using OpenCVForUnity.CoreModule;
using OpenCVForUnity.UtilsModule;
using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
namespace OpenCVForUnity.FaceModule
{
// C++: class Face
public class Face
{
//
// C++: Ptr_Facemark cv::face::createFacemarkAAM()
//
public static Facemark createFacemarkAAM()
{
return Facemark.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(face_Face_createFacemarkAAM_10()));
}
//
// C++: Ptr_Facemark cv::face::createFacemarkLBF()
//
public static Facemark createFacemarkLBF()
{
return Facemark.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(face_Face_createFacemarkLBF_10()));
}
//
// C++: Ptr_Facemark cv::face::createFacemarkKazemi()
//
public static Facemark createFacemarkKazemi()
{
return Facemark.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(face_Face_createFacemarkKazemi_10()));
}
//
// C++: bool cv::face::getFacesHAAR(Mat image, Mat& faces, String face_cascade_name)
//
/**
* Default face detector
* This function is mainly utilized by the implementation of a Facemark Algorithm.
* End users are advised to use function Facemark::getFaces which can be manually defined
* and circumvented to the algorithm by Facemark::setFaceDetector.
*
* param image The input image to be processed.
* param faces Output of the function which represent region of interest of the detected faces.
* Each face is stored in cv::Rect container.
*
* <B>Example of usage</B>
*
* std::vector<cv::Rect> faces;
* CParams params("haarcascade_frontalface_alt.xml");
* cv::face::getFaces(frame, faces, ¶ms);
* for(int j=0;j<faces.size();j++){
* cv::rectangle(frame, faces[j], cv::Scalar(255,0,255));
* }
* cv::imshow("detection", frame);
*
* param face_cascade_name automatically generated
* return automatically generated
*/
public static bool getFacesHAAR(Mat image, Mat faces, string face_cascade_name)
{
if (image != null) image.ThrowIfDisposed();
if (faces != null) faces.ThrowIfDisposed();
return face_Face_getFacesHAAR_10(image.nativeObj, faces.nativeObj, face_cascade_name);
}
//
// C++: bool cv::face::loadDatasetList(String imageList, String annotationList, vector_String images, vector_String annotations)
//
/**
* A utility to load list of paths to training image and annotation file.
* param imageList The specified file contains paths to the training images.
* param annotationList The specified file contains paths to the training annotations.
* param images The loaded paths of training images.
* param annotations The loaded paths of annotation files.
*
* Example of usage:
*
* String imageFiles = "images_path.txt";
* String ptsFiles = "annotations_path.txt";
* std::vector<String> images_train;
* std::vector<String> landmarks_train;
* loadDatasetList(imageFiles,ptsFiles,images_train,landmarks_train);
*
* return automatically generated
*/
public static bool loadDatasetList(string imageList, string annotationList, List images, List annotations)
{
Mat images_mat = Converters.vector_String_to_Mat(images);
Mat annotations_mat = Converters.vector_String_to_Mat(annotations);
return face_Face_loadDatasetList_10(imageList, annotationList, images_mat.nativeObj, annotations_mat.nativeObj);
}
//
// C++: bool cv::face::loadTrainingData(String filename, vector_String images, Mat& facePoints, char delim = ' ', float offset = 0.0f)
//
/**
* A utility to load facial landmark dataset from a single file.
*
* param filename The filename of a file that contains the dataset information.
* Each line contains the filename of an image followed by
* pairs of x and y values of facial landmarks points separated by a space.
* Example
*
* /home/user/ibug/image_003_1.jpg 336.820955 240.864510 334.238298 260.922709 335.266918 ...
* /home/user/ibug/image_005_1.jpg 376.158428 230.845712 376.736984 254.924635 383.265403 ...
*
* param images A vector where each element represent the filename of image in the dataset.
* Images are not loaded by default to save the memory.
* param facePoints The loaded landmark points for all training data.
* param delim Delimiter between each element, the default value is a whitespace.
* param offset An offset value to adjust the loaded points.
*
* <B>Example of usage</B>
*
* cv::String imageFiles = "../data/images_train.txt";
* cv::String ptsFiles = "../data/points_train.txt";
* std::vector<String> images;
* std::vector<std::vector<Point2f> > facePoints;
* loadTrainingData(imageFiles, ptsFiles, images, facePoints, 0.0f);
*
* return automatically generated
*/
public static bool loadTrainingData(string filename, List images, Mat facePoints, char delim, float offset)
{
if (facePoints != null) facePoints.ThrowIfDisposed();
Mat images_mat = Converters.vector_String_to_Mat(images);
return face_Face_loadTrainingData_10(filename, images_mat.nativeObj, facePoints.nativeObj, delim, offset);
}
/**
* A utility to load facial landmark dataset from a single file.
*
* param filename The filename of a file that contains the dataset information.
* Each line contains the filename of an image followed by
* pairs of x and y values of facial landmarks points separated by a space.
* Example
*
* /home/user/ibug/image_003_1.jpg 336.820955 240.864510 334.238298 260.922709 335.266918 ...
* /home/user/ibug/image_005_1.jpg 376.158428 230.845712 376.736984 254.924635 383.265403 ...
*
* param images A vector where each element represent the filename of image in the dataset.
* Images are not loaded by default to save the memory.
* param facePoints The loaded landmark points for all training data.
* param delim Delimiter between each element, the default value is a whitespace.
*
* <B>Example of usage</B>
*
* cv::String imageFiles = "../data/images_train.txt";
* cv::String ptsFiles = "../data/points_train.txt";
* std::vector<String> images;
* std::vector<std::vector<Point2f> > facePoints;
* loadTrainingData(imageFiles, ptsFiles, images, facePoints, 0.0f);
*
* return automatically generated
*/
public static bool loadTrainingData(string filename, List images, Mat facePoints, char delim)
{
if (facePoints != null) facePoints.ThrowIfDisposed();
Mat images_mat = Converters.vector_String_to_Mat(images);
return face_Face_loadTrainingData_11(filename, images_mat.nativeObj, facePoints.nativeObj, delim);
}
/**
* A utility to load facial landmark dataset from a single file.
*
* param filename The filename of a file that contains the dataset information.
* Each line contains the filename of an image followed by
* pairs of x and y values of facial landmarks points separated by a space.
* Example
*
* /home/user/ibug/image_003_1.jpg 336.820955 240.864510 334.238298 260.922709 335.266918 ...
* /home/user/ibug/image_005_1.jpg 376.158428 230.845712 376.736984 254.924635 383.265403 ...
*
* param images A vector where each element represent the filename of image in the dataset.
* Images are not loaded by default to save the memory.
* param facePoints The loaded landmark points for all training data.
*
* <B>Example of usage</B>
*
* cv::String imageFiles = "../data/images_train.txt";
* cv::String ptsFiles = "../data/points_train.txt";
* std::vector<String> images;
* std::vector<std::vector<Point2f> > facePoints;
* loadTrainingData(imageFiles, ptsFiles, images, facePoints, 0.0f);
*
* return automatically generated
*/
public static bool loadTrainingData(string filename, List images, Mat facePoints)
{
if (facePoints != null) facePoints.ThrowIfDisposed();
Mat images_mat = Converters.vector_String_to_Mat(images);
return face_Face_loadTrainingData_12(filename, images_mat.nativeObj, facePoints.nativeObj);
}
//
// C++: bool cv::face::loadTrainingData(String imageList, String groundTruth, vector_String images, Mat& facePoints, float offset = 0.0f)
//
/**
* A utility to load facial landmark information from the dataset.
*
* param imageList A file contains the list of image filenames in the training dataset.
* param groundTruth A file contains the list of filenames
* where the landmarks points information are stored.
* The content in each file should follow the standard format (see face::loadFacePoints).
* param images A vector where each element represent the filename of image in the dataset.
* Images are not loaded by default to save the memory.
* param facePoints The loaded landmark points for all training data.
* param offset An offset value to adjust the loaded points.
*
* <B>Example of usage</B>
*
* cv::String imageFiles = "../data/images_train.txt";
* cv::String ptsFiles = "../data/points_train.txt";
* std::vector<String> images;
* std::vector<std::vector<Point2f> > facePoints;
* loadTrainingData(imageFiles, ptsFiles, images, facePoints, 0.0f);
*
*
* example of content in the images_train.txt
*
* /home/user/ibug/image_003_1.jpg
* /home/user/ibug/image_004_1.jpg
* /home/user/ibug/image_005_1.jpg
* /home/user/ibug/image_006.jpg
*
*
* example of content in the points_train.txt
*
* /home/user/ibug/image_003_1.pts
* /home/user/ibug/image_004_1.pts
* /home/user/ibug/image_005_1.pts
* /home/user/ibug/image_006.pts
*
* return automatically generated
*/
public static bool loadTrainingData(string imageList, string groundTruth, List images, Mat facePoints, float offset)
{
if (facePoints != null) facePoints.ThrowIfDisposed();
Mat images_mat = Converters.vector_String_to_Mat(images);
return face_Face_loadTrainingData_13(imageList, groundTruth, images_mat.nativeObj, facePoints.nativeObj, offset);
}
/**
* A utility to load facial landmark information from the dataset.
*
* param imageList A file contains the list of image filenames in the training dataset.
* param groundTruth A file contains the list of filenames
* where the landmarks points information are stored.
* The content in each file should follow the standard format (see face::loadFacePoints).
* param images A vector where each element represent the filename of image in the dataset.
* Images are not loaded by default to save the memory.
* param facePoints The loaded landmark points for all training data.
*
* <B>Example of usage</B>
*
* cv::String imageFiles = "../data/images_train.txt";
* cv::String ptsFiles = "../data/points_train.txt";
* std::vector<String> images;
* std::vector<std::vector<Point2f> > facePoints;
* loadTrainingData(imageFiles, ptsFiles, images, facePoints, 0.0f);
*
*
* example of content in the images_train.txt
*
* /home/user/ibug/image_003_1.jpg
* /home/user/ibug/image_004_1.jpg
* /home/user/ibug/image_005_1.jpg
* /home/user/ibug/image_006.jpg
*
*
* example of content in the points_train.txt
*
* /home/user/ibug/image_003_1.pts
* /home/user/ibug/image_004_1.pts
* /home/user/ibug/image_005_1.pts
* /home/user/ibug/image_006.pts
*
* return automatically generated
*/
public static bool loadTrainingData(string imageList, string groundTruth, List images, Mat facePoints)
{
if (facePoints != null) facePoints.ThrowIfDisposed();
Mat images_mat = Converters.vector_String_to_Mat(images);
return face_Face_loadTrainingData_14(imageList, groundTruth, images_mat.nativeObj, facePoints.nativeObj);
}
//
// C++: bool cv::face::loadTrainingData(vector_String filename, vector_vector_Point2f trainlandmarks, vector_String trainimages)
//
/**
* This function extracts the data for training from .txt files which contains the corresponding image name and landmarks.
* The first file in each file should give the path of the image whose
* landmarks are being described in the file. Then in the subsequent
* lines there should be coordinates of the landmarks in the image
* i.e each line should be of the form x,y
* where x represents the x coordinate of the landmark and y represents
* the y coordinate of the landmark.
*
* For reference you can see the files as provided in the
* <a href="http://www.ifp.illinois.edu/~vuongle2/helen/">HELEN dataset</a>
*
* param filename A vector of type cv::String containing name of the .txt files.
* param trainlandmarks A vector of type cv::Point2f that would store shape or landmarks of all images.
* param trainimages A vector of type cv::String which stores the name of images whose landmarks are tracked
* return A boolean value. It returns true when it reads the data successfully and false otherwise
*/
public static bool loadTrainingData(List filename, List trainlandmarks, List trainimages)
{
Mat filename_mat = Converters.vector_String_to_Mat(filename);
List trainlandmarks_tmplm = new List((trainlandmarks != null) ? trainlandmarks.Count : 0);
Mat trainlandmarks_mat = Converters.vector_vector_Point2f_to_Mat(trainlandmarks, trainlandmarks_tmplm);
Mat trainimages_mat = Converters.vector_String_to_Mat(trainimages);
return face_Face_loadTrainingData_15(filename_mat.nativeObj, trainlandmarks_mat.nativeObj, trainimages_mat.nativeObj);
}
//
// C++: bool cv::face::loadFacePoints(String filename, Mat& points, float offset = 0.0f)
//
/**
* A utility to load facial landmark information from a given file.
*
* param filename The filename of file contains the facial landmarks data.
* param points The loaded facial landmark points.
* param offset An offset value to adjust the loaded points.
*
* <B>Example of usage</B>
*
* std::vector<Point2f> points;
* face::loadFacePoints("filename.txt", points, 0.0f);
*
*
* The annotation file should follow the default format which is
*
* version: 1
* n_points: 68
* {
* 212.716603 499.771793
* 230.232816 566.290071
* ...
* }
*
* where n_points is the number of points considered
* and each point is represented as its position in x and y.
* return automatically generated
*/
public static bool loadFacePoints(string filename, Mat points, float offset)
{
if (points != null) points.ThrowIfDisposed();
return face_Face_loadFacePoints_10(filename, points.nativeObj, offset);
}
/**
* A utility to load facial landmark information from a given file.
*
* param filename The filename of file contains the facial landmarks data.
* param points The loaded facial landmark points.
*
* <B>Example of usage</B>
*
* std::vector<Point2f> points;
* face::loadFacePoints("filename.txt", points, 0.0f);
*
*
* The annotation file should follow the default format which is
*
* version: 1
* n_points: 68
* {
* 212.716603 499.771793
* 230.232816 566.290071
* ...
* }
*
* where n_points is the number of points considered
* and each point is represented as its position in x and y.
* return automatically generated
*/
public static bool loadFacePoints(string filename, Mat points)
{
if (points != null) points.ThrowIfDisposed();
return face_Face_loadFacePoints_11(filename, points.nativeObj);
}
//
// C++: void cv::face::drawFacemarks(Mat& image, Mat points, Scalar color = Scalar(255,0,0))
//
/**
* Utility to draw the detected facial landmark points
*
* param image The input image to be processed.
* param points Contains the data of points which will be drawn.
* param color The color of points in BGR format represented by cv::Scalar.
*
* <B>Example of usage</B>
*
* std::vector<Rect> faces;
* std::vector<std::vector<Point2f> > landmarks;
* facemark->getFaces(img, faces);
* facemark->fit(img, faces, landmarks);
* for(int j=0;j<rects.size();j++){
* face::drawFacemarks(frame, landmarks[j], Scalar(0,0,255));
* }
*
*/
public static void drawFacemarks(Mat image, Mat points, Scalar color)
{
if (image != null) image.ThrowIfDisposed();
if (points != null) points.ThrowIfDisposed();
face_Face_drawFacemarks_10(image.nativeObj, points.nativeObj, color.val[0], color.val[1], color.val[2], color.val[3]);
}
/**
* Utility to draw the detected facial landmark points
*
* param image The input image to be processed.
* param points Contains the data of points which will be drawn.
*
* <B>Example of usage</B>
*
* std::vector<Rect> faces;
* std::vector<std::vector<Point2f> > landmarks;
* facemark->getFaces(img, faces);
* facemark->fit(img, faces, landmarks);
* for(int j=0;j<rects.size();j++){
* face::drawFacemarks(frame, landmarks[j], Scalar(0,0,255));
* }
*
*/
public static void drawFacemarks(Mat image, Mat points)
{
if (image != null) image.ThrowIfDisposed();
if (points != null) points.ThrowIfDisposed();
face_Face_drawFacemarks_11(image.nativeObj, points.nativeObj);
}
#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
const string LIBNAME = "__Internal";
#else
const string LIBNAME = "opencvforunity";
#endif
// C++: Ptr_Facemark cv::face::createFacemarkAAM()
[DllImport(LIBNAME)]
private static extern IntPtr face_Face_createFacemarkAAM_10();
// C++: Ptr_Facemark cv::face::createFacemarkLBF()
[DllImport(LIBNAME)]
private static extern IntPtr face_Face_createFacemarkLBF_10();
// C++: Ptr_Facemark cv::face::createFacemarkKazemi()
[DllImport(LIBNAME)]
private static extern IntPtr face_Face_createFacemarkKazemi_10();
// C++: bool cv::face::getFacesHAAR(Mat image, Mat& faces, String face_cascade_name)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_getFacesHAAR_10(IntPtr image_nativeObj, IntPtr faces_nativeObj, string face_cascade_name);
// C++: bool cv::face::loadDatasetList(String imageList, String annotationList, vector_String images, vector_String annotations)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadDatasetList_10(string imageList, string annotationList, IntPtr images_mat_nativeObj, IntPtr annotations_mat_nativeObj);
// C++: bool cv::face::loadTrainingData(String filename, vector_String images, Mat& facePoints, char delim = ' ', float offset = 0.0f)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_10(string filename, IntPtr images_mat_nativeObj, IntPtr facePoints_nativeObj, char delim, float offset);
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_11(string filename, IntPtr images_mat_nativeObj, IntPtr facePoints_nativeObj, char delim);
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_12(string filename, IntPtr images_mat_nativeObj, IntPtr facePoints_nativeObj);
// C++: bool cv::face::loadTrainingData(String imageList, String groundTruth, vector_String images, Mat& facePoints, float offset = 0.0f)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_13(string imageList, string groundTruth, IntPtr images_mat_nativeObj, IntPtr facePoints_nativeObj, float offset);
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_14(string imageList, string groundTruth, IntPtr images_mat_nativeObj, IntPtr facePoints_nativeObj);
// C++: bool cv::face::loadTrainingData(vector_String filename, vector_vector_Point2f trainlandmarks, vector_String trainimages)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadTrainingData_15(IntPtr filename_mat_nativeObj, IntPtr trainlandmarks_mat_nativeObj, IntPtr trainimages_mat_nativeObj);
// C++: bool cv::face::loadFacePoints(String filename, Mat& points, float offset = 0.0f)
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadFacePoints_10(string filename, IntPtr points_nativeObj, float offset);
[DllImport(LIBNAME)]
[return: MarshalAs(UnmanagedType.U1)]
private static extern bool face_Face_loadFacePoints_11(string filename, IntPtr points_nativeObj);
// C++: void cv::face::drawFacemarks(Mat& image, Mat points, Scalar color = Scalar(255,0,0))
[DllImport(LIBNAME)]
private static extern void face_Face_drawFacemarks_10(IntPtr image_nativeObj, IntPtr points_nativeObj, double color_val0, double color_val1, double color_val2, double color_val3);
[DllImport(LIBNAME)]
private static extern void face_Face_drawFacemarks_11(IntPtr image_nativeObj, IntPtr points_nativeObj);
}
}