void cvCLAdaptEqualize(const CvArr* srcarr, CvArr* dstarr,
unsigned int xdivs, unsigned int ydivs, unsigned int bins,
float limit, int range)
{
double min_val, max_val;
unsigned char min, max;
int type;
IplImage sstub, *src = cvGetImage(srcarr, &sstub);
IplImage dstub, *dst = cvGetImage(dstarr, &dstub);
if ((src == NULL) || (dst == NULL))
CV_ERROR( CV_StsUnsupportedFormat, "NULL value passed as image to function" );
CV_CALL( type = cvGetElemType( src ));
if( type != CV_8UC1 )
CV_ERROR( CV_StsUnsupportedFormat, "Only 8uC1 images are supported" );
CV_CALL( type = cvGetElemType( src ));
if( type != CV_8UC1 )
CV_ERROR( CV_StsUnsupportedFormat, "Only 8uC1 images are supported" );
//if( !CV_ARE_SIZES_EQ( src, dst )) // Modified by Shervin Emami, 17Nov2010.
if (src->width != dst->width || src->height != dst->height)
CV_ERROR( CV_StsUnmatchedSizes, "src and dst images must be equal sizes" );
if (((xdivs < 2) || (xdivs > 16)) || ((ydivs < 2) || (ydivs > 16)))
CV_ERROR( CV_StsBadFlag, "xdivs and ydivs must in range (MIN=2 MAX = 16)" );
if ((bins < 2) || (bins > 256))
CV_ERROR( CV_StsBadFlag, "bins must in range (MIN=2 MAX = 256)" );
// copy src to dst for in-place CLAHE.
cvCopy(src, dst);
// If the dimensions of the image are not a multiple of the xdivs and ydivs, then enlarge the image to be a correct size and then shrink the image.
// Also make sure the image is aligned to 8 pixels width, so that OpenCV won't add extra padding to the image.
// Added by Shervin Emami, 17Nov2010.
int enlarged = 0;
int origW = dst->width;
int origH = dst->height;
IplImage *tmpDst = 0;
if ((dst->width & (8-1)) || (dst->height & (8-1)) || (dst->width % xdivs) || (dst->height % ydivs)) {
int newW = ((dst->width + 8-1) & -8); // Align to 8 pixels, so that widthStep hopefully equals width.
newW = ((newW + xdivs-1) & -xdivs); // Also align for CLAHE.
int newH = ((dst->height + ydivs-1) & -ydivs);
//std::cout << "w=" << dst->width << ", h=" << dst->height << ". new w = " << newW << ", h = " << newH << std::endl;
IplImage *enlargedDst = cvCreateImage(cvSize(newW, newH), dst->depth, dst->nChannels);
cvResize(dst, enlargedDst, CV_INTER_CUBIC);
//cvReleaseImage(&dst);
tmpDst = dst;
dst = enlargedDst; // Use the enlarged image instead of the original dst image.
enlarged = 1; // signal that we need to shrink later!
}
// Check if OpenCV adds padding bytes on each row. Added by Shervin Emami, 17Nov2010.
if (dst->width != dst->widthStep)
CV_ERROR( CV_StsBadFlag, "dst->widthStep should be the same as dst->width. The IplImage has padding, so use a larger image." );
// check number of xdivs and ydivs is a multiple of image dimensions
if (dst->width % xdivs)
CV_ERROR( CV_StsBadFlag, "xdiv must be an integer multiple of image width " );
if (dst->height % ydivs)
CV_ERROR( CV_StsBadFlag, "ydiv must be an integer multiple of image height " );
// get the min and max values of the image
if (range == CV_CLAHE_RANGE_INPUT) {
cvMinMaxLoc(dst, &min_val, &max_val);
min = (unsigned char) min_val;
max = (unsigned char) max_val;
} else {
min = 0;
max = 255;
}
// call CLHAHE for in-place CLAHE
//int rcode =
CLAHE((kz_pixel_t*) (dst->imageData), (unsigned int) dst->width, (unsigned int)
dst->height, (kz_pixel_t) min, (kz_pixel_t) max, (unsigned int) xdivs, (unsigned int) ydivs,
(unsigned int) bins, (float) limit);
//printf("RCODE %i\n", rcode);
// If the dst image was enlarged to fit the alignment, then shrink it back now.
// Added by Shervin Emami, 17Nov2010.
if (enlarged) {
//std::cout << "w=" << dst->width << ", h=" << dst->height << ". orig w=" << origW << ", h=" << origH << std::endl;
cvResize(dst, tmpDst, CV_INTER_CUBIC); // Shrink the enlarged image back into the original dst image.
cvReleaseImage(&dst); // Free the enlarged image.
}
}
TiXmlElement* FileFormatUtils::createXMLMatrix(const char* element_name, const CvMat *matrix) {
if (!matrix) return NULL;
TiXmlElement* xml_matrix = new TiXmlElement(element_name);
int precision;
if (cvGetElemType(matrix) == CV_32F) {
xml_matrix->SetAttribute("type", "CV_32F");
precision = std::numeric_limits<float>::digits10 + 2;
}
else if (cvGetElemType(matrix) == CV_64F) {
xml_matrix->SetAttribute("type", "CV_64F");
precision = std::numeric_limits<double>::digits10 + 2;
}
else {
delete xml_matrix;
return NULL;
}
xml_matrix->SetAttribute("rows", matrix->rows);
xml_matrix->SetAttribute("cols", matrix->cols);
for (int r = 0; r < matrix->rows; ++r) {
for (int c = 0; c < matrix->cols; ++c) {
TiXmlElement *xml_data = new TiXmlElement("data");
xml_matrix->LinkEndChild(xml_data);
std::stringstream ss;
ss.precision(precision);
ss<<cvGetReal2D(matrix, r, c);
xml_data->LinkEndChild(new TiXmlText(ss.str().c_str()));
}
}
return xml_matrix;
}
CVAPI(void) cvShowImageEx(const char * id, const CvArr * arr,
const int cm)
{
CvMat * src, src_stub;
double minval, maxval, maxdiff; CvPoint minloc, maxloc;
int type = cvGetElemType(arr);
CvMat * disp, * src_scaled;
int i, j;
if (!CV_IS_MAT(arr))
src = cvGetMat(arr, &src_stub);
else{
src = (CvMat*)arr;
}
src = cvCloneMat(src);
if ( (src->rows<60) || (src->rows<60) )
{
CvMat * orig = cvCloneMat(src);
int scale=60./MIN(orig->rows, orig->cols);
cvReleaseMat(&src);
src = cvCreateMat(orig->rows*scale, orig->cols*scale,
CV_MAT_TYPE(orig->type));
int m,n;
if (CV_MAT_TYPE(src->type)==CV_64F){
for (m=0;m<orig->rows;m++) {
for (n=0;n<orig->cols;n++) {
for (i=0;i<scale;i++) {
for (j=0;j<scale;j++) {
CV_MAT_ELEM(*src, double, m*scale+i, n*scale+j) = CV_MAT_ELEM(*orig, double, m, n);
}
}
}
}
}else if (CV_MAT_TYPE(src->type)==CV_32F){
/*
* call-seq:
* sub(val[,mask])
*
* Return new CvScalar if <i>val</i> is CvScalar or compatible object.
* self[I] - val[I]
* Or return new CvMat if <i>val</i> is CvMat or subclass.
*/
VALUE
rb_sub(int argc, VALUE *argv, VALUE self)
{
VALUE val, mask;
rb_scan_args(argc, argv, "11", &val, &mask);
if (rb_obj_is_kind_of(val, cCvMat::rb_class())) {
CvArr *val_ptr = CVARR(val);
VALUE dest = Qnil;
try {
dest = cCvMat::new_object(cvGetSize(val_ptr), cvGetElemType(val_ptr));
cvSubRS(val_ptr, *CVSCALAR(self), CVARR(dest), MASK(mask));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
return dest;
}
else {
CvScalar *src = CVSCALAR(self);
CvScalar scl = VALUE_TO_CVSCALAR(val);
return new_object(cvScalar(src->val[0] - scl.val[0],
src->val[1] - scl.val[1],
src->val[2] - scl.val[2],
src->val[3] - scl.val[3]));
}
}
void cvPolyLineAA( CvArr* img, CvPoint** pts, int* npts, int contours,
int is_closed, double color, int scale )
{
cvPolyLine( img, pts, npts, contours, is_closed,
cvColorToScalar(color, cvGetElemType(img)),
1, CV_AA, scale );
}
// Rearrange the quadrants of Fourier image so that the origin is at
// the image center
// src & dst arrays of equal size & type
void
cvShiftDFT(CvArr *src_arr, CvArr *dst_arr )
{
CvMat *tmp = NULL;
CvMat q1stub, q2stub;
CvMat q3stub, q4stub;
CvMat d1stub, d2stub;
CvMat d3stub, d4stub;
CvMat *q1, *q2, *q3, *q4;
CvMat *d1, *d2, *d3, *d4;
CvSize size = cvGetSize(src_arr);
CvSize dst_size = cvGetSize(dst_arr);
int cx, cy;
if(dst_size.width != size.width ||
dst_size.height != size.height){
cvError( CV_StsUnmatchedSizes, "cvShiftDFT", "Source and Destination arrays must have equal sizes", __FILE__, __LINE__ );
}
if(src_arr==dst_arr){
tmp = rb_cvCreateMat(size.height/2, size.width/2, cvGetElemType(src_arr));
}
cx = size.width/2;
cy = size.height/2; // image center
q1 = cvGetSubRect( src_arr, &q1stub, cvRect(0,0,cx, cy) );
q2 = cvGetSubRect( src_arr, &q2stub, cvRect(cx,0,cx,cy) );
q3 = cvGetSubRect( src_arr, &q3stub, cvRect(cx,cy,cx,cy) );
q4 = cvGetSubRect( src_arr, &q4stub, cvRect(0,cy,cx,cy) );
d1 = cvGetSubRect( src_arr, &d1stub, cvRect(0,0,cx,cy) );
d2 = cvGetSubRect( src_arr, &d2stub, cvRect(cx,0,cx,cy) );
d3 = cvGetSubRect( src_arr, &d3stub, cvRect(cx,cy,cx,cy) );
d4 = cvGetSubRect( src_arr, &d4stub, cvRect(0,cy,cx,cy) );
if(src_arr!=dst_arr){
if( !CV_ARE_TYPES_EQ( q1, d1 )){
cvError( CV_StsUnmatchedFormats, "cvShiftDFT", "Source and Destination arrays must have the same format", __FILE__, __LINE__ );
}
cvCopy(q3, d1, 0);
cvCopy(q4, d2, 0);
cvCopy(q1, d3, 0);
cvCopy(q2, d4, 0);
}
else{
cvCopy(q3, tmp, 0);
cvCopy(q1, q3, 0);
cvCopy(tmp, q1, 0);
cvCopy(q4, tmp, 0);
cvCopy(q2, q4, 0);
cvCopy(tmp, q2, 0);
}
if (tmp != NULL)
{
cvReleaseMat(&tmp);
}
}
void cvEllipseAA( CvArr* img, CvPoint center, CvSize axes,
double angle, double start_angle,
double end_angle, double color,
int scale)
{
cvEllipse( img, center, axes, angle, start_angle, end_angle,
cvColorToScalar(color, cvGetElemType(img)), 1, CV_AA, scale );
}
void test(CvMat* t)
{
//获取矩阵的数据类型
int type = cvGetElemType(t);
CvHistogram
//获取矩阵的维度信息
int size[10];
int dims = cvGetDims(t, size);
int x = cvGetDimSize(t, 0);
int y = cvGetDimSize(t, 1);
}
double CxCore_MulSpectrumsTest::get_success_error_level( int test_case_idx, int i, int j )
{
CV_UNUSED(test_case_idx);
CV_Assert(i == OUTPUT);
CV_Assert(j == 0);
int elem_depth = CV_MAT_DEPTH(cvGetElemType(test_array[i][j]));
CV_Assert(elem_depth == CV_32F || elem_depth == CV_64F);
element_wise_relative_error = false;
double maxInputValue = 1000; // ArrayTest::get_minmax_bounds
double err = 8 * maxInputValue; // result = A*B + C*D
return (elem_depth == CV_32F ? FLT_EPSILON : DBL_EPSILON) * err;
}
void CvArrTest::fill_array( int /*test_case_idx*/, int i, int j, CvMat* arr )
{
if( i == REF_INPUT_OUTPUT )
cvTsCopy( &test_mat[INPUT_OUTPUT][j], arr, 0 );
else if( i == INPUT || i == INPUT_OUTPUT || i == MASK )
{
int type = cvGetElemType( arr );
CvScalar low, high;
get_minmax_bounds( i, j, type, &low, &high );
cvTsRandUni( ts->get_rng(), arr, low, high );
}
}
/*
* call-seq:
* sub(val[,mask])
*
* Return new CvScalar if <i>val</i> is CvScalar or compatible object.
* self[I] - val[I]
* Or return new CvMat if <i>val</i> is CvMat or subclass.
*/
VALUE
rb_sub(int argc, VALUE *argv, VALUE self)
{
VALUE val, mask;
rb_scan_args(argc, argv, "11", &val, &mask);
if(rb_obj_is_kind_of(val, cCvMat::rb_class())){
VALUE dest = cCvMat::new_object(cvGetSize(CVARR(val)), cvGetElemType(CVARR(val)));
cvSubRS(CVARR(val), *CVSCALAR(self), CVARR(dest), MASK(mask));
return dest;
}else{
CvScalar *src = CVSCALAR(self), scl = VALUE_TO_CVSCALAR(val);
return new_object(cvScalar(src->val[0] - scl.val[0],
src->val[1] - scl.val[1],
src->val[2] - scl.val[2],
src->val[3] - scl.val[3]));
}
}
////////////////////////compute the meshgrid arrays needed for LPF//////////////////////////////////////////////////
// CDM compute meshgrid frequency matrices (ok!)
// see Gonzalez Digital image processing using matlab page93 function dftuv
void CLightSet::CDM(int M,int N,CvMat *mat)
{
int width = mat->rows;
int height = mat->cols;
if (M != width && N != height)
{
//cout<<"ERROR! THE SIZE DOES NOT MATCH WITH MAT"<<endl;
return;
}
if (cvGetElemType(mat) < CV_32F)
{
//cout<<"ERROR! THE TYPE DOES NOT MATCH WITH MAT"<<endl;
return;
}
CvMat *U,*V;
U = cvCreateMat(M,N,CV_32FC1);
V = cvCreateMat(M,N,CV_32FC1);
for (int u = 0; u < M; ++u)
for (int v =0 ;v < N; ++v)
{
float tm1,tm2;
tm1 = (float)((u > cvRound(M/2))?u-M:u);
tm2 = (float)((v > cvRound(N/2))?v-N:v);
*( (float *)CV_MAT_ELEM_PTR(*U,u,v) ) = tm1;
*( (float *)CV_MAT_ELEM_PTR(*V,u,v) ) = tm2;
}
for ( int u = 0; u < M; ++u)
for (int v =0 ;v < N; ++v)
{
float t1,t2;
t1 = CV_MAT_ELEM(*U,float,u,v);
t2 = CV_MAT_ELEM(*V,float,u,v);
*( (float *)CV_MAT_ELEM_PTR(*mat,u,v) ) = sqrt(t1*t1 + t2*t2);
}
}
static bool check_size_type(const CvMat* src, const char* name)
{
if(src->rows != src->cols)
{
fprintf(stderr, "MT_Cholesky Error: %s must be a square matrix.\n",
name);
return false;
}
if(cvGetElemType(src) != CV_64FC1)
{
fprintf(stderr,
"MT_Cholesky Error: %s must be a single-channel "
"matrix of doubles.\n",
name);
return false;
}
return true;
}
void MT_CVQuadraticMul(const CvMat* X,
const CvMat* W,
CvMat* dst,
bool transpose_X,
CvMat* tmp_prod)
{
bool own_prod = (tmp_prod == NULL);
if(own_prod)
{
tmp_prod = cvCreateMat(W->rows, X->cols, cvGetElemType(X));
}
cvGEMM(W, X, 1.0, NULL, 1.0, tmp_prod, transpose_X ? CV_GEMM_B_T : 0);
cvGEMM(X, tmp_prod, 1.0, NULL, 1.0, dst, transpose_X ? 0 : CV_GEMM_A_T);
if(own_prod)
{
cvReleaseMat(&tmp_prod);
}
}
bool FileFormatUtils::parseXMLMatrix(const TiXmlElement *xml_matrix, CvMat *matrix) {
if (!xml_matrix || !matrix) return false;
int type, rows, cols;
if (!decodeXMLMatrix(xml_matrix, type, rows, cols)) return false;
if (type != cvGetElemType(matrix)) return false;
if (rows != matrix->rows) return false;
if (cols != matrix->cols) return false;
const TiXmlElement *xml_data = xml_matrix->FirstChildElement("data");
for (int r = 0; r < matrix->rows; ++r) {
for (int c = 0; c < matrix->cols; ++c) {
if (!xml_data) return false;
double value = atof(xml_data->GetText());
cvSetReal2D(matrix, r, c, value);
xml_data = (const TiXmlElement *) xml_data->NextSibling("data");
}
}
return true;
}
bool CvCalibFilter::FindEtalon( CvMat** mats )
{
bool result = true;
if( !mats || etalonPointCount == 0 )
{
assert(0);
result = false;
}
if( result )
{
int i, tempPointCount0 = etalonPointCount*2;
for( i = 0; i < cameraCount; i++ )
{
if( !latestPoints[i] )
latestPoints[i] = (CvPoint2D32f*)
cvAlloc( tempPointCount0*2*sizeof(latestPoints[0]));
}
for( i = 0; i < cameraCount; i++ )
{
CvSize size;
int tempPointCount = tempPointCount0;
bool found = false;
if( !CV_IS_MAT(mats[i]) && !CV_IS_IMAGE(mats[i]))
{
assert(0);
break;
}
size = cvGetSize(mats[i]);
if( size.width != imgSize.width || size.height != imgSize.height )
{
imgSize = size;
}
if( !grayImg || grayImg->width != imgSize.width ||
grayImg->height != imgSize.height )
{
cvReleaseMat( &grayImg );
cvReleaseMat( &tempImg );
grayImg = cvCreateMat( imgSize.height, imgSize.width, CV_8UC1 );
tempImg = cvCreateMat( imgSize.height, imgSize.width, CV_8UC1 );
}
if( !storage )
storage = cvCreateMemStorage();
switch( etalonType )
{
case CV_CALIB_ETALON_CHESSBOARD:
if( CV_MAT_CN(cvGetElemType(mats[i])) == 1 )
cvCopy( mats[i], grayImg );
else
cvCvtColor( mats[i], grayImg, CV_BGR2GRAY );
found = cvFindChessBoardCornerGuesses( grayImg, tempImg, storage,
cvSize( cvRound(etalonParams[0]),
cvRound(etalonParams[1])),
latestPoints[i], &tempPointCount ) != 0;
if( found )
cvFindCornerSubPix( grayImg, latestPoints[i], tempPointCount,
cvSize(5,5), cvSize(-1,-1),
cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,10,0.1));
break;
default:
assert(0);
result = false;
break;
}
latestCounts[i] = found ? tempPointCount : -tempPointCount;
result = result && found;
}
}
if( storage )
cvClearMemStorage( storage );
return result;
}
double ArrayTest::get_success_error_level( int /*test_case_idx*/, int i, int j )
{
int elem_depth = CV_MAT_DEPTH(cvGetElemType(test_array[i][j]));
assert( i == OUTPUT || i == INPUT_OUTPUT );
return elem_depth < CV_32F ? 0 : elem_depth == CV_32F ? FLT_EPSILON*100: DBL_EPSILON*5000;
}
/* old drawing functions */
void cvLineAA( CvArr* img, CvPoint pt1, CvPoint pt2, double color, int scale)
{
cvLine( img, pt1, pt2, cvColorToScalar(color, cvGetElemType(img)), 1, CV_AA, scale );
}
void cvCircleAA( CvArr* img, CvPoint center, int radius, double color, int scale)
{
cvCircle( img, center, radius, cvColorToScalar(color, cvGetElemType(img)), 1, CV_AA, scale );
}
/**
* Euclidean distance transform of a binary image,
* Computation performed upon 'short' values
*
* @param src IN: positive pixels are treated as background
* @param distxArr OUT:
* @param distyArr OUT:
*/
void cvCalcEuclideanDistance(
const CvArr * src, // positive pixels are treated as background
CvArr * distxArr, CvArr * distyArr)
{
CV_FUNCNAME("cvEuclideanDistance");
int x, y, i;
int offset_u, offset_ur, offset_r, offset_rd,
offset_d, offset_dl, offset_l, offset_lu;
double olddist2, newdist2, newdistx, newdisty;
int changed;
__BEGIN__;
// CV_ASSERT(cvGetElemType(src)==CV_16S);
// CV_ASSERT(cvGetElemType(distxArr)==CV_16S);
// CV_ASSERT(cvGetElemType(distyArr)==CV_16S);
CvMat srcHeader, distHeaderX, distHeaderY;
CvMat * srcImage = cvGetMat(src, &srcHeader);
CvMat * distImageX = cvGetMat(distxArr, &distHeaderX);
CvMat * distImageY = cvGetMat(distyArr, &distHeaderY);
CvMat * srcImage2 =
cvCreateMat(srcImage->rows, srcImage->cols, CV_16S);
CvMat * distImageX2 =
cvCreateMat(srcImage->rows, srcImage->cols, CV_16S);
CvMat * distImageY2 =
cvCreateMat(srcImage->rows, srcImage->cols, CV_16S);
if (cvGetElemType(src)!=CV_16S) cvConvert(srcImage, srcImage2);
else cvCopy(srcImage, srcImage2);
CvMat distImageXheader, distImageYheader;
CvMat * distImageXreshaped =
cvReshape(distImageX2, &distImageXheader, 0, 1);
CvMat * distImageYreshaped =
cvReshape(distImageY2, &distImageYheader, 0, 1);
int w = srcImage->cols;
int h = srcImage->rows;
short * distx = (short*)distImageXreshaped->data.ptr;
short * disty = (short*)distImageYreshaped->data.ptr;
// Initialize index offsets for the current image width
offset_u = -w;
offset_ur = -w+1;
offset_r = 1;
offset_rd = w+1;
offset_d = w;
offset_dl = w-1;
offset_l = -1;
offset_lu = -w-1;
/* Initialize the distance images to be all large values */
for(i=0; i<w*h; i++)
// if(img(i) <= 0.0)
if(CV_MAT_ELEM(*srcImage2, short, i/w, i%w) <= 0.0)
{
distx[i] = 32000; // Large but still representable in a short, and
disty[i] = 32000; // 32000^2 + 32000^2 does not overflow an int
}
else
{
void cvFillImage( CvArr* mat, double color )
{
cvSet( mat, cvColorToScalar(color, cvGetElemType(mat)), 0 );
}
int CvArrTest::validate_test_results( int test_case_idx )
{
static const char* arr_names[] = { "input", "input/output", "output",
"ref input/output", "ref output",
"temporary", "mask" };
int i, j;
prepare_to_validation( test_case_idx );
for( i = 0; i < 2; i++ )
{
int i0 = i == 0 ? OUTPUT : INPUT_OUTPUT;
int i1 = i == 0 ? REF_OUTPUT : REF_INPUT_OUTPUT;
int count = test_array[i0].size();
assert( count == test_array[i1].size() );
for( j = 0; j < count; j++ )
{
double err_level;
CvPoint idx = {0,0};
double max_diff = 0;
int code;
char msg[100];
if( !test_array[i1][j] )
continue;
err_level = get_success_error_level( test_case_idx, i0, j );
code = cvTsCmpEps( &test_mat[i0][j], &test_mat[i1][j], &max_diff, err_level, &idx,
element_wise_relative_error );
switch( code )
{
case -1:
sprintf( msg, "Too big difference (=%g)", max_diff );
code = CvTS::FAIL_BAD_ACCURACY;
break;
case -2:
strcpy( msg, "Invalid output" );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
case -3:
strcpy( msg, "Invalid output in the reference array" );
code = CvTS::FAIL_INVALID_OUTPUT;
break;
default:
continue;
}
ts->printf( CvTS::LOG, "%s in %s array %d at (%d,%d)\n", msg,
arr_names[i0], j, idx.x, idx.y );
for( i0 = 0; i0 < max_arr; i0++ )
{
int count = test_array[i0].size();
if( i0 == REF_INPUT_OUTPUT || i0 == OUTPUT || i0 == TEMP )
continue;
for( i1 = 0; i1 < count; i1++ )
{
CvArr* arr = test_array[i0][i1];
if( arr )
{
CvSize size = cvGetSize(arr);
int type = cvGetElemType(arr);
ts->printf( CvTS::LOG, "%s array %d type=%sC%d, size=(%d,%d)\n",
arr_names[i0], i1, cvTsGetTypeName(type),
CV_MAT_CN(type), size.width, size.height );
}
}
}
ts->set_failed_test_info( code );
return code;
}
}
return 0;
}
/**
* Transforms points from the ground plane (z=-h) in the world frame
* into points on the image in image frame (uv-coordinates)
*
* \param inPoints 2xN array of input points on the ground in world coordinates
* \param outPoints 2xN output points in on the image in image coordinates
* \param cameraInfo the camera parameters
*
*/
void mcvTransformGround2Image(const CvMat *inPoints,
CvMat *outPoints, const CameraInfo *cameraInfo)
{
//add two rows to the input points
CvMat *inPoints3 = cvCreateMat(inPoints->rows+1, inPoints->cols,
cvGetElemType(inPoints));
cvSet(inPoints3, cvScalar(0));
//copy inPoints to first two rows
CvMat inPoints2, inPointsr3;
cvGetRows(inPoints3, &inPoints2, 0, 2);
cvGetRow(inPoints3, &inPointsr3, 2);
cvSet(&inPointsr3, cvRealScalar(-cameraInfo->cameraHeight));
cvCopy(inPoints, &inPoints2);
//create the transformation matrix
float c1 = cos(cameraInfo->pitch);
float s1 = sin(cameraInfo->pitch);
float c2 = cos(cameraInfo->yaw);
float s2 = sin(cameraInfo->yaw);
float matp[] = {
cameraInfo->focalLength.x * c2 + c1*s2* cameraInfo->opticalCenter.x,
-cameraInfo->focalLength.x * s2 + c1*c2* cameraInfo->opticalCenter.x,
- s1 * cameraInfo->opticalCenter.x,
s2 * (-cameraInfo->focalLength.y * s1 + c1* cameraInfo->opticalCenter.y),
c2 * (-cameraInfo->focalLength.y * s1 + c1* cameraInfo->opticalCenter.y),
-cameraInfo->focalLength.y * c1 - s1* cameraInfo->opticalCenter.y,
c1*s2,
c1*c2,
-s1
};
CvMat mat = cvMat(3, 3, FLOAT_MAT_TYPE, matp);
//multiply
//std::cout << " inPoints3.rows " << inPoints3->rows << " inPoints3.cols "<< inPoints3->cols << "\n ";
cvMatMul(&mat, inPoints3, inPoints3);
//divide by last row of inPoints4
for (int i=0; i<inPoints->cols; i++)
{
float div = CV_MAT_ELEM(inPointsr3, float, 0, i);
CV_MAT_ELEM(*inPoints3, float, 0, i) =
CV_MAT_ELEM(*inPoints3, float, 0, i) / div ;
CV_MAT_ELEM(*inPoints3, float, 1, i) =
CV_MAT_ELEM(*inPoints3, float, 1, i) / div;
if(isnan(CV_MAT_ELEM(*inPoints3, float, 0, i) ) || isnan(CV_MAT_ELEM(*inPoints3, float, 1, i) ))
{
cout << "cameraInfo->pitch " << cameraInfo->pitch << endl;
cout << "cameraInfo->yaw " << cameraInfo->yaw << endl;
cout << "opticalCenter.x " << cameraInfo->opticalCenter.x << endl;
cout << "opticalCenter.y " << cameraInfo->opticalCenter.y << endl;
cout << "focalLength.x " << cameraInfo->focalLength.x << endl;
cout << "focalLength.y " << cameraInfo->focalLength.y << endl;
}
//if(isnan(CV_MAT_ELEM(*inPoints3, float, 1, i) )) cout << "JAP!!!2 div " << div <<endl;
}
//put back the result into outPoints
//std::cout << " inPoints2.rows " << inPoints2.rows << " inPoints2.cols "<< inPoints2.cols << "\n ";
// std::cout << " outPoints.rows " << outPoints->rows << " outPoints.cols "<< outPoints->cols << "\n ";
cvCopy(&inPoints2, outPoints);
// std::cout << " outPoints.rows " << outPoints->rows << " outPoints.cols "<< outPoints->cols << "\n ";
//clear
cvReleaseMat(&inPoints3);
}
/**
* Transforms points from the image frame (uv-coordinates)
* into the real world frame on the ground plane (z=-height)
*
* \param inPoints input points in the image frame
* \param outPoints output points in the world frame on the ground
* (z=-height)
* \param cemaraInfo the input camera parameters
*
*/
void mcvTransformImage2Ground(const CvMat *inPoints,
CvMat *outPoints, const CameraInfo *cameraInfo)
{
//add two rows to the input points
CvMat *inPoints4 = cvCreateMat(inPoints->rows+2, inPoints->cols,
cvGetElemType(inPoints));
//copy inPoints to first two rows
CvMat inPoints2, inPoints3, inPointsr4, inPointsr3;
cvGetRows(inPoints4, &inPoints2, 0, 2);
cvGetRows(inPoints4, &inPoints3, 0, 3);
cvGetRow(inPoints4, &inPointsr3, 2);
cvGetRow(inPoints4, &inPointsr4, 3);
cvSet(&inPointsr3, cvRealScalar(1));
cvCopy(inPoints, &inPoints2);
//create the transformation matrix
float c1 = cos(cameraInfo->pitch);
float s1 = sin(cameraInfo->pitch);
float c2 = cos(cameraInfo->yaw);
float s2 = sin(cameraInfo->yaw);
float matp[] = {
-cameraInfo->cameraHeight*c2/cameraInfo->focalLength.x,
cameraInfo->cameraHeight*s1*s2/cameraInfo->focalLength.y,
(cameraInfo->cameraHeight*c2*cameraInfo->opticalCenter.x/
cameraInfo->focalLength.x)-
(cameraInfo->cameraHeight *s1*s2* cameraInfo->opticalCenter.y/
cameraInfo->focalLength.y) - cameraInfo->cameraHeight *c1*s2,
cameraInfo->cameraHeight *s2 /cameraInfo->focalLength.x,
cameraInfo->cameraHeight *s1*c2 /cameraInfo->focalLength.y,
(-cameraInfo->cameraHeight *s2* cameraInfo->opticalCenter.x
/cameraInfo->focalLength.x)-(cameraInfo->cameraHeight *s1*c2*
cameraInfo->opticalCenter.y /cameraInfo->focalLength.y) -
cameraInfo->cameraHeight *c1*c2,
0,
cameraInfo->cameraHeight *c1 /cameraInfo->focalLength.y,
(-cameraInfo->cameraHeight *c1* cameraInfo->opticalCenter.y /
cameraInfo->focalLength.y) + cameraInfo->cameraHeight *s1,
0,
-c1 /cameraInfo->focalLength.y,
(c1* cameraInfo->opticalCenter.y /cameraInfo->focalLength.y) - s1,
};
CvMat mat = cvMat(4, 3, CV_32FC1, matp);
//multiply
cvMatMul(&mat, &inPoints3, inPoints4);
//divide by last row of inPoints4
for (int i=0; i<inPoints->cols; i++)
{
float div = CV_MAT_ELEM(inPointsr4, float, 0, i);
CV_MAT_ELEM(*inPoints4, float, 0, i) =
CV_MAT_ELEM(*inPoints4, float, 0, i) / div ;
CV_MAT_ELEM(*inPoints4, float, 1, i) =
CV_MAT_ELEM(*inPoints4, float, 1, i) / div;
}
//put back the result into outPoints
cout << "cameraInfo->cameraHeight " << cameraInfo->cameraHeight << endl;
cvCopy(&inPoints2, outPoints);
//clear
cvReleaseMat(&inPoints4);
}
/*! \fn FaceDetectorPlugin::checkZone(Zone *zone, const Image *zmImage)
* \param zone is a zone where faces will be detected
* \param zmImage is an image to perform face detection (in the form of ZM' Image)
* \return true if there were objects detected in given image and
* false otherwise
*/
bool FaceDetectorPlugin::checkZone(Zone *zone, const Image *zmImage)
{
//log(LOG_DEBUG, "Entering checkZone.");
double score;
Polygon zone_polygon = Polygon(zone->GetPolygon()); // Polygon of interest of the processed zone.
//char szMessage[50];
//sprintf(szMessage, "Polygon of the zone has %d vertices.", zone_polygon.getNumCoords());
//log(LOG_WARNING, szMessage);
//zone->ResetStats();
/*
log(LOG_WARNING, "precheck");
if ( !zone->CheckOverloadCount() )
{
log(LOG_WARNING, "CheckOverloadCount() return false, we'll return false.");
return(false);
}
*/
//zmLoadConfig();
// An image for highlighting detected objects.
Image *pMaskImage = new Image(zmImage->Width(), zmImage->Height(), ZM_COLOUR_GRAY8, ZM_SUBPIX_ORDER_NONE );
pMaskImage->Fill(BLACK);
//log(LOG_WARNING, "FILLBLACK.");
// An temporary image in the form of ZM for making from it CvMat.
// If don't use temp image, after rgb->bgr it will change.
Image *tempZmImage = new Image(*zmImage);
CvMat* cvInputImage = NULL;
CvMat* pScaledImage = NULL;
bool bDoResizing = (m_fImageScaleFactor != 1.0); // resize image or not
if (tempZmImage->Colours() == ZM_COLOUR_GRAY8)
{
// if image is not colored, create an one-channel CvMat.
cvInputImage = cvCreateMat(tempZmImage->Height(), tempZmImage->Width(), CV_8UC1);
unsigned char *buffer = (unsigned char*)tempZmImage->Buffer();
cvSetData(cvInputImage, buffer, tempZmImage->Width());
}
// NEXTIME XXX TODO: manage also 32 bit images!
else
{
// otherwise create a three-channel CvMat and then convert colors from RGB to BGR.
cvInputImage = cvCreateMat(tempZmImage->Height(), tempZmImage->Width(), CV_8UC3);
unsigned char *buffer = (unsigned char*)tempZmImage->Buffer();
cvSetData(cvInputImage, buffer, tempZmImage->Width() * 3);
cvCvtColor(cvInputImage, cvInputImage, CV_RGB2BGR);
}
if (bDoResizing)
{
int nNewWidth = int (m_fImageScaleFactor * zmImage->Width());
int nNewHeight = int (m_fImageScaleFactor * tempZmImage->Height());
int nImageElemType = cvGetElemType(cvInputImage);
pScaledImage = cvCreateMat(nNewHeight, nNewWidth, nImageElemType);
cvResize(cvInputImage, pScaledImage, CV_INTER_LINEAR);
}
//Process image
vector<CvRect> foundObjects;
if (bDoResizing)
foundObjects = _opencvHaarDetect(pScaledImage);
else
foundObjects = _opencvHaarDetect(cvInputImage);
if (foundObjects.size() > 0)
log(LOG_INFO, "OBJECTS WERE DETECTED");
score = 0;
for (vector<CvRect>::iterator it = foundObjects.begin(); it < foundObjects.end(); it++)
{
// Process found objects.
// Scale object's coordinates back if image has been scaled.
int x1 = int(it->x/m_fImageScaleFactor), x2 = int((it->x + it->width)/m_fImageScaleFactor), y1 = int(it->y/m_fImageScaleFactor), y2 = int((it->y + it->height)/m_fImageScaleFactor);
// Check if object's rectangle is inside zone's polygon of interest.
Coord rectVertCoords[4] = {Coord(x1, y1), Coord(x1, y2), Coord(x2, y1), Coord(x2, y2)};
int nNumVertInside = 0;
for (int i = 0; i < 4; i++)
{
nNumVertInside += zone_polygon.isInside(rectVertCoords[i]);
}
if (nNumVertInside < 3)
// if at least three rectangle coordinates are inside polygon, consider rectangle as belonging to the zone
// otherwise process next object
continue;
// Fill a box with object in the mask
Box *faceBox = new Box(x1, y1, x2, y2);
pMaskImage->Fill(WHITE, faceBox);
// Calculate score as portion of object area in the image
score += (100.0*(it->width)*(it->height)/m_fImageScaleFactor/m_fImageScaleFactor)/zone_polygon.Area();
delete faceBox;
}
if (score == 0)
{
//log(LOG_DEBUG, "No objects found. Exit.");
delete pMaskImage;
delete tempZmImage;
if (cvInputImage)
cvReleaseMat(&cvInputImage);
if (pScaledImage)
cvReleaseMat(&pScaledImage);
return( false );
}
if ( m_fMinAlarmScore && ( score < m_fMinAlarmScore) )
{
delete pMaskImage;
delete tempZmImage;
if (cvInputImage)
cvReleaseMat(&cvInputImage);
if (pScaledImage)
cvReleaseMat(&pScaledImage);
return( false );
}
if ( m_fMaxAlarmScore && (score > m_fMaxAlarmScore) )
{
zone->SetOverloadCount(zone->GetOverloadFrames());
delete pMaskImage;
delete tempZmImage;
if (cvInputImage)
cvReleaseMat(&cvInputImage);
if (pScaledImage)
cvReleaseMat(&pScaledImage);
return( false );
}
zone->SetScore(max(1, (int)score));
//Get mask by highlighting contours of objects and overlaying them with previous contours.
Rgb alarm_colour = RGB_GREEN;
Image *hlZmImage = pMaskImage->HighlightEdges(alarm_colour, ZM_COLOUR_RGB24,
ZM_SUBPIX_ORDER_RGB, &zone_polygon.Extent());
if (zone->Alarmed())
{
// if there were previous detection and they have already set up alarm image
// then overlay it with current mask
Image* pPrevZoneMask = new Image(*(zone->AlarmImage()));
pPrevZoneMask->Overlay(*hlZmImage);
zone->SetAlarmImage(pPrevZoneMask);
delete pPrevZoneMask;
}
else
zone->SetAlarmImage(hlZmImage);
delete pMaskImage;
delete hlZmImage;
delete tempZmImage;
if (cvInputImage)
cvReleaseMat(&cvInputImage);
if (pScaledImage)
cvReleaseMat(&pScaledImage);
//log(LOG_DEBUG, "Leaving checkZone.");
return true;
}
/* Warps source into destination by a perspective transform */
static void cvWarpPerspective( CvArr* src, CvArr* dst, double quad[4][2] )
{
CV_FUNCNAME( "cvWarpPerspective" );
__BEGIN__;
#ifdef __IPL_H__
IplImage src_stub, dst_stub;
IplImage* src_img;
IplImage* dst_img;
CV_CALL( src_img = cvGetImage( src, &src_stub ) );
CV_CALL( dst_img = cvGetImage( dst, &dst_stub ) );
iplWarpPerspectiveQ( src_img, dst_img, quad, IPL_WARP_R_TO_Q,
IPL_INTER_CUBIC | IPL_SMOOTH_EDGE );
#else
int fill_value = 0;
double c[3][3]; /* transformation coefficients */
double q[4][2]; /* rearranged quad */
int left = 0;
int right = 0;
int next_right = 0;
int next_left = 0;
double y_min = 0;
double y_max = 0;
double k_left, b_left, k_right, b_right;
uchar* src_data;
int src_step;
CvSize src_size;
uchar* dst_data;
int dst_step;
CvSize dst_size;
double d = 0;
int direction = 0;
int i;
if( !src || (!CV_IS_IMAGE( src ) && !CV_IS_MAT( src )) ||
cvGetElemType( src ) != CV_8UC1 ||
cvGetDims( src ) != 2 )
{
CV_ERROR( CV_StsBadArg,
"Source must be two-dimensional array of CV_8UC1 type." );
}
if( !dst || (!CV_IS_IMAGE( dst ) && !CV_IS_MAT( dst )) ||
cvGetElemType( dst ) != CV_8UC1 ||
cvGetDims( dst ) != 2 )
{
CV_ERROR( CV_StsBadArg,
"Destination must be two-dimensional array of CV_8UC1 type." );
}
CV_CALL( cvGetRawData( src, &src_data, &src_step, &src_size ) );
CV_CALL( cvGetRawData( dst, &dst_data, &dst_step, &dst_size ) );
CV_CALL( cvGetPerspectiveTransform( src_size, quad, c ) );
/* if direction > 0 then vertices in quad follow in a CW direction,
otherwise they follow in a CCW direction */
direction = 0;
for( i = 0; i < 4; ++i )
{
int ni = i + 1; if( ni == 4 ) ni = 0;
int pi = i - 1; if( pi == -1 ) pi = 3;
d = (quad[i][0] - quad[pi][0])*(quad[ni][1] - quad[i][1]) -
(quad[i][1] - quad[pi][1])*(quad[ni][0] - quad[i][0]);
int cur_direction = CV_SIGN(d);
if( direction == 0 )
{
direction = cur_direction;
}
else if( direction * cur_direction < 0 )
{
direction = 0;
break;
}
}
if( direction == 0 )
{
CV_ERROR( CV_StsBadArg, "Quadrangle is nonconvex or degenerated." );
}
/* <left> is the index of the topmost quad vertice
if there are two such vertices <left> is the leftmost one */
left = 0;
for( i = 1; i < 4; ++i )
{
if( (quad[i][1] < quad[left][1]) ||
((quad[i][1] == quad[left][1]) && (quad[i][0] < quad[left][0])) )
{
left = i;
}
}
/* rearrange <quad> vertices in such way that they follow in a CW
direction and the first vertice is the topmost one and put them
into <q> */
if( direction > 0 )
{
for( i = left; i < 4; ++i )
{
q[i-left][0] = quad[i][0];
q[i-left][1] = quad[i][1];
}
for( i = 0; i < left; ++i )
{
q[4-left+i][0] = quad[i][0];
q[4-left+i][1] = quad[i][1];
}
}
else
{
for( i = left; i >= 0; --i )
{
q[left-i][0] = quad[i][0];
q[left-i][1] = quad[i][1];
}
for( i = 3; i > left; --i )
{
q[4+left-i][0] = quad[i][0];
q[4+left-i][1] = quad[i][1];
}
}
left = right = 0;
/* if there are two topmost points, <right> is the index of the rightmost one
otherwise <right> */
if( q[left][1] == q[left+1][1] )
{
right = 1;
}
/* <next_left> follows <left> in a CCW direction */
next_left = 3;
/* <next_right> follows <right> in a CW direction */
next_right = right + 1;
/* subtraction of 1 prevents skipping of the first row */
y_min = q[left][1] - 1;
/* left edge equation: y = k_left * x + b_left */
k_left = (q[left][0] - q[next_left][0]) /
(q[left][1] - q[next_left][1]);
b_left = (q[left][1] * q[next_left][0] -
q[left][0] * q[next_left][1]) /
(q[left][1] - q[next_left][1]);
/* right edge equation: y = k_right * x + b_right */
k_right = (q[right][0] - q[next_right][0]) /
(q[right][1] - q[next_right][1]);
b_right = (q[right][1] * q[next_right][0] -
q[right][0] * q[next_right][1]) /
(q[right][1] - q[next_right][1]);
for(;;)
{
int x, y;
y_max = MIN( q[next_left][1], q[next_right][1] );
int iy_min = MAX( cvRound(y_min), 0 ) + 1;
int iy_max = MIN( cvRound(y_max), dst_size.height - 1 );
double x_min = k_left * iy_min + b_left;
double x_max = k_right * iy_min + b_right;
/* walk through the destination quadrangle row by row */
for( y = iy_min; y <= iy_max; ++y )
{
int ix_min = MAX( cvRound( x_min ), 0 );
int ix_max = MIN( cvRound( x_max ), dst_size.width - 1 );
for( x = ix_min; x <= ix_max; ++x )
{
/* calculate coordinates of the corresponding source array point */
double div = (c[2][0] * x + c[2][1] * y + c[2][2]);
double src_x = (c[0][0] * x + c[0][1] * y + c[0][2]) / div;
double src_y = (c[1][0] * x + c[1][1] * y + c[1][2]) / div;
int isrc_x = cvFloor( src_x );
int isrc_y = cvFloor( src_y );
double delta_x = src_x - isrc_x;
double delta_y = src_y - isrc_y;
uchar* s = src_data + isrc_y * src_step + isrc_x;
int i00, i10, i01, i11;
i00 = i10 = i01 = i11 = (int) fill_value;
/* linear interpolation using 2x2 neighborhood */
if( isrc_x >= 0 && isrc_x <= src_size.width &&
isrc_y >= 0 && isrc_y <= src_size.height )
{
i00 = s[0];
}
if( isrc_x >= -1 && isrc_x < src_size.width &&
isrc_y >= 0 && isrc_y <= src_size.height )
{
i10 = s[1];
}
if( isrc_x >= 0 && isrc_x <= src_size.width &&
isrc_y >= -1 && isrc_y < src_size.height )
{
i01 = s[src_step];
}
if( isrc_x >= -1 && isrc_x < src_size.width &&
isrc_y >= -1 && isrc_y < src_size.height )
{
i11 = s[src_step+1];
}
double i0 = i00 + (i10 - i00)*delta_x;
double i1 = i01 + (i11 - i01)*delta_x;
((uchar*)(dst_data + y * dst_step))[x] = (uchar) (i0 + (i1 - i0)*delta_y);
}
x_min += k_left;
x_max += k_right;
}
if( (next_left == next_right) ||
(next_left+1 == next_right && q[next_left][1] == q[next_right][1]) )
{
break;
}
if( y_max == q[next_left][1] )
{
left = next_left;
next_left = left - 1;
k_left = (q[left][0] - q[next_left][0]) /
(q[left][1] - q[next_left][1]);
b_left = (q[left][1] * q[next_left][0] -
q[left][0] * q[next_left][1]) /
(q[left][1] - q[next_left][1]);
}
if( y_max == q[next_right][1] )
{
right = next_right;
next_right = right + 1;
k_right = (q[right][0] - q[next_right][0]) /
(q[right][1] - q[next_right][1]);
b_right = (q[right][1] * q[next_right][0] -
q[right][0] * q[next_right][1]) /
(q[right][1] - q[next_right][1]);
}
y_min = y_max;
}
#endif /* #ifndef __IPL_H__ */
__END__;
}
bool MT_Cholesky(const CvMat* src, CvMat* dst, unsigned int orientation)
{
if(!check_size_type(src, "Input"))
{
return false;
}
if(!dst)
{
fprintf(stderr, "MT_Cholesky Error: Output is not allocated.\n");
return false;
}
else
{
if((dst->rows != src->rows) || (dst->cols != src->cols) ||
(cvGetElemType(dst) != cvGetElemType(src)))
{
fprintf(stderr,
"MT_Cholesky Error: Output matrix must be same size"
" and type as input.\n");
return false;
}
}
if((orientation != MT_CHOLESKY_UPPER_TRIANGULAR) &&
(orientation != MT_CHOLESKY_LOWER_TRIANGULAR))
{
fprintf(stderr,
"MT_Cholesky Error: Orientation must be either "
"MT_CHOLESKY_UPPER_TRIANGULAR (%d) or "
"MT_CHOLESKY_LOWER_TRIANGULAR (%d).\n",
MT_CHOLESKY_UPPER_TRIANGULAR,
MT_CHOLESKY_LOWER_TRIANGULAR);
return false;
}
double p;
unsigned int R = src->rows;
cvSet(dst, cvScalar(0));
double* src_data = src->data.db;
double* dst_data = dst->data.db;
for(int i = 0; i < R; i++)
{
for(int j = 0; j < R; j++)
{
if(i < j)
{
continue;
}
p = 0;
if(i==j)
{
p = src_data[i*R + i];
for(int k = 0; k <= j-1; k++)
{
p -= dst_data[i*R+k]*dst_data[i*R+k];
}
if( p < 0 ){ // NOTE these may not be numerically correct, but it is a safeguard
p = fabs(p);
}
if( p == 0 ){
p = 1e-6;
}
dst_data[i*R+i] = sqrt(p);
} else {
p = src_data[i*R+j];
for(int k = 0; k <= j-1; k++)
{
p -= dst_data[i*R+k]*dst_data[j*R+k];
}
dst_data[i*R+j] = p/dst_data[j*R+j];
}
}
}
if(orientation == MT_CHOLESKY_UPPER_TRIANGULAR)
{
cvTranspose(dst, dst);
}
return true;
}
