mirror of
https://gitcode.com/gh_mirrors/ope/OpenFace.git
synced 2025-12-30 04:52:29 +00:00
Adapting matlab video demo. Removing duplicate Piece Wise Affine Warp code
This commit is contained in:
Tadas Baltrusaitis
2
.gitignore
vendored
2
.gitignore
vendored
@@ -82,3 +82,5 @@ lib/3rdParty/CameraEnumerator/x64/
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matlab_runners/Action Unit Experiments/out_bosph/
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matlab_runners/Action Unit Experiments/out_bp4d/
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matlab_runners/Feature Point Experiments/300VW_experiment/
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gui/OpenFaceOffline/obj/
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gui/OpenFaceDemo/obj/
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38
OpenFace.sln
38
OpenFace.sln
@@ -43,166 +43,128 @@ Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CameraEnumerator", "lib\3rd
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
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Debug|Win32 = Debug|Win32
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Debug|x64 = Debug|x64
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Release|Any CPU = Release|Any CPU
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Release|Win32 = Release|Win32
|
||||
Release|x64 = Release|x64
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EndGlobalSection
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GlobalSection(ProjectConfigurationPlatforms) = postSolution
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@@ -33,7 +33,7 @@
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||||
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||||
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@@ -98,7 +98,7 @@
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||||
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|
||||
<SDLCheck>false</SDLCheck>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;$(SolutionDir)lib/local/LandmarkDetector/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<EnableEnhancedInstructionSet>StreamingSIMDExtensions2</EnableEnhancedInstructionSet>
|
||||
<MultiProcessorCompilation>true</MultiProcessorCompilation>
|
||||
</ClCompile>
|
||||
@@ -117,7 +117,7 @@
|
||||
<WarningLevel>Level3</WarningLevel>
|
||||
<Optimization>Disabled</Optimization>
|
||||
<SDLCheck>false</SDLCheck>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;$(SolutionDir)lib/local/LandmarkDetector/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<EnableEnhancedInstructionSet>AdvancedVectorExtensions</EnableEnhancedInstructionSet>
|
||||
<MultiProcessorCompilation>true</MultiProcessorCompilation>
|
||||
<PreprocessorDefinitions>WIN64;_DEBUG;_LIB;EIGEN_MPL2_ONLY;%(PreprocessorDefinitions)</PreprocessorDefinitions>
|
||||
@@ -140,7 +140,7 @@
|
||||
<IntrinsicFunctions>true</IntrinsicFunctions>
|
||||
<SDLCheck>
|
||||
</SDLCheck>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;$(SolutionDir)lib/local/LandmarkDetector/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<EnableEnhancedInstructionSet>StreamingSIMDExtensions2</EnableEnhancedInstructionSet>
|
||||
<MultiProcessorCompilation>true</MultiProcessorCompilation>
|
||||
</ClCompile>
|
||||
@@ -165,7 +165,7 @@
|
||||
<IntrinsicFunctions>true</IntrinsicFunctions>
|
||||
<SDLCheck>
|
||||
</SDLCheck>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<AdditionalIncludeDirectories>./include;$(SolutionDir)lib/local/Utilities/include;$(SolutionDir)lib/local/LandmarkDetector/include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
|
||||
<EnableEnhancedInstructionSet>AdvancedVectorExtensions</EnableEnhancedInstructionSet>
|
||||
<MultiProcessorCompilation>true</MultiProcessorCompilation>
|
||||
<PreprocessorDefinitions>WIN64;NDEBUG;_LIB;%(PreprocessorDefinitions)</PreprocessorDefinitions>
|
||||
@@ -187,13 +187,15 @@
|
||||
<ProjectReference Include="..\..\3rdParty\dlib\dlib.vcxproj">
|
||||
<Project>{b47a5f12-2567-44e9-ae49-35763ec82149}</Project>
|
||||
</ProjectReference>
|
||||
<ProjectReference Include="..\LandmarkDetector\LandmarkDetector.vcxproj">
|
||||
<Project>{bdc1d107-de17-4705-8e7b-cdde8bfb2bf8}</Project>
|
||||
</ProjectReference>
|
||||
<ProjectReference Include="..\Utilities\Utilities.vcxproj">
|
||||
<Project>{8e741ea2-9386-4cf2-815e-6f9b08991eac}</Project>
|
||||
</ProjectReference>
|
||||
</ItemGroup>
|
||||
<ItemGroup>
|
||||
<ClCompile Include="src\FaceAnalyserParameters.cpp" />
|
||||
<ClCompile Include="src\PAW.cpp" />
|
||||
<ClCompile Include="src\PDM.cpp" />
|
||||
<ClCompile Include="src\SVM_dynamic_lin.cpp" />
|
||||
<ClCompile Include="src\SVM_static_lin.cpp" />
|
||||
@@ -206,7 +208,6 @@
|
||||
</ClInclude>
|
||||
<ClCompile Include="src\FaceAnalyser.cpp" />
|
||||
<ClCompile Include="src\Face_utils.cpp" />
|
||||
<ClInclude Include="include\PAW.h" />
|
||||
<ClInclude Include="include\PDM.h" />
|
||||
<ClInclude Include="include\SVM_dynamic_lin.h" />
|
||||
<ClInclude Include="include\SVM_static_lin.h" />
|
||||
|
||||
@@ -36,9 +36,6 @@
|
||||
<ClInclude Include="include\PDM.h">
|
||||
<Filter>Header Files</Filter>
|
||||
</ClInclude>
|
||||
<ClInclude Include="include\PAW.h">
|
||||
<Filter>Header Files</Filter>
|
||||
</ClInclude>
|
||||
<ClInclude Include="include\FaceAnalyserParameters.h">
|
||||
<Filter>Header Files</Filter>
|
||||
</ClInclude>
|
||||
@@ -65,9 +62,6 @@
|
||||
<ClCompile Include="src\PDM.cpp">
|
||||
<Filter>Source Files</Filter>
|
||||
</ClCompile>
|
||||
<ClCompile Include="src\PAW.cpp">
|
||||
<Filter>Source Files</Filter>
|
||||
</ClCompile>
|
||||
<ClCompile Include="src\FaceAnalyserParameters.cpp">
|
||||
<Filter>Source Files</Filter>
|
||||
</ClCompile>
|
||||
|
||||
@@ -1,138 +0,0 @@
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
|
||||
// all rights reserved.
|
||||
//
|
||||
// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
|
||||
//
|
||||
// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
|
||||
// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
|
||||
//
|
||||
// License can be found in OpenFace-license.txt
|
||||
//
|
||||
// * Any publications arising from the use of this software, including but
|
||||
// not limited to academic journal and conference publications, technical
|
||||
// reports and manuals, must cite at least one of the following works:
|
||||
//
|
||||
// OpenFace: an open source facial behavior analysis toolkit
|
||||
// Tadas Baltru<72>aitis, Peter Robinson, and Louis-Philippe Morency
|
||||
// in IEEE Winter Conference on Applications of Computer Vision, 2016
|
||||
//
|
||||
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
|
||||
// Erroll Wood, Tadas Baltru<72>aitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
|
||||
// in IEEE International. Conference on Computer Vision (ICCV), 2015
|
||||
//
|
||||
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
|
||||
// Tadas Baltru<72>aitis, Marwa Mahmoud, and Peter Robinson
|
||||
// in Facial Expression Recognition and Analysis Challenge,
|
||||
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
|
||||
//
|
||||
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
|
||||
// Tadas Baltru<72>aitis, Peter Robinson, and Louis-Philippe Morency.
|
||||
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
|
||||
//
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
#ifndef __PAWA_h_
|
||||
#define __PAWA_h_
|
||||
|
||||
// OpenCV includes
|
||||
#include <opencv2/core/core.hpp>
|
||||
|
||||
namespace FaceAnalysis
|
||||
{
|
||||
//===========================================================================
|
||||
/**
|
||||
A Piece-wise Affine Warp
|
||||
The ideas for this piece-wise affine triangular warping are taken from the
|
||||
Active appearance models revisited by Iain Matthews and Simon Baker in IJCV 2004
|
||||
This is used for both validation of landmark detection, and for avatar animation
|
||||
|
||||
The code is based on the CLM tracker by Jason Saragih et al.
|
||||
*/
|
||||
|
||||
class PAW{
|
||||
public:
|
||||
// Number of pixels after the warping to neutral shape
|
||||
int number_of_pixels;
|
||||
|
||||
// Minimum x coordinate in destination
|
||||
float min_x;
|
||||
|
||||
// minimum y coordinate in destination
|
||||
float min_y;
|
||||
|
||||
// Destination points (landmarks to be warped to)
|
||||
cv::Mat_<float> destination_landmarks;
|
||||
|
||||
// Destination points (landmarks to be warped from)
|
||||
cv::Mat_<float> source_landmarks;
|
||||
|
||||
// Triangulation, each triangle is warped using an affine transform
|
||||
cv::Mat_<int> triangulation;
|
||||
|
||||
// Triangle index, indicating which triangle each of destination pixels lies in
|
||||
cv::Mat_<int> triangle_id;
|
||||
|
||||
// Indicating if the destination warped pixels is valid (lies within a face)
|
||||
cv::Mat_<uchar> pixel_mask;
|
||||
|
||||
// A number of precomputed coefficients that are helpful for quick warping
|
||||
|
||||
// affine coefficients for all triangles (see Matthews and Baker 2004)
|
||||
// 6 coefficients for each triangle (are computed from alpha and beta)
|
||||
// This is computed during each warp based on source landmarks
|
||||
cv::Mat_<float> coefficients;
|
||||
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> alpha;
|
||||
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> beta;
|
||||
|
||||
// x-source of warped points
|
||||
cv::Mat_<float> map_x;
|
||||
|
||||
// y-source of warped points
|
||||
cv::Mat_<float> map_y;
|
||||
|
||||
// Default constructor
|
||||
PAW(){;}
|
||||
|
||||
// Construct a warp from a destination shape and triangulation
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation);
|
||||
|
||||
// The final optional argument allows for optimisation if the triangle indices from previous frame are known (for tracking in video)
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation, float in_min_x, float in_min_y, float in_max_x, float in_max_y);
|
||||
|
||||
// Copy constructor
|
||||
PAW(const PAW& other);
|
||||
|
||||
void Read(std::ifstream &s);
|
||||
|
||||
// The actual warping
|
||||
void Warp(const cv::Mat& image_to_warp, cv::Mat& destination_image, const cv::Mat_<float>& landmarks_to_warp);
|
||||
|
||||
// Compute coefficients needed for warping
|
||||
void CalcCoeff();
|
||||
|
||||
// Perform the actual warping
|
||||
void WarpRegion(cv::Mat_<float>& map_x, cv::Mat_<float>& map_y);
|
||||
|
||||
inline int NumberOfLandmarks() const {return destination_landmarks.rows/2;} ;
|
||||
inline int NumberOfTriangles() const {return triangulation.rows;} ;
|
||||
|
||||
// The width and height of the warped image
|
||||
inline int constWidth() const {return pixel_mask.cols;}
|
||||
inline int Height() const {return pixel_mask.rows;}
|
||||
|
||||
private:
|
||||
|
||||
// Helper functions for dealing with triangles
|
||||
static bool sameSide(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3);
|
||||
static bool pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3);
|
||||
static int findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess = -1);
|
||||
|
||||
};
|
||||
//===========================================================================
|
||||
}
|
||||
#endif
|
||||
@@ -215,7 +215,7 @@ namespace FaceAnalysis
|
||||
|
||||
destination_landmarks = cv::Mat(destination_landmarks.t()).reshape(1, 1).t();
|
||||
|
||||
FaceAnalysis::PAW paw(destination_landmarks, triangulation, 0, 0, aligned_face.cols-1, aligned_face.rows-1);
|
||||
LandmarkDetector::PAW paw(destination_landmarks, triangulation, 0, 0, aligned_face.cols-1, aligned_face.rows-1);
|
||||
|
||||
// Mask each of the channels (a bit of a roundabout way, but OpenCV 3.1 in debug mode doesn't seem to be able to handle a more direct way using split and merge)
|
||||
vector<cv::Mat> aligned_face_channels(aligned_face.channels());
|
||||
|
||||
@@ -1,514 +0,0 @@
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
|
||||
// all rights reserved.
|
||||
//
|
||||
// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
|
||||
//
|
||||
// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
|
||||
// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
|
||||
//
|
||||
// License can be found in OpenFace-license.txt
|
||||
//
|
||||
// * Any publications arising from the use of this software, including but
|
||||
// not limited to academic journal and conference publications, technical
|
||||
// reports and manuals, must cite at least one of the following works:
|
||||
//
|
||||
// OpenFace: an open source facial behavior analysis toolkit
|
||||
// Tadas Baltru<72>aitis, Peter Robinson, and Louis-Philippe Morency
|
||||
// in IEEE Winter Conference on Applications of Computer Vision, 2016
|
||||
//
|
||||
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
|
||||
// Erroll Wood, Tadas Baltru<72>aitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
|
||||
// in IEEE International. Conference on Computer Vision (ICCV), 2015
|
||||
//
|
||||
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
|
||||
// Tadas Baltru<72>aitis, Marwa Mahmoud, and Peter Robinson
|
||||
// in Facial Expression Recognition and Analysis Challenge,
|
||||
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
|
||||
//
|
||||
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
|
||||
// Tadas Baltru<72>aitis, Peter Robinson, and Louis-Philippe Morency.
|
||||
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
|
||||
//
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
|
||||
#include "PAW.h"
|
||||
|
||||
// OpenCV includes
|
||||
#include <opencv2/core/core.hpp>
|
||||
#include <opencv2/imgproc.hpp>
|
||||
|
||||
#include "Face_utils.h"
|
||||
|
||||
using namespace FaceAnalysis;
|
||||
|
||||
// Copy constructor
|
||||
PAW::PAW(const PAW& other) : destination_landmarks(other.destination_landmarks.clone()), source_landmarks(other.source_landmarks.clone()), triangulation(other.triangulation.clone()),
|
||||
triangle_id(other.triangle_id.clone()), pixel_mask(other.pixel_mask.clone()), coefficients(other.coefficients.clone()), alpha(other.alpha.clone()), beta(other.beta.clone()), map_x(other.map_x.clone()), map_y(other.map_y.clone())
|
||||
{
|
||||
this->number_of_pixels = other.number_of_pixels;
|
||||
this->min_x = other.min_x;
|
||||
this->min_y = other.min_y;
|
||||
}
|
||||
|
||||
// A constructor from destination shape and triangulation
|
||||
PAW::PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation)
|
||||
{
|
||||
// Initialise some variables directly
|
||||
this->destination_landmarks = destination_shape;
|
||||
this->triangulation = triangulation;
|
||||
|
||||
int num_points = destination_shape.rows/2;
|
||||
|
||||
int num_tris = triangulation.rows;
|
||||
|
||||
// Pre-compute the rest
|
||||
alpha = cv::Mat_<float>(num_tris, 3);
|
||||
beta = cv::Mat_<float>(num_tris, 3);
|
||||
|
||||
cv::Mat_<float> xs = destination_shape(cv::Rect(0, 0, 1, num_points));
|
||||
cv::Mat_<float> ys = destination_shape(cv::Rect(0, num_points, 1, num_points));
|
||||
|
||||
// Create a vector representation of the control points
|
||||
std::vector<std::vector<float>> destination_points;
|
||||
|
||||
for (int tri = 0; tri < num_tris; ++tri)
|
||||
{
|
||||
int j = triangulation.at<int>(tri, 0);
|
||||
int k = triangulation.at<int>(tri, 1);
|
||||
int l = triangulation.at<int>(tri, 2);
|
||||
|
||||
float c1 = ys.at<float>(l) - ys.at<float>(j);
|
||||
float c2 = xs.at<float>(l) - xs.at<float>(j);
|
||||
float c4 = ys.at<float>(k) - ys.at<float>(j);
|
||||
float c3 = xs.at<float>(k) - xs.at<float>(j);
|
||||
|
||||
float c5 = c3*c1 - c2*c4;
|
||||
|
||||
alpha.at<float>(tri, 0) = (ys.at<float>(j) * c2 - xs.at<float>(j) * c1) / c5;
|
||||
alpha.at<float>(tri, 1) = c1/c5;
|
||||
alpha.at<float>(tri, 2) = -c2/c5;
|
||||
|
||||
beta.at<float>(tri, 0) = (xs.at<float>(j) * c4 - ys.at<float>(j) * c3)/c5;
|
||||
beta.at<float>(tri, 1) = -c4/c5;
|
||||
beta.at<float>(tri, 2) = c3/c5;
|
||||
|
||||
// Add points corresponding to triangles as optimisation
|
||||
std::vector<float> triangle_points(10);
|
||||
|
||||
triangle_points[0] = xs.at<float>(j);
|
||||
triangle_points[1] = ys.at<float>(j);
|
||||
triangle_points[2] = xs.at<float>(k);
|
||||
triangle_points[3] = ys.at<float>(k);
|
||||
triangle_points[4] = xs.at<float>(l);
|
||||
triangle_points[5] = ys.at<float>(l);
|
||||
|
||||
cv::Vec3f xs_three(triangle_points[0], triangle_points[2], triangle_points[4]);
|
||||
cv::Vec3f ys_three(triangle_points[1], triangle_points[3], triangle_points[5]);
|
||||
|
||||
double min_x, max_x, min_y, max_y;
|
||||
cv::minMaxIdx(xs_three, &min_x, &max_x);
|
||||
cv::minMaxIdx(ys_three, &min_y, &max_y);
|
||||
|
||||
triangle_points[6] = (float) max_x;
|
||||
triangle_points[7] = (float) max_y;
|
||||
|
||||
triangle_points[8] = (float) min_x;
|
||||
triangle_points[9] = (float) min_y;
|
||||
|
||||
destination_points.push_back(triangle_points);
|
||||
|
||||
}
|
||||
|
||||
double max_x;
|
||||
double max_y;
|
||||
double min_x_d;
|
||||
double min_y_d;
|
||||
|
||||
minMaxLoc(xs, &min_x_d, &max_x);
|
||||
minMaxLoc(ys, &min_y_d, &max_y);
|
||||
|
||||
min_x = min_x_d;
|
||||
min_y = min_y_d;
|
||||
|
||||
int w = (int)(max_x - min_x + 1.5);
|
||||
int h = (int)(max_y - min_y + 1.5);
|
||||
|
||||
// Round the min_x and min_y for simplicity?
|
||||
|
||||
pixel_mask = cv::Mat_<uchar>(h, w, (uchar)0);
|
||||
triangle_id = cv::Mat_<int>(h, w, -1);
|
||||
|
||||
int curr_tri = -1;
|
||||
|
||||
for(int y = 0; y < pixel_mask.rows; y++)
|
||||
{
|
||||
for(int x = 0; x < pixel_mask.cols; x++)
|
||||
{
|
||||
curr_tri = findTriangle(cv::Point_<float>(x + min_x, y + min_y), destination_points, curr_tri);
|
||||
// If there is a triangle at this location
|
||||
if(curr_tri != -1)
|
||||
{
|
||||
triangle_id.at<int>(y, x) = curr_tri;
|
||||
pixel_mask.at<uchar>(y, x) = 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Preallocate maps and coefficients
|
||||
coefficients.create(num_tris, 6);
|
||||
map_x.create(pixel_mask.rows,pixel_mask.cols);
|
||||
map_y.create(pixel_mask.rows,pixel_mask.cols);
|
||||
|
||||
|
||||
}
|
||||
|
||||
// Manually define min and max values
|
||||
PAW::PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation, float in_min_x, float in_min_y, float in_max_x, float in_max_y)
|
||||
{
|
||||
// Initialise some variables directly
|
||||
this->destination_landmarks = destination_shape;
|
||||
this->triangulation = triangulation;
|
||||
|
||||
int num_points = destination_shape.rows/2;
|
||||
|
||||
int num_tris = triangulation.rows;
|
||||
|
||||
// Pre-compute the rest
|
||||
alpha = cv::Mat_<float>(num_tris, 3);
|
||||
beta = cv::Mat_<float>(num_tris, 3);
|
||||
|
||||
cv::Mat_<float> xs = destination_shape(cv::Rect(0, 0, 1, num_points));
|
||||
cv::Mat_<float> ys = destination_shape(cv::Rect(0, num_points, 1, num_points));
|
||||
|
||||
// Create a vector representation of the control points
|
||||
std::vector<std::vector<float>> destination_points;
|
||||
|
||||
for (int tri = 0; tri < num_tris; ++tri)
|
||||
{
|
||||
int j = triangulation.at<int>(tri, 0);
|
||||
int k = triangulation.at<int>(tri, 1);
|
||||
int l = triangulation.at<int>(tri, 2);
|
||||
|
||||
float c1 = ys.at<float>(l) - ys.at<float>(j);
|
||||
float c2 = xs.at<float>(l) - xs.at<float>(j);
|
||||
float c4 = ys.at<float>(k) - ys.at<float>(j);
|
||||
float c3 = xs.at<float>(k) - xs.at<float>(j);
|
||||
|
||||
float c5 = c3*c1 - c2*c4;
|
||||
|
||||
alpha.at<float>(tri, 0) = (ys.at<float>(j) * c2 - xs.at<float>(j) * c1) / c5;
|
||||
alpha.at<float>(tri, 1) = c1/c5;
|
||||
alpha.at<float>(tri, 2) = -c2/c5;
|
||||
|
||||
beta.at<float>(tri, 0) = (xs.at<float>(j) * c4 - ys.at<float>(j) * c3)/c5;
|
||||
beta.at<float>(tri, 1) = -c4/c5;
|
||||
beta.at<float>(tri, 2) = c3/c5;
|
||||
|
||||
// Add points corresponding to triangles as optimisation
|
||||
std::vector<float> triangle_points(10);
|
||||
|
||||
triangle_points[0] = xs.at<float>(j);
|
||||
triangle_points[1] = ys.at<float>(j);
|
||||
triangle_points[2] = xs.at<float>(k);
|
||||
triangle_points[3] = ys.at<float>(k);
|
||||
triangle_points[4] = xs.at<float>(l);
|
||||
triangle_points[5] = ys.at<float>(l);
|
||||
|
||||
cv::Vec3f xs_three(triangle_points[0], triangle_points[2], triangle_points[4]);
|
||||
cv::Vec3f ys_three(triangle_points[1], triangle_points[3], triangle_points[5]);
|
||||
|
||||
double min_x, max_x, min_y, max_y;
|
||||
cv::minMaxIdx(xs_three, &min_x, &max_x);
|
||||
cv::minMaxIdx(ys_three, &min_y, &max_y);
|
||||
|
||||
triangle_points[6] = (float)max_x;
|
||||
triangle_points[7] = (float)max_y;
|
||||
|
||||
triangle_points[8] = (float)min_x;
|
||||
triangle_points[9] = (float)min_y;
|
||||
|
||||
destination_points.push_back(triangle_points);
|
||||
|
||||
}
|
||||
|
||||
float max_x;
|
||||
float max_y;
|
||||
|
||||
min_x = in_min_x;
|
||||
min_y = in_min_y;
|
||||
|
||||
max_x = in_max_x;
|
||||
max_y = in_max_y;
|
||||
|
||||
int w = (int)(max_x - min_x + 1.5);
|
||||
int h = (int)(max_y - min_y + 1.5);
|
||||
|
||||
// Round the min_x and min_y for simplicity?
|
||||
|
||||
pixel_mask = cv::Mat_<uchar>(h, w, (uchar)0);
|
||||
triangle_id = cv::Mat_<int>(h, w, -1);
|
||||
|
||||
int curr_tri = -1;
|
||||
|
||||
for(int y = 0; y < pixel_mask.rows; y++)
|
||||
{
|
||||
for(int x = 0; x < pixel_mask.cols; x++)
|
||||
{
|
||||
curr_tri = findTriangle(cv::Point_<float>(x + min_x, y + min_y), destination_points, curr_tri);
|
||||
// If there is a triangle at this location
|
||||
if(curr_tri != -1)
|
||||
{
|
||||
triangle_id.at<int>(y, x) = curr_tri;
|
||||
pixel_mask.at<uchar>(y, x) = 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Preallocate maps and coefficients
|
||||
coefficients.create(num_tris, 6);
|
||||
map_x.create(pixel_mask.rows,pixel_mask.cols);
|
||||
map_y.create(pixel_mask.rows,pixel_mask.cols);
|
||||
|
||||
}
|
||||
|
||||
//===========================================================================
|
||||
void PAW::Read(std::ifstream& stream)
|
||||
{
|
||||
|
||||
stream.read ((char*)&number_of_pixels, 4);
|
||||
double min_x_d, min_y_d;
|
||||
stream.read ((char*)&min_x_d, 8);
|
||||
stream.read ((char*)&min_y_d, 8);
|
||||
min_x = (float)min_x_d;
|
||||
min_y = (float)min_y_d;
|
||||
|
||||
cv::Mat_<double> destination_landmarks_d;
|
||||
ReadMatBin(stream, destination_landmarks_d);
|
||||
destination_landmarks_d.convertTo(destination_landmarks, CV_32F);
|
||||
|
||||
ReadMatBin(stream, triangulation);
|
||||
|
||||
ReadMatBin(stream, triangle_id);
|
||||
|
||||
cv::Mat tmpMask;
|
||||
ReadMatBin(stream, tmpMask);
|
||||
tmpMask.convertTo(pixel_mask, CV_8U);
|
||||
|
||||
cv::Mat_<double> alpha_d;
|
||||
ReadMatBin(stream, alpha_d);
|
||||
alpha_d.convertTo(alpha, CV_32F);
|
||||
|
||||
cv::Mat_<double> beta_d;
|
||||
ReadMatBin(stream, beta_d);
|
||||
beta_d.convertTo(beta, CV_32F);
|
||||
|
||||
map_x.create(pixel_mask.rows,pixel_mask.cols);
|
||||
map_y.create(pixel_mask.rows,pixel_mask.cols);
|
||||
|
||||
coefficients.create(this->NumberOfTriangles(),6);
|
||||
|
||||
source_landmarks = destination_landmarks;
|
||||
}
|
||||
|
||||
//=============================================================================
|
||||
// cropping from the source image to the destination image using the shape in s, used to determine if shape fitting converged successfully
|
||||
void PAW::Warp(const cv::Mat& image_to_warp, cv::Mat& destination_image, const cv::Mat_<float>& landmarks_to_warp)
|
||||
{
|
||||
|
||||
// set the current shape
|
||||
source_landmarks = landmarks_to_warp.clone();
|
||||
|
||||
// prepare the mapping coefficients using the current shape
|
||||
this->CalcCoeff();
|
||||
|
||||
// Do the actual mapping computation (where to warp from)
|
||||
this->WarpRegion(map_x, map_y);
|
||||
|
||||
// Do the actual warp (with bi-linear interpolation)
|
||||
remap(image_to_warp, destination_image, map_x, map_y, CV_INTER_LINEAR);
|
||||
|
||||
}
|
||||
|
||||
|
||||
//=============================================================================
|
||||
// Calculate the warping coefficients
|
||||
void PAW::CalcCoeff()
|
||||
{
|
||||
int p = this->NumberOfLandmarks();
|
||||
|
||||
for(int l = 0; l < this->NumberOfTriangles(); l++)
|
||||
{
|
||||
|
||||
int i = triangulation.at<int>(l,0);
|
||||
int j = triangulation.at<int>(l,1);
|
||||
int k = triangulation.at<int>(l,2);
|
||||
|
||||
float c1 = source_landmarks.at<float>(i , 0);
|
||||
float c2 = source_landmarks.at<float>(j , 0) - c1;
|
||||
float c3 = source_landmarks.at<float>(k , 0) - c1;
|
||||
float c4 = source_landmarks.at<float>(i + p, 0);
|
||||
float c5 = source_landmarks.at<float>(j + p, 0) - c4;
|
||||
float c6 = source_landmarks.at<float>(k + p, 0) - c4;
|
||||
|
||||
// Get a pointer to the coefficient we will be precomputing
|
||||
float *coeff = coefficients.ptr<float>(l);
|
||||
|
||||
// Extract the relevant alphas and betas
|
||||
float *c_alpha = alpha.ptr<float>(l);
|
||||
float *c_beta = beta.ptr<float>(l);
|
||||
|
||||
coeff[0] = c1 + c2 * c_alpha[0] + c3 * c_beta[0];
|
||||
coeff[1] = c2 * c_alpha[1] + c3 * c_beta[1];
|
||||
coeff[2] = c2 * c_alpha[2] + c3 * c_beta[2];
|
||||
coeff[3] = c4 + c5 * c_alpha[0] + c6 * c_beta[0];
|
||||
coeff[4] = c5 * c_alpha[1] + c6 * c_beta[1];
|
||||
coeff[5] = c5 * c_alpha[2] + c6 * c_beta[2];
|
||||
}
|
||||
}
|
||||
|
||||
//======================================================================
|
||||
// Compute the mapping coefficients
|
||||
void PAW::WarpRegion(cv::Mat_<float>& mapx, cv::Mat_<float>& mapy)
|
||||
{
|
||||
|
||||
cv::MatIterator_<float> xp = mapx.begin();
|
||||
cv::MatIterator_<float> yp = mapy.begin();
|
||||
cv::MatIterator_<uchar> mp = pixel_mask.begin();
|
||||
cv::MatIterator_<int> tp = triangle_id.begin();
|
||||
|
||||
// The coefficients corresponding to the current triangle
|
||||
float * a;
|
||||
|
||||
// Current triangle being processed
|
||||
int k=-1;
|
||||
|
||||
for(int y = 0; y < pixel_mask.rows; y++)
|
||||
{
|
||||
float yi = float(y) + min_y;
|
||||
|
||||
for(int x = 0; x < pixel_mask.cols; x++)
|
||||
{
|
||||
float xi = float(x) + min_x;
|
||||
|
||||
if(*mp == 0)
|
||||
{
|
||||
*xp = -1;
|
||||
*yp = -1;
|
||||
}
|
||||
else
|
||||
{
|
||||
// triangle corresponding to the current pixel
|
||||
int j = *tp;
|
||||
|
||||
// If it is different from the previous triangle point to new coefficients
|
||||
// This will always be the case in the first iteration, hence a will not point to nothing
|
||||
if(j != k)
|
||||
{
|
||||
// Update the coefficient pointer if a new triangle is being processed
|
||||
a = coefficients.ptr<float>(j);
|
||||
k = j;
|
||||
}
|
||||
|
||||
//ap is now the pointer to the coefficients
|
||||
float *ap = a;
|
||||
|
||||
//look at the first coefficient (and increment). first coefficient is an x offset
|
||||
float xo = *ap++;
|
||||
//second coefficient is an x scale as a function of x
|
||||
xo += *ap++ * xi;
|
||||
//third coefficient ap(2) is an x scale as a function of y
|
||||
*xp = float(xo + *ap++ * yi);
|
||||
|
||||
//then fourth coefficient ap(3) is a y offset
|
||||
float yo = *ap++;
|
||||
//fifth coeff adds coeff[4]*x to y
|
||||
yo += *ap++ * xi;
|
||||
//final coeff adds coeff[5]*y to y
|
||||
*yp = float(yo + *ap++ * yi);
|
||||
|
||||
}
|
||||
mp++; tp++; xp++; yp++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ============================================================
|
||||
// Helper functions to determine which point a triangle lies in
|
||||
// ============================================================
|
||||
|
||||
// Is the point (x0,y0) on same side as a half-plane defined by (x1,y1), (x2, y2), and (x3, y3)
|
||||
bool PAW::sameSide(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
{
|
||||
|
||||
float x = (x3-x2)*(y0-y2) - (x0-x2)*(y3-y2);
|
||||
float y = (x3-x2)*(y1-y2) - (x1-x2)*(y3-y2);
|
||||
|
||||
return x*y >= 0;
|
||||
|
||||
}
|
||||
|
||||
// if point (x0, y0) is on same side for all three half-planes it is in a triangle
|
||||
bool PAW::pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
{
|
||||
bool same_1 = sameSide(x0, y0, x1, y1, x2, y2, x3, y3);
|
||||
bool same_2 = sameSide(x0, y0, x2, y2, x1, y1, x3, y3);
|
||||
bool same_3 = sameSide(x0, y0, x3, y3, x1, y1, x2, y2);
|
||||
|
||||
return same_1 && same_2 && same_3;
|
||||
|
||||
}
|
||||
|
||||
// Find if a given point lies in the triangles
|
||||
int PAW::findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess)
|
||||
{
|
||||
|
||||
int num_tris = control_points.size();
|
||||
|
||||
int tri = -1;
|
||||
|
||||
float x0 = point.x;
|
||||
float y0 = point.y;
|
||||
|
||||
// Allow a guess for speed (so as not to go through all triangles)
|
||||
if(guess != -1)
|
||||
{
|
||||
|
||||
bool in_triangle = pointInTriangle(x0, y0, control_points[guess][0], control_points[guess][1], control_points[guess][2], control_points[guess][3], control_points[guess][4], control_points[guess][5]);
|
||||
if(in_triangle)
|
||||
{
|
||||
return guess;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
for (int i = 0; i < num_tris; ++i)
|
||||
{
|
||||
|
||||
float max_x = control_points[i][6];
|
||||
float max_y = control_points[i][7];
|
||||
|
||||
float min_x = control_points[i][8];
|
||||
float min_y = control_points[i][9];
|
||||
|
||||
// Skip the check if the point is outside the bounding box of the triangle
|
||||
|
||||
if( max_x < x0 || min_x > x0 || max_y < y0 || min_y > y0)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
bool in_triangle = pointInTriangle(x0, y0,
|
||||
control_points[i][0], control_points[i][1],
|
||||
control_points[i][2], control_points[i][3],
|
||||
control_points[i][4], control_points[i][5]);
|
||||
|
||||
if(in_triangle)
|
||||
{
|
||||
tri = i;
|
||||
break;
|
||||
}
|
||||
}
|
||||
return tri;
|
||||
}
|
||||
@@ -50,86 +50,89 @@ namespace LandmarkDetector
|
||||
The code is based on the CLM tracker by Jason Saragih et al.
|
||||
*/
|
||||
|
||||
class PAW{
|
||||
public:
|
||||
// Number of pixels after the warping to neutral shape
|
||||
int number_of_pixels;
|
||||
class PAW {
|
||||
public:
|
||||
// Number of pixels after the warping to neutral shape
|
||||
int number_of_pixels;
|
||||
|
||||
// Minimum x coordinate in destination
|
||||
float min_x;
|
||||
// Minimum x coordinate in destination
|
||||
float min_x;
|
||||
|
||||
// minimum y coordinate in destination
|
||||
float min_y;
|
||||
// minimum y coordinate in destination
|
||||
float min_y;
|
||||
|
||||
// Destination points (landmarks to be warped to)
|
||||
cv::Mat_<float> destination_landmarks;
|
||||
// Destination points (landmarks to be warped to)
|
||||
cv::Mat_<float> destination_landmarks;
|
||||
|
||||
// Destination points (landmarks to be warped from)
|
||||
cv::Mat_<float> source_landmarks;
|
||||
// Destination points (landmarks to be warped from)
|
||||
cv::Mat_<float> source_landmarks;
|
||||
|
||||
// Triangulation, each triangle is warped using an affine transform
|
||||
cv::Mat_<int> triangulation;
|
||||
// Triangulation, each triangle is warped using an affine transform
|
||||
cv::Mat_<int> triangulation;
|
||||
|
||||
// Triangle index, indicating which triangle each of destination pixels lies in
|
||||
cv::Mat_<int> triangle_id;
|
||||
// Triangle index, indicating which triangle each of destination pixels lies in
|
||||
cv::Mat_<int> triangle_id;
|
||||
|
||||
// Indicating if the destination warped pixels is valid (lies within a face)
|
||||
cv::Mat_<uchar> pixel_mask;
|
||||
// Indicating if the destination warped pixels is valid (lies within a face)
|
||||
cv::Mat_<uchar> pixel_mask;
|
||||
|
||||
// A number of precomputed coefficients that are helpful for quick warping
|
||||
|
||||
// affine coefficients for all triangles (see Matthews and Baker 2004)
|
||||
// 6 coefficients for each triangle (are computed from alpha and beta)
|
||||
// This is computed during each warp based on source landmarks
|
||||
cv::Mat_<float> coefficients;
|
||||
// A number of precomputed coefficients that are helpful for quick warping
|
||||
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> alpha;
|
||||
// affine coefficients for all triangles (see Matthews and Baker 2004)
|
||||
// 6 coefficients for each triangle (are computed from alpha and beta)
|
||||
// This is computed during each warp based on source landmarks
|
||||
cv::Mat_<float> coefficients;
|
||||
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> beta;
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> alpha;
|
||||
|
||||
// x-source of warped points
|
||||
cv::Mat_<float> map_x;
|
||||
// matrix of (c,x,y) coeffs for alpha
|
||||
cv::Mat_<float> beta;
|
||||
|
||||
// y-source of warped points
|
||||
cv::Mat_<float> map_y;
|
||||
// x-source of warped points
|
||||
cv::Mat_<float> map_x;
|
||||
|
||||
// Default constructor
|
||||
PAW(){;}
|
||||
// y-source of warped points
|
||||
cv::Mat_<float> map_y;
|
||||
|
||||
// Construct a warp from a destination shape and triangulation
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation);
|
||||
// Default constructor
|
||||
PAW() { ; }
|
||||
|
||||
// The final optional argument allows for optimisation if the triangle indices from previous frame are known (for tracking in video)
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation, float in_min_x, float in_min_y, float in_max_x, float in_max_y);
|
||||
// Construct a warp from a destination shape and triangulation
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation);
|
||||
|
||||
// Copy constructor
|
||||
PAW(const PAW& other);
|
||||
// The final optional argument allows for optimisation if the triangle indices from previous frame are known (for tracking in video)
|
||||
PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation, float in_min_x, float in_min_y, float in_max_x, float in_max_y);
|
||||
|
||||
void Read(std::ifstream &s);
|
||||
// Copy constructor
|
||||
PAW(const PAW& other);
|
||||
|
||||
// The actual warping
|
||||
void Warp(const cv::Mat& image_to_warp, cv::Mat& destination_image, const cv::Mat_<float>& landmarks_to_warp);
|
||||
|
||||
// Compute coefficients needed for warping
|
||||
void CalcCoeff();
|
||||
void Read(std::ifstream &s);
|
||||
|
||||
// Perform the actual warping
|
||||
void WarpRegion(cv::Mat_<float>& map_x, cv::Mat_<float>& map_y);
|
||||
// The actual warping
|
||||
void Warp(const cv::Mat& image_to_warp, cv::Mat& destination_image, const cv::Mat_<float>& landmarks_to_warp);
|
||||
|
||||
inline int NumberOfLandmarks() const {return destination_landmarks.rows/2;} ;
|
||||
inline int NumberOfTriangles() const {return triangulation.rows;} ;
|
||||
// Compute coefficients needed for warping
|
||||
void CalcCoeff();
|
||||
|
||||
// The width and height of the warped image
|
||||
inline int constWidth() const {return pixel_mask.cols;}
|
||||
inline int Height() const {return pixel_mask.rows;}
|
||||
|
||||
private:
|
||||
// Perform the actual warping
|
||||
void WarpRegion(cv::Mat_<float>& map_x, cv::Mat_<float>& map_y);
|
||||
|
||||
int findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess = -1) const;
|
||||
inline int NumberOfLandmarks() const { return destination_landmarks.rows / 2; };
|
||||
inline int NumberOfTriangles() const { return triangulation.rows; };
|
||||
|
||||
};
|
||||
//===========================================================================
|
||||
// The width and height of the warped image
|
||||
inline int constWidth() const { return pixel_mask.cols; }
|
||||
inline int Height() const { return pixel_mask.rows; }
|
||||
|
||||
private:
|
||||
|
||||
// Helper functions for dealing with triangles
|
||||
static bool sameSide(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3);
|
||||
static bool pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3);
|
||||
static int findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess = -1);
|
||||
|
||||
};
|
||||
//===========================================================================
|
||||
}
|
||||
#endif
|
||||
|
||||
@@ -165,7 +165,6 @@ PAW::PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangul
|
||||
|
||||
}
|
||||
|
||||
|
||||
// Manually define min and max values
|
||||
PAW::PAW(const cv::Mat_<float>& destination_shape, const cv::Mat_<int>& triangulation, float in_min_x, float in_min_y, float in_max_x, float in_max_y)
|
||||
{
|
||||
@@ -287,23 +286,23 @@ void PAW::Read(std::ifstream& stream)
|
||||
min_y = (float)min_y_d;
|
||||
|
||||
cv::Mat_<double> destination_landmarks_d;
|
||||
LandmarkDetector::ReadMatBin(stream, destination_landmarks_d);
|
||||
ReadMatBin(stream, destination_landmarks_d);
|
||||
destination_landmarks_d.convertTo(destination_landmarks, CV_32F);
|
||||
|
||||
LandmarkDetector::ReadMatBin(stream, triangulation);
|
||||
ReadMatBin(stream, triangulation);
|
||||
|
||||
LandmarkDetector::ReadMatBin(stream, triangle_id);
|
||||
ReadMatBin(stream, triangle_id);
|
||||
|
||||
cv::Mat tmpMask;
|
||||
LandmarkDetector::ReadMatBin(stream, tmpMask);
|
||||
ReadMatBin(stream, tmpMask);
|
||||
tmpMask.convertTo(pixel_mask, CV_8U);
|
||||
|
||||
cv::Mat_<double> alpha_d;
|
||||
LandmarkDetector::ReadMatBin(stream, alpha_d);
|
||||
ReadMatBin(stream, alpha_d);
|
||||
alpha_d.convertTo(alpha, CV_32F);
|
||||
|
||||
cv::Mat_<double> beta_d;
|
||||
LandmarkDetector::ReadMatBin(stream, beta_d);
|
||||
ReadMatBin(stream, beta_d);
|
||||
beta_d.convertTo(beta, CV_32F);
|
||||
|
||||
map_x.create(pixel_mask.rows, pixel_mask.cols);
|
||||
@@ -441,18 +440,18 @@ void PAW::WarpRegion(cv::Mat_<float>& mapx, cv::Mat_<float>& mapy)
|
||||
// ============================================================
|
||||
|
||||
// Is the point (x0,y0) on same side as a half-plane defined by (x1,y1), (x2, y2), and (x3, y3)
|
||||
bool sameSide(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
bool PAW::sameSide(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
{
|
||||
|
||||
float x = (x3-x2)*(y0-y2) - (x0-x2)*(y3-y2);
|
||||
float y = (x3-x2)*(y1-y2) - (x1-x2)*(y3-y2);
|
||||
|
||||
return x*y >= 0;
|
||||
float x = (x3 - x2)*(y0 - y2) - (x0 - x2)*(y3 - y2);
|
||||
float y = (x3 - x2)*(y1 - y2) - (x1 - x2)*(y3 - y2);
|
||||
|
||||
return x*y >= 0;
|
||||
|
||||
}
|
||||
|
||||
// if point (x0, y0) is on same side for all three half-planes it is in a triangle
|
||||
bool pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
bool PAW::pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2, float x3, float y3)
|
||||
{
|
||||
bool same_1 = sameSide(x0, y0, x1, y1, x2, y2, x3, y3);
|
||||
bool same_2 = sameSide(x0, y0, x2, y2, x1, y1, x3, y3);
|
||||
@@ -463,7 +462,7 @@ bool pointInTriangle(float x0, float y0, float x1, float y1, float x2, float y2,
|
||||
}
|
||||
|
||||
// Find if a given point lies in the triangles
|
||||
int PAW::findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess) const
|
||||
int PAW::findTriangle(const cv::Point_<float>& point, const std::vector<std::vector<float>>& control_points, int guess)
|
||||
{
|
||||
|
||||
int num_tris = control_points.size();
|
||||
|
||||
@@ -40,7 +40,7 @@ verbose = true;
|
||||
for img=1:numel(images)
|
||||
image_orig = imread([root_dir images(img).name]);
|
||||
|
||||
% Face detectiopn
|
||||
% Face detection
|
||||
[bboxs] = detect_faces(image_orig, 'mtcnn');
|
||||
|
||||
% If MTCNN detector not available, can use the cascaded regression one
|
||||
|
||||
@@ -14,17 +14,14 @@ verbose = true;
|
||||
record = true;
|
||||
|
||||
%% loading the patch experts
|
||||
[clmParams, pdm] = Load_CLM_params_vid();
|
||||
% Default OpenFace landmark model, using CE-CLM patch experts
|
||||
[patches, pdm, clmParams, early_term_params] = Load_CECLM_general();
|
||||
|
||||
% An accurate CCNF (or CLNF) model
|
||||
[patches] = Load_Patch_Experts( '../models/general/', 'ccnf_patches_*_general.mat', [], [], clmParams);
|
||||
% A simpler (but less accurate SVR)
|
||||
% [patches] = Load_Patch_Experts( '../models/wild/', 'svr_patches_*_wild.mat', [], [], clmParams);
|
||||
% faster but less accurate
|
||||
%[patches, pdm, clmParams] = Load_CLNF_general();
|
||||
|
||||
% A general SVR
|
||||
% [patches] = Load_Patch_Experts( '../models/general/', 'svr_patches_*_general.mat', [], [], clmParams);
|
||||
|
||||
clmParams.multi_modal_types = patches(1).multi_modal_types;
|
||||
% even faster but even less accurate
|
||||
%[patches, pdm, clmParams] = Load_CLM_general();
|
||||
|
||||
% load the face validator and add its dependency
|
||||
load('../face_validation/trained/faceCheckers.mat', 'faceCheckers');
|
||||
@@ -72,12 +69,11 @@ for v=1:numel(vids)
|
||||
image_orig = read(vr, i);
|
||||
if((~det && mod(i,4) == 0) || ~initialised)
|
||||
|
||||
[bboxs, det_shapes, confidences] = detect_face_mtcnn(image_orig);
|
||||
% First attempt to use the Matlab one (fastest but not as accurate, if not present use yu et al.)
|
||||
% [bboxs, det_shapes] = detect_faces(image_orig, {'cascade', 'yu'});
|
||||
% Zhu and Ramanan and Yu et al. are slower, but also more accurate
|
||||
% and can be used when vision toolbox is unavailable
|
||||
% [bboxs, det_shapes] = detect_faces(image_orig, {'yu', 'zhu'});
|
||||
% Face detection
|
||||
[bboxs] = detect_faces(image_orig, 'mtcnn');
|
||||
|
||||
% If MTCNN detector not available, can use the cascaded regression one
|
||||
% [bboxs] = detect_faces(image_orig, 'cascade');
|
||||
|
||||
if(~isempty(bboxs))
|
||||
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
function setup(varargin)
|
||||
|
||||
run vlfeat-0.9.20/toolbox/vl_setup ;
|
||||
run D:\soft\matconvnet-master\matconvnet-master\matlab/vl_setupnn ;
|
||||
addpath D:\soft\matconvnet-master\matconvnet-master\examples ;
|
||||
%run vlfeat-0.9.20/toolbox/vl_setup ;
|
||||
run C:\matconvnet\matconvnet-1.0-beta25\matlab/vl_setupnn ;
|
||||
addpath C:\matconvnet\matconvnet-1.0-beta25\examples ;
|
||||
|
||||
opts.useGpu = false ;
|
||||
opts.verbose = false ;
|
||||
|
||||
Reference in New Issue
Block a user