Merge pull request #2154 from LaurentBerger:py_face_landmark (84c882d0) · Commits · SUMMER2020 / students / proj-2020194

modules/face/include/opencv2/face/facemark.hpp

+2 −2

Original line number	Diff line number	Diff line
		@@ -74,8 +74,8 @@ public:
		@endcode
		*/
		CV_WRAP virtual bool fit( InputArray image,
		const std::vector<Rect>& faces,
		CV_OUT std::vector<std::vector<Point2f> >& landmarks ) = 0;
		InputArray faces,
		OutputArrayOfArrays landmarks) = 0;
		}; /* Facemark*/

modules/face/include/opencv2/face/facemarkAAM.hpp

+1 −1

Original line number	Diff line number	Diff line
		@@ -146,7 +146,7 @@ public:
		};

		//! overload with additional Config structures
		virtual bool fitConfig( InputArray image, const std::vector<Rect>& roi, std::vector<std::vector<Point2f> >& _landmarks, const std::vector<Config> &runtime_params ) = 0;
		virtual bool fitConfig( InputArray image, InputArray roi, OutputArrayOfArrays _landmarks, const std::vector<Config> &runtime_params ) = 0;


		//! initializer

modules/face/samples/landmarks_demo.py

0 → 100644

+29 −0

Original line number	Diff line number	Diff line
		import random
		import numpy as np
		import cv2 as cv

		frame1 = cv.imread(cv.samples.findFile('lena.jpg'))
		if frame1 is None:
		print("image not found")
		exit()
		frame = np.vstack((frame1,frame1))
		facemark = cv.face.createFacemarkLBF()
		try:
		facemark.loadModel(cv.samples.findFile('lbfmodel.yaml'))
		except cv.error:
		print("Model not found\nlbfmodel.yaml can be download at")
		print("https://raw.githubusercontent.com/kurnianggoro/GSOC2017/master/data/lbfmodel.yaml")
		cascade = cv.CascadeClassifier(cv.samples.findFile('lbpcascade_frontalface_improved.xml'))
		if cascade.empty() :
		print("cascade not found")
		exit()
		faces = cascade.detectMultiScale(frame, 1.05, 3, cv.CASCADE_SCALE_IMAGE, (30, 30))
		ok, landmarks = facemark.fit(frame, faces=faces)
		cv.imshow("Image", frame)
		for marks in landmarks:
		couleur = (random.randint(0,255),
		random.randint(0,255),
		random.randint(0,255))
		cv.face.drawFacemarks(frame, marks, couleur)
		cv.imshow("Image Landmarks", frame)
		cv.waitKey()

modules/face/src/face_alignmentimpl.hpp

+1 −1

Original line number	Diff line number	Diff line
		@@ -73,7 +73,7 @@ public:
		void loadModel(String fs) CV_OVERRIDE;
		bool setFaceDetector(FN_FaceDetector f, void* userdata) CV_OVERRIDE;
		bool getFaces(InputArray image, OutputArray faces) CV_OVERRIDE;
		bool fit(InputArray image, const std::vector<Rect>& faces, CV_OUT std::vector<std::vector<Point2f> >& landmarks ) CV_OVERRIDE;
		bool fit(InputArray image, InputArray faces, OutputArrayOfArrays landmarks ) CV_OVERRIDE;
		void training(String imageList, String groundTruth);
		bool training(vector<Mat>& images, vector< vector<Point2f> >& landmarks,string filename,Size scale,string modelFilename) CV_OVERRIDE;
		// Destructor for the class.

modules/face/src/facemarkAAM.cpp

+43 −6

Original line number	Diff line number	Diff line
		@@ -103,11 +103,11 @@ public:

		bool getData(void * items) CV_OVERRIDE;

		bool fitConfig( InputArray image, const std::vector<Rect>& roi, std::vector<std::vector<Point2f> >& _landmarks, const std::vector<Config> &runtime_params ) CV_OVERRIDE;
		bool fitConfig( InputArray image, InputArray roi, OutputArrayOfArrays _landmarks, const std::vector<Config> &runtime_params ) CV_OVERRIDE;

		protected:

		bool fit( InputArray image, const std::vector<Rect>& faces, CV_OUT std::vector<std::vector<Point2f> >& landmarks ) CV_OVERRIDE;
		bool fit( InputArray image, InputArray faces, OutputArrayOfArrays landmarks ) CV_OVERRIDE;
		bool fitImpl( const Mat image, std::vector<Point2f>& landmarks,const Mat R,const Point2f T,const float scale, const int sclIdx=0 );

		bool addTrainingSample(InputArray image, InputArray landmarks) CV_OVERRIDE;
		@@ -322,18 +322,54 @@ void FacemarkAAMImpl::training(void* parameters){
		if(params.verbose) printf("Training is completed\n");
		}

		bool FacemarkAAMImpl::fit( InputArray image, const std::vector<Rect>& roi, CV_OUT std::vector<std::vector<Point2f> >& _landmarks )
		/**
		* @brief Copy the contents of a corners vector to an OutputArray, settings its size.
		*/
		static void _copyVector2Output(std::vector< std::vector< Point2f > > &vec, OutputArrayOfArrays out)
		{
		out.create((int)vec.size(), 1, CV_32FC2);

		if (out.isMatVector()) {
		for (unsigned int i = 0; i < vec.size(); i++) {
		out.create(68, 1, CV_32FC2, i);
		Mat &m = out.getMatRef(i);
		Mat(Mat(vec[i]).t()).copyTo(m);
		}
		}
		else if (out.isUMatVector()) {
		for (unsigned int i = 0; i < vec.size(); i++) {
		out.create(68, 1, CV_32FC2, i);
		UMat &m = out.getUMatRef(i);
		Mat(Mat(vec[i]).t()).copyTo(m);
		}
		}
		else if (out.kind() == _OutputArray::STD_VECTOR_VECTOR) {
		for (unsigned int i = 0; i < vec.size(); i++) {
		out.create(68, 1, CV_32FC2, i);
		Mat m = out.getMat(i);
		Mat(Mat(vec[i]).t()).copyTo(m);
		}
		}
		else {
		CV_Error(cv::Error::StsNotImplemented,
		"Only Mat vector, UMat vector, and vector<vector> OutputArrays are currently supported.");
		}
		}


		bool FacemarkAAMImpl::fit( InputArray image, InputArray roi, OutputArrayOfArrays _landmarks )
		{
		std::vector<Config> config; // empty
		return fitConfig(image, roi, _landmarks, config);
		}

		bool FacemarkAAMImpl::fitConfig( InputArray image, const std::vector<Rect>& roi, std::vector<std::vector<Point2f> >& _landmarks, const std::vector<Config> &configs )
		bool FacemarkAAMImpl::fitConfig( InputArray image, InputArray roi, OutputArrayOfArrays _landmarks, const std::vector<Config> &configs )
		{
		const std::vector<Rect> & faces = roi;
		Mat roimat = roi.getMat();
		std::vector<Rect> faces = roimat.reshape(4, roimat.rows);
		if(faces.size()<1) return false;

		std::vector<std::vector<Point2f> > & landmarks = _landmarks;
		std::vector<std::vector<Point2f> > landmarks;
		landmarks.resize(faces.size());

		Mat img = image.getMat();
		@@ -354,6 +390,7 @@ bool FacemarkAAMImpl::fitConfig( InputArray image, const std::vector<Rect>& roi,
		fitImpl(img, landmarks[i], R,t, scale);
		}
		}
		_copyVector2Output(landmarks, _landmarks);

		return true;
		}