//M*/
#include "cvtest.h"
-
-#if 0
-
-#include "highgui.h"
-#include <vector>
-#include <string>
-using namespace std;
+#include <fstream>
+#include <iostream>
using namespace cv;
+using namespace std;
+#define GET_RES 0
class CV_CalonderTest : public CvTest
{
public:
- CV_CalonderTest();
- ~CV_CalonderTest();
-protected:
+ CV_CalonderTest() : CvTest("CalonderDescriptorExtractor", "CalonderDescriptorExtractor::compute") {}
+protected:
void run(int);
-
-
- void cvmSet6(CvMat* m, int row, int col, float val1, float val2, float val3, float val4, float val5, float val6);
- void FindAffineTransform(const vector<CvPoint>& p1, const vector<CvPoint>& p2, CvMat* affine);
- void MapVectorAffine(const vector<CvPoint>& p1, vector<CvPoint>& p2, CvMat* transform);
- float CalcAffineReprojectionError(const vector<CvPoint>& p1, const vector<CvPoint>& p2, CvMat* transform);
- void ExtractFeatures(const IplImage* image, vector<CvPoint>& points);
- void TrainDetector(RTreeClassifier& detector, int/* patch_size*/, const vector<CvPoint>& train_points,const IplImage* train_image, int n_keypoints = 0);
- void GetCorrespondences(const RTreeClassifier& detector, int patch_size,
- const vector<CvPoint>& objectKeypoints, const vector<CvPoint>& imageKeypoints, const IplImage* image,
- vector<CvPoint>& object, vector<CvPoint>& features);
-
- // Scales the source image (x and y) and rotate to the angle (Positive values mean counter-clockwise rotation)
- void RotateAndScale(const IplImage* src, IplImage* dst, float angle, float scale_x, float scale_y);
- // Scales the source image point and rotate to the angle (Positive values mean counter-clockwise rotation)
- void RotateAndScale(const CvPoint& src, CvPoint& dst, const CvPoint& center, float angle, float scale_x, float scale_y);
- float RunTestsSeries(const IplImage* train_image, vector<CvPoint>& keypoints/*, bool drawResults = false*/);
- //returns 1 in the case of success, 0 otherwise
- int SaveKeypoints(const vector<CvPoint>& points, const char* path);
- ////returns 1 in the case of success, 0 otherwise
- int LoadKeypoints(vector<CvPoint>& points, const char* path);
-
- void ExtractKeypointSignatures(const IplImage* test_image, int patch_size, const RTreeClassifier& detector, const vector<CvPoint>& keypoints, vector<vector<float> >& signatures);
- //returns 1 in the case of success, 0 otherwise
- int SaveKeypointSignatures(const char* path, const vector<vector<float> >& signatures);
- //returns 1 in the case of success, 0 otherwise
- int LoadKeypointSignatures(const char* path, vector<vector<float> >& signatures);
-
- //returns 1 in the case signatures are identical, 0 otherwise
- int CompareSignatures(const vector<vector<float> > & signatures1, const vector<vector<float> >& signatures2);
-
-
};
-void CV_CalonderTest::cvmSet6(CvMat* m, int row, int col, float val1, float val2, float val3, float val4, float val5, float val6)
+void writeMatInBin( const Mat& mat, const string& filename )
{
- cvmSet(m, row, col, val1);
- cvmSet(m, row, col + 1, val2);
- cvmSet(m, row, col + 2, val3);
- cvmSet(m, row, col + 3, val4);
- cvmSet(m, row, col + 4, val5);
- cvmSet(m, row, col + 5, val6);
+ ofstream os( filename.c_str() );
+ int type = mat.type();
+ os.write( (char*)&mat.rows, sizeof(int) );
+ os.write( (char*)&mat.cols, sizeof(int) );
+ os.write( (char*)&type, sizeof(int) );
+ os.write( (char*)&mat.step, sizeof(int) );
+ os.write( (char*)mat.data, mat.step*mat.rows );
}
-void CV_CalonderTest::FindAffineTransform(const vector<CvPoint>& p1, const vector<CvPoint>& p2, CvMat* affine)
+Mat readMatFromBin( const string& filename )
{
- int eq_num = 2*(int)p1.size();
- CvMat* A = cvCreateMat(eq_num, 6, CV_32FC1);
- CvMat* B = cvCreateMat(eq_num, 1, CV_32FC1);
- CvMat* X = cvCreateMat(6, 1, CV_32FC1);
-
- for(int i = 0; i < (int)p1.size(); i++)
- {
- cvmSet6(A, 2*i, 0, (float)p1[i].x, (float)p1[i].y, 1, 0, 0, 0);
- cvmSet6(A, 2*i + 1, 0, 0, 0, 0, (float)p1[i].x, (float)p1[i].y, 1);
- cvmSet(B, 2*i, 0, (double)p2[i].x);
- cvmSet(B, 2*i + 1, 0, (double)p2[i].y);
- }
-
- cvSolve(A, B, X, CV_SVD);
-
- cvmSet(affine, 0, 0, cvmGet(X, 0, 0));
- cvmSet(affine, 0, 1, cvmGet(X, 1, 0));
- cvmSet(affine, 0, 2, cvmGet(X, 2, 0));
- cvmSet(affine, 1, 0, cvmGet(X, 3, 0));
- cvmSet(affine, 1, 1, cvmGet(X, 4, 0));
- cvmSet(affine, 1, 2, cvmGet(X, 5, 0));
-
- cvReleaseMat(&A);
- cvReleaseMat(&B);
- cvReleaseMat(&X);
+ ifstream is( filename.c_str() );
+ int rows, cols, type, step;
+ is.read( (char*)&rows, sizeof(int) );
+ is.read( (char*)&cols, sizeof(int) );
+ is.read( (char*)&type, sizeof(int) );
+ is.read( (char*)&step, sizeof(int) );
+
+ uchar* data = (uchar*)cvAlloc(step*rows);
+ is.read( (char*)data, step*rows );
+ return Mat( rows, cols, type, data );
}
-void CV_CalonderTest::MapVectorAffine(const vector<CvPoint>& p1, vector<CvPoint>& p2, CvMat* transform)
+void CV_CalonderTest::run(int)
{
- double a = cvmGet(transform, 0, 0);
- double b = cvmGet(transform, 0, 1);
- double c = cvmGet(transform, 0, 2);
- double d = cvmGet(transform, 1, 0);
- double e = cvmGet(transform, 1, 1);
- double f = cvmGet(transform, 1, 2);
-
- for(int i = 0; i < (int)p1.size(); i++)
+ string dir = string(ts->get_data_path()) + "/calonder";
+ Mat img = imread(dir +"/boat.png",0);
+ if( img.empty() )
{
- double x = a*p1[i].x + b*p1[i].y + c;
- double y = d*p1[i].x + e*p1[i].y + f;
- p2.push_back(cvPoint((int)x, (int)y));
+ ts->printf(CvTS::LOG, "Test image can not be read\n");
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ return;
}
-}
+ vector<KeyPoint> keypoints;
+#if GET_RES
+ FastFeatureDetector fd;
+ fd.detect(img, keypoints);
-float CV_CalonderTest::CalcAffineReprojectionError(const vector<CvPoint>& p1, const vector<CvPoint>& p2, CvMat* transform)
-{
- vector<CvPoint> mapped_p1;
- MapVectorAffine(p1, mapped_p1, transform);
- float error = 0;
- for(int i = 0; i < (int)p2.size(); i++)
+ FileStorage fs( dir + "/keypoints.xml", FileStorage::WRITE );
+ if( fs.isOpened() )
+ write( fs, "keypoints", keypoints );
+ else
{
- //float l = length(p2[i] - mapped_p1[i]);
- error += ((p2[i].x - mapped_p1[i].x)*(p2[i].x - mapped_p1[i].x)+(p2[i].y - mapped_p1[i].y)*(p2[i].y - mapped_p1[i].y));
+ ts->printf(CvTS::LOG, "File for writting keypoints can not be opened\n");
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ return;
}
-
- error /= p2.size();
-
- return error;
-}
-
-void CV_CalonderTest::ExtractFeatures(const IplImage* image, vector<CvPoint>& points)
-{
- points.clear();
- CvMemStorage* storage = cvCreateMemStorage(0);
- CvSeq *keypoints = 0, *descriptors = 0;
- CvSURFParams params = cvSURFParams(1000, 1);
- cvExtractSURF( image, 0, &keypoints, &descriptors, storage, params );
-
-
- CvSURFPoint* point;
- for (int i=0;i<keypoints->total;i++)
- {
- point=(CvSURFPoint*)cvGetSeqElem(keypoints,i);
- points.push_back(cvPoint((int)(point->pt.x),(int)(point->pt.y)));
- }
- cvReleaseMemStorage(&storage);
-}
-
-void CV_CalonderTest::TrainDetector(RTreeClassifier& detector, int/* patch_size*/, const vector<CvPoint>& train_points,const IplImage* train_image, int n_keypoints)
-{
- vector<BaseKeypoint> base_set;
- int n = (int)(train_points.size());
- if (n_keypoints)
- n = n_keypoints;
- for (int i=0;i<n;i++)
- {
- base_set.push_back(BaseKeypoint(train_points[i].x,train_points[i].y,const_cast<IplImage*>(train_image)));
- }
-
- //Detector training
- //CvRNG r = cvRNG(1);
- RNG rng( cvRandInt(this->ts->get_rng()));
- PatchGenerator gen(0,255,2,false,0.7,1.3,-CV_PI/3,CV_PI/3,-CV_PI/3,CV_PI/3);
-
- //int64 t0 = cvGetTickCount();
- detector.train(base_set,rng,gen,6,DEFAULT_DEPTH,3000,(int)base_set.size(),detector.DEFAULT_NUM_QUANT_BITS,false);
- //int64 t1 = cvGetTickCount();
- //printf("Train: %f s\n",(float)(t1-t0)/cvGetTickFrequency()*1e-6);
-
-
-}
-
-void CV_CalonderTest::GetCorrespondences(const RTreeClassifier& detector, int patch_size,
- const vector<CvPoint>& objectKeypoints, const vector<CvPoint>& imageKeypoints, const IplImage* image,
- vector<CvPoint>& object, vector<CvPoint>& features)
-{
- IplImage* test_image = cvCloneImage(image);
- object.clear();
- features.clear();
-
- float* signature = new float[(const_cast<RTreeClassifier&>(detector)).original_num_classes()];
- float* best_corr;
- int* best_corr_idx;
- if (imageKeypoints.size() > 0)
- {
- best_corr = new float[(int)imageKeypoints.size()];
- best_corr_idx = new int[(int)imageKeypoints.size()];
-
-
- for(int i=0; i < (int)imageKeypoints.size(); i++)
- {
- int part_idx = -1;
- float prob = 0.0f;
- //CvPoint center = cvPoint((int)(imageKeypoints[i].x),(int)(imageKeypoints[i].y));
-
- CvRect roi = cvRect((int)(imageKeypoints[i].x) - patch_size/2,(int)(imageKeypoints[i].y) - patch_size/2, patch_size, patch_size);
- cvSetImageROI(test_image, roi);
- roi = cvGetImageROI(test_image);
- if(roi.width != patch_size || roi.height != patch_size)
- {
- best_corr_idx[i] = part_idx;
- best_corr[i] = prob;
- }
- else
- {
- cvSetImageROI(test_image, roi);
- IplImage* roi_image = cvCreateImage(cvSize(roi.width, roi.height), test_image->depth, test_image->nChannels);
- cvCopy(test_image,roi_image);
-
- (const_cast<RTreeClassifier&>(detector)).getSignature(roi_image, signature);
-
-
- for (int j = 0; j< (const_cast<RTreeClassifier&>(detector)).original_num_classes();j++)
- {
- if (prob < signature[j])
- {
- part_idx = j;
- prob = signature[j];
- }
- }
-
- best_corr_idx[i] = part_idx;
- best_corr[i] = prob;
-
-
- if (roi_image)
- cvReleaseImage(&roi_image);
- }
- cvResetImageROI(test_image);
- }
-
- float min_prob = 0.0f;
-
- for (int j=0;j<(int)objectKeypoints.size();j++)
- {
- float prob = 0.0f;
- int idx = -1;
- for (int i = 0; i<(int)imageKeypoints.size();i++)
- {
- if ((best_corr_idx[i]!=j)||(best_corr[i] < min_prob))
- continue;
-
- if (best_corr[i] > prob)
- {
- prob = best_corr[i];
- idx = i;
- }
- }
- if (idx >=0)
- {
- object.push_back(objectKeypoints[j]);
- features.push_back(imageKeypoints[idx]);
- }
- }
-
- if (best_corr)
- delete[] best_corr;
- if (best_corr_idx)
- delete[] best_corr_idx;
- }
- cvReleaseImage(&test_image);
- if (signature)
- delete[] signature;
-}
-
-
-// Scales the source image (x and y) and rotate to the angle (Positive values mean counter-clockwise rotation)
-void CV_CalonderTest::RotateAndScale(const IplImage* src, IplImage* dst, float angle, float scale_x, float scale_y)
-{
- IplImage* temp = cvCreateImage(cvSize((int)(src->width*scale_x),(int)(src->height*scale_y)),src->depth,src->nChannels);
-
- cvResize(src,temp);
-
- CvMat* transform = cvCreateMat(2,3,CV_32FC1);
- cv2DRotationMatrix(cvPoint2D32f(((double)temp->width)/2,((double)temp->height)/2), angle*180/CV_PI,
- 1.0f, transform );
-
- cvWarpAffine( temp, dst, transform,CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS);
- cvReleaseImage(&temp);
- cvReleaseMat(&transform);
-}
-
-// Scales the source image point and rotate to the angle (Positive values mean counter-clockwise rotation)
-void CV_CalonderTest::RotateAndScale(const CvPoint& src, CvPoint& dst, const CvPoint& center, float angle, float scale_x, float scale_y)
-{
- CvPoint temp;
- temp.x = (int)(src.x*scale_x);
- temp.y = (int)(src.y*scale_y);
-
- CvMat* transform = cvCreateMat(2,3,CV_32FC1);
- cv2DRotationMatrix(cvPoint2D32f((double)center.x*scale_x,(double)center.y*scale_y), angle*180/CV_PI,
- 1.0f, transform );
-
- double a = cvmGet(transform, 0, 0);
- double b = cvmGet(transform, 0, 1);
- double c = cvmGet(transform, 0, 2);
- double d = cvmGet(transform, 1, 0);
- double e = cvmGet(transform, 1, 1);
- double f = cvmGet(transform, 1, 2);
-
- double x = a*temp.x + b*temp.y + c;
- double y = d*temp.x + e*temp.y + f;
- dst= cvPoint((int)x, (int)y);
-
- cvReleaseMat(&transform);
-}
-
-float CV_CalonderTest::RunTestsSeries(const IplImage* train_image, vector<CvPoint>& keypoints)
-{
- float angles[] = {(float)-CV_PI/4,(float)CV_PI/4};
- float scales_x[] = {0.85f,1.15f};
- float scales_y[] = {0.85f,1.15f};
- int n_angles = 4;
- int n_scales_x = 3;
- int n_scales_y = 3;
- int accuracy = 4;
- int are_keypoints_loaded = (int)keypoints.size();
-
- int total_cases = n_angles*n_scales_x*n_scales_y;
- int n_case = 0;
-
- int length = max(train_image->width,train_image->height);
- int move_x = (int)(1.5*scales_x[0]*length);
- int move_y = (int)(1.5*scales_y[0]*length);
- IplImage* test_image = cvCreateImage(cvSize((int)(scales_x[1]*(move_x+length*1.5)),(int)(scales_y[1]*(move_y+length*1.5))),
- train_image->depth, train_image->nChannels);
- cvSet(test_image,cvScalar(0));
-
- cvSetImageROI(test_image,cvRect(move_x,move_y,train_image->width,train_image->height));
- cvCopy(train_image,test_image);
- cvResetImageROI(test_image);
-
- vector<CvPoint> objectKeypoints;
- if (!are_keypoints_loaded)
- {
- ExtractFeatures(train_image,objectKeypoints);
- for (int i=0;i<(int)objectKeypoints.size();i++)
- {
- keypoints.push_back(objectKeypoints[i]);
- }
- }
- else
- {
- for (int i=0;i<(int)keypoints.size();i++)
- {
- objectKeypoints.push_back(keypoints[i]);
- }
- }
-
- //Checking signatures are identical
- vector <vector<float> > signatures1;
- string signatures_path = string(ts->get_data_path()) + "calonder/signatures.txt";
- int can_load_signatures = LoadKeypointSignatures(signatures_path.c_str(),signatures1);
- // end of region
-
- RTreeClassifier detector;
- int patch_size = PATCH_SIZE;
- //this->update_progress(1,0,total_cases,5);
- TrainDetector(detector,patch_size,objectKeypoints,train_image,20);
-
- //Checking signatures are identical
- vector <vector<float> > signatures2;
- ExtractKeypointSignatures(train_image,patch_size,detector,objectKeypoints,signatures2);
- if (!can_load_signatures)
- {
- //SaveKeypointSignatures(signatures_path.c_str(),signatures2);
- }
- else
- {
- // if (!CompareSignatures(signatures1,signatures2))
- // return 0;
- }
- // end of region
-
-
-
- int points_total = 0;
- int points_correct = 0;
-
-
- vector<CvPoint> imageKeypoints;
- vector<CvPoint> object;
- vector<CvPoint> features;
- IplImage* temp = cvCloneImage(test_image);
-
- int progress = 0;
-
-
- //int64 t0 = cvGetTickCount();
- //printf("\n\n-----------\nTest started\n-----------\n");
- for (float angle = angles[0]; angle<=angles[1];angle+=(n_angles > 1 ?(angles[1]-angles[0])/n_angles : 1))
- {
- for (float scale_x = scales_x[0]; scale_x<=scales_x[1];scale_x+=(n_scales_x > 1 ? (scales_x[1]-scales_x[0])/n_scales_x : 1))
- {
- for (float scale_y = scales_y[0]; scale_y<=scales_y[1];scale_y+=(n_scales_y > 1 ? (scales_y[1]-scales_y[0])/n_scales_y : 1))
- {
- //printf("---\nAngle: %f, scaleX: %f, scaleY: %f\n", angle,scale_x,scale_y);
- cvSet(temp,cvScalar(0));
- imageKeypoints.clear();
- object.clear();
- features.clear();
-
- RotateAndScale(test_image,temp,angle,scale_x,scale_y);
- ExtractFeatures(temp,imageKeypoints);
- GetCorrespondences(detector,patch_size,objectKeypoints,imageKeypoints,temp,object,features);
-
- int correct = 0;
- CvPoint res;
- for (int i = 0; i< (int)object.size(); i++)
- {
-
- CvPoint current = object[i];
- current.x+=move_x;
- current.y+=move_y;
- RotateAndScale(current,res,cvPoint(temp->width/2,temp->height/2),angle,scale_x,scale_y);
- int dist = (res.x - features[i].x)*(res.x - features[i].x)+(res.y - features[i].y)*(res.y - features[i].y);
- if (dist < accuracy*accuracy)
- correct++;
- }
- //printf("Image points: %d\nCorrespondences found: %d/%d\n", (int)imageKeypoints.size(), correct, (int)object.size());
- points_correct+=correct;
- points_total+=(int)object.size();
- progress = update_progress( progress, n_case++, total_cases, 0 );
- //if (drawResults)
- //{
- // DrawResult(train_image, temp,object,features);
- //}
- }
- }
- }
-// int64 t1 = cvGetTickCount();
- //printf("%f s\n",(float)(t1-t0)/cvGetTickFrequency()*1e-6);
- cvReleaseImage(&temp);
- cvReleaseImage(&test_image);
- //printf("\n\n-----------\nTest completed\n-----------\n");
- //printf("Total correspondences found: %d/%d\n", points_correct, points_total);
- //FILE* f = fopen("test_result.txt","w");
- //fprintf(f,"Total correspondences found: %d/%d\n", points_correct, points_total);
- //fclose(f);
- if (points_total < 1)
- {
- points_correct = 0;
- points_total = 1;
- }
- return (float)points_correct/(float)points_total;
-
-}
-
-CV_CalonderTest::CV_CalonderTest() : CvTest("calonder","RTreeClassifier")
-{
-}
-
-CV_CalonderTest::~CV_CalonderTest() {}
-
-int CV_CalonderTest::SaveKeypoints(const vector<CvPoint>& points, const char* path)
-{
- FILE* f = fopen(path,"w");
- if (f==NULL)
- {
- return 0;
- }
- for (int i=0;i<(int)points.size();i++)
- {
- fprintf(f,"%d,%d\n",points[i].x,points[i].y);
- }
- fclose(f);
- return 1;
-}
-
-int CV_CalonderTest::LoadKeypoints(vector<CvPoint>& points, const char* path)
-{
- FILE* f = fopen(path,"r");
- points.clear();
-
- if (f==NULL)
- {
- return 0;
- }
-
- while (!feof(f))
- {
- int x,y;
- fscanf(f,"%d,%d\n",&x,&y);
- points.push_back(cvPoint(x,y));
- }
- fclose(f);
- return 1;
-}
-
-void CV_CalonderTest::ExtractKeypointSignatures(const IplImage* test_image, int patch_size, const RTreeClassifier& detector, const vector<CvPoint>& keypoints, vector<vector<float> >& signatures)
-{
- IplImage* _test_image = cvCloneImage(test_image);
- signatures.clear();
-
- float* signature = new float[(const_cast<RTreeClassifier&>(detector)).original_num_classes()];
-
- for (int i=0;i<(int)keypoints.size();i++)
- {
- CvRect roi = cvRect((int)(keypoints[i].x) - patch_size/2,(int)(keypoints[i].y) - patch_size/2, patch_size, patch_size);
- cvSetImageROI(_test_image, roi);
- roi = cvGetImageROI(_test_image);
- if(roi.width != patch_size || roi.height != patch_size)
- {
- continue;
- }
-
- cvSetImageROI(_test_image, roi);
- IplImage* roi_image = cvCreateImage(cvSize(roi.width, roi.height), _test_image->depth, _test_image->nChannels);
- cvCopy(_test_image,roi_image);
-
- (const_cast<RTreeClassifier&>(detector)).getSignature(roi_image, signature);
-
- vector<float> vec;
-
- for (int j=0;j<(const_cast<RTreeClassifier&>(detector)).original_num_classes();j++)
- {
- vec.push_back(signature[j]);
- }
- signatures.push_back(vec);
-
- cvReleaseImage(&roi_image);
-
- }
-
- delete[] signature;
- cvReleaseImage(&_test_image);
-}
-
-
-
-
-int CV_CalonderTest::SaveKeypointSignatures(const char* path, const vector<vector<float> >& signatures)
-{
- FILE* f = fopen(path,"w");
- if (!f)
- return 0;
-
- for (int i=0;i<(int)signatures.size();i++)
- {
- for (int j=0;j<(int)signatures[i].size();j++)
- {
- fprintf(f,"%f",signatures[i][j]);
- if (j<((int)signatures[i].size()-1))
- fprintf(f,",");
- }
- if (i<((int)signatures.size()-1))
- fprintf(f,"\n");
- }
- fclose(f);
-
- return 1;
-}
-
-int CV_CalonderTest::LoadKeypointSignatures(const char* path, vector<vector<float> >& signatures)
-{
- signatures.clear();
- FILE* f = fopen(path,"r");
- if (!f)
- return 0;
-
- char line[4096];
- vector<float> vec;
- char* tok;
-
- while(fgets(line,4096,f))
- {
- vec.clear();
- float val;
- tok = strtok(line,",");
- if (tok)
- {
- sscanf(tok,"%f",&val);
- vec.push_back(val);
- tok = strtok(NULL,",");
- while (tok)
- {
- sscanf(tok,"%f",&val);
- vec.push_back(val);
- tok = strtok(NULL,",");
- }
- signatures.push_back(vec);
- }
- }
-
- fclose(f);
- return(1);
-}
-
-int CV_CalonderTest::CompareSignatures(const vector<vector<float> >& signatures1, const vector<vector<float> >& signatures2)
-{
- if (signatures1.size() != signatures2.size())
- {
- return 0;
- }
-
- float accuracy = 0.05f;
- for (int i=0;i<(int)signatures1.size();i++)
- {
- if (signatures1[i].size() != signatures2[i].size())
- {
- return 0;
- }
- for (int j=0;j<(int)signatures1[i].size();j++)
- {
- if (abs(signatures1[i][j]-signatures2[i][j]) > accuracy)
- return 0;
- }
- }
- return 1;
-}
-
-
-void CV_CalonderTest::run( int /* start_from */)
-{
- string train_image_path = string(ts->get_data_path()) + "calonder/baboon200.jpg";
- string train_keypoints_path = string(ts->get_data_path()) + "calonder/train_features.txt";
- IplImage* train_image = cvLoadImage(train_image_path.c_str(),0);
-
- if (!train_image)
- {
- ts->printf( CvTS::LOG, "Unable to open train image calonder/baboon200.jpg");
- ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
- return;
- }
+#else
+ FileStorage fs( dir + "/keypoints.xml", FileStorage::READ);
+ if( fs.isOpened() )
+ read( fs.getFirstTopLevelNode(), keypoints );
+ else
+ {
+ ts->printf(CvTS::LOG, "File for reading keypoints can not be opened\n");
+ ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+ return;
+ }
+#endif
+ CalonderDescriptorExtractor<float> fde(dir + "/classifier.rtc");
+
+ Mat fdescriptors;
+ double t = getTickCount();
+ fde.compute(img, keypoints, fdescriptors);
+ t = getTickCount() - t;
+ ts->printf(CvTS::LOG, "\nAverage time of computiting float descriptor = %g ms\n", t/((double)cvGetTickFrequency()*1000.)/fdescriptors.rows );
+
+#if GET_RES
+ assert(fdescriptors.type() == CV_32FC1);
+ writeMatInBin( fdescriptors, "" );
+#else
+ Mat ros_fdescriptors = readMatFromBin( dir + "/ros_float_desc" );
+ double fnorm = norm(fdescriptors, ros_fdescriptors, NORM_INF );
+ ts->printf(CvTS::LOG, "nofm (inf) BTW valid and calculated float descriptors = %f\n", fnorm );
+ if( fnorm > FLT_EPSILON )
+ ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
+#endif
- // Testing rtree classifier
- float min_accuracy = 0.35f;
- vector<CvPoint> train_keypoints;
- train_keypoints.clear();
- float correctness;
- if (!LoadKeypoints(train_keypoints,train_keypoints_path.c_str()))
- {
- correctness = RunTestsSeries(train_image,train_keypoints);
- SaveKeypoints(train_keypoints,train_keypoints_path.c_str());
- }
- else
- {
- correctness = RunTestsSeries(train_image,train_keypoints);
- }
- if (correctness > min_accuracy)
- ts->set_failed_test_info(CvTS::OK);
- else
- {
- ts->set_failed_test_info(CvTS::FAIL_BAD_ACCURACY);
- ts->printf( CvTS::LOG, "Correct correspondences: %f, less than %f",correctness,min_accuracy);
- }
+ CalonderDescriptorExtractor<uchar> cde(dir + "/classifier.rtc");
+ Mat cdescriptors;
+ t = getTickCount();
+ cde.compute(img, keypoints, cdescriptors);
+ t = getTickCount() - t;
+ ts->printf(CvTS::LOG, "Average time of computiting uchar descriptor = %g ms\n", t/((double)cvGetTickFrequency()*1000.)/cdescriptors.rows );
+
+#if GET_RES
+ assert(cdescriptors.type() == CV_8UC1);
+ writeMatInBin( fdescriptors, "" );
+#else
+ Mat ros_cdescriptors = readMatFromBin( dir + "/ros_uchar_desc" );
+ double cnorm = norm(cdescriptors, ros_cdescriptors, NORM_INF );
+ ts->printf(CvTS::LOG, "nofm (inf) BTW valid and calculated uchar descriptors = %f\n", cnorm );
+ if( cnorm > FLT_EPSILON )
+ ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
+#endif
}
-CV_CalonderTest calonder_test;
-
-#endif
+CV_CalonderTest calonderTest;
projects / platform / upstream / opencv.git / commitdiff