data := NewMatWithSize(3, 4, MatTypeCV32F)
+	defer data.Close()
+	data.SetFloatAt(0, 0, float32(1))
+	data.SetFloatAt(0, 1, float32(2))
+	data.SetFloatAt(0, 2, float32(2))
+	data.SetFloatAt(0, 3, float32(4))
+	data.SetFloatAt(1, 0, float32(2))
+	data.SetFloatAt(1, 1, float32(4))
+	data.SetFloatAt(1, 2, float32(4))
+	data.SetFloatAt(1, 3, float32(8))
+	data.SetFloatAt(2, 0, float32(0))
+	data.SetFloatAt(2, 1, float32(0))
+	data.SetFloatAt(2, 2, float32(0))
+	data.SetFloatAt(2, 3, float32(0))
+
+	mean := NewMatWithSize(1, 4, MatTypeCV32F)
+	defer mean.Close()
+	mean.SetFloatAt(0, 0, float32(2))
+	mean.SetFloatAt(0, 1, float32(4))
+	mean.SetFloatAt(0, 2, float32(4))
+	mean.SetFloatAt(0, 3, float32(8))
+
+	vectors := NewMatWithSizeFromScalar(NewScalar(0, 0, 0, 0), 1, 4, MatTypeCV32F)
+	defer vectors.Close()
+	vectors.SetFloatAt(0, 0, float32(0.2))
+	vectors.SetFloatAt(0, 1, float32(0.4))
+	vectors.SetFloatAt(0, 2, float32(0.4))
+	vectors.SetFloatAt(0, 3, float32(0.8))
+
+	result := NewMat()
+	defer result.Close()
+
+	PCAProject(data, mean, vectors, &result)
+	if result.Empty() {
+		t.Error("PCABackProject should not have empty result.")
+	}
+}
+
 func TestMatExp(t *testing.T) {
 	src := NewMatWithSize(10, 10, MatTypeCV32F)
 	dst := NewMat()