Background subtractor GMG: removed flexitype, fixed build errors.

This commit is contained in:
Andrey Kamaev
2012-06-30 20:47:09 +00:00
parent afe11f69fb
commit dec38e5949
3 changed files with 187 additions and 288 deletions

View File

@@ -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)
double color;
switch(image.depth())
{
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 = (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)
{