Commit dec38e59 authored by Andrey Kamaev's avatar Andrey Kamaev

Background subtractor GMG: removed flexitype, fixed build errors.

parent afe11f69
......@@ -199,75 +199,7 @@ protected:
*/
class CV_EXPORTS BackgroundSubtractorGMG: public cv::BackgroundSubtractor
{
private:
/**
* A general flexible datatype.
*
* Used internally to enable background subtraction algorithm to be robust to any input Mat type.
* Datatype can be char, unsigned char, int, unsigned int, long int, float, or double.
*/
union flexitype{
char c;
uchar uc;
int i;
unsigned int ui;
long int li;
float f;
double d;
flexitype(){d = 0.0;} //!< Default constructor, set all bits of the union to 0.
flexitype(char cval){c = cval;} //!< Char type constructor
bool operator ==(flexitype& rhs)
{
return d == rhs.d;
}
//! Char type assignment operator
flexitype& operator =(char cval){
if (this->c == cval){return *this;}
c = cval; return *this;
}
flexitype(unsigned char ucval){uc = ucval;} //!< unsigned char type constructor
//! unsigned char type assignment operator
flexitype& operator =(unsigned char ucval){
if (this->uc == ucval){return *this;}
uc = ucval; return *this;
}
flexitype(int ival){i = ival;} //!< int type constructor
//! int type assignment operator
flexitype& operator =(int ival){
if (this->i == ival){return *this;}
i = ival; return *this;
}
flexitype(unsigned int uival){ui = uival;} //!< unsigned int type constructor
//! unsigned int type assignment operator
flexitype& operator =(unsigned int uival){
if (this->ui == uival){return *this;}
ui = uival; return *this;
}
flexitype(float fval){f = fval;} //!< float type constructor
//! float type assignment operator
flexitype& operator =(float fval){
if (this->f == fval){return *this;}
f = fval; return *this;
}
flexitype(long int lival){li = lival;} //!< long int type constructor
//! long int type assignment operator
flexitype& operator =(long int lival){
if (this->li == lival){return *this;}
li = lival; return *this;
}
flexitype(double dval){d=dval;} //!< double type constructor
//! double type assignment operator
flexitype& operator =(double dval){
if (this->d == dval){return *this;}
d = dval; return *this;
}
};
protected:
/**
* Used internally to represent a single feature in a histogram.
* Feature is a color and an associated likelihood (weight in the histogram).
......@@ -387,7 +319,7 @@ public:
* @param min minimum value taken on by pixels in image sequence. Usually 0
* @param max maximum value taken on by pixels in image sequence. e.g. 1.0 or 255
*/
void initializeType(InputArray image, flexitype min, flexitype max);
void initializeType(InputArray image, double min, double max);
/**
* Selectively update the background model. Only update background model for pixels identified
* as background.
......@@ -417,24 +349,20 @@ protected:
double decisionThreshold; //!< value above which pixel is determined to be FG.
int smoothingRadius; //!< smoothing radius, in pixels, for cleaning up FG image.
flexitype maxVal, minVal;
double maxVal, minVal;
/*
* General Parameters
*/
size_t imWidth; //!< width of image.
size_t imHeight; //!< height of image.
size_t numPixels;
int imWidth; //!< width of image.
int imHeight; //!< height of image.
size_t numPixels;
int imageDepth; //!< Depth of image, e.g. CV_8U
unsigned int numChannels; //!< Number of channels in image.
unsigned int numChannels; //!< Number of channels in image.
bool isDataInitialized;
//!< After general parameters are set, data structures must be initialized.
size_t elemSize; //!< store image mat element sizes
size_t elemSize1;
/*
* Data Structures
*/
......
......@@ -67,7 +67,7 @@ BackgroundSubtractorGMG::BackgroundSubtractorGMG()
smoothingRadius = 7;
}
void BackgroundSubtractorGMG::initializeType(InputArray _image,flexitype min, flexitype max)
void BackgroundSubtractorGMG::initializeType(InputArray _image, double min, double max)
{
minVal = min;
maxVal = max;
......@@ -114,7 +114,6 @@ void BackgroundSubtractorGMG::initializeType(InputArray _image,flexitype min, fl
* Detect and accommodate the image depth
*/
Mat image = _image.getMat();
imageDepth = image.depth(); // 32f, 8u, etc.
numChannels = image.channels();
/*
......@@ -127,16 +126,15 @@ void BackgroundSubtractorGMG::initializeType(InputArray _image,flexitype min, fl
/*
* Data Structure Initialization
*/
Size imsize = image.size();
imWidth = imsize.width;
imHeight = imsize.height;
numPixels = imWidth*imHeight;
imWidth = image.cols;
imHeight = image.rows;
numPixels = image.total();
pixels.resize(numPixels);
frameNum = 0;
// used to iterate through matrix of type unknown at compile time
elemSize = image.elemSize();
elemSize1 = image.elemSize1();
//elemSize = image.elemSize();
//elemSize1 = image.elemSize1();
vector<PixelModelGMG>::iterator pixel;
vector<PixelModelGMG>::iterator pixel_end = pixels.end();
......@@ -145,8 +143,8 @@ void BackgroundSubtractorGMG::initializeType(InputArray _image,flexitype min, fl
pixel->setMaxFeatures(maxFeatures);
}
fgMaskImage = Mat::zeros(imHeight,imWidth,CV_8UC1); // 8-bit unsigned mask. 255 for FG, 0 for BG
posteriorImage = Mat::zeros(imHeight,imWidth,CV_32FC1); // float for storing probabilities. Can be viewed directly with imshow.
fgMaskImage = Mat::zeros(imHeight, imWidth, CV_8UC1); // 8-bit unsigned mask. 255 for FG, 0 for BG
posteriorImage = Mat::zeros(imHeight, imWidth, CV_32FC1); // float for storing probabilities. Can be viewed directly with imshow.
isDataInitialized = true;
}
......@@ -171,7 +169,7 @@ void BackgroundSubtractorGMG::operator()(InputArray _image, OutputArray _fgmask,
Mat image = _image.getMat();
_fgmask.create(Size(imHeight,imWidth),CV_8U);
_fgmask.create(imHeight,imWidth,CV_8U);
fgMaskImage = _fgmask.getMat(); // 8-bit unsigned mask. 255 for FG, 0 for BG
/*
......@@ -183,54 +181,32 @@ void BackgroundSubtractorGMG::operator()(InputArray _image, OutputArray _fgmask,
vector<PixelModelGMG>::iterator pixel;
vector<PixelModelGMG>::iterator pixel_end = pixels.end();
size_t i;
//#pragma omp parallel
//#pragma omp parallel
for (i = 0, pixel=pixels.begin(); pixel != pixel_end; ++i,++pixel)
{
HistogramFeatureGMG newFeature;
newFeature.color.clear();
int irow = int(i / imWidth);
int icol = i % imWidth;
for (size_t c = 0; c < numChannels; ++c)
{
/*
* Perform quantization. in each channel. (color-min)*(levels)/(max-min).
* Shifts min to 0 and scales, finally casting to an int.
*/
size_t quantizedColor;
// pixel at data+elemSize*i. Individual channel c at data+elemSize*i+elemSize1*c
if (imageDepth == CV_8U)
{
uchar *color = (uchar*)(image.data+elemSize*i+elemSize1*c);
quantizedColor = (size_t)((double)(*color-minVal.uc)*quantizationLevels/(maxVal.uc-minVal.uc));
}
else if (imageDepth == CV_8S)
{
char *color = (char*)(image.data+elemSize*i+elemSize1*c);
quantizedColor = (size_t)((double)(*color-minVal.c)*quantizationLevels/(maxVal.c-minVal.c));
}
else if (imageDepth == CV_16U)
{
unsigned int *color = (unsigned int*)(image.data+elemSize*i+elemSize1*c);
quantizedColor = (size_t)((double)(*color-minVal.ui)*quantizationLevels/(maxVal.ui-minVal.ui));
}
else if (imageDepth == CV_16S)
{
int *color = (int*)(image.data+elemSize*i+elemSize1*c);
quantizedColor = (size_t)((double)(*color-minVal.i)*quantizationLevels/(maxVal.i-minVal.i));
}
else if (imageDepth == CV_32F)
{
float *color = (float*)image.data+elemSize*i+elemSize1*c;
quantizedColor = (size_t)((double)(*color-minVal.ui)*quantizationLevels/(maxVal.ui-minVal.ui));
}
else if (imageDepth == CV_32S)
{
long int *color = (long int*)(image.data+elemSize*i+elemSize1*c);
quantizedColor = (size_t)((double)(*color-minVal.li)*quantizationLevels/(maxVal.li-minVal.li));
}
else if (imageDepth == CV_64F)
double color;
switch(image.depth())
{
double *color = (double*)image.data+elemSize*i+elemSize1*c;
quantizedColor = (size_t)((double)(*color-minVal.d)*quantizationLevels/(maxVal.d-minVal.d));
case CV_8U: color = image.ptr<uchar>(irow)[icol * numChannels + c]; break;
case CV_8S: color = image.ptr<schar>(irow)[icol * numChannels + c]; break;
case CV_16U: color = image.ptr<ushort>(irow)[icol * numChannels + c]; break;
case CV_16S: color = image.ptr<short>(irow)[icol * numChannels + c]; break;
case CV_32S: color = image.ptr<int>(irow)[icol * numChannels + c]; break;
case CV_32F: color = image.ptr<float>(irow)[icol * numChannels + c]; break;
case CV_64F: color = image.ptr<double>(irow)[icol * numChannels + c]; break;
default: color = 0; break;
}
size_t quantizedColor = (size_t)((color-minVal)*quantizationLevels/(maxVal-minVal));
newFeature.color.push_back(quantizedColor);
}
// now that the feature is ready for use, put it in the histogram
......@@ -251,7 +227,7 @@ void BackgroundSubtractorGMG::operator()(InputArray _image, OutputArray _fgmask,
*/
int row,col;
col = i%imWidth;
row = (i-col)/imWidth;
row = int(i-col)/imWidth;
posteriorImage.at<float>(row,col) = (1.0f-posterior);
}
pixel->setLastObservedFeature(newFeature);
......@@ -284,10 +260,10 @@ void BackgroundSubtractorGMG::updateBackgroundModel(InputArray _mask)
Mat maskImg = _mask.getMat();
//#pragma omp parallel
for (size_t i = 0; i < imHeight; ++i)
for (int i = 0; i < imHeight; ++i)
{
//#pragma omp parallel
for (size_t j = 0; j < imWidth; ++j)
for (int j = 0; j < imWidth; ++j)
{
if (frameNum <= numInitializationFrames + 1)
{
......
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