Changeset 89 for foam/trunk

Timestamp:

06/03/2009 10:01:22 AM (12 years ago)

Author:

dave

Message:

renamed faceident as it's not so simple these days

Location:

foam/trunk

Files:

• faceident (moved) (moved from foam/trunk/simple-faceident)
• faceident/CHANGES (copied) (copied from foam/trunk/simple-faceident/CHANGES)
• faceident/LICENCE (copied) (copied from foam/trunk/simple-faceident/LICENCE)
• faceident/Makefile (copied) (copied from foam/trunk/simple-faceident/Makefile)
• faceident/README (copied) (copied from foam/trunk/simple-faceident/README)
• faceident/haarcascade_frontalface_alt.xml (copied) (copied from foam/trunk/simple-faceident/haarcascade_frontalface_alt.xml)
• faceident/src (copied) (copied from foam/trunk/simple-faceident/src)
• vision/Makefile (modified) (1 diff)
• vision/src/Image.cpp (modified) (3 diffs)
• vision/src/Image.h (modified) (1 diff)
• vision/src/Matrix.h (modified) (4 diffs)
• vision/src/PCA.cpp (modified) (2 diffs)
• vision/src/PCA.h (modified) (2 diffs)
• vision/src/PCAClassifier.cpp (moved) (moved from foam/trunk/vision/src/PCASubspaceClassifier.cpp) (1 diff)
• vision/src/PCAClassifier.h (moved) (moved from foam/trunk/vision/src/PCASubspaceClassifier.h) (1 diff)
• vision/src/SVD.cpp (modified) (2 diffs)
• vision/src/main.cpp (modified) (3 diffs)

foam/trunk/vision/Makefile

@@ -5 +5 @@
         src/Rendering.cpp\
         src/Classifier.cpp\
-        src/PCASubspaceClassifier.cpp\
+        src/PCAClassifier.cpp\
         src/LDAClassifier.cpp\
         src/PCA.cpp\

foam/trunk/vision/src/Image.cpp

@@ -43 +43 @@
 }
 
-Image::Image(int w, int h, int c, const Vector<float> &v)
+Image::Image(int w, int h, int c, const Vector<float> &v, float gain)
 {
         m_Image=cvCreateImage(cvSize(w, h), 8, c);
@@ -54 +54 @@
                         for (int c=0; c<m_Image->nChannels; c++)
                         {
-                                s.val[c]=v[pos++]*256.0f;
+                                s.val[c]=(0.5+v[pos++]*gain)*127.0f;
                         }
                         cvSet2D(m_Image,y,x,s);
@@ -203 +203 @@
                                 y+py>0 && y+py<m_Image->height)
                         {
-                cvSet2D(m_Image,y+py,x+px,cvGet2D(image.m_Image,y,x));
+                if (image.m_Image->nChannels==1) 
+                                {
+                                        CvScalar v;
+                                        v.val[0]=cvGet2D(image.m_Image,y,x).val[0];
+                                        v.val[1]=cvGet2D(image.m_Image,y,x).val[0];
+                                        v.val[2]=cvGet2D(image.m_Image,y,x).val[0];
+                        cvSet2D(m_Image,y+py,x+px,v);
+                                }
+                                else 
+                                {
+                                        cvSet2D(m_Image,y+py,x+px,cvGet2D(image.m_Image,y,x));
+                                }
                         }
                 }

foam/trunk/vision/src/Image.h

@@ -29 +29 @@
         Image(const Image &other);
         Image(const IplImage *other); // copies the given image
-        Image(int w, int h, int c, const Vector<float> &v);
+        Image(int w, int h, int c, const Vector<float> &v, float gain=1.0f);
         ~Image();
 

foam/trunk/vision/src/Matrix.h

@@ -92 +92 @@
         Vector<T> GetRowVector(unsigned int r) const; 
         Vector<T> GetColVector(unsigned int c) const; 
+        void SetRowVector(unsigned int r, const Vector<T> &row);
+        void SetColVector(unsigned int c, const Vector<T> &col);
          
         void Print() const;
@@ -107 +109 @@
         Matrix &operator*=(const Matrix &other);
         
+        void SortRows(Vector<T> &v);
+        void SortCols(Vector<T> &v);
+
         static void RunTests();
         
@@ -303 +308 @@
 }
 
+
+//todo: use memcpy for these 4 functions
 template<class T>
 Vector<T> Matrix<T>::GetRowVector(unsigned int r) const
@@ -326 +333 @@
         return ret;
 }
+
+template<class T>
+void Matrix<T>::SetRowVector(unsigned int r, const Vector<T> &row)
+{
+        assert(r<m_Rows);
+        assert(row.Size()==m_Cols);
+        for (unsigned int j=0; j<m_Cols; j++)
+        {
+                (*this)[r][j]=row[j];
+        }
+}
+
+template<class T>
+void Matrix<T>::SetColVector(unsigned int c, const Vector<T> &col)
+{
+        assert(c<m_Cols);
+        assert(col.Size()==m_Rows);
+        for (unsigned int i=0; i<m_Rows; i++)
+        {
+                (*this)[i][c]=col[i];
+        }
+}
+
+// sort rows by v
+template<class T>
+void Matrix<T>::SortRows(Vector<T> &v)
+{
+        assert(v.Size()==m_Rows);
+        
+        bool sorted=false;
+        while(!sorted)
+        {
+                sorted=true;
+                
+                for (unsigned int i=0; i<v.Size()-1; i++)
+                {
+                        if (v[i]<v[i+1])
+                        {
+                                sorted=false;
+                                float vtmp = v[i];
+                                v[i]=v[i+1];
+                                v[i+1]=vtmp;
+                                
+                                Vector<float> rtmp = GetRowVector(i);
+                                SetRowVector(i,GetRowVector(i+1));
+                                SetRowVector(i+1,rtmp);
+                        }
+                }
+        }
+}
+
+// sort cols by v
+template<class T>
+void Matrix<T>::SortCols(Vector<T> &v)
+{
+        assert(v.Size()==m_Cols);
+        
+        bool sorted=false;
+        while(!sorted)
+        {
+                sorted=true;
+                
+                for (unsigned int i=0; i<v.Size()-1; i++)
+                {
+                        if (v[i]<v[i+1])
+                        {
+                                sorted=false;
+                                float vtmp = v[i];
+                                v[i]=v[i+1];
+                                v[i+1]=vtmp;
+                                
+                                Vector<float> rtmp = GetColVector(i);
+                                SetColVector(i,GetColVector(i+1));
+                                SetColVector(i+1,rtmp);
+                        }
+                }
+        }
+}
+
 
 template<class T>

foam/trunk/vision/src/PCA.cpp

@@ -39 +39 @@
         for (FeatureVec::iterator vi = m_Features.begin(); vi!=m_Features.end(); ++vi)
         {
-                cerr<<vi->IsInf()<<endl;
                 Mean+=*vi;
         }
@@ -53 +52 @@
         
         // allocate the transform matrix (this is where it'll run out of memory)
-        cerr<<"Allocating "<<m_FeatureSize*m_FeatureSize*sizeof(float)/1024/1024<<" megs for covariance matrix"<<endl;
+        cerr<<"Allocating "<<m_FeatureSize*m_FeatureSize*sizeof(float)/1024/1024.0<<" megs for covariance matrix"<<endl;
         m_EigenTransform = Matrix<float>(m_FeatureSize,m_FeatureSize);
         m_EigenTransform.Zero();

foam/trunk/vision/src/PCA.h

@@ -32 +32 @@
         PCA(unsigned int FeatureSize);
         ~PCA();
+        
+        typedef std::vector<Vector<float> > FeatureVec;
 
         void AddFeature(Vector<float> v) { m_Features.push_back(v); }
@@ -40 +42 @@
         const Vector<float> &GetEigenValues() { return m_EigenValues; }
         const Matrix<float> &GetEigenTransform() { return m_EigenTransform; }
-
+        const FeatureVec &GetFeatures() { return m_Features; }
+        
 private:        
 
         void CalcMean();
 
-        typedef std::vector<Vector<float> > FeatureVec;
 
         FeatureVec m_Features;

foam/trunk/vision/src/PCAClassifier.cpp

@@ -15 +15 @@
 // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
 
-#include "PCASubspaceClassifier.h"
+#include "PCAClassifier.h"
 
-PCASubspaceClassifier::PCASubspaceClassifier(unsigned int FeatureSize) :
+PCAClassifier::PCAClassifier(unsigned int FeatureSize) :
 Classifier(FeatureSize)
 {
 }
 
-PCASubspaceClassifier::~PCASubspaceClassifier()
+PCAClassifier::~PCAClassifier()
 {
 }

foam/trunk/vision/src/PCAClassifier.h

@@ -25 +25 @@
 #define FOAM_PCA_CLASSIFIER
 
-class PCASubspaceClassifier : public Classifier
+class PCAClassifier : public Classifier
 {
 public:
-        PCASubspaceClassifier(unsigned int FeatureSize);
-        ~PCASubspaceClassifier();
+        PCAClassifier(unsigned int FeatureSize);
+        ~PCAClassifier();
                 
 private:

foam/trunk/vision/src/SVD.cpp

@@ -57 +57 @@
 #include <stdlib.h>
 #include <math.h>
+#include <algorithm>
+#include <list>
 #include "SVD.h"
+
+using namespace std;
 
 #define SIGN(a, b) ((b) >= 0.0 ? fabs(a) : -fabs(a))
 #define MAX(x,y) ((x)>(y)?(x):(y))
 
-static double PYTHAG(double a, double b)
-{
-    double at = fabs(a), bt = fabs(b), ct, result;
-
-    if (at > bt)       { ct = bt / at; result = at * sqrt(1.0 + ct * ct); }
-    else if (bt > 0.0) { ct = at / bt; result = bt * sqrt(1.0 + ct * ct); }
-    else result = 0.0;
-    return(result);
-}
+///////////////////////////////////////////////////////
 
 Vector<float> SVD(Matrix<float> &m)
@@ -77 +73 @@
         Matrix<float> v(m.GetRows(),m.GetCols());
         dsvd(m, m.GetRows(), m.GetCols(), w.GetRawData(), v);
+        m.SortCols(w);
         return w;
+}
+
+///////////////////////////////////////////////////////
+
+static double PYTHAG(double a, double b)
+{
+    double at = fabs(a), bt = fabs(b), ct, result;
+
+    if (at > bt)       { ct = bt / at; result = at * sqrt(1.0 + ct * ct); }
+    else if (bt > 0.0) { ct = at / bt; result = bt * sqrt(1.0 + ct * ct); }
+    else result = 0.0;
+    return(result);
 }
 

foam/trunk/vision/src/main.cpp

@@ -23 +23 @@
 #include "Vector.h"
 #include "PCA.h"
+#include <glob.h>
 
 using namespace std;
@@ -32 +33 @@
 double scale = 1;
 
-PCA pca(Image("data/a-id0001-image0000.png").RGB2GRAY().NumElements());
-int tw=Image("data/a-id0001-image0000.png").RGB2GRAY().m_Image->width;
-int th=Image("data/a-id0001-image0000.png").RGB2GRAY().m_Image->height;
-int tc=Image("data/a-id0001-image0000.png").RGB2GRAY().m_Image->nChannels;
+Image ti("data/spot-1.png");
+PCA pca(ti.RGB2GRAY().Scale(30,40).NumElements());
 
 void TestPCA()
 {
-        pca.AddFeature(Image("data/a-id0001-image0000.png").RGB2GRAY().ToFloatVector());
-        pca.AddFeature(Image("data/a-id0001-image0001.png").RGB2GRAY().ToFloatVector());
-        pca.AddFeature(Image("data/a-id0002-image0000.png").RGB2GRAY().ToFloatVector());
-        pca.AddFeature(Image("data/a-id0002-image0001.png").RGB2GRAY().ToFloatVector());
-        cerr<<"pre calc"<<endl;
+        ti=ti.RGB2GRAY().Scale(30,40);
+        glob_t g;
+        glob("data/pca/*.png",GLOB_PERIOD,NULL,&g);
+        for (unsigned int n=0; n<g.gl_pathc; n++)
+        {
+                string path=g.gl_pathv[n];
+                cerr<<path<<endl;
+                Image im(path);
+                //im.SubMean();
+                pca.AddFeature(im.RGB2GRAY().Scale(30,40).ToFloatVector());
+        }
+        globfree (&g);
         pca.Calculate();
-        cerr<<"post calc"<<endl;
 }
 
@@ -259 +264 @@
         // PCA display
         
-        for (int i=0; i<10; i++)
-        {
-                camera.Blit(Image(tw,th,tc,pca.GetEigenTransform().GetRowVector(i)),i*50,100);
-        }
+        camera.Clear();
+
+        for (unsigned int i=0; i<pca.GetFeatures().size(); i++)
+        {
+                camera.Blit(Image(30,40,1,pca.GetFeatures()[i]),(i%20)*32,(i/20)*42);
+        }
+        
+        for (unsigned int i=0; i<pca.GetEigenTransform().GetCols(); i++)
+        {
+                camera.Blit(Image(30,40,1,pca.GetEigenTransform().GetColVector(i),5),(i%20)*32,200+(i/20)*42);
+        }
+        
+        pca.GetEigenValues().Print();
 
     cvShowImage("result", camera.m_Image);