BOOL CRunHistoRange::CallIpp(BOOL bMessage)
{
UpdateLUT(FALSE);
CParmHistoRangeDlg dlg(this);
UpdateData(&dlg, FALSE);
if (dlg.DoModal() != IDOK)
return FALSE;
ShowHistogram();
UpdateLUT();
return TRUE;
}
bool AdaptiveHistogramCamshift::ToggleShowHistogram()
{
if (!m_showHistogram)
{
ShowHistogram();
}
else
{
HideHistogram();
}
return m_showHistogram;
}
void AdaptiveHistogramCamshift::Init(const CvSize& frameSize,
const InitParams& initParams)
{
// Get frame size
m_frameSize = frameSize;
// Load init params.
m_histDims = initParams.histDims;
m_vMin = initParams.vMin;
m_vMax = initParams.vMax;
m_sMin = initParams.sMin;
m_sBox = initParams.sBox;
m_histRanges[0] = initParams.histRanges[0] * 0.5f;
m_histRanges[1] = initParams.histRanges[1] * 0.5f;
// Create histograms
float* histRanges[2] = { &m_histRanges[0], &m_histRanges[1] };
m_hist = cvCreateHist(1, &m_histDims, CV_HIST_ARRAY, histRanges, 1);
m_histSubdiv = cvCreateHist(1, &m_histDims, CV_HIST_ARRAY, histRanges, 1);
m_histTrackWnd = cvCreateHist(1, &m_histDims, CV_HIST_ARRAY, histRanges, 1);
// Create images
m_imgHue = cvCreateImage(m_frameSize, 8, 1);
m_imgMask = cvCreateImage(m_frameSize, 8, 1);
m_imgHSV = cvCreateImage(m_frameSize, 8, 3);
m_imgBackproject = cvCreateImage(m_frameSize, 8, 1);
cvZero(m_imgBackproject);
// Create histogram image
m_histImg = cvCreateImage( m_frameSize, 8, 3 );
cvZero( m_histImg );
// Show controlsGUI, backproject, histogram
if (initParams.showControlsGUI)
{
ShowControlsGUI();
}
if (initParams.showBackproject)
{
ShowBackproject();
}
if (initParams.showHistogram)
{
ShowHistogram();
}
// Set initialized flag
m_initialized = true;
}
void AdaptiveHistogramCamshift::AdaptHistogram(IplImage* hue, IplImage* mask, IplImage* out)
{
// Prepare to analyze new track window
const CvRect& updateHistRect = m_trackCompRect;
// Now subdivide the track window and sum all pixels in each square
// subdivision of size m_sBox using pixel values given by the
// current hustogram. When we are done, we will normalize the sum
// from each subdivision and then be able to tell roughly how
// similar each subregion is to the track histogram.
// Make sure box size is greater than or equal to 2, and protect from
// changes made in GUI
const int sBox = std::max(m_sBox, 2);
if (sBox != m_sBox)
{
m_sBox = sBox;
cvSetTrackbarPos(ControlNames[ControlName_SBox], m_controlsGUIWndName.c_str(), sBox);
}
std::vector<float> subdivs;
int numRows, numCols;
SubdivideSumTrackWnd(sBox, &numRows, &numCols, &subdivs);
// Check window is less than sBox in size.
if (subdivs.empty())
{
return;
}
// Histogram for image subdivisions
for (int i = 0; i < m_histDims; ++i)
{
float *bin = cvGetHistValue_1D(m_histTrackWnd, i);
*bin = 0;
}
// Find the max vlaue of the subdivisions
float maxVal = *std::max_element(subdivs.begin(), subdivs.end());;
// DEBUG maxval
//printf("maxVal: %f\n", maxVal);
// Step through all subdivisions and weight them into a new histogram
// if they are greater than minVal. The weight function is r^2 where
// r is the ratio of the subdivision value to the max subdivision
// value.
if (maxVal > 0)
{
float minVal = maxVal * 0.125f;
float* subdivsCur = &subdivs[0];
for (int i = 0; i < numRows; ++i)
{
for (int j = 0; j < numCols; ++j, ++subdivsCur)
{
// Create a box around this area
CvPoint roiP1 = cvPoint(updateHistRect.x + sBox * j, updateHistRect.y + sBox * i);
CvPoint roiP2 = cvPoint(roiP1.x + sBox, roiP1.y + sBox);
if (*subdivsCur < minVal)
{
if(*subdivsCur > (minVal * 0.0625))
{
// Get ratio to max subdivision
float ratioMaxSubdiv = *subdivsCur / maxVal;
// Get color of surrounding box
CvScalar boxColor = colors[GREEN];
for (int colorInd = 0; colorInd < 3; ++colorInd)
{
boxColor.val[colorInd] *= ratioMaxSubdiv;
}
// Draw the box (darker green means less weight)
if (out)
{
cvRectangle(out, roiP1, roiP2, boxColor, 1);
}
}
else
{
// Draw a red box around this subdivision since it is not used
if (out)
{
cvRectangle(out, roiP1, roiP2, colors[RED], 1 );
}
}
}
else
{
// Get ratio to max subdivision
float ratioMaxSubdiv = *subdivsCur / maxVal;
// Get weight into histogram of track window
float weightVal = ratioMaxSubdiv * ratioMaxSubdiv;
// DEBUG weights
//printf("w %d: %f\t", j, weightVal);
// Get color of surrounding box
CvScalar boxColor = colors[GREEN];
for (int colorInd = 0; colorInd < 3; ++colorInd)
{
boxColor.val[colorInd] *= ratioMaxSubdiv;
}
// Draw the box (darker green means less weight)
if (out)
{
cvRectangle(out, roiP1, roiP2, boxColor, 1);
}
// Weight this subdivision into the histogram for the track window
CvRect thisSubdivRect = cvRect(roiP1.x, roiP1.y, sBox, sBox);
cvSetImageROI(hue, thisSubdivRect);
cvSetImageROI(mask, thisSubdivRect);
cvCalcHist(&hue, m_histSubdiv, 0, mask);
cvResetImageROI(hue);
cvResetImageROI(mask);
// Weight this into the track window histogram
for (int binNum = 0; binNum < m_histDims; ++binNum)
{
float* thisBin = cvGetHistValue_1D(m_histTrackWnd, binNum);
*thisBin *= (1.0f - weightVal);
*thisBin += static_cast<float>(cvGetReal1D(m_histSubdiv->bins, binNum)) * weightVal;
}
}
}
// DEBUG weights
//printf("\n");
}
// DEBUG weights
//printf("\n");
}
// DEBUG histograms
//printf("Wnd BEFORE WT\n");
//for( int i = 0; i < m_histDims; i++ ) {
// float *bin = cvGetHistValue_1D( m_histTrackWnd, i );
// printf("%2d: %3.1f ", i, *bin);
// if( 0 == (i+1) % 8 ) {
// printf("\n");
// }
//}
// Now scale track window histogram to tracking histogram scale
float trackWndHistMaxVal;
cvGetMinMaxHistValue(m_histTrackWnd, 0, &trackWndHistMaxVal, 0, 0);
cvConvertScale(m_histTrackWnd->bins, m_histTrackWnd->bins,
trackWndHistMaxVal ? HIST_SCALE / trackWndHistMaxVal : 0., 0);
// Use aging to weight track window histogram into tracking histogram
float averageBin = 0;
for (int binNum = 0; binNum < m_histDims; ++binNum)
{
float* thisBin = cvGetHistValue_1D(m_hist, binNum);
*thisBin *= (1.0f - (m_ageRatio / 100.0f));
*thisBin += static_cast<float>(cvGetReal1D(m_histTrackWnd->bins, binNum)) *
(m_ageRatio / 100.0f);
averageBin += *thisBin;
}
averageBin /= m_histDims;
// DEBUG average bin
//printf("Avg bin: %f.\n", averageBin);
// See if this histogram is dying
//if( averageBin < SMALLEST_AVG_HIST_BIN ) {
// cvConvertScale( m_hist->bins, m_hist->bins, SMALLEST_AVG_HIST_BIN / averageBin, 0 );
// DEBUG averageBin
//printf("Hist saved for average bin: %f\n", averageBin);
//}
// DEBUG track hist
//printf("Track\n");
//for( int i = 0; i < m_histDims; i++ ) {
// float *bin = cvGetHistValue_1D( m_hist, i );
// printf("%2d: %3.1f ", i, *bin);
// if( 0 == (i+1) % 8 ) {
// printf("\n");
// }
//}
//printf("\n");
// Now compute histogram image
cvZero(m_histImg);
for (int i = 0; i < m_histDims; ++i)
{
const double raw = cvGetReal1D(m_hist->bins, i) * (m_histImg->height / HIST_SCALE);
const int val = cvRound(raw);
CvScalar color = hsv2rgb((i * m_histRanges[1]) / m_histDims);
cvRectangle(m_histImg,
cvPoint(i * m_binWidth, m_histImg->height),
cvPoint((i + 1) * m_binWidth, m_histImg->height - val),
color, -1, 8, 0);
}
// Show histogram
if (m_showHistogram)
{
ShowHistogram();
}
}
