Blob::Blob( const Blob &_src )
: perimeter_(*this),
area_(*this),
ellipse_(*this),
bounding_rect_(*this)
{
CV_FUNCNAME( "Blob::Blob(const Blob &)" );
__BEGIN__;
ISL_CALL( this->alloc() );
ISL_CALL( this->copy_edges(_src.edges_) );
this->perimeter_.copy_data(_src.perimeter_);
this->area_.copy_data(_src.area_);
this->ellipse_.copy_data(_src.ellipse_);
this->bounding_rect_.copy_data(_src.bounding_rect_);
__END__;
if( cvGetErrStatus() < 0 )
this->release();
__ISL_CHECK_ERROR__;
}
// create IplImage header
CV_IMPL IplImage *
cvCreateImageHeader( CvSize size, int depth, int channels )
{
IplImage *img = 0;
CV_FUNCNAME( "cvCreateImageHeader" );
__BEGIN__;
if( !CvIPL.createHeader )
{
CV_CALL( img = (IplImage *)cvAlloc( sizeof( *img )));
CV_CALL( cvInitImageHeader( img, size, depth, channels, IPL_ORIGIN_TL, 4, 1 ));
}
else
{
char *colorModel;
char *channelSeq;
icvGetColorModel( channels, &colorModel, &channelSeq );
img = CvIPL.createHeader( channels, 0, depth, colorModel, channelSeq,
IPL_DATA_ORDER_PIXEL, IPL_ORIGIN_TL, 4,
size.width, size.height, 0, 0, 0, 0 );
}
__END__;
if( cvGetErrStatus() < 0 && img )
cvReleaseImageHeader( &img );
return img;
}
PrincipalAxis::PrincipalAxis(double mx, double my, double cxx, double cxy, double cyy)
: major_(0)
, minor_(0)
{
CV_FUNCNAME( "PrincipalAxis::PrincipalAxis" );
__BEGIN__;
CV_CALL( this->covariance_ = cvCreateMat( 2, 2, CV_64FC1 ) );
CV_CALL( this->eigen_vectors_ = cvCreateMat( 2, 2, CV_64FC1 ) );
CV_CALL( this->eigen_values_ = cvCreateMat( 2, 1, CV_64FC1 ) );
CV_CALL( cvZero(this->covariance_ ) );
CV_CALL( cvZero(this->eigen_vectors_) );
CV_CALL( cvZero(this->eigen_values_ ) );
this->compute(mx, my, cxx, cxy, cyy);
__END__;
if( cvGetErrStatus() < 0 )
{
__ISL_DISABLE_ERROR__;
this->release();
__ISL_RESTORE_ERROR__;
}
__ISL_CHECK_ERROR__;
}
CV_IMPL IplConvKernel *
cvCreateStructuringElementEx( int cols, int rows,
int anchorX, int anchorY,
int shape, int *values )
{
IplConvKernel *element = 0;
int i, size = rows * cols;
int element_size = sizeof(*element) + size*sizeof(element->values[0]);
CV_FUNCNAME( "cvCreateStructuringElementEx" );
__BEGIN__;
if( !values && shape == CV_SHAPE_CUSTOM )
CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );
if( cols <= 0 || rows <= 0 ||
(unsigned) anchorX >= (unsigned) cols ||
(unsigned) anchorY >= (unsigned) rows )
CV_ERROR_FROM_STATUS( CV_BADSIZE_ERR );
CV_CALL( element = (IplConvKernel *)cvAlloc(element_size + 32));
if( !element )
CV_ERROR_FROM_STATUS( CV_OUTOFMEM_ERR );
element->nCols = cols;
element->nRows = rows;
element->anchorX = anchorX;
element->anchorY = anchorY;
element->nShiftR = shape < CV_SHAPE_ELLIPSE ? shape : CV_SHAPE_CUSTOM;
element->values = (int*)(element + 1);
if( shape == CV_SHAPE_CUSTOM )
{
if( !values )
CV_ERROR( CV_StsNullPtr, "Null pointer to the custom element mask" );
for( i = 0; i < size; i++ )
element->values[i] = values[i];
}
else
{
CvMat el_hdr = cvMat( rows, cols, CV_32SC1, element->values );
CV_CALL( CvMorphology::init_binary_element(&el_hdr,
shape, cvPoint(anchorX,anchorY)));
}
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseStructuringElement( &element );
return element;
}
/* Note: this has been copied verbatim from <opencv_root>/interfaces/python/cv.cpp */
static int convert_to_IplImage(PyObject *o, IplImage **dst)
{
iplimage_t *ipl = (iplimage_t*)o;
void *buffer;
Py_ssize_t buffer_len;
if (!is_iplimage(o)) {
return -1; //failmsg("Argument must be IplImage");
} else if (PyString_Check(ipl->data)) {
cvSetData(ipl->a, PyString_AsString(ipl->data) + ipl->offset, ipl->a->widthStep);
assert(cvGetErrStatus() == 0);
*dst = ipl->a;
return 1;
} else if (ipl->data && PyObject_AsWriteBuffer(ipl->data, &buffer, &buffer_len) == 0) {
cvSetData(ipl->a, (void*)((char*)buffer + ipl->offset), ipl->a->widthStep);
assert(cvGetErrStatus() == 0);
*dst = ipl->a;
return 1;
} else {
return -1;// failmsg("IplImage argument has no data");
}
}
PHP_OPENCV_API void php_opencv_throw_exception(TSRMLS_D)
{
char * error_message;
int status = cvGetErrStatus();
if (status >= 0) {
return;
}
error_message = estrdup(cvErrorStr(status));
zend_throw_exception(opencv_ce_cvexception, error_message, status TSRMLS_CC);
efree(error_message);
return;
}
void
Blob::alloc()
{
CV_FUNCNAME( "Blob::alloc" );
__BEGIN__;
CV_CALL( this->storage_ = cvCreateMemStorage(0) );
CV_CALL( this->edges_ = cvCreateSeq(CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_CURVE, sizeof(CvContour), sizeof(CvPoint) , this->storage_) );
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseMemStorage(&this->storage_);
__ISL_CHECK_ERROR__;
}
CV_IMPL IplImage*
cvCreateGLCMImage( CvGLCM* GLCM, int step )
{
IplImage* dest = 0;
CV_FUNCNAME( "cvCreateGLCMImage" );
__BEGIN__;
float* destData;
int sideLoop1, sideLoop2;
if( !GLCM )
CV_ERROR( CV_StsNullPtr, "" );
if( !(GLCM->matrices) )
CV_ERROR( CV_StsNullPtr, "Matrices are not allocated" );
if( (unsigned)step >= (unsigned)(GLCM->numMatrices) )
CV_ERROR( CV_StsOutOfRange, "The step index is out of range" );
dest = cvCreateImage( cvSize( GLCM->matrixSideLength, GLCM->matrixSideLength ), IPL_DEPTH_32F, 1 );
destData = (float*)(dest->imageData);
for( sideLoop1 = 0; sideLoop1 < GLCM->matrixSideLength; sideLoop1++)
/* for( sideLoop1 = 0; sideLoop1 < GLCM->matrixSideLength;
sideLoop1++, (float*&)destData += dest->widthStep )*/
{
for( sideLoop2=0; sideLoop2 < GLCM->matrixSideLength; sideLoop2++ )
{
double matrixValue = GLCM->matrices[step][sideLoop1][sideLoop2];
// destData[ sideLoop2 ] = (float)matrixValue;
// cvSetReal2D(dest, sideLoop1, sideLoop2, matrixValue);
((float*)(dest->imageData + sideLoop1 * dest->widthStep))[sideLoop2] = (float)matrixValue;
// destData[ sideLoop2 ] = (float)matrixValue;
}
}
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseImage( &dest );
return dest;
}
// create CvMat and underlying date
CV_IMPL CvMat*
cvCreateMat( int height, int width, int type )
{
CvMat* arr = 0;
CV_FUNCNAME( "cvCreateMat" );
__BEGIN__;
CV_CALL( arr = cvCreateMatHeader( height, width, type ));
CV_CALL( cvCreateData( arr ));
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseMat( &arr );
return arr;
}
CV_IMPL void
icvStartScanGraph( CvGraph* graph, CvGraphScanner* scanner,
CvGraphVtx* vtx, int mask )
{
CvMemStorage* child_storage = 0;
CV_FUNCNAME("icvStartScanGraph");
__BEGIN__;
if( !graph || !scanner )
CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );
if( !(graph->storage ))
CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );
memset( scanner, 0, sizeof(*scanner));
scanner->graph = graph;
scanner->mask = mask;
scanner->vtx = vtx;
scanner->index = vtx == 0 ? 0 : -1;
CV_CALL( child_storage = cvCreateChildMemStorage( graph->storage ));
CV_CALL( scanner->stack = cvCreateSeq( 0, sizeof(CvSet),
sizeof(CvGraphItem), child_storage ));
CV_CALL( icvSeqElemsClearMask( (CvSeq*)graph,
CV_FIELD_OFFSET( flags, CvGraphVtx ),
CV_GRAPH_ITEM_VISITED_FLAG|
CV_GRAPH_SEARCH_TREE_NODE_FLAG ));
CV_CALL( icvSeqElemsClearMask( (CvSeq*)(graph->edges),
CV_FIELD_OFFSET( flags, CvGraphEdge ),
CV_GRAPH_ITEM_VISITED_FLAG ));
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseMemStorage( &child_storage );
}
Blob::Blob(const CvSeq* _edges)
: perimeter_(*this),
area_(*this),
ellipse_(*this),
bounding_rect_(*this)
{
CV_FUNCNAME( "Blob::Blob(const CvSeq*)" );
__BEGIN__;
ISL_CALL( this->alloc() );
ISL_CALL( this->copy_edges(_edges) );
__END__;
if( cvGetErrStatus() < 0 )
this->release();
__ISL_CHECK_ERROR__;
}
// Create CvMat header only
CV_IMPL CvMat*
cvCreateMatHeader( int height, int width, int type )
{
CvMat* arr = 0;
CV_FUNCNAME( "cvCreateMatHeader" );
__BEGIN__;
CV_CALL( arr = (CvMat*)cvAlloc( sizeof(*arr)));
CV_CALL( cvInitMatHeader( arr, height, width, type, 0,
icvAlign(width*cvPixSize(type),4) ));
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseMatHeader( &arr );
return arr;
}
// create IplImage header and allocate underlying data
CV_IMPL IplImage *
cvCreateImage( CvSize size, int depth, int channels )
{
IplImage *img = 0;
CV_FUNCNAME( "cvCreateImage" );
__BEGIN__;
CV_CALL( img = cvCreateImageHeader( size, depth, channels ));
assert( img );
CV_CALL( cvCreateData( img ));
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseImage( &img );
return img;
}
CvGLCM*
cvCreateGLCM( const IplImage* srcImage,
int stepMagnitude,
const int* srcStepDirections,/* should be static array..
or if not the user should handle de-allocation */
int numStepDirections,
int optimizationType )
{
static const int defaultStepDirections[] = { 0,1, -1,1, -1,0, -1,-1 };
int* memorySteps = 0;
CvGLCM* newGLCM = 0;
int* stepDirections = 0;
CV_FUNCNAME( "cvCreateGLCM" );
__BEGIN__;
uchar* srcImageData = 0;
CvSize srcImageSize;
int srcImageStep;
int stepLoop;
const int maxNumGreyLevels8u = CV_MAX_NUM_GREY_LEVELS_8U;
if( !srcImage )
CV_ERROR( CV_StsNullPtr, "" );
if( srcImage->nChannels != 1 )
CV_ERROR( CV_BadNumChannels, "Number of channels must be 1");
if( srcImage->depth != IPL_DEPTH_8U )
CV_ERROR( CV_BadDepth, "Depth must be equal IPL_DEPTH_8U");
// no Directions provided, use the default ones - 0 deg, 45, 90, 135
if( !srcStepDirections )
{
srcStepDirections = defaultStepDirections;
}
CV_CALL( stepDirections = (int*)cvAlloc( numStepDirections*2*sizeof(stepDirections[0])));
memcpy( stepDirections, srcStepDirections, numStepDirections*2*sizeof(stepDirections[0]));
cvGetRawData( srcImage, &srcImageData, &srcImageStep, &srcImageSize );
// roll together Directions and magnitudes together with knowledge of image (step)
CV_CALL( memorySteps = (int*)cvAlloc( numStepDirections*sizeof(memorySteps[0])));
for( stepLoop = 0; stepLoop < numStepDirections; stepLoop++ )
{
stepDirections[stepLoop*2 + 0] *= stepMagnitude;
stepDirections[stepLoop*2 + 1] *= stepMagnitude;
memorySteps[stepLoop] = stepDirections[stepLoop*2 + 0]*srcImageStep +
stepDirections[stepLoop*2 + 1];
}
CV_CALL( newGLCM = (CvGLCM*)cvAlloc(sizeof(newGLCM[0])));
memset( newGLCM, 0, sizeof(newGLCM[0]) );
//memset( newGLCM, 0, sizeof(newGLCM) );
newGLCM->matrices = 0;
newGLCM->numMatrices = numStepDirections;
newGLCM->optimizationType = optimizationType;
if( optimizationType <= CV_GLCM_OPTIMIZATION_LUT )
{
int lookupTableLoop, imageColLoop, imageRowLoop, lineOffset = 0;
// if optimization type is set to lut, then make one for the image
if( optimizationType == CV_GLCM_OPTIMIZATION_LUT )
{
for( imageRowLoop = 0; imageRowLoop < srcImageSize.height;
imageRowLoop++, lineOffset += srcImageStep )
{
for( imageColLoop = 0; imageColLoop < srcImageSize.width; imageColLoop++ )
{
newGLCM->forwardLookupTable[srcImageData[lineOffset+imageColLoop]]=1;
}
}
newGLCM->numLookupTableElements = 0;
for( lookupTableLoop = 0; lookupTableLoop < maxNumGreyLevels8u; lookupTableLoop++ )
{
if( newGLCM->forwardLookupTable[ lookupTableLoop ] != 0 )
{
newGLCM->forwardLookupTable[ lookupTableLoop ] =
newGLCM->numLookupTableElements;
newGLCM->reverseLookupTable[ newGLCM->numLookupTableElements ] =
lookupTableLoop;
newGLCM->numLookupTableElements++;
}
}
}
// otherwise make a "LUT" which contains all the gray-levels (for code-reuse)
else if( optimizationType == CV_GLCM_OPTIMIZATION_NONE )
{
for( lookupTableLoop = 0; lookupTableLoop <maxNumGreyLevels8u; lookupTableLoop++ )
{
newGLCM->forwardLookupTable[ lookupTableLoop ] = lookupTableLoop;
newGLCM->reverseLookupTable[ lookupTableLoop ] = lookupTableLoop;
}
newGLCM->numLookupTableElements = maxNumGreyLevels8u;
}
newGLCM->matrixSideLength = newGLCM->numLookupTableElements;
icvCreateGLCM_LookupTable_8u_C1R( srcImageData, srcImageStep, srcImageSize,
newGLCM, stepDirections,
numStepDirections, memorySteps );
}
else if( optimizationType == CV_GLCM_OPTIMIZATION_HISTOGRAM )
{
CV_ERROR( CV_StsBadFlag, "Histogram-based method is not implemented" );
/* newGLCM->numMatrices *= 2;
newGLCM->matrixSideLength = maxNumGreyLevels8u*2;
icvCreateGLCM_Histogram_8uC1R( srcImageStep, srcImageSize, srcImageData,
newGLCM, numStepDirections,
stepDirections, memorySteps );
*/
}
__END__;
cvFree( &memorySteps );
cvFree( &stepDirections );
if( cvGetErrStatus() < 0 )
{
cvFree( &newGLCM );
}
return newGLCM;
}
/*
Initializes scanner structure.
Prepare image for scanning ( clear borders and convert all pixels to 0-1.
*/
CV_IMPL CvContourScanner
cvStartFindContours( void* _img, CvMemStorage* storage,
int header_size, int mode,
int method, CvPoint offset )
{
int y;
int step;
CvSize size;
uchar *img = 0;
CvContourScanner scanner = 0;
CvMat stub, *mat = (CvMat*)_img;
CV_FUNCNAME( "cvStartFindContours" );
__BEGIN__;
if( !storage )
CV_ERROR( CV_StsNullPtr, "" );
CV_CALL( mat = cvGetMat( mat, &stub ));
if( !CV_IS_MASK_ARR( mat ))
CV_ERROR( CV_StsUnsupportedFormat, "[Start]FindContours support only 8uC1 images" );
size = cvSize( mat->width, mat->height );
step = mat->step;
img = (uchar*)(mat->data.ptr);
if( method < 0 || method > CV_CHAIN_APPROX_TC89_KCOS )
CV_ERROR_FROM_STATUS( CV_BADRANGE_ERR );
if( header_size < (int) (method == CV_CHAIN_CODE ? sizeof( CvChain ) : sizeof( CvContour )))
CV_ERROR_FROM_STATUS( CV_BADSIZE_ERR );
scanner = (CvContourScanner)cvAlloc( sizeof( *scanner ));
if( !scanner )
CV_ERROR_FROM_STATUS( CV_OUTOFMEM_ERR );
memset( scanner, 0, sizeof( *scanner ));
scanner->storage1 = scanner->storage2 = storage;
scanner->img0 = (char *) img;
scanner->img = (char *) (img + step);
scanner->img_step = step;
scanner->img_size.width = size.width - 1; /* exclude rightest column */
scanner->img_size.height = size.height - 1; /* exclude bottomost row */
scanner->mode = mode;
scanner->offset = offset;
scanner->pt.x = scanner->pt.y = 1;
scanner->lnbd.x = 0;
scanner->lnbd.y = 1;
scanner->nbd = 2;
scanner->mode = (int) mode;
scanner->frame_info.contour = &(scanner->frame);
scanner->frame_info.is_hole = 1;
scanner->frame_info.next = 0;
scanner->frame_info.parent = 0;
scanner->frame_info.rect = cvRect( 0, 0, size.width, size.height );
scanner->l_cinfo = 0;
scanner->subst_flag = 0;
scanner->frame.flags = CV_SEQ_FLAG_HOLE;
scanner->approx_method2 = scanner->approx_method1 = method;
if( method == CV_CHAIN_APPROX_TC89_L1 || method == CV_CHAIN_APPROX_TC89_KCOS )
scanner->approx_method1 = CV_CHAIN_CODE;
if( scanner->approx_method1 == CV_CHAIN_CODE )
{
scanner->seq_type1 = CV_SEQ_CHAIN_CONTOUR;
scanner->header_size1 = scanner->approx_method1 == scanner->approx_method2 ?
header_size : sizeof( CvChain );
scanner->elem_size1 = sizeof( char );
}
else
{
scanner->seq_type1 = CV_SEQ_POLYGON;
scanner->header_size1 = scanner->approx_method1 == scanner->approx_method2 ?
header_size : sizeof( CvContour );
scanner->elem_size1 = sizeof( CvPoint );
}
scanner->header_size2 = header_size;
if( scanner->approx_method2 == CV_CHAIN_CODE )
{
scanner->seq_type2 = scanner->seq_type1;
scanner->elem_size2 = scanner->elem_size1;
}
else
{
scanner->seq_type2 = CV_SEQ_POLYGON;
scanner->elem_size2 = sizeof( CvPoint );
}
scanner->seq_type1 = scanner->approx_method1 == CV_CHAIN_CODE ?
CV_SEQ_CHAIN_CONTOUR : CV_SEQ_POLYGON;
scanner->seq_type2 = scanner->approx_method2 == CV_CHAIN_CODE ?
CV_SEQ_CHAIN_CONTOUR : CV_SEQ_POLYGON;
cvSaveMemStoragePos( storage, &(scanner->initial_pos) );
if( method > CV_CHAIN_APPROX_SIMPLE )
{
scanner->storage1 = cvCreateChildMemStorage( scanner->storage2 );
}
if( mode > CV_RETR_LIST )
{
scanner->cinfo_storage = cvCreateChildMemStorage( scanner->storage2 );
scanner->cinfo_set = cvCreateSet( 0, sizeof( CvSet ), sizeof( _CvContourInfo ),
scanner->cinfo_storage );
if( scanner->cinfo_storage == 0 || scanner->cinfo_set == 0 )
CV_ERROR_FROM_STATUS( CV_OUTOFMEM_ERR );
}
/* make zero borders */
memset( img, 0, size.width );
memset( img + step * (size.height - 1), 0, size.width );
for( y = 1, img += step; y < size.height - 1; y++, img += step )
{
img[0] = img[size.width - 1] = 0;
}
/* converts all pixels to 0 or 1 */
cvThreshold( mat, mat, 0, 1, CV_THRESH_BINARY );
CV_CHECK();
__END__;
if( cvGetErrStatus() < 0 )
cvFree( &scanner );
return scanner;
}
static void
icvCreateGLCM_LookupTable_8u_C1R( const uchar* srcImageData,
int srcImageStep,
CvSize srcImageSize,
CvGLCM* destGLCM,
int* steps,
int numSteps,
int* memorySteps )
{
int* stepIncrementsCounter = 0;
CV_FUNCNAME( "icvCreateGLCM_LookupTable_8u_C1R" );
__BEGIN__;
int matrixSideLength = destGLCM->matrixSideLength;
int stepLoop, sideLoop1, sideLoop2;
int colLoop, rowLoop, lineOffset = 0;
double*** matrices = 0;
// allocate memory to the matrices
CV_CALL( destGLCM->matrices = (double***)cvAlloc( sizeof(matrices[0])*numSteps ));
matrices = destGLCM->matrices;
for( stepLoop=0; stepLoop<numSteps; stepLoop++ )
{
CV_CALL( matrices[stepLoop] = (double**)cvAlloc( sizeof(matrices[0][0])*matrixSideLength ));
CV_CALL( matrices[stepLoop][0] = (double*)cvAlloc( sizeof(matrices[0][0][0])*
matrixSideLength*matrixSideLength ));
memset( matrices[stepLoop][0], 0, matrixSideLength*matrixSideLength*
sizeof(matrices[0][0][0]) );
for( sideLoop1 = 1; sideLoop1 < matrixSideLength; sideLoop1++ )
{
matrices[stepLoop][sideLoop1] = matrices[stepLoop][sideLoop1-1] + matrixSideLength;
}
}
CV_CALL( stepIncrementsCounter = (int*)cvAlloc( numSteps*sizeof(stepIncrementsCounter[0])));
memset( stepIncrementsCounter, 0, numSteps*sizeof(stepIncrementsCounter[0]) );
// generate GLCM for each step
for( rowLoop=0; rowLoop<srcImageSize.height; rowLoop++, lineOffset+=srcImageStep )
{
for( colLoop=0; colLoop<srcImageSize.width; colLoop++ )
{
int pixelValue1 = destGLCM->forwardLookupTable[srcImageData[lineOffset + colLoop]];
for( stepLoop=0; stepLoop<numSteps; stepLoop++ )
{
int col2, row2;
row2 = rowLoop + steps[stepLoop*2 + 0];
col2 = colLoop + steps[stepLoop*2 + 1];
if( col2>=0 && row2>=0 && col2<srcImageSize.width && row2<srcImageSize.height )
{
int memoryStep = memorySteps[ stepLoop ];
int pixelValue2 = destGLCM->forwardLookupTable[ srcImageData[ lineOffset + colLoop + memoryStep ] ];
// maintain symmetry
matrices[stepLoop][pixelValue1][pixelValue2] ++;
matrices[stepLoop][pixelValue2][pixelValue1] ++;
// incremenet counter of total number of increments
stepIncrementsCounter[stepLoop] += 2;
}
}
}
}
// normalize matrices. each element is a probability of gray value i,j adjacency in direction/magnitude k
for( sideLoop1=0; sideLoop1<matrixSideLength; sideLoop1++ )
{
for( sideLoop2=0; sideLoop2<matrixSideLength; sideLoop2++ )
{
for( stepLoop=0; stepLoop<numSteps; stepLoop++ )
{
matrices[stepLoop][sideLoop1][sideLoop2] /= double(stepIncrementsCounter[stepLoop]);
}
}
}
destGLCM->matrices = matrices;
__END__;
cvFree( &stepIncrementsCounter );
if( cvGetErrStatus() < 0 )
cvReleaseGLCM( &destGLCM, CV_GLCM_GLCM );
}
void
cvCreateGLCMDescriptors( CvGLCM* destGLCM, int descriptorOptimizationType )
{
CV_FUNCNAME( "cvCreateGLCMDescriptors" );
__BEGIN__;
int matrixLoop;
if( !destGLCM )
CV_ERROR( CV_StsNullPtr, "" );
if( !(destGLCM->matrices) )
CV_ERROR( CV_StsNullPtr, "Matrices are not allocated" );
CV_CALL( cvReleaseGLCM( &destGLCM, CV_GLCM_DESC ));
if( destGLCM->optimizationType != CV_GLCM_OPTIMIZATION_HISTOGRAM )
{
destGLCM->descriptorOptimizationType = destGLCM->numDescriptors = descriptorOptimizationType;
}
else
{
CV_ERROR( CV_StsBadFlag, "Histogram-based method is not implemented" );
// destGLCM->descriptorOptimizationType = destGLCM->numDescriptors = CV_GLCMDESC_OPTIMIZATION_HISTOGRAM;
}
CV_CALL( destGLCM->descriptors = (double**)
cvAlloc( destGLCM->numMatrices*sizeof(destGLCM->descriptors[0])));
for( matrixLoop = 0; matrixLoop < destGLCM->numMatrices; matrixLoop ++ )
{
CV_CALL( destGLCM->descriptors[ matrixLoop ] =
(double*)cvAlloc( destGLCM->numDescriptors*sizeof(destGLCM->descriptors[0][0])));
memset( destGLCM->descriptors[matrixLoop], 0, destGLCM->numDescriptors*sizeof(destGLCM->descriptors[0][0]) );
switch( destGLCM->descriptorOptimizationType )
{
case CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST:
icvCreateGLCMDescriptors_AllowDoubleNest( destGLCM, matrixLoop );
break;
default:
CV_ERROR( CV_StsBadFlag,
"descriptorOptimizationType different from CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST\n"
"is not supported" );
/*
case CV_GLCMDESC_OPTIMIZATION_ALLOWTRIPLENEST:
icvCreateGLCMDescriptors_AllowTripleNest( destGLCM, matrixLoop );
break;
case CV_GLCMDESC_OPTIMIZATION_HISTOGRAM:
if(matrixLoop < destGLCM->numMatrices>>1)
icvCreateGLCMDescriptors_Histogram( destGLCM, matrixLoop);
break;
*/
}
}
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseGLCM( &destGLCM, CV_GLCM_DESC );
}
static void*
icvLoadImage( const char* filename, int flags, bool load_as_matrix )
{
GrFmtReader* reader = 0;
IplImage* image = 0;
CvMat hdr, *matrix = 0;
int depth = 8;
CV_FUNCNAME( "cvLoadImage" );
__BEGIN__;
CvSize size;
int iscolor;
int cn;
if( !filename || strlen(filename) == 0 )
CV_ERROR( CV_StsNullPtr, "null filename" );
reader = g_Filters.FindReader( filename );
if( !reader )
EXIT;
if( !reader->ReadHeader() )
EXIT;
size.width = reader->GetWidth();
size.height = reader->GetHeight();
if( flags == -1 )
iscolor = reader->IsColor();
else
{
if( (flags & CV_LOAD_IMAGE_COLOR) != 0 ||
((flags & CV_LOAD_IMAGE_ANYCOLOR) != 0 && reader->IsColor()) )
iscolor = 1;
else
iscolor = 0;
if( (flags & CV_LOAD_IMAGE_ANYDEPTH) != 0 )
{
reader->UseNativeDepth(true);
depth = reader->GetDepth();
}
}
cn = iscolor ? 3 : 1;
if( load_as_matrix )
{
int type;
if(reader->IsFloat() && depth != 8)
type = CV_32F;
else
type = ( depth <= 8 ) ? CV_8U : ( depth <= 16 ) ? CV_16U : CV_32S;
CV_CALL( matrix = cvCreateMat( size.height, size.width, CV_MAKETYPE(type, cn) ));
}
else
{
int type;
if(reader->IsFloat() && depth != 8)
type = IPL_DEPTH_32F;
else
type = ( depth <= 8 ) ? IPL_DEPTH_8U : ( depth <= 16 ) ? IPL_DEPTH_16U : IPL_DEPTH_32S;
CV_CALL( image = cvCreateImage( size, type, cn ));
matrix = cvGetMat( image, &hdr );
}
if( !reader->ReadData( matrix->data.ptr, matrix->step, iscolor ))
{
if( load_as_matrix )
cvReleaseMat( &matrix );
else
cvReleaseImage( &image );
EXIT;
}
__END__;
delete reader;
if( cvGetErrStatus() < 0 )
{
if( load_as_matrix )
cvReleaseMat( &matrix );
else
cvReleaseImage( &image );
}
return load_as_matrix ? (void*)matrix : (void*)image;
}
CV_IMPL int
cvSaveImage( const char* filename, const CvArr* arr )
{
int origin = 0;
GrFmtWriter* writer = 0;
CvMat *temp = 0, *temp2 = 0;
CV_FUNCNAME( "cvSaveImage" );
__BEGIN__;
CvMat stub, *image;
int channels, ipl_depth;
if( !filename || strlen(filename) == 0 )
CV_ERROR( CV_StsNullPtr, "null filename" );
CV_CALL( image = cvGetMat( arr, &stub ));
if( CV_IS_IMAGE( arr ))
origin = ((IplImage*)arr)->origin;
channels = CV_MAT_CN( image->type );
if( channels != 1 && channels != 3 && channels != 4 )
CV_ERROR( CV_BadNumChannels, "" );
writer = g_Filters.FindWriter( filename );
if( !writer )
CV_ERROR( CV_StsError, "could not find a filter for the specified extension" );
if( origin )
{
CV_CALL( temp = cvCreateMat(image->rows, image->cols, image->type) );
CV_CALL( cvFlip( image, temp, 0 ));
image = temp;
}
ipl_depth = cvCvToIplDepth(image->type);
if( !writer->IsFormatSupported(ipl_depth) )
{
assert( writer->IsFormatSupported(IPL_DEPTH_8U) );
CV_CALL( temp2 = cvCreateMat(image->rows,
image->cols, CV_MAKETYPE(CV_8U,channels)) );
CV_CALL( cvConvertImage( image, temp2 ));
image = temp2;
ipl_depth = IPL_DEPTH_8U;
}
if( !writer->WriteImage( image->data.ptr, image->step, image->width,
image->height, ipl_depth, channels ))
CV_ERROR( CV_StsError, "could not save the image" );
__END__;
delete writer;
cvReleaseMat( &temp );
cvReleaseMat( &temp2 );
return cvGetErrStatus() >= 0;
}
CV_IMPL CvBGStatModel*
cvCreateGaussianBGModel2( IplImage* first_frame, CvGaussBGStatModel2Params* parameters )
{
CvGaussBGModel2* bg_model = 0;
int w,h;
CV_FUNCNAME( "cvCreateGaussianBGModel2" );
__BEGIN__;
CvGaussBGStatModel2Params params;
if( !CV_IS_IMAGE(first_frame) )
CV_ERROR( CV_StsBadArg, "Invalid or NULL first_frame parameter" );
if( first_frame->nChannels>CV_BGFG_MOG2_NDMAX )
CV_ERROR( CV_StsBadArg, "Maxumum number of channels in the image is excedded (change CV_BGFG_MOG2_MAXBANDS constant)!" );
CV_CALL( bg_model = (CvGaussBGModel2*)cvAlloc( sizeof(*bg_model) ));
memset( bg_model, 0, sizeof(*bg_model) );
bg_model->type = CV_BG_MODEL_MOG2;
bg_model->release = (CvReleaseBGStatModel) icvReleaseGaussianBGModel2;
bg_model->update = (CvUpdateBGStatModel) icvUpdateGaussianBGModel2;
//init parameters
if( parameters == NULL )
{
memset(¶ms, 0, sizeof(params));
// These constants are defined in cvaux/include/cvaux.h
params.bShadowDetection = 1;
params.bPostFiltering=0;
params.minArea=CV_BGFG_MOG2_MINAREA;
//set parameters
// K - max number of Gaussians per pixel
params.nM = CV_BGFG_MOG2_NGAUSSIANS;//4;
// Tb - the threshold - n var
//pGMM->fTb = 4*4;
params.fTb = CV_BGFG_MOG2_STD_THRESHOLD*CV_BGFG_MOG2_STD_THRESHOLD;
// Tbf - the threshold
//pGMM->fTB = 0.9f;//1-cf from the paper
params.fTB = CV_BGFG_MOG2_BACKGROUND_THRESHOLD;
// Tgenerate - the threshold
params.fTg = CV_BGFG_MOG2_STD_THRESHOLD_GENERATE*CV_BGFG_MOG2_STD_THRESHOLD_GENERATE;//update the mode or generate new
//pGMM->fSigma= 11.0f;//sigma for the new mode
params.fVarInit = CV_BGFG_MOG2_VAR_INIT;
params.fVarMax = CV_BGFG_MOG2_VAR_MAX;
params.fVarMin = CV_BGFG_MOG2_VAR_MIN;
// alpha - the learning factor
params.fAlphaT = 1.0f/CV_BGFG_MOG2_WINDOW_SIZE;//0.003f;
// complexity reduction prior constant
params.fCT = CV_BGFG_MOG2_CT;//0.05f;
//shadow
// Shadow detection
params.nShadowDetection = (unsigned char)CV_BGFG_MOG2_SHADOW_VALUE;//value 0 to turn off
params.fTau = CV_BGFG_MOG2_SHADOW_TAU;//0.5f;// Tau - shadow threshold
}
else
{
params = *parameters;
}
bg_model->params = params;
//image data
w = first_frame->width;
h = first_frame->height;
bg_model->params.nWidth = w;
bg_model->params.nHeight = h;
bg_model->params.nND = first_frame->nChannels;
//allocate GMM data
//GMM for each pixel
bg_model->data.rGMM = (CvPBGMMGaussian*) malloc(w*h * params.nM * sizeof(CvPBGMMGaussian));
//used modes per pixel
bg_model->data.rnUsedModes = (unsigned char* ) malloc(w*h);
memset(bg_model->data.rnUsedModes,0,w*h);//no modes used
//prepare storages
CV_CALL( bg_model->background = cvCreateImage(cvSize(w,h), IPL_DEPTH_8U, first_frame->nChannels));
CV_CALL( bg_model->foreground = cvCreateImage(cvSize(w,h), IPL_DEPTH_8U, 1));
//for eventual filtering
CV_CALL( bg_model->storage = cvCreateMemStorage());
bg_model->countFrames = 0;
__END__;
if( cvGetErrStatus() < 0 )
{
CvBGStatModel* base_ptr = (CvBGStatModel*)bg_model;
if( bg_model && bg_model->release )
bg_model->release( &base_ptr );
else
cvFree( &bg_model );
bg_model = 0;
}
return (CvBGStatModel*)bg_model;
}
CV_IMPL CvBGStatModel*
cvCreateGaussianBGModel( IplImage* first_frame, CvGaussBGStatModelParams* parameters )
{
CvGaussBGModel* bg_model = 0;
CV_FUNCNAME( "cvCreateGaussianBGModel" );
__BEGIN__;
double var_init;
CvGaussBGStatModelParams params;
int i, j, k, m, n;
//init parameters
if( parameters == NULL )
{ /* These constants are defined in cvaux/include/cvaux.h: */
params.win_size = CV_BGFG_MOG_WINDOW_SIZE;
params.bg_threshold = CV_BGFG_MOG_BACKGROUND_THRESHOLD;
params.std_threshold = CV_BGFG_MOG_STD_THRESHOLD;
params.weight_init = CV_BGFG_MOG_WEIGHT_INIT;
params.variance_init = CV_BGFG_MOG_SIGMA_INIT*CV_BGFG_MOG_SIGMA_INIT;
params.minArea = CV_BGFG_MOG_MINAREA;
params.n_gauss = CV_BGFG_MOG_NGAUSSIANS;
}
else
{
params = *parameters;
}
if( !CV_IS_IMAGE(first_frame) )
CV_ERROR( CV_StsBadArg, "Invalid or NULL first_frame parameter" );
CV_CALL( bg_model = (CvGaussBGModel*)cvAlloc( sizeof(*bg_model) ));
memset( bg_model, 0, sizeof(*bg_model) );
bg_model->type = CV_BG_MODEL_MOG;
bg_model->release = (CvReleaseBGStatModel)icvReleaseGaussianBGModel;
bg_model->update = (CvUpdateBGStatModel)icvUpdateGaussianBGModel;
bg_model->params = params;
//prepare storages
CV_CALL( bg_model->g_point = (CvGaussBGPoint*)cvAlloc(sizeof(CvGaussBGPoint)*
((first_frame->width*first_frame->height) + 256)));
CV_CALL( bg_model->background = cvCreateImage(cvSize(first_frame->width,
first_frame->height), IPL_DEPTH_8U, first_frame->nChannels));
CV_CALL( bg_model->foreground = cvCreateImage(cvSize(first_frame->width,
first_frame->height), IPL_DEPTH_8U, 1));
CV_CALL( bg_model->storage = cvCreateMemStorage());
//initializing
var_init = 2 * params.std_threshold * params.std_threshold;
CV_CALL( bg_model->g_point[0].g_values =
(CvGaussBGValues*)cvAlloc( sizeof(CvGaussBGValues)*params.n_gauss*
(first_frame->width*first_frame->height + 128)));
for( i = 0, n = 0; i < first_frame->height; i++ )
{
for( j = 0; j < first_frame->width; j++, n++ )
{
const int p = i*first_frame->widthStep+j*first_frame->nChannels;
bg_model->g_point[n].g_values =
bg_model->g_point[0].g_values + n*params.n_gauss;
bg_model->g_point[n].g_values[0].weight = 1; //the first value seen has weight one
bg_model->g_point[n].g_values[0].match_sum = 1;
for( m = 0; m < first_frame->nChannels; m++)
{
bg_model->g_point[n].g_values[0].variance[m] = var_init;
bg_model->g_point[n].g_values[0].mean[m] = (unsigned char)first_frame->imageData[p + m];
}
for( k = 1; k < params.n_gauss; k++)
{
bg_model->g_point[n].g_values[k].weight = 0;
bg_model->g_point[n].g_values[k].match_sum = 0;
for( m = 0; m < first_frame->nChannels; m++){
bg_model->g_point[n].g_values[k].variance[m] = var_init;
bg_model->g_point[n].g_values[k].mean[m] = 0;
}
}
}
}
bg_model->countFrames = 0;
__END__;
if( cvGetErrStatus() < 0 )
{
CvBGStatModel* base_ptr = (CvBGStatModel*)bg_model;
if( bg_model && bg_model->release )
bg_model->release( &base_ptr );
else
cvFree( &bg_model );
bg_model = 0;
}
return (CvBGStatModel*)bg_model;
}
int testfaceLib_pThread ( const char* str_video, int trackerType, int multiviewType, int recognizerType, const char* str_facesetxml, int threads,
bool blink, bool smile, bool gender, bool age, bool recog, bool quiet, bool saveface, const char* sfolder, bool bEnableAutoCluster )
{
FILE* fp_imaginfo = fopen( "imaginfo.txt", "w" );
bool bAutoFocus = false;
IplImage *imgAutoFocus = NULL;
int sampleRate =1;
if(str_facesetxml == NULL)
str_facesetxml = "faceset_model.xml";
int prob_estimate[7];
char sState[256];
EnumViewAngle viewAngle = (EnumViewAngle)multiviewType;
//dynamic clustering for smooth ID registration
//bEnableAutoCluster = true;
CxlibFaceAnalyzer faceAnalyzer(viewAngle, (EnumTrackerType)trackerType, blink, smile, gender, age, recog, sampleRate, str_facesetxml, recognizerType, bEnableAutoCluster);
/////////////////////////////////////////////////////////////////////////////////////
// init GUI window
const char* str_title = "Face Tester";
if( ! quiet )
cvNamedWindow( str_title, CV_WINDOW_AUTOSIZE );
char sCaptionInfo[256] = "";
CvFont *pFont = new CvFont;
cvInitFont(pFont, CV_FONT_HERSHEY_PLAIN, 0.85, 0.85, 0, 1);
// load GUI smile icon images
IplImage *pImgSmileBGR;
IplImage *pImgSmileMask;
if(age == 0)
{ // smile icon
pImgSmileBGR = cvLoadImage( "smile.bmp" );
pImgSmileMask = cvLoadImage( "smilemask.bmp", 0 );
}
else
{ // gender/age/smile icons
pImgSmileBGR = cvLoadImage( "faceicon.bmp" );
pImgSmileMask = cvLoadImage( "faceiconMask.bmp", 0 );
}
IplImage *pImgSmileBGRA = cvCreateImage( cvSize(pImgSmileBGR->width, pImgSmileBGR->height), IPL_DEPTH_8U, 4 );
cvCvtColor(pImgSmileBGR, pImgSmileBGRA, CV_BGR2BGRA );
// open video source
size_t len = strlen( str_video );
bool is_piclist = (0 == stricmp( str_video + len - 4, ".txt" ));
CxImageSeqReader* vidcap = NULL;
if( is_piclist )
vidcap = new CxPicListReader( str_video );
else
vidcap = new CxVideoReader( str_video );
if( cvGetErrStatus() < 0 )
{
cvSetErrStatus( CV_StsOk );
return -1;
}
// when using camera, set to 640x480, 30fps
if( isdigit(str_video[0]) != 0 && str_video[1] == '\0' )
{
vidcap->width( 640 );
vidcap->height( 480 );
vidcap->fps( 30 );
}
// print beginning info
printf( "tracker cascade: '%s'\n", trackerType== TRA_HAAR ? "haar" : (recognizerType== TRA_SURF ? "surf" : "pf tracker SURF"));
printf( "face recognizer: '%s'\n", recognizerType == RECOGNIZER_BOOST_GB240 ? "boost gabor240" : "cascade gloh" );
printf( "video: '%s', %dx%d, %2.1f fps\n", str_video,
vidcap->width(), vidcap->height(), vidcap->fps() );
// set mouse event process
CxMouseParam mouse_faceparam;
mouse_faceparam.updated = false;
mouse_faceparam.play = true;
mouse_faceparam.ret_online_collecting = 0;
static const int MAX_FACES = 16;
if(! quiet)
{
mouse_faceparam.play = true;
mouse_faceparam.updated = false;
mouse_faceparam.face_num = faceAnalyzer.getMaxFaceNum();
mouse_faceparam.rects = faceAnalyzer.getFaceRects();
mouse_faceparam.image = NULL;
mouse_faceparam.cut_big_face= faceAnalyzer.getBigCutFace();
mouse_faceparam.typeRecognizer = 0;
mouse_faceparam.faceRecognizer = &faceAnalyzer;
mouse_faceparam.ret_online_collecting = 0;
cvSetMouseCallback( str_title, my_mouse_callback, (void*)&mouse_faceparam );
faceAnalyzer.setMouseParam(&mouse_faceparam);
}
// init count ticks
int64 ticks, start_ticks, total_ticks;
int64 tracker_total_ticks;
double tracker_fps, total_fps;
start_ticks = total_ticks = 0;
tracker_total_ticks = 0;
// loop for each frame of a video/camera
int frames = 0;
IplImage *pImg = NULL;
while( ! vidcap->eof() )
{
// capture a video frame
if( mouse_faceparam.play == true)
pImg = vidcap->query();
else
continue;
if ( pImg == NULL )
break;
// make a copy, flip if upside-down
CvImage image( cvGetSize(pImg), pImg->depth, pImg->nChannels );
if( pImg->origin == IPL_ORIGIN_BL ) //flip live camera's frame
cvFlip( pImg, image );
else
cvCopy( pImg, image );
// convert to gray_image for face analysis
CvImage gray_image( image.size(), image.depth(), 1 );
if( image.channels() == 3 )
cvCvtColor( image, gray_image, CV_BGR2GRAY );
else
cvCopy( image, gray_image );
///////////////////////////////////////////////////////////////////
// do face tracking and face recognition
start_ticks = ticks = cvGetTickCount();
if( is_piclist )
faceAnalyzer.detect(gray_image, prob_estimate, sState);
else
faceAnalyzer.track(gray_image, prob_estimate, sState, image); // track face in each frame but recognize by pthread
//faceAnalyzer.detect(gray_image, prob_estimate, sState);// track and recognizer face in each frame
int face_num = faceAnalyzer.getFaceNum();
ticks = cvGetTickCount() - ticks;
tracker_fps = 1000.0 / ( 1e-3 * ticks / cvGetTickFrequency() );
tracker_total_ticks += ticks;
//set param for mouse event processing
if(!quiet)
{
mouse_faceparam.face_num = face_num;
mouse_faceparam.image = image;
}
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, "%s %d", vidcap->filename(), face_num );
// blink/smile/gender/age/face recognize section
for( int i=0; i<face_num; i++ )
{
// get face rect and id from face tracker
CvRectItem rectItem = faceAnalyzer.getFaceRect(i);
CvRect rect = rectItem.rc;
int face_trackid = rectItem.fid;
float probSmile = faceAnalyzer.getFaceSmileProb(i);
int bBlink = faceAnalyzer.getFaceBlink(i);
int bSmile = faceAnalyzer.getFaceSmile(i);
int bGender = faceAnalyzer.getFaceGender(i);
int nAgeID = faceAnalyzer.getFaceAge(i);
int nFaceID = faceAnalyzer.getFaceID(i);
float fFaceProb= faceAnalyzer.getFaceProb(i);
char *sFaceCaption = NULL;
char sFaceNameBuff[256];
char *sFaceName = faceAnalyzer.getFaceName(i);
if(sFaceName[0] != '\0')
{
sprintf(sFaceNameBuff, "%s %.2f", sFaceName, fFaceProb);
sFaceCaption = sFaceName;
sFaceCaption = sFaceNameBuff;
}
if( ! quiet )
{
CvPoint2D32f *landmark6 = NULL;
sprintf(sCaptionInfo, "FPS:%04d, %s", (int)tracker_fps, sState);
int trackid = -1; //face_trackid , don't display trackid if -1
cxlibDrawFaceBlob( image, pFont, trackid, rect, landmark6, probSmile,
bBlink, bSmile, bGender, nAgeID, sFaceCaption, NULL,
pImgSmileBGR, pImgSmileBGRA, pImgSmileMask);
}
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, " %d %d %d %d", rect.x, rect.y, rect.width, rect.height );
}
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, "\n" );
///////////////////////////////////////////////////////////////////
total_ticks += (cvGetTickCount() - start_ticks);
// frame face_num
frames++;
//auto focus faces
if(quiet == false && bAutoFocus)
{
if(imgAutoFocus)
cvCopy(image, imgAutoFocus);
else
imgAutoFocus = cvCloneImage(image);
CvRectItem *rects = faceAnalyzer.getFaceRects();
cxlibAutoFocusFaceImage(imgAutoFocus, image, rects, face_num);
}
// next frame if quiet
if( quiet )
continue;
else
{
// draw status info for custom interaction
if(mouse_faceparam.ret_online_collecting == 1)
{
sprintf(sCaptionInfo, "Collecting faces for track_id = %d", mouse_faceparam.ret_facetrack_id);
//draw face collecting region
cvLine(image, cvPoint(image.width()/4, 0), cvPoint(image.width()/4, image.height()-1), CV_RGB(255,255,0), 2);
cvLine(image, cvPoint(image.width()*3/4, 0), cvPoint(image.width()*3/4, image.height()-1), CV_RGB(255,255,0), 2);
}
else
sprintf(sCaptionInfo, "FPS:%04d, %s", (int)tracker_fps, sState);
cxlibDrawCaption( image, pFont, sCaptionInfo);
}
//show Image
if (image.width() <= 800)
cvShowImage( str_title, image );
else
{ // display scaled smaller aimge
CvImage scale_image (cvSize(800, image.height()*800/image.width()), image.depth(), 3 );
cvResize (image, scale_image);
cvShowImage( str_title, scale_image );
}
// user interaction
int key = cvWaitKey(1);
//int key = cvWaitKey(0);
if( key == ' ' ) // press space bar to pause the video play
cvWaitKey( 0 );
else if( key == 27 ) // press 'esc' to exit
break;
else if( key == 'a' )
{ // add new face name
if(face_num > 0)
{
CvRect rect = faceAnalyzer.getFaceRect(0).rc;
int x = rect.x+rect.width/2;
int y = rect.y+rect.height/2;
addFaceSet( x, y, &mouse_faceparam);
}
}
else if( key == 'c' )
{ //enable flag to collect face exemplars for the selected face name
mouse_faceparam.ret_online_collecting = 1; //enable online face exemplar collecting
}
else if( key == 'z' )
bAutoFocus = !bAutoFocus;
else if(key >= 0)
{
if(mouse_faceparam.ret_online_collecting == 1)
{ // stop collecting face exemplars
mouse_faceparam.ret_online_collecting = 0; //disable online face exemplar collecting
mouse_faceparam.ret_facetrack_id = -1;
}
if( key == 's')
{
// save faceset xml model
faceAnalyzer.saveFaceModelXML("faceset_model.xml");
sprintf(sCaptionInfo, "%s", "saved the face model");
cxlibDrawCaption( pImg, pFont, sCaptionInfo);
cvShowImage( str_title, pImg );
cvWaitKey( 400 );
}
}
}
// print info about fps
float temp = 1e-6f / cvGetTickFrequency();
tracker_fps = 1.0f / ( tracker_total_ticks * temp / frames );
total_fps = 1.0f / (total_ticks * temp / frames);
printf( "Total frames:%d Speed:%.1f fps\n", frames, total_fps);
printf( "FPS: %.1f ", tracker_fps);
//save updated faceset model
if(mouse_faceparam.updated == true)
{
sprintf(sCaptionInfo, "%s", "press key 's' to save updated face model or other keys to cancel");
cxlibDrawCaption( pImg, pFont, sCaptionInfo);
cvShowImage( str_title, pImg );
int key = cvWaitKey();
if( key == 's')
faceAnalyzer.saveFaceModelXML("faceset_model.xml");
}
//save merged face model for dynamic clustering of smoothID
vFaceSet vMergedFaceSet;
int minWeight =10;
faceAnalyzer.getMergedFaceSet(vMergedFaceSet, minWeight);
faceAnalyzer.saveFaceModelXML("faceset_modelMerged.xml", &vMergedFaceSet);
//release global GUI data
if( !quiet )
cvDestroyWindow( str_title );
cvReleaseImage(&pImgSmileBGR);
cvReleaseImage(&pImgSmileBGRA);
cvReleaseImage(&pImgSmileMask);
delete pFont;
delete vidcap;
if( fp_imaginfo != NULL )
fclose( fp_imaginfo );
return 0;
}
int testfaceLib_sThread ( const char* str_video, int trackerType, int multiviewType, int recognizerType, const char* str_facesetxml, int threads,
bool blink, bool smile, bool gender, bool age, bool recog, bool quiet, bool saveface, const char* sfolder, bool bEnableAutoCluster)
{
int faceimgID = 0;
char driver[8];
char dir[1024];
char fname[1024];
char ext[8];
char sImgPath[1024];
if(sfolder)
{
char sysCommand[128];
sprintf (sysCommand, "mkdir %s", sfolder);
system (sysCommand);
sprintf(sImgPath, "%s//%s", sfolder, "imaginfo.txt");
sprintf(fname, "%s//%s", sfolder, "faceinfo.txt");
}
else
{
sprintf(sImgPath, "%s", "imaginfo.txt");
sprintf(fname, "%s", "faceinfo.txt");
}
FILE* fp_imaginfo = fopen( sImgPath, "wt" );
FILE* fp_faceinfo = fopen( fname, "wt" );
bool bAutoFocus = false;
IplImage *imgAutoFocus = NULL;
/////////////////////////////////////////////////////////////////////////////////////
// init GUI window
const char* str_title = "Face Tester";
if( ! quiet )
cvNamedWindow( str_title, CV_WINDOW_AUTOSIZE );
char sCaptionInfo[256]="";
CvFont *pFont = new CvFont;
cvInitFont(pFont, CV_FONT_HERSHEY_PLAIN, 0.85, 0.85, 0, 1);
// load GUI smile icon images
IplImage *pImgSmileBGR;
IplImage *pImgSmileMask;
if(age == 0)
{
pImgSmileBGR = cvLoadImage( "smile.bmp" );
pImgSmileMask = cvLoadImage( "smilemask.bmp", 0 );
}
else
{
pImgSmileBGR = cvLoadImage( "faceicon.bmp" );
pImgSmileMask = cvLoadImage( "faceiconMask.bmp", 0 );
}
IplImage *pImgSmileBGRA = cvCreateImage( cvSize(pImgSmileBGR->width, pImgSmileBGR->height), IPL_DEPTH_8U, 4 );
cvCvtColor(pImgSmileBGR, pImgSmileBGRA, CV_BGR2BGRA );
// open video source
size_t len = strlen( str_video );
bool is_piclist = (0 == stricmp( str_video + len - 4, ".txt" ));
CxImageSeqReader* vidcap = NULL;
if( is_piclist )
vidcap = new CxPicListReader( str_video );
else
vidcap = new CxVideoReader( str_video );
if( cvGetErrStatus() < 0 )
{
cvSetErrStatus( CV_StsOk );
return -1;
}
// when using camera, set to 640x480, 30fps
if( isdigit(str_video[0]) != 0 && str_video[1] == '\0' )
{
vidcap->width( 640 );
vidcap->height( 480 );
vidcap->fps( 30 );
}
// print beginning info
printf( "tracker cascade: '%s'\n", trackerType == TRA_HAAR ? "haar" : (trackerType== TRA_SURF ? "surf" : "pf tracker SURF"));
printf( "face recognizer: '%s'\n", recognizerType == RECOGNIZER_BOOST_GB240 ? "boost gabor240" : "cascade gloh" );
printf( "video: '%s', %dx%d, %2.1f fps\n", str_video,
vidcap->width(), vidcap->height(), vidcap->fps() );
// config face tracker
const int face_max = 16;
CvRectItem rects[face_max];
tagDetectConfig configParam;
EnumViewAngle viewAngle = (EnumViewAngle)multiviewType;
CxlibFaceDetector detector;
detector.init(viewAngle, (EnumFeaType)trackerType);
detector.config( configParam );
CxlibFaceTracker tracker;
tracker.init(viewAngle, (EnumTrackerType)trackerType);
tracker.config( configParam, TR_NLEVEL_3 );
if( cvGetErrStatus() < 0 )
{
cvSetErrStatus( CV_StsOk );
return -1;
}
// config landmark detector
CvPoint2D32f landmark6[6+1]; // consider both 6-pt and 7-pt
float parameters[16];
bool bLandmark = false;
CxlibLandmarkDetector landmarkDetector(LDM_6PT);
int size_smallface = 64;
int size_bigface = 128;
CxlibAlignFace cutFace(size_smallface, size_bigface);
// config blink/smile/gender detector
int bBlink = 0, bSmile = 0, bGender = 0, bAge = 0; //+1, -1, otherwise 0: no process
float probBlink = 0, probSmile = 0, probGender = 0, probAge[4];
int nAgeID = 0;
CxlibBlinkDetector blinkDetector(size_smallface);
CxlibSmileDetector smileDetector(size_smallface);
CxlibGenderDetector genderDetector(size_smallface);
CxlibAgeDetector ageDetector(size_bigface);
// config face recognizer
float probFaceID = 0;
if(str_facesetxml == NULL)
str_facesetxml = "faceset_model.xml";
CxlibFaceRecognizer faceRecognizer( size_bigface, recognizerType );
if(recog) faceRecognizer.loadFaceModelXML(str_facesetxml);
// set mouse event process
CxMouseParam mouse_faceparam;
mouse_faceparam.updated = false;
mouse_faceparam.play = true;
mouse_faceparam.ret_online_collecting = 0;
if(! quiet)
{
mouse_faceparam.face_num = face_max;
mouse_faceparam.rects = rects;
mouse_faceparam.image = NULL;
mouse_faceparam.cut_big_face= cutFace.getBigCutFace();
mouse_faceparam.typeRecognizer = 1;
mouse_faceparam.faceRecognizer = &faceRecognizer;
cvSetMouseCallback( str_title, my_mouse_callback, (void*)&mouse_faceparam );
}
// init count ticks
int64 ticks, start_ticks, total_ticks;
int64 tracker_total_ticks, landmark_total_ticks, align_total_ticks,
blink_total_ticks, smile_total_ticks, gender_total_ticks, age_total_ticks, recg_total_ticks;
double frame_fps, tracker_fps, landmark_fps, align_fps, blink_fps, smile_fps, gender_fps, age_fps, recg_fps, total_fps;
start_ticks = total_ticks = 0;
tracker_total_ticks = landmark_total_ticks = align_total_ticks = 0;
blink_total_ticks = smile_total_ticks = gender_total_ticks = age_total_ticks = recg_total_ticks = 0;
tracker_fps = landmark_fps = align_fps = blink_fps = smile_fps = gender_fps = age_fps = recg_fps = total_fps = 0.0;
// loop for each frame of a video/camera
int frames = 0;
IplImage *pImg = NULL;
int print_faceid=-1;
float print_score = 0;
std::string print_facename;
bool bRunLandmark = blink || smile|| gender|| age|| recog || saveface;
IplImage *thumbnailImg = cvCreateImage(cvSize(THUMBNAIL_WIDTH, THUMBNAIL_HEIGHT), IPL_DEPTH_8U, 3);
//dynamic clustering for smooth ID registration
//bEnableAutoCluster = true;
if( is_piclist ) bEnableAutoCluster = false;
while( ! vidcap->eof() )
{
// capture a video frame
if( mouse_faceparam.play == true)
pImg = vidcap->query();
else
continue;
if ( pImg == NULL )
continue;
// make a copy, flip if upside-down
CvImage image( cvGetSize(pImg), pImg->depth, pImg->nChannels );
if( pImg->origin == IPL_ORIGIN_BL ) //flip live camera's frame
cvFlip( pImg, image );
else
cvCopy( pImg, image );
// convert to gray_image for face analysis
CvImage gray_image( image.size(), image.depth(), 1 );
if( image.channels() == 3 )
cvCvtColor( image, gray_image, CV_BGR2GRAY );
else
cvCopy( image, gray_image );
// do face tracking
start_ticks = ticks = cvGetTickCount();
int face_num = 0;
if( is_piclist )
face_num = detector.detect( gray_image, rects, face_max );
else
face_num = tracker.track( gray_image, rects, face_max, image ); // track in a video for faster speed
//face_num = tracker.detect( gray_image, rects, face_max ); // detect in an image
//set param for mouse event processing
if(!quiet)
{
mouse_faceparam.face_num = face_num;
mouse_faceparam.image = image;
}
ticks = cvGetTickCount() - ticks;
tracker_fps = 1000.0 / ( 1e-3 * ticks / cvGetTickFrequency() );
tracker_total_ticks += ticks;
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, "%s %d", vidcap->filename(), face_num );
// blink/smile/gender/age/face recognize section
for( int i=0; i<face_num; i++ )
//for( int i=0; i< MIN(1,face_num); i++ )
{
// get face rect and id from face tracker
CvRect rect = rects[i].rc;
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, " %d %d %d %d %f", rect.x, rect.y, rect.width, rect.height, rects[i].prob );
int face_trackid = rects[i].fid;
float like = rects[i].prob;
int angle= rects[i].angle;
// filter out outer faces
if( rect.x+rect.width > gray_image.width() || rect.x < 0 ) continue;
if( rect.y+rect.height > gray_image.height() || rect.y < 0 ) continue;
//tracker.getThumbnail(image, rect, thumbnailImg);
// detect landmark points
ticks = cvGetTickCount();
if(bRunLandmark)
{
if( is_piclist )
bLandmark = landmarkDetector.detect( gray_image, &rect, landmark6, parameters, angle ); //detect in an image
else
bLandmark = landmarkDetector.track( gray_image, &rect, landmark6, parameters, angle ); // track in a video for faster speed
ticks = cvGetTickCount() - ticks;
landmark_fps = 1000.0 / ( 1e-3 * ticks / cvGetTickFrequency() );
landmark_total_ticks += ticks;
}
else
bLandmark = false;
if(quiet == false && bLandmark == false)
{
//DrawFaceRect
cxlibDrawFaceRect(image, rect);
continue;
}
// warped align face and hist eq to delighting
ticks = cvGetTickCount();
cutFace.init(gray_image, rect, landmark6);
ticks = cvGetTickCount() - ticks;
if(ticks > 1)
align_fps = 1000.0 / ( 1e-3 * ticks / cvGetTickFrequency() );
else
{ align_fps = 0;
ticks = 0;
}
align_total_ticks += ticks;
if(saveface) //save face icon for training later
{
//save cutfaces
if(sfolder)
{
#ifdef WIN32
_splitpath(vidcap->filename(),driver,dir,fname,ext);
sprintf(sImgPath, "%s//%s%s", sfolder, fname,ext);
#else
sprintf(sImgPath, "%s//%06d.jpg", sfolder, faceimgID++);
#endif
}
else
sprintf(sImgPath, "%s#.jpg", vidcap->filename());
cvSaveImage(sImgPath, cutFace.getBigCutFace());
}
// detect blink
bBlink = 0;
probBlink = 0;
if(blink && bLandmark)
{
ticks = cvGetTickCount();
float blink_threshold = blinkDetector.getDefThreshold();//0.5;
int ret = blinkDetector.predict( &cutFace, &probBlink);
if(probBlink > blink_threshold )
bBlink = 1; //eye close
else
bBlink = -1; //eye open
ticks = cvGetTickCount() - ticks;
blink_fps = 1000.0/(1e-3*ticks/cvGetTickFrequency());
blink_total_ticks += ticks;
print_score = probBlink;
}
else blink_fps = 0;
// detect smile
bSmile = 0;
probSmile = 0;
if ( smile && bLandmark )
{
ticks = cvGetTickCount();
float smile_threshold = smileDetector.getDefThreshold(); //0.48;
int ret = smileDetector.predict(&cutFace, &probSmile);
if(probSmile > smile_threshold)
bSmile = 1; //smile
else
bSmile = -1; //not smile
ticks = cvGetTickCount() - ticks;
smile_fps = 1000.0 /( 1e-3 * ticks / cvGetTickFrequency() );
smile_total_ticks += ticks;
print_score = probSmile;
}
else smile_fps = 0;
//detect gender
bGender = 0;
probGender = 0;
if(gender && bLandmark)
{
ticks = cvGetTickCount();
float gender_threshold = genderDetector.getDefThreshold(); // 0.42;
int ret = genderDetector.predict(&cutFace, &probGender);
if(probGender > gender_threshold)
bGender = 1; //female
else
bGender = -1; //male
//bGender = -1:male, 1:female, 0: null
// smooth prediction result
if( ! is_piclist )
bGender = genderDetector.voteLabel(face_trackid, bGender);
ticks = cvGetTickCount() - ticks;
gender_fps = 1000.0/(1e-3*ticks/cvGetTickFrequency());
gender_total_ticks += ticks;
print_score = probGender;
}
else gender_fps = 0;
//detect age
nAgeID = -1;
if(age && bLandmark && rect.width*rect.height > 40*40)
{
ticks = cvGetTickCount();
//nAgeID = 0:"Baby", 1:"Kid", 2:"Adult", 3:"Senior"
nAgeID = ageDetector.predict(&cutFace, probAge);
// smooth prediction result
if( ! is_piclist )
nAgeID = ageDetector.voteLabel(face_trackid, nAgeID);
ticks = cvGetTickCount() - ticks;
age_fps = 1000.0/(1e-3*ticks/cvGetTickFrequency());
age_total_ticks += ticks;
print_score = probAge[nAgeID];
//if( ! quiet ) cxDrawAignFace2Image(image, pCutFace2);
}
else
{
age_fps = 0;
}
// recognize the face id
// we only do recognition every 5 frames,interval
char *sFaceCaption = NULL;
char sFaceCaptionBuff[256];
int face_id = 0;
probFaceID = 0;
if ( recog && bLandmark )
{
ticks = cvGetTickCount();
float face_threshold = faceRecognizer.getDefThreshold();
/////////////////////////////////////////////////////////////////////////////////////////
int face_id = -1;
if(bEnableAutoCluster & !is_piclist)
{
bool bAutocluster = true;
if(mouse_faceparam.ret_online_collecting) bAutocluster = false;
//face clustering
face_id = faceRecognizer.predict(&cutFace, &probFaceID, bAutocluster, face_trackid, frames);
}
else//face recognition
face_id = faceRecognizer.predict(&cutFace, &probFaceID);
/////////////////////////////////////////////////////////////////////////////////////////
ticks = cvGetTickCount() - ticks;
recg_fps = 1000.0f / ( 1e-3 * ticks / cvGetTickFrequency() );
recg_total_ticks += ticks;
// smooth prediction result
if( ! is_piclist && !bEnableAutoCluster)
{
if(probFaceID > face_threshold*1.0)
face_id = faceRecognizer.voteLabel(face_trackid, face_id);
else
face_id = faceRecognizer.voteLabel(face_trackid, -1);
}
else if(probFaceID <= face_threshold)
{
face_id =-1;
}
//set face name caption
if(face_id >= 0)
{
// recognized face name
const char* sFaceName = faceRecognizer.getFaceName(face_id);
sprintf(sFaceCaptionBuff, "%s %.2f", sFaceName, probFaceID);
//sprintf(sFaceCaptionBuff, "%s", sFaceName); //dispaly score
sFaceCaption = sFaceCaptionBuff;
print_score = probFaceID;
print_faceid = face_id;
}
else
{ // failed to recognize
//sprintf(sFaceCaptionBuff, "N\A %.2f", probFaceID);
//sFaceCaption = sFaceCaptionBuff;
}
// collect and save unknown face exemplars
if(probFaceID < face_threshold*0.9 || face_id != mouse_faceparam.ret_faceset_id )
{
if(mouse_faceparam.ret_online_collecting && (face_num ==1 || face_trackid == mouse_faceparam.ret_facetrack_id))
{
if( rect.x > gray_image.width()/4 && rect.x+rect.width < gray_image.width()*3/4 )
{
mouse_faceparam.updated = true;
int nFaceSetIdx = faceRecognizer.getFaceSetIdx(mouse_faceparam.ret_faceset_id);
bool bflag = faceRecognizer.tryInsertFace(cutFace.getBigCutFace(), nFaceSetIdx);
//printf("insert flag %d\n", bflag);
}
}
}
}
else recg_fps = 0;
if( ! quiet )
{
sprintf(sCaptionInfo, "FPS: %03d Fd:%04d Ld:%04d Fa:%04d Bl:%04d Sm:%04d Ge:%04d Ag:%03d Rc:%03d",
(int)frame_fps, (int)tracker_fps, (int)landmark_fps, (int)align_fps,
(int)blink_fps, (int)smile_fps, (int)gender_fps, (int)age_fps, (int)recg_fps);
//sprintf(sFaceCaptionBuff, "%.2f", print_score);
//sFaceCaption = sFaceCaptionBuff;
int trackid = -1; //face_trackid. don't display trackid if -1
cxlibDrawFaceBlob( image, pFont, trackid, rect, landmark6, probSmile,
bBlink, bSmile, bGender, nAgeID, sFaceCaption, NULL,
pImgSmileBGR, pImgSmileBGRA, pImgSmileMask);
}
// log file
if( fp_faceinfo != NULL )
{
// index, rect, landmark6, bBlink, probBlink, bSmile, probSmile, bGender, probGender, nAgeID, probAge[nAgeID], face_id, probFaceID
//fprintf( fp_faceinfo, "#%s# @%s@ ", vidcap->filename(), sImgPath);
fprintf( fp_faceinfo, "#%s# ", vidcap->filename());
fprintf( fp_faceinfo, "faceidx=( %06d %02d )", vidcap->index(), i+1 );
fprintf( fp_faceinfo, " rect=( %3d %3d %3d %3d )", rect.x, rect.y, rect.width, rect.height );
fprintf( fp_faceinfo, " landmark6=(" );
int l;
for( l = 0; l < 6; l++ )
fprintf( fp_faceinfo, " %3.0f %3.0f", landmark6[l].x, landmark6[l].y );
fprintf( fp_faceinfo, " )");
fprintf( fp_faceinfo, " blink=( %+d %f )", bBlink, probBlink );
fprintf( fp_faceinfo, " smile=( %+d %f )", bSmile, probSmile );
fprintf( fp_faceinfo, " gender=( %+d %f )", bGender, probGender );
fprintf( fp_faceinfo, " agegroup=( %+d %f )", nAgeID, (nAgeID >= 0 && nAgeID < 4) ? probAge[nAgeID] : 1.0f );
fprintf( fp_faceinfo, " identity=( %+d %f )", face_id, probFaceID );
fprintf( fp_faceinfo, "\n" );
}
}
if( fp_imaginfo != NULL )
fprintf( fp_imaginfo, "\n" );
ticks = cvGetTickCount() - start_ticks;
total_ticks += (ticks);
frame_fps = 1000.0f / ( 1e-3 * ticks / cvGetTickFrequency() );
// frame face_num
frames++;
//auto focus faces
if(quiet == false && bAutoFocus)
{
if(imgAutoFocus)
cvCopy(image, imgAutoFocus);
else
imgAutoFocus = cvCloneImage(image);
cxlibAutoFocusFaceImage(imgAutoFocus, image, rects, face_num);
}
// next frame if quiet
if( quiet )
continue;
else
{
// draw status info for custom interaction
if(mouse_faceparam.ret_online_collecting == 1)
{
sprintf(sCaptionInfo, "Collecting faces for track_id = %d", mouse_faceparam.ret_facetrack_id);
//draw face collecting region
cvLine(image, cvPoint(image.width()/4, 0), cvPoint(image.width()/4, image.height()-1), CV_RGB(255,255,0), 2);
cvLine(image, cvPoint(image.width()*3/4, 0), cvPoint(image.width()*3/4, image.height()-1), CV_RGB(255,255,0), 2);
}
else
sprintf(sCaptionInfo, "FPS: %03d Fd:%04d Ld:%04d Fa:%04d Bl:%04d Sm:%04d Ge:%04d Ag:%03d Rc:%03d",
(int)frame_fps, (int)tracker_fps, (int)landmark_fps, (int)align_fps,
(int)blink_fps, (int)smile_fps, (int)gender_fps, (int)age_fps, (int)recg_fps);
cxlibDrawCaption( image, pFont, sCaptionInfo);
}
//show Image
if (image.width() <= 800)
{
//show image
cvShowImage( str_title, image );
}
else
{ // show scaled smaller image
CvImage scale_image (cvSize(800, image.height()*800/image.width()), image.depth(), 3 );
cvResize (image, scale_image);
cvShowImage( str_title, scale_image );
}
// user interaction
int key = cvWaitKey( 30 );
//int key = cvWaitKey( );
if( key == ' ' ) // press the spacebar to pause the video play
cvWaitKey( 0 );
else if( key == 27 )
break; // press 'esc' to exit
else if( key == 'a' )
{ // add new face name
if(face_num > 0)
{
CvRect rect = rects[0].rc;
int x = rect.x+rect.width/2;
int y = rect.y+rect.height/2;
addFaceSet( x, y, &mouse_faceparam);
}
}
else if( key == 'c' )
{ // collect face exemplars for current selected facename
mouse_faceparam.ret_online_collecting = 1; //enable online face exemplar collecting
}
else if( key == 'z' )
// turn on/off the autofocus flag
bAutoFocus = !bAutoFocus;
else if(key >= 0)
{
if(mouse_faceparam.ret_online_collecting == 1)
{ // stop collecting faces
mouse_faceparam.ret_online_collecting = 0; //disable online face exemplar collecting
mouse_faceparam.ret_facetrack_id = -1;
}
if( key == 's')
{ // save face models
faceRecognizer.saveFaceModelXML("faceset_model.xml");
sprintf(sCaptionInfo, "%s", "saved the face model");
cxlibDrawCaption( pImg, pFont, sCaptionInfo);
cvShowImage( str_title, pImg );
cvWaitKey( 400 );
}
}
}
// print speed info about fps
float temp = 1e-6f / cvGetTickFrequency();
tracker_fps = 1.0f / ( tracker_total_ticks * temp / frames );
if (landmark_total_ticks != 0.0)
landmark_fps = 1.0f / ( landmark_total_ticks * temp / frames );
if (align_total_ticks != 0.0)
align_fps = 1.0f / ( align_total_ticks * temp / frames );
if (blink_total_ticks != 0.0)
blink_fps = 1.0f / (blink_total_ticks * temp / frames);
if (smile_total_ticks != 0.0)
smile_fps = 1.0f / (smile_total_ticks * temp / frames);
if (gender_total_ticks != 0.0)
gender_fps = 1.0f / (gender_total_ticks * temp / frames);
if (age_total_ticks != 0.0)
age_fps = 1.0f / (age_total_ticks * temp / frames);
if (recg_total_ticks != 0.0)
recg_fps = 1.0f / (recg_total_ticks * temp / frames);
total_fps = 1.0f / (total_ticks * temp / frames);
printf( "Total frames:%d Speed:%.1f fps\n", frames, total_fps);
printf( "FPS: Fd:%.1f Ld:%.1f Fa:%.1f Bl:%.1f Sm:%.1f Ge:%.1f Ag:%.1f Rc:%.1f",
tracker_fps, landmark_fps, align_fps,
blink_fps, smile_fps, gender_fps, age_fps, recg_fps);
//save updated face model
if(mouse_faceparam.updated == true)
{
sprintf(sCaptionInfo, "%s", "press key 's' to save updated face model or other keys to cancel");
cxlibDrawCaption( pImg, pFont, sCaptionInfo);
cvShowImage( str_title, pImg );
int key = cvWaitKey();
if( key == 's')
faceRecognizer.saveFaceModelXML("faceset_model.xml");
}
//save merged face model for dynamic clustering of smoothID
vFaceSet vMergedFaceSet;
int minWeight = 10;
faceRecognizer.getMergedFaceSet(vMergedFaceSet, minWeight);
faceRecognizer.saveFaceModelXML("faceset_modelMerged.xml", &vMergedFaceSet);
//faceRecognizer.saveFaceModelXML("faceset_modelMerged#.xml");
//release buff
//release global GUI data
if( !quiet )
cvDestroyWindow( str_title );
cvReleaseImage(&thumbnailImg);
cvReleaseImage(&pImgSmileBGR);
cvReleaseImage(&pImgSmileBGRA);
cvReleaseImage(&pImgSmileMask);
delete pFont;
delete vidcap;
if( fp_imaginfo != NULL )
fclose( fp_imaginfo );
if( fp_faceinfo != NULL )
fclose( fp_faceinfo );
return 0;
}
// Function createBGMeanStatModel initializes foreground detection process
// parameters:
// first_frame - frame from video sequence
// parameters - (optional) if NULL default parameters of the algorithm will be used
// p_model - pointer to CvFGDStatModel structure
CV_IMPL CvBGStatModel*
createBGMeanStatModel( IplImage* first_frame, BGMeanStatModelParams* parameters ){
BGMeanStatModel* p_model = 0;
CV_FUNCNAME( "createBGMeanStatModel" );
__BEGIN__;
int i, j, k, pixel_count, buf_size;
BGMeanStatModelParams params;
if( !CV_IS_IMAGE(first_frame) )
CV_ERROR( CV_StsBadArg, "Invalid or NULL first_frame parameter" );
if (first_frame->nChannels != 3)
CV_ERROR( CV_StsBadArg, "first_frame must have 1-3 color channels" );
// Initialize parameters:
if( parameters == NULL ){
params.n_frames = BGFG_MEAN_NFRAMES;
params.bg_update_rate = BGFG_MEAN_BG_UPDATE_RATE;
params.fg_update_rate = BGFG_MEAN_FG_UPDATE_RATE;
params.sg_params.is_obj_without_holes = BGFG_SEG_OBJ_WITHOUT_HOLES;
params.sg_params.perform_morphing = BGFG_SEG_PERFORM_MORPH;
params.sg_params.minArea = BGFG_SEG_MINAREA;
params.perform_segmentation = 1;
}else{
params = *parameters;
}
CV_CALL( p_model = (BGMeanStatModel*)cvAlloc( sizeof(*p_model) ));
memset( p_model, 0, sizeof(*p_model) );
p_model->type = BG_MODEL_MEAN;
p_model->release = (CvReleaseBGStatModel)releaseBGMeanStatModel;
p_model->update = (CvUpdateBGStatModel)updateBGMeanStatModel;;
p_model->params = params;
//init frame counters. Max value so first call will inialize bg & fg: FIXME: fast initialization??
p_model->bg_frame_count = params.bg_update_rate;
p_model->fg_frame_count = params.fg_update_rate;
// Initialize storage pools:
pixel_count = first_frame->width * first_frame->height * sizeof(uchar);
buf_size = pixel_count * first_frame->nChannels * params.n_frames;
CV_CALL( p_model->frame_cbuffer = (uchar*)cvAlloc(buf_size) );
memset( p_model->frame_cbuffer, 0, buf_size );
p_model->cbuffer_idx = 0;
p_model->cbuffer_nentries_init = 0;
buf_size = pixel_count * first_frame->nChannels * sizeof(double);
CV_CALL( p_model->mean = (double*)cvAlloc(buf_size) );
CV_CALL( p_model->std_dev = (double*)cvAlloc(buf_size) );
// Init temporary images:
CV_CALL( p_model->foreground = cvCreateImage(cvSize(first_frame->width, first_frame->height),
IPL_DEPTH_8U, 1));
CV_CALL( p_model->background = cvCloneImage(first_frame));
CV_CALL( p_model->storage = cvCreateMemStorage(0));
__END__;
if( cvGetErrStatus() < 0 ){
CvBGStatModel* base_ptr = (CvBGStatModel*)p_model;
if( p_model && p_model->release )
p_model->release( &base_ptr );
else
cvFree( &p_model );
p_model = 0;
}
return (CvBGStatModel*)p_model;
}
CV_IMPL CvFileStorage*
cvOpenFileStorage( const char* query, CvMemStorage* dststorage, int flags, const char* encoding )
{
CvFileStorage* fs = 0;
int default_block_size = 1 << 18;
bool append = (flags & 3) == CV_STORAGE_APPEND;
bool mem = (flags & CV_STORAGE_MEMORY) != 0;
bool write_mode = (flags & 3) != 0;
bool write_base64 = (write_mode || append) && (flags & CV_STORAGE_BASE64) != 0;
bool isGZ = false;
size_t fnamelen = 0;
const char * filename = query;
std::vector<std::string> params;
if ( !mem )
{
params = analyze_file_name( query );
if ( !params.empty() )
filename = params.begin()->c_str();
if ( write_base64 == false && is_param_exist( params, "base64" ) )
write_base64 = (write_mode || append);
}
if( !filename || filename[0] == '\0' )
{
if( !write_mode )
CV_Error( CV_StsNullPtr, mem ? "NULL or empty filename" : "NULL or empty buffer" );
mem = true;
}
else
fnamelen = strlen(filename);
if( mem && append )
CV_Error( CV_StsBadFlag, "CV_STORAGE_APPEND and CV_STORAGE_MEMORY are not currently compatible" );
fs = (CvFileStorage*)cvAlloc( sizeof(*fs) );
CV_Assert(fs);
memset( fs, 0, sizeof(*fs));
fs->memstorage = cvCreateMemStorage( default_block_size );
fs->dststorage = dststorage ? dststorage : fs->memstorage;
fs->flags = CV_FILE_STORAGE;
fs->write_mode = write_mode;
if( !mem )
{
fs->filename = (char*)cvMemStorageAlloc( fs->memstorage, fnamelen+1 );
strcpy( fs->filename, filename );
char* dot_pos = strrchr(fs->filename, '.');
char compression = '\0';
if( dot_pos && dot_pos[1] == 'g' && dot_pos[2] == 'z' &&
(dot_pos[3] == '\0' || (cv_isdigit(dot_pos[3]) && dot_pos[4] == '\0')) )
{
if( append )
{
cvReleaseFileStorage( &fs );
CV_Error(CV_StsNotImplemented, "Appending data to compressed file is not implemented" );
}
isGZ = true;
compression = dot_pos[3];
if( compression )
dot_pos[3] = '\0', fnamelen--;
}
if( !isGZ )
{
fs->file = fopen(fs->filename, !fs->write_mode ? "rt" : !append ? "wt" : "a+t" );
if( !fs->file )
goto _exit_;
}
else
{
#if USE_ZLIB
char mode[] = { fs->write_mode ? 'w' : 'r', 'b', compression ? compression : '3', '\0' };
fs->gzfile = gzopen(fs->filename, mode);
if( !fs->gzfile )
goto _exit_;
#else
cvReleaseFileStorage( &fs );
CV_Error(CV_StsNotImplemented, "There is no compressed file storage support in this configuration");
#endif
}
}
fs->roots = 0;
fs->struct_indent = 0;
fs->struct_flags = 0;
fs->wrap_margin = 71;
if( fs->write_mode )
{
int fmt = flags & CV_STORAGE_FORMAT_MASK;
if( mem )
fs->outbuf = new std::deque<char>;
if( fmt == CV_STORAGE_FORMAT_AUTO && filename )
{
const char* dot_pos = NULL;
const char* dot_pos2 = NULL;
// like strrchr() implementation, but save two last positions simultaneously
for (const char* pos = filename; pos[0] != 0; pos++)
{
if (pos[0] == '.')
{
dot_pos2 = dot_pos;
dot_pos = pos;
}
}
if (cv_strcasecmp(dot_pos, ".gz") && dot_pos2 != NULL)
{
dot_pos = dot_pos2;
}
fs->fmt
= (cv_strcasecmp(dot_pos, ".xml") || cv_strcasecmp(dot_pos, ".xml.gz"))
? CV_STORAGE_FORMAT_XML
: (cv_strcasecmp(dot_pos, ".json") || cv_strcasecmp(dot_pos, ".json.gz"))
? CV_STORAGE_FORMAT_JSON
: CV_STORAGE_FORMAT_YAML
;
}
else if ( fmt != CV_STORAGE_FORMAT_AUTO )
{
fs->fmt = fmt;
}
else
{
fs->fmt = CV_STORAGE_FORMAT_XML;
}
// we use factor=6 for XML (the longest characters (' and ") are encoded with 6 bytes (' and ")
// and factor=4 for YAML ( as we use 4 bytes for non ASCII characters (e.g. \xAB))
int buf_size = CV_FS_MAX_LEN*(fs->fmt == CV_STORAGE_FORMAT_XML ? 6 : 4) + 1024;
if (append)
{
fseek( fs->file, 0, SEEK_END );
if (ftell(fs->file) == 0)
append = false;
}
fs->write_stack = cvCreateSeq( 0, sizeof(CvSeq), fs->fmt == CV_STORAGE_FORMAT_XML ?
sizeof(CvXMLStackRecord) : sizeof(int), fs->memstorage );
fs->is_first = 1;
fs->struct_indent = 0;
fs->struct_flags = CV_NODE_EMPTY;
fs->buffer_start = fs->buffer = (char*)cvAlloc( buf_size + 1024 );
fs->buffer_end = fs->buffer_start + buf_size;
fs->base64_writer = 0;
fs->is_default_using_base64 = write_base64;
fs->state_of_writing_base64 = base64::fs::Uncertain;
fs->is_write_struct_delayed = false;
fs->delayed_struct_key = 0;
fs->delayed_struct_flags = 0;
fs->delayed_type_name = 0;
if( fs->fmt == CV_STORAGE_FORMAT_XML )
{
size_t file_size = fs->file ? (size_t)ftell( fs->file ) : (size_t)0;
fs->strstorage = cvCreateChildMemStorage( fs->memstorage );
if( !append || file_size == 0 )
{
if( encoding )
{
if( strcmp( encoding, "UTF-16" ) == 0 ||
strcmp( encoding, "utf-16" ) == 0 ||
strcmp( encoding, "Utf-16" ) == 0 )
{
cvReleaseFileStorage( &fs );
CV_Error( CV_StsBadArg, "UTF-16 XML encoding is not supported! Use 8-bit encoding\n");
}
CV_Assert( strlen(encoding) < 1000 );
char buf[1100];
sprintf(buf, "<?xml version=\"1.0\" encoding=\"%s\"?>\n", encoding);
icvPuts( fs, buf );
}
else
icvPuts( fs, "<?xml version=\"1.0\"?>\n" );
icvPuts( fs, "<opencv_storage>\n" );
}
else
{
int xml_buf_size = 1 << 10;
char substr[] = "</opencv_storage>";
int last_occurence = -1;
xml_buf_size = MIN(xml_buf_size, int(file_size));
fseek( fs->file, -xml_buf_size, SEEK_END );
char* xml_buf = (char*)cvAlloc( xml_buf_size+2 );
// find the last occurrence of </opencv_storage>
for(;;)
{
int line_offset = (int)ftell( fs->file );
char* ptr0 = icvGets( fs, xml_buf, xml_buf_size ), *ptr;
if( !ptr0 )
break;
ptr = ptr0;
for(;;)
{
ptr = strstr( ptr, substr );
if( !ptr )
break;
last_occurence = line_offset + (int)(ptr - ptr0);
ptr += strlen(substr);
}
}
cvFree( &xml_buf );
if( last_occurence < 0 )
{
cvReleaseFileStorage( &fs );
CV_Error( CV_StsError, "Could not find </opencv_storage> in the end of file.\n" );
}
icvCloseFile( fs );
fs->file = fopen( fs->filename, "r+t" );
CV_Assert(fs->file);
fseek( fs->file, last_occurence, SEEK_SET );
// replace the last "</opencv_storage>" with " <!-- resumed -->", which has the same length
icvPuts( fs, " <!-- resumed -->" );
fseek( fs->file, 0, SEEK_END );
icvPuts( fs, "\n" );
}
fs->start_write_struct = icvXMLStartWriteStruct;
fs->end_write_struct = icvXMLEndWriteStruct;
fs->write_int = icvXMLWriteInt;
fs->write_real = icvXMLWriteReal;
fs->write_string = icvXMLWriteString;
fs->write_comment = icvXMLWriteComment;
fs->start_next_stream = icvXMLStartNextStream;
}
else if( fs->fmt == CV_STORAGE_FORMAT_YAML )
{
if( !append)
icvPuts( fs, "%YAML:1.0\n---\n" );
else
icvPuts( fs, "...\n---\n" );
fs->start_write_struct = icvYMLStartWriteStruct;
fs->end_write_struct = icvYMLEndWriteStruct;
fs->write_int = icvYMLWriteInt;
fs->write_real = icvYMLWriteReal;
fs->write_string = icvYMLWriteString;
fs->write_comment = icvYMLWriteComment;
fs->start_next_stream = icvYMLStartNextStream;
}
else
{
if( !append )
icvPuts( fs, "{\n" );
else
{
bool valid = false;
long roffset = 0;
for ( ;
fseek( fs->file, roffset, SEEK_END ) == 0;
roffset -= 1 )
{
const char end_mark = '}';
if ( fgetc( fs->file ) == end_mark )
{
fseek( fs->file, roffset, SEEK_END );
valid = true;
break;
}
}
if ( valid )
{
icvCloseFile( fs );
fs->file = fopen( fs->filename, "r+t" );
CV_Assert(fs->file);
fseek( fs->file, roffset, SEEK_END );
fputs( ",", fs->file );
}
else
{
CV_Error( CV_StsError, "Could not find '}' in the end of file.\n" );
}
}
fs->struct_indent = 4;
fs->start_write_struct = icvJSONStartWriteStruct;
fs->end_write_struct = icvJSONEndWriteStruct;
fs->write_int = icvJSONWriteInt;
fs->write_real = icvJSONWriteReal;
fs->write_string = icvJSONWriteString;
fs->write_comment = icvJSONWriteComment;
fs->start_next_stream = icvJSONStartNextStream;
}
}
else
{
if( mem )
{
fs->strbuf = filename;
fs->strbufsize = fnamelen;
}
size_t buf_size = 1 << 20;
const char* yaml_signature = "%YAML";
const char* json_signature = "{";
const char* xml_signature = "<?xml";
char buf[16];
icvGets( fs, buf, sizeof(buf)-2 );
char* bufPtr = cv_skip_BOM(buf);
size_t bufOffset = bufPtr - buf;
if(strncmp( bufPtr, yaml_signature, strlen(yaml_signature) ) == 0)
fs->fmt = CV_STORAGE_FORMAT_YAML;
else if(strncmp( bufPtr, json_signature, strlen(json_signature) ) == 0)
fs->fmt = CV_STORAGE_FORMAT_JSON;
else if(strncmp( bufPtr, xml_signature, strlen(xml_signature) ) == 0)
fs->fmt = CV_STORAGE_FORMAT_XML;
else if(fs->strbufsize == bufOffset)
CV_Error(CV_BADARG_ERR, "Input file is empty");
else
CV_Error(CV_BADARG_ERR, "Unsupported file storage format");
if( !isGZ )
{
if( !mem )
{
fseek( fs->file, 0, SEEK_END );
buf_size = ftell( fs->file );
}
else
buf_size = fs->strbufsize;
buf_size = MIN( buf_size, (size_t)(1 << 20) );
buf_size = MAX( buf_size, (size_t)(CV_FS_MAX_LEN*2 + 1024) );
}
icvRewind(fs);
fs->strbufpos = bufOffset;
fs->str_hash = cvCreateMap( 0, sizeof(CvStringHash),
sizeof(CvStringHashNode), fs->memstorage, 256 );
fs->roots = cvCreateSeq( 0, sizeof(CvSeq),
sizeof(CvFileNode), fs->memstorage );
fs->buffer = fs->buffer_start = (char*)cvAlloc( buf_size + 256 );
fs->buffer_end = fs->buffer_start + buf_size;
fs->buffer[0] = '\n';
fs->buffer[1] = '\0';
//mode = cvGetErrMode();
//cvSetErrMode( CV_ErrModeSilent );
CV_TRY
{
switch (fs->fmt)
{
case CV_STORAGE_FORMAT_XML : { icvXMLParse ( fs ); break; }
case CV_STORAGE_FORMAT_YAML: { icvYMLParse ( fs ); break; }
case CV_STORAGE_FORMAT_JSON: { icvJSONParse( fs ); break; }
default: break;
}
}
CV_CATCH_ALL
{
fs->is_opened = true;
cvReleaseFileStorage( &fs );
CV_RETHROW();
}
//cvSetErrMode( mode );
// release resources that we do not need anymore
cvFree( &fs->buffer_start );
fs->buffer = fs->buffer_end = 0;
}
fs->is_opened = true;
_exit_:
if( fs )
{
if( cvGetErrStatus() < 0 || (!fs->file && !fs->gzfile && !fs->outbuf && !fs->strbuf) )
{
cvReleaseFileStorage( &fs );
}
else if( !fs->write_mode )
{
icvCloseFile(fs);
// we close the file since it's not needed anymore. But icvCloseFile() resets is_opened,
// which may be misleading. Since we restore the value of is_opened.
fs->is_opened = true;
}
}
return fs;
}
int cveGetErrStatus()
{
return cvGetErrStatus();
}
// Function cvCreateFGDStatModel initializes foreground detection process
// parameters:
// first_frame - frame from video sequence
// parameters - (optional) if NULL default parameters of the algorithm will be used
// p_model - pointer to CvFGDStatModel structure
CV_IMPL CvBGStatModel*
cvCreateFGDStatModel( IplImage* first_frame, CvFGDStatModelParams* parameters )
{
CvFGDStatModel* p_model = 0;
CV_FUNCNAME( "cvCreateFGDStatModel" );
__BEGIN__;
int i, j, k, pixel_count, buf_size;
CvFGDStatModelParams params;
if( !CV_IS_IMAGE(first_frame) )
CV_ERROR( CV_StsBadArg, "Invalid or NULL first_frame parameter" );
if (first_frame->nChannels != 3)
CV_ERROR( CV_StsBadArg, "first_frame must have 3 color channels" );
// Initialize parameters:
if( parameters == NULL )
{
params.Lc = CV_BGFG_FGD_LC;
params.N1c = CV_BGFG_FGD_N1C;
params.N2c = CV_BGFG_FGD_N2C;
params.Lcc = CV_BGFG_FGD_LCC;
params.N1cc = CV_BGFG_FGD_N1CC;
params.N2cc = CV_BGFG_FGD_N2CC;
params.delta = CV_BGFG_FGD_DELTA;
params.alpha1 = CV_BGFG_FGD_ALPHA_1;
params.alpha2 = CV_BGFG_FGD_ALPHA_2;
params.alpha3 = CV_BGFG_FGD_ALPHA_3;
params.T = CV_BGFG_FGD_T;
params.minArea = CV_BGFG_FGD_MINAREA;
params.is_obj_without_holes = 1;
params.perform_morphing = 1;
}
else
{
params = *parameters;
}
CV_CALL( p_model = (CvFGDStatModel*)cvAlloc( sizeof(*p_model) ));
memset( p_model, 0, sizeof(*p_model) );
p_model->type = CV_BG_MODEL_FGD;
p_model->release = (CvReleaseBGStatModel)icvReleaseFGDStatModel;
p_model->update = (CvUpdateBGStatModel)icvUpdateFGDStatModel;;
p_model->params = params;
// Initialize storage pools:
pixel_count = first_frame->width * first_frame->height;
buf_size = pixel_count*sizeof(p_model->pixel_stat[0]);
CV_CALL( p_model->pixel_stat = (CvBGPixelStat*)cvAlloc(buf_size) );
memset( p_model->pixel_stat, 0, buf_size );
buf_size = pixel_count*params.N2c*sizeof(p_model->pixel_stat[0].ctable[0]);
CV_CALL( p_model->pixel_stat[0].ctable = (CvBGPixelCStatTable*)cvAlloc(buf_size) );
memset( p_model->pixel_stat[0].ctable, 0, buf_size );
buf_size = pixel_count*params.N2cc*sizeof(p_model->pixel_stat[0].cctable[0]);
CV_CALL( p_model->pixel_stat[0].cctable = (CvBGPixelCCStatTable*)cvAlloc(buf_size) );
memset( p_model->pixel_stat[0].cctable, 0, buf_size );
for( i = 0, k = 0; i < first_frame->height; i++ ) {
for( j = 0; j < first_frame->width; j++, k++ )
{
p_model->pixel_stat[k].ctable = p_model->pixel_stat[0].ctable + k*params.N2c;
p_model->pixel_stat[k].cctable = p_model->pixel_stat[0].cctable + k*params.N2cc;
}
}
// Init temporary images:
CV_CALL( p_model->Ftd = cvCreateImage(cvSize(first_frame->width, first_frame->height), IPL_DEPTH_8U, 1));
CV_CALL( p_model->Fbd = cvCreateImage(cvSize(first_frame->width, first_frame->height), IPL_DEPTH_8U, 1));
CV_CALL( p_model->foreground = cvCreateImage(cvSize(first_frame->width, first_frame->height), IPL_DEPTH_8U, 1));
CV_CALL( p_model->background = cvCloneImage(first_frame));
CV_CALL( p_model->prev_frame = cvCloneImage(first_frame));
CV_CALL( p_model->storage = cvCreateMemStorage());
__END__;
if( cvGetErrStatus() < 0 )
{
CvBGStatModel* base_ptr = (CvBGStatModel*)p_model;
if( p_model && p_model->release )
p_model->release( &base_ptr );
else
cvFree( &p_model );
p_model = 0;
}
return (CvBGStatModel*)p_model;
}
CV_IMPL void*
cvLoad( const char* filename, CvMemStorage* memstorage,
const char* name, const char** _real_name )
{
void* ptr = 0;
const char* real_name = 0;
cv::FileStorage fs(cvOpenFileStorage(filename, memstorage, CV_STORAGE_READ));
CvFileNode* node = 0;
if( !fs.isOpened() )
return 0;
if( name )
{
node = cvGetFileNodeByName( *fs, 0, name );
}
else
{
int i, k;
for( k = 0; k < (*fs)->roots->total; k++ )
{
CvSeq* seq;
CvSeqReader reader;
node = (CvFileNode*)cvGetSeqElem( (*fs)->roots, k );
CV_Assert(node != NULL);
if( !CV_NODE_IS_MAP( node->tag ))
return 0;
seq = node->data.seq;
node = 0;
cvStartReadSeq( seq, &reader, 0 );
// find the first element in the map
for( i = 0; i < seq->total; i++ )
{
if( CV_IS_SET_ELEM( reader.ptr ))
{
node = (CvFileNode*)reader.ptr;
goto stop_search;
}
CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
}
}
stop_search:
;
}
if( !node )
CV_Error( CV_StsObjectNotFound, "Could not find the/an object in file storage" );
real_name = cvGetFileNodeName( node );
ptr = cvRead( *fs, node, 0 );
// sanity check
if( !memstorage && (CV_IS_SEQ( ptr ) || CV_IS_SET( ptr )) )
CV_Error( CV_StsNullPtr,
"NULL memory storage is passed - the loaded dynamic structure can not be stored" );
if( cvGetErrStatus() < 0 )
{
cvRelease( (void**)&ptr );
real_name = 0;
}
if( _real_name)
{
if (real_name)
{
*_real_name = (const char*)cvAlloc(strlen(real_name));
memcpy((void*)*_real_name, real_name, strlen(real_name));
} else {
*_real_name = 0;
}
}
return ptr;
}
