void givedepth(IplImage *localimagergb)
{ IplImage*localimage=cvCreateImage(cvGetSize(localimagergb),IPL_DEPTH_8U,3);
cvCvtColor(localimagergb,localimage,CV_BGR2HSV);
IplImage *blobbedscaling=cvCreateImage(cvGetSize(localimagergb),IPL_DEPTH_8U,3);
uchar *itemp=(uchar *)(localimage->imageData);
IplImage *binaryscaling=cvCreateImage(cvGetSize(localimagergb),IPL_DEPTH_8U,1);
uchar *itemp1=(uchar *)(binaryscaling ->imageData);
for(int i=0;i<hi2->height;i++){
for(int j=0;j<hi2->width;j++){
if((itemp[i*localimage->widthStep+j*localimage->nChannels] <hh)
&&
(itemp[i*localimage->widthStep+j*localimage->nChannels]>hl)
&&
(itemp[i*localimage->widthStep+j*localimage->nChannels+1]<sh)
&&
(itemp[i*localimage->widthStep+j*localimage->nChannels+1]>sl)
&&
( itemp[i*localimage->widthStep+j*localimage->nChannels+2]<vh)
&&
( itemp[i*localimage->widthStep+j*localimage->nChannels+2]>vl) //previous 124
) {
itemp1[i*binaryscaling->widthStep+j]=0; //dark regions black rest white
}
else
itemp1[i*binaryscaling->widthStep+j]=255;
}}
cvErode( binaryscaling, binaryscaling, NULL, 4);
cvDilate(binaryscaling, binaryscaling, NULL, 4);
CBlobResult blob;
CBlob *currentBlob=NULL;
blob=CBlobResult(binaryscaling,NULL,255);
blob.Filter(blob,B_EXCLUDE,CBlobGetArea(),B_LESS,500);
cvMerge(binaryscaling,binaryscaling,binaryscaling,NULL,blobbedscaling);
CBlob hand1,hand2; //two blobs,one for each hand
blob.GetNthBlob( CBlobGetArea(), 0, (hand2));
blob.GetNthBlob( CBlobGetArea(), 1, (hand1 ));
hand1.FillBlob(blobbedscaling,CV_RGB(0,0,255)); //fill the color of blob of hand one with blue
hand2.FillBlob(blobbedscaling,CV_RGB(0,255,0)); //fill the color of blob of hand two with green
coordinates (blobbedscaling,0);
}
/* Fetch a frame (if available) and process it, calling appropriate
callbacks when data becomes available. */
void MarkerCapture::tick(){
IplImage *thresh_frame = NULL;
CBlobResult blobs;
// Acquire the lock, update the current frame.
pthread_mutex_lock(&frame_mutex);
current_frame = cvCloneImage(cvQueryFrame(camera));
if(color_acquired && current_frame){
thresh_frame = apply_threshold(current_frame, target_color);
}else{
// create a suplicant.
thresh_frame = cvCreateImage(cvGetSize(current_frame),IPL_DEPTH_8U,1);
}
pthread_mutex_unlock(&frame_mutex);
// Lock released. Done messing with buffers.
if(frame_update_callback){
(*frame_update_callback)(this, current_frame, thresh_frame);
}
if(color_acquired){
blobs = detect_blobs(thresh_frame, CV_BLOB_SIZE_MIN);
if(blobs.GetNumBlobs() >= 2){ // need 2 or more blobs for positional fix.
MarkerPositionEstimate position;
// fetch the two largest blobs, by area.
CBlob blob0, blob1;
blobs.GetNthBlob(CBlobGetArea(), 0, blob0);
blobs.GetNthBlob(CBlobGetArea(), 1, blob1);
// perform positional calculations
position.distance = distance(blob0, blob1);
position.angle = angle(blob0, blob1);
position.blob0_center = blob_center(blob0);
position.blob1_center = blob_center(blob1);
// call the update handler.
if(position_update_callback){
(*position_update_callback)(this, position);
}
}
blobs.ClearBlobs();
}
pthread_mutex_lock(&frame_mutex);
cvReleaseImage(¤t_frame);
cvReleaseImage(&thresh_frame);
pthread_mutex_unlock(&frame_mutex);
int curr_time = clock();
fps = CLOCKS_PER_SEC/(double)(curr_time - time);
time = curr_time;
}
void TabletopSegmentor::pcCallback(sensor_msgs::PointCloud2::ConstPtr pc_msg) {
if(!pc_lock.try_lock())
return;
pcl::PointCloud<pcl::PointXYZRGB> pc_full, pc_full_frame;
pcl::fromROSMsg(*pc_msg, pc_full);
string base_frame("/base_link");
ros::Time now = ros::Time::now();
tf_listener.waitForTransform(pc_msg->header.frame_id, base_frame, now, ros::Duration(3.0));
pcl_ros::transformPointCloud(base_frame, pc_full, pc_full_frame, tf_listener);
// pc_full_frame is in torso lift frame
cv::Mat cur_height_img = cv::Mat::zeros(imgx, imgy, CV_8U);
BOOST_FOREACH(const pcl::PointXYZRGB& pt, pc_full_frame.points) {
if(pt.x != pt.x || pt.y != pt.y || pt.z != pt.z)
continue;
int32_t x, y, z;
x = (pt.x - minx)/(maxx-minx) * imgx;
y = (pt.y - miny)/(maxy-miny) * imgy;
z = (pt.z - minz)/(maxz-minz) * 256;
if(x < 0 || y < 0) continue;
if(x >= imgx || y >= imgy) continue;
if(z < 0 || z >= 256) continue;
if(cur_height_img.at<uint8_t>(x, y) == 0 || cur_height_img.at<uint8_t>(x, y) < (uint8_t) z)
cur_height_img.at<uint8_t>(x, y) = (uint8_t) z;
}
cv::max(height_img_max, cur_height_img, height_img_max);
cv::Mat cur_height_img_flt;
cur_height_img.convertTo(cur_height_img_flt, CV_32F);
height_img_sum += cur_height_img_flt;
cv::Mat cur_count(imgx, imgy, CV_8U);
cur_count = (cur_height_img > 0) / 255;
cv::Mat cur_count_flt(imgx, imgy, CV_32F);
cur_count.convertTo(cur_count_flt, CV_32F);
height_img_count += cur_count_flt;
cv::Mat height_img_avg_flt = height_img_sum / height_img_count;
cv::Mat height_img_avg(imgx, imgy, CV_8U);
height_img_avg_flt.convertTo(height_img_avg, CV_8U);
height_img_avg = height_img_max;
cv::Mat height_hist(256, 1, CV_32F, cv::Scalar(0));
for(uint32_t x=0;x<imgx;x++)
for(uint32_t y=0;y<imgy;y++) {
if(height_img_avg.at<uint8_t>(x,y) == 255)
height_img_avg.at<uint8_t>(x,y) = 0;
if(height_img_avg.at<uint8_t>(x,y) != 0) {
height_hist.at<float>(height_img_avg.at<uint8_t>(x,y), 0)++;
}
}
////////////////////// Finding best table height /////////////////////////
uint32_t gfiltlen = 25;
float stddev = 256/(maxz-minz) * 0.015;
cv::Mat gauss_filt(gfiltlen, 1, CV_32F, cv::Scalar(0));
for(uint32_t i=0;i<gfiltlen;i++)
gauss_filt.at<float>(i,0) = 0.39894 / stddev * std::exp(-(i-((float)gfiltlen)/2)*(i-((float)gfiltlen)/2)/(2*stddev*stddev));
//cout << gauss_filt;
uint32_t maxval = 0, maxidx = 0;
for(uint32_t i=0;i<256-gfiltlen;i++) {
uint32_t sum = 0;
for(uint32_t j=0;j<gfiltlen;j++)
sum += height_hist.at<float>(i+j,0) * gauss_filt.at<float>(j,0);
if(sum > maxval && i != 0) {
maxval = sum;
maxidx = i+gfiltlen/2;
}
}
int32_t table_height = ((int32_t)maxidx);
//printf("%d %d, ", maxval, maxidx);
/////////////////////////// Getting table binary /////////////////////
cv::Mat height_img_thresh(imgx, imgy, CV_8U);
height_img_thresh = height_img_avg.clone();
for(uint32_t x=0;x<imgx;x++)
for(uint32_t y=0;y<imgy;y++) {
if(std::fabs(table_height - ((int32_t)height_img_thresh.at<uint8_t>(x,y))) < stddev*2)
height_img_thresh.at<uint8_t>(x,y) = 255;
else
height_img_thresh.at<uint8_t>(x,y) = 0;
}
//////////////////////////////////////////////////////////////////
IplImage height_img_thresh_ipl = height_img_thresh;
IplConvKernel* element = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
cvMorphologyEx(&height_img_thresh_ipl, &height_img_thresh_ipl, NULL, element, CV_MOP_CLOSE, num_closes);
//cvMorphologyEx(&height_img_thresh, &height_img_thresh, NULL, element, CV_MOP_OPEN, 2);
cv::Mat height_img_thresh_blob = height_img_thresh.clone();
IplImage blob_img = height_img_thresh_blob;
CBlobResult blobs = CBlobResult(&blob_img, NULL, 0);
//blobs.Filter(blobs, B_EXCLUDE, CBlobGetArea(), B_LESS, 10);
CBlob biggestblob;
blobs.GetNthBlob(CBlobGetArea(), 0, biggestblob);
cv::Mat table_blob(imgx, imgy, CV_8U, cv::Scalar(0)); IplImage table_blob_img = table_blob;
biggestblob.FillBlob(&table_blob_img, cv::Scalar(150));
//drawCvBox2D(blob_img, table_roi, cv::Scalar(50), 1);
CvBox2D table_roi = biggestblob.GetEllipse(); table_roi.angle *= CV_PI/180;
cv::Mat table_hull(imgx, imgy, CV_8U, cv::Scalar(0));
IplImage hull_img = table_hull;
fillCvBox2D(hull_img, table_roi, cv::Scalar(255));
//printf("Cvbox: %f, %f, %f, %f, %f\n", table_roi.center.x, table_roi.center.y, table_roi.size.width, table_roi.size.height, table_roi.angle);
//cv::Mat height_morph(imgx, imgy, CV_8U, cv::Scalar(0));
//cv::Mat tmp_img(imgx, imgy, CV_8U, cv::Scalar(0));
//IplImage t1 = height_img_thresh; IplImage = height_morph;
cv::Mat above_table(imgx, imgy, CV_8U);
bitwise_and(height_img_max > table_height + stddev*2, table_hull, above_table);
IplImage above_table_img = above_table;
CBlobResult obj_blobs = CBlobResult(&above_table_img, NULL, 0);
obj_blobs.Filter(obj_blobs, B_EXCLUDE, CBlobGetArea(), B_LESS, obj_min_area);
CBlob cur_obj_blob;
vector<float> obj_cents_x, obj_cents_y, obj_cents_r, obj_areas, obj_dists;
vector<uint32_t> obj_inds;
for(int i=0;i<obj_blobs.GetNumBlobs();i++) {
obj_blobs.GetNthBlob(CBlobGetArea(), i, cur_obj_blob);
CvBox2D obj_box = cur_obj_blob.GetEllipse();
obj_cents_x.push_back(obj_box.center.x);
obj_cents_y.push_back(obj_box.center.y);
obj_cents_r.push_back(obj_box.angle * CV_PI/180);
obj_areas.push_back(cur_obj_blob.Area());
obj_dists.push_back((obj_box.center.x-imgx/2)*(obj_box.center.x-imgx/2)+obj_box.center.y*obj_box.center.y);
obj_inds.push_back(i);
}
boost::function<bool(uint32_t, uint32_t)> sortind = boost::bind(&compind, _1, _2, obj_dists);
sort(obj_inds.begin(), obj_inds.end(), sortind);
obj_poses.poses.clear();
for(uint32_t i=0;i<obj_inds.size();i++) {
float posey = obj_cents_x[obj_inds[i]], posex = obj_cents_y[obj_inds[i]];
float poser = -obj_cents_r[obj_inds[i]] + 3*CV_PI/2;
geometry_msgs::Pose cpose;
cpose.position.x = posex/imgx*(maxx-minx) + minx;
cpose.position.y = posey/imgy*(maxy-miny) + miny;
cpose.position.z = table_height/256.0*(maxz-minz) + minz;
btMatrix3x3 quatmat; btQuaternion quat;
quatmat.setEulerZYX(poser, 0 , 0);
quatmat.getRotation(quat);
cpose.orientation.x = quat.x(); cpose.orientation.y = quat.y();
cpose.orientation.z = quat.z(); cpose.orientation.w = quat.w();
CvPoint centerpt; centerpt.y = posex; centerpt.x = posey;
printf("[%d](%f, %f, area: %f)\n", i, posex, posey, obj_areas[obj_inds[i]]);
IplImage height_img_max_ipl = height_img_max;
cvCircle(&height_img_max_ipl, centerpt, 3, cv::Scalar(200), 2);
obj_poses.poses.push_back(cpose);
}
obj_poses.header.stamp = ros::Time::now();
obj_poses.header.frame_id = base_frame;
obj_arr_pub.publish(obj_poses);
cv_bridge::CvImage cvb_height_img;
//cvb_height_img.image = height_img_avg;
//cvb_height_img.image = height_img_max;
//cvb_height_img.image = height_morph;
//cvb_height_img.image = obj_img;
//cvb_height_img.image = height_img_thresh_blob;
//cvb_height_img.image = table_blob;
//cvb_height_img.image = height_img_thresh;
cvb_height_img.image = above_table;
//cvb_height_img.image = table_edge;
cvb_height_img.header.stamp = ros::Time::now();
cvb_height_img.header.frame_id = base_frame;
cvb_height_img.encoding = enc::MONO8;
height_pub.publish(cvb_height_img.toImageMsg());
pc_full_frame.header.stamp = ros::Time::now();
pc_full_frame.header.frame_id = base_frame;
//pc_pub.publish(pc_full_frame);
if(obj_poses.poses.size() > 0)
obj_poses_found = true;
//delete element;
pc_lock.unlock();
}
void
Auvsi_Recognize::extractLetter( void )
{
typedef cv::Vec<unsigned char, 1> VT_binary;
#ifdef TWO_CHANNEL
typedef cv::Vec<T, 2> VT;
#else
typedef cv::Vec<T, 3> VT;
#endif
typedef cv::Vec<int, 1> IT;
// Erode input slightly
cv::Mat input;
cv::erode( _shape, input, cv::Mat() );
// Remove any small white blobs left over
CBlobResult blobs;
CBlob * currentBlob;
CBlob biggestBlob;
IplImage binaryIpl = input;
blobs = CBlobResult( &binaryIpl, NULL, 0 );
blobs.GetNthBlob( CBlobGetArea(), 0, biggestBlob );
blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_GREATER_OR_EQUAL, biggestBlob.Area() );
for (int i = 0; i < blobs.GetNumBlobs(); i++ )
{
currentBlob = blobs.GetBlob(i);
currentBlob->FillBlob( &binaryIpl, cvScalar(0));
}
// Perform k-means on this region only
int areaLetter = (int)biggestBlob.Area();
cv::Mat kMeansInput = cv::Mat( areaLetter, 1, _image.type() );
// Discard if we couldn't extract a letter
if( areaLetter <= 0 )
{
_letter = cv::Mat( _shape );
_letter = cv::Scalar(0);
return;
}
cv::MatIterator_<VT_binary> binaryIterator = input.begin<VT_binary>();
cv::MatIterator_<VT_binary> binaryEnd = input.end<VT_binary>();
cv::MatIterator_<VT> kMeansIterator = kMeansInput.begin<VT>();
for( ; binaryIterator != binaryEnd; ++binaryIterator )
{
if( (*binaryIterator)[0] > 0 )
{
(*kMeansIterator) = _image.at<VT>( binaryIterator.pos() );
++kMeansIterator;
}
}
// Get k-means labels
cv::Mat labels = doClustering<T>( kMeansInput, 2, false );
int numZeros = areaLetter - cv::countNonZero( labels );
bool useZeros = numZeros < cv::countNonZero( labels );
// Reshape into original form
_letter = cv::Mat( _shape.size(), _shape.type() );
_letter = cv::Scalar(0);
binaryIterator = input.begin<VT_binary>();
binaryEnd = input.end<VT_binary>();
cv::MatIterator_<IT> labelsIterator = labels.begin<IT>();
for( int index = 0; binaryIterator != binaryEnd; ++binaryIterator )
{
if( (*binaryIterator)[0] > 0 )
{
// Whichever label was the minority, we make that value white and all other values black
unsigned char value = (*labelsIterator)[0];
if( useZeros )
if( value )
value = 0;
else
value = 255;
else
if( value )
value = 255;
else
value = 0;
_letter.at<VT_binary>( binaryIterator.pos() ) = VT_binary( value );
++labelsIterator;
}
}
}
void
Auvsi_Recognize::extractShape( void )
{
typedef cv::Vec<T, 1> VT;
// Reduce input to two colors
cv::Mat reducedColors = doClustering<T>( _image, 2 );
cv::Mat grayScaled, binary;
// Make output grayscale
grayScaled = convertToGray( reducedColors );
//cv::cvtColor( reducedColors, grayScaled, CV_RGB2GRAY );
// Make binary
double min, max;
cv::minMaxLoc( grayScaled, &min, &max );
cv::threshold( grayScaled, binary, min, 1.0, cv::THRESH_BINARY );
// ensure that background is black, image white
if( binary.at<VT>(0, 0)[0] > 0.0f )
cv::threshold( grayScaled, binary, min, 1.0, cv::THRESH_BINARY_INV );
binary.convertTo( binary, CV_8U, 255.0f );
// Fill in all black regions smaller than largest black region with white
CBlobResult blobs;
CBlob * currentBlob;
IplImage binaryIpl = binary;
blobs = CBlobResult( &binaryIpl, NULL, 255 );
// Get area of biggest blob
CBlob biggestBlob;
blobs.GetNthBlob( CBlobGetArea(), 0, biggestBlob );
// Remove all blobs of smaller area
blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_GREATER_OR_EQUAL, biggestBlob.Area() );
for (int i = 0; i < blobs.GetNumBlobs(); i++ )
{
currentBlob = blobs.GetBlob(i);
currentBlob->FillBlob( &binaryIpl, cvScalar(255));
}
// Fill in all small white regions black
blobs = CBlobResult( &binaryIpl, NULL, 0 );
blobs.GetNthBlob( CBlobGetArea(), 0, biggestBlob );
blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_GREATER_OR_EQUAL, biggestBlob.Area() );
for (int i = 0; i < blobs.GetNumBlobs(); i++ )
{
currentBlob = blobs.GetBlob(i);
currentBlob->FillBlob( &binaryIpl, cvScalar(0));
}
binary = cv::Scalar(0);
biggestBlob.FillBlob( &binaryIpl, cvScalar(255));
_shape = binary;
}
// A Simple Camera Capture Framework
int main() {
CvCapture* capture = cvCaptureFromCAM( 0 );
if( !capture ) {
fprintf( stderr, "ERROR: capture is NULL \n" );
return -1;
}
#ifdef HALF_SIZE_CAPTURE
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_WIDTH, 352/2);
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_HEIGHT, 288/2);
#endif
// Create a window in which the captured images will be presented
cvNamedWindow( "Source Image Window", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "Back Projected Image", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "Brightness and Contrast Window", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "Blob Output Window", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "Histogram Window", 0);
cvNamedWindow( "Rainbow Window", CV_WINDOW_AUTOSIZE );
// Capture one frame to get image attributes:
source_frame = cvQueryFrame( capture );
if( !source_frame ) {
fprintf( stderr, "ERROR: frame is null...\n" );
return -1;
}
cvCreateTrackbar("histogram\nnormalization", "Back Projected Image", &normalization_sum, 6000, NULL);
cvCreateTrackbar("brightness", "Brightness and Contrast Window", &_brightness, 200, NULL);
cvCreateTrackbar("contrast", "Brightness and Contrast Window", &_contrast, 200, NULL);
cvCreateTrackbar("threshold", "Blob Output Window", &blob_extraction_threshold, 255, NULL);
cvCreateTrackbar("min blob size", "Blob Output Window", &min_blob_size, 2000, NULL);
cvCreateTrackbar("max blob size", "Blob Output Window", &max_blob_size, source_frame->width*source_frame->height/4, NULL);
inputImage = cvCreateImage(cvGetSize(source_frame), IPL_DEPTH_8U, 1);
histAdjustedImage = cvCreateImage(cvGetSize(source_frame), IPL_DEPTH_8U, 1);
outputImage = cvCreateImage(cvGetSize(source_frame), IPL_DEPTH_8U, 3 );
hist_image = cvCreateImage(cvSize(320,200), 8, 1);
rainbowImage = cvCreateImage(cvGetSize(source_frame), IPL_DEPTH_8U, 3 );
// object that will contain blobs of inputImage
CBlobResult blobs;
CBlob my_enumerated_blob;
cvInitFont(&font, CV_FONT_HERSHEY_SIMPLEX|CV_FONT_ITALIC, hScale, vScale, 0, lineWidth);
// Some brightness/contrast stuff:
bright_cont_image = cvCloneImage(inputImage);
lut_mat = cvCreateMatHeader( 1, 256, CV_8UC1 );
cvSetData( lut_mat, lut, 0 );
while( 1 ) {
// Get one frame
source_frame = cvQueryFrame( capture );
if( !source_frame ) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
cvShowImage( "Source Image Window", source_frame );
// Do not release the frame!
cvCvtColor(source_frame, inputImage, CV_RGB2GRAY);
// Histogram Stuff!
my_hist = cvCreateHist(1, hist_size_array, CV_HIST_ARRAY, ranges, 1);
cvCalcHist( &inputImage, my_hist, 0, NULL );
cvNormalizeHist(my_hist, normalization_sum);
// NOTE: First argument MUST have an ampersand, or a segmentation fault will result
cvCalcBackProject(&inputImage, histAdjustedImage, my_hist);
// Histogram Picture
int bin_w;
float max_value = 0;
cvGetMinMaxHistValue( my_hist, 0, &max_value, 0, 0 );
cvScale( my_hist->bins, my_hist->bins, ((double)hist_image->height)/max_value, 0 );
cvSet( hist_image, cvScalarAll(255), 0 );
bin_w = cvRound((double)hist_image->width/hist_size);
for(int i = 0; i < hist_size; i++ )
cvRectangle( hist_image, cvPoint(i*bin_w, hist_image->height), cvPoint((i+1)*bin_w, hist_image->height - cvRound(cvGetReal1D(my_hist->bins,i))), cvScalarAll(0), -1, 8, 0 );
cvShowImage( "Histogram Window", hist_image );
cvShowImage("Back Projected Image", histAdjustedImage);
// Brightness/contrast loop stuff:
int brightness = _brightness - 100;
int contrast = _contrast - 100;
/*
* The algorithm is by Werner D. Streidt
* (http://visca.com/ffactory/archives/5-99/msg00021.html)
*/
if( contrast > 0 ) {
double delta = 127.*contrast/100;
double a = 255./(255. - delta*2);
double b = a*(brightness - delta);
for(int i = 0; i < 256; i++ )
{
int v = cvRound(a*i + b);
if( v < 0 ) v = 0;
if( v > 255 ) v = 255;
lut[i] = (uchar)v;
}
}
else {
double delta = -128.*contrast/100;
double a = (256.-delta*2)/255.;
double b = a*brightness + delta;
for(int i = 0; i < 256; i++ ) {
int v = cvRound(a*i + b);
if( v < 0 )
v = 0;
if( v > 255 )
v = 255;
lut[i] = (uchar)v;
}
}
cvLUT( inputImage, bright_cont_image, lut_mat );
cvShowImage( "Brightness and Contrast Window", bright_cont_image);
// ---------------
// Blob Manipulation Code begins here:
// Extract the blobs using a threshold of 100 in the image
blobs = CBlobResult( bright_cont_image, NULL, blob_extraction_threshold, true );
// discard the blobs with less area than 5000 pixels
// ( the criteria to filter can be any class derived from COperadorBlob )
blobs.Filter( blobs, B_INCLUDE, CBlobGetArea(), B_GREATER_OR_EQUAL, min_blob_size);
blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_GREATER, max_blob_size);
// build an output image equal to the input but with 3 channels (to draw the coloured blobs)
cvMerge( bright_cont_image, bright_cont_image, bright_cont_image, NULL, outputImage );
// plot the selected blobs in a output image
for (int i=0; i < blobs.GetNumBlobs(); i++) {
blobs.GetNthBlob( CBlobGetArea(), i, my_enumerated_blob );
// Color 5/6 of the color wheel (300 degrees)
my_enumerated_blob.FillBlob( outputImage, cv_hsv2rgb((float)i/blobs.GetNumBlobs() * 300, 1, 1));
}
// END Blob Manipulation Code
// ---------------
sprintf(str, "Count: %d", blobs.GetNumBlobs());
cvPutText(outputImage, str, cvPoint(50, 25), &font, cvScalar(255,0,255));
cvShowImage("Blob Output Window", outputImage);
/*
// Rainbow manipulation:
for (int i=0; i < CV_CAP_PROP_FRAME_WIDTH; i++) {
for (int j=0; j < CV_CAP_PROP_FRAME_HEIGHT; j++) {
// This line is not figure out yet...
// pixel_color_set = ((uchar*)(rainbowImage->imageData + rainbowImage->widthStep * j))[i * 3]
((uchar*)(rainbowImage->imageData + rainbowImage->widthStep * j))[i * 3] = 30;
((uchar*)(rainbowImage->imageData + rainbowImage->widthStep * j))[i * 3 + 1] = 30;
((uchar*)(rainbowImage->imageData + rainbowImage->widthStep * j))[i * 3 + 2] = 30;
}
}
cvShowImage("Rainbow Window", rainbowImage);
*/
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
if( (cvWaitKey(10) & 255) == 27 ) break;
}
cvReleaseImage(&inputImage);
cvReleaseImage(&histAdjustedImage);
cvReleaseImage(&hist_image);
cvReleaseImage(&bright_cont_image);
cvReleaseImage(&outputImage);
cvReleaseImage(&rainbowImage);
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyAllWindows();
return 0;
}
void TabletopDetector::pcCallback(sensor_msgs::PointCloud2::ConstPtr pc_msg) {
if(!pc_lock.try_lock())
return;
pcl::PointCloud<pcl::PointXYZRGB> pc_full, pc_full_frame;
pcl::fromROSMsg(*pc_msg, pc_full);
string base_frame("/base_link");
ros::Time now = ros::Time::now();
tf_listener.waitForTransform(pc_msg->header.frame_id, base_frame, now, ros::Duration(3.0));
pcl_ros::transformPointCloud(base_frame, pc_full, pc_full_frame, tf_listener);
// pc_full_frame is in torso lift frame
cv::Mat cur_height_img = cv::Mat::zeros(imgx, imgy, CV_8U);
BOOST_FOREACH(const pcl::PointXYZRGB& pt, pc_full_frame.points) {
if(pt.x != pt.x || pt.y != pt.y || pt.z != pt.z)
continue;
int32_t x, y, z;
x = (pt.x - minx)/(maxx-minx) * imgx;
y = (pt.y - miny)/(maxy-miny) * imgy;
z = (pt.z - minz)/(maxz-minz) * 256;
if(x < 0 || y < 0) continue;
if(x >= imgx || y >= imgy) continue;
if(z < 0 || z >= 256) continue;
if(cur_height_img.at<uint8_t>(x, y) == 0 || cur_height_img.at<uint8_t>(x, y) < (uint8_t) z)
cur_height_img.at<uint8_t>(x, y) = (uint8_t) z;
}
cv::max(height_img_max, cur_height_img, height_img_max);
cv::Mat cur_height_img_flt;
cur_height_img.convertTo(cur_height_img_flt, CV_32F);
height_img_sum += cur_height_img_flt;
cv::Mat cur_count(imgx, imgy, CV_8U);
cur_count = (cur_height_img > 0) / 255;
cv::Mat cur_count_flt(imgx, imgy, CV_32F);
cur_count.convertTo(cur_count_flt, CV_32F);
height_img_count += cur_count_flt;
cv::Mat height_img_avg_flt = height_img_sum / height_img_count;
cv::Mat height_img_avg(imgx, imgy, CV_8U);
height_img_avg_flt.convertTo(height_img_avg, CV_8U);
height_img_avg = height_img_max;
cv::Mat height_hist(256, 1, CV_32F, cv::Scalar(0));
for(uint32_t x=0;x<imgx;x++)
for(uint32_t y=0;y<imgy;y++) {
if(height_img_avg.at<uint8_t>(x,y) == 255)
height_img_avg.at<uint8_t>(x,y) = 0;
if(height_img_avg.at<uint8_t>(x,y) != 0) {
height_hist.at<float>(height_img_avg.at<uint8_t>(x,y), 0)++;
}
}
////////////////////// Finding best table height /////////////////////////
uint32_t gfiltlen = 25;
float stddev = 256/(maxz-minz) * 0.015;
cv::Mat gauss_filt(gfiltlen, 1, CV_32F, cv::Scalar(0));
for(uint32_t i=0;i<gfiltlen;i++)
gauss_filt.at<float>(i,0) = 0.39894 / stddev * std::exp(-(i-((float)gfiltlen)/2)*(i-((float)gfiltlen)/2)/(2*stddev*stddev));
//cout << gauss_filt;
uint32_t maxval = 0, maxidx = 0;
for(uint32_t i=0;i<256-gfiltlen;i++) {
uint32_t sum = 0;
for(uint32_t j=0;j<gfiltlen;j++)
sum += height_hist.at<float>(i+j,0) * gauss_filt.at<float>(j,0);
if(sum > maxval && i != 0) {
maxval = sum;
maxidx = i+gfiltlen/2;
}
}
int32_t table_height = ((int32_t)maxidx);
//printf("%d %d, ", maxval, maxidx);
/////////////////////////// Getting table binary /////////////////////
cv::Mat height_img_thresh(imgx, imgy, CV_8U);
height_img_thresh = height_img_avg.clone();
for(uint32_t x=0;x<imgx;x++)
for(uint32_t y=0;y<imgy;y++) {
if(std::fabs(table_height - ((int32_t)height_img_thresh.at<uint8_t>(x,y))) < stddev*2)
height_img_thresh.at<uint8_t>(x,y) = 255;
else
height_img_thresh.at<uint8_t>(x,y) = 0;
}
//////////////////////////////////////////////////////////////////
IplImage height_img_thresh_ipl = height_img_thresh;
IplConvKernel* element = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
cvMorphologyEx(&height_img_thresh_ipl, &height_img_thresh_ipl, NULL, element, CV_MOP_CLOSE, num_closes);
//cvMorphologyEx(&height_img_thresh, &height_img_thresh, NULL, element, CV_MOP_OPEN, 2);
cv::Mat height_img_thresh_blob = height_img_thresh.clone();
IplImage blob_img = height_img_thresh_blob;
CBlobResult blobs = CBlobResult(&blob_img, NULL, 0);
//blobs.Filter(blobs, B_EXCLUDE, CBlobGetArea(), B_LESS, 10);
CBlob biggestblob;
blobs.GetNthBlob(CBlobGetArea(), 0, biggestblob);
cv::Mat table_blob(imgx, imgy, CV_8U, cv::Scalar(0)); IplImage table_blob_img = table_blob;
biggestblob.FillBlob(&table_blob_img, cv::Scalar(150));
//drawCvBox2D(blob_img, table_roi, cv::Scalar(50), 1);
CvBox2D table_roi = biggestblob.GetEllipse(); table_roi.angle *= CV_PI/180;
cv::Mat table_hull(imgx, imgy, CV_8U, cv::Scalar(0));
IplImage hull_img = table_hull;
fillCvBox2D(hull_img, table_roi, cv::Scalar(255));
//printf("Cvbox: %f, %f, %f, %f, %f\n", table_roi.center.x, table_roi.center.y, table_roi.size.width, table_roi.size.height, table_roi.angle);
//cv::Mat height_morph(imgx, imgy, CV_8U, cv::Scalar(0));
//cv::Mat tmp_img(imgx, imgy, CV_8U, cv::Scalar(0));
//IplImage t1 = height_img_thresh; IplImage = height_morph;
cv::Mat table_edge(imgx, imgy, CV_8U);
cv::Sobel(table_blob, table_edge, CV_8U, 0, 1, 1);
cv::Mat above_table(imgx, imgy, CV_8U);
bitwise_and(height_img_max > table_height + stddev*2, table_hull, above_table);
IplImage above_table_img = above_table;
CBlobResult obj_blobs = CBlobResult(&above_table_img, NULL, 0);
CBlob biggest_obj_blob;
double objcentx = 0, objcenty = 0;
if(obj_blobs.GetNumBlobs() > 0) {
obj_blobs.GetNthBlob(CBlobGetArea(), 0, biggest_obj_blob);
CvBox2D obj_box = biggest_obj_blob.GetEllipse();
objcenty = obj_box.center.x, objcentx = obj_box.center.y;
}
//double objcentx = 0, objcenty = 0;
//cv::Mat table_edge = height_morph.clone();
//cvMorphologyEx(&height_img, &height_morph, NULL, element, CV_MOP_CLOSE);
//cvFillPoly(&ipl_hull, rpts, npts, 1, cv::Scalar(255));
//cv::Mat obj_img(imgx, imgy, CV_8U, cv::Scalar(0));
//std::vector<int32_t> xfeats, yfeats, zfeats;
//double sumobjx = 0, sumobjy = 0, sumobja = 0;
//for(uint32_t y=0;y<imgx;y++)
// for(uint32_t x=0;x<imgx;x++)
// if(table_hull.at<uint8_t>(x,y) == 255 && height_morph.at<uint8_t>(x,y) == 0
// && height_img_avg.at<uint8_t>(x,y) > table_height + stddev*2) {
// obj_img.at<uint8_t>(x,y) = height_img_avg.at<uint8_t>(x,y);
// sumobjx += x; sumobjy += y; sumobja ++;
// //xfeats.push_back(x); yfeats.push_back(y);
// //zfeats.push_back(height_img.at<uint8_t>(x,y));
// }
//double objcentx = sumobjx/sumobja, objcenty = sumobjy/sumobja;
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* lines = 0;
cv::Mat lines_img = height_img_max.clone();
IplImage lines_img_ipl = lines_img;
IplImage table_edge_ipl = table_edge;
cvMorphologyEx(&table_edge_ipl, &table_edge_ipl, NULL, element, CV_MOP_DILATE, num_edge_dilate);
lines = cvHoughLines2(&table_edge_ipl, storage, CV_HOUGH_STANDARD, 1, degree_bins*CV_PI/180, hough_thresh, 0, 0);
vector<float> theta_bins, rho_bins;
vector<uint32_t> count_bins;
for(uint32_t i=0; i < (uint32_t) lines->total; i++) {
float* line = (float*)cvGetSeqElem(lines, i);
float rho = line[0];
float theta = line[1];
bool found_same = false;
for(int32_t j=theta_bins.size()-1; j >= 0; j--) {
if(fabs(theta_bins[j]/count_bins[j] - theta) < theta_gran &&
fabs(rho_bins[j]/count_bins[j] - rho) < rho_gran) {
theta_bins[j] += theta;
rho_bins[j] += rho;
count_bins[j]++;
found_same = true;
break;
}
}
if(!found_same) {
theta_bins.push_back(theta);
rho_bins.push_back(rho);
count_bins.push_back(1);
}
double a = cos(theta), b = sin(theta);
double x0 = a*rho, y0 = b*rho;
CvPoint pt1, pt2;
a = cos(theta); b = sin(theta);
//a = cos(theta+CV_PI/2); b = sin(theta+CV_PI/2);
//x0 = objcenty; y0 = objcentx;
pt1.x = cvRound(x0 + 1000*(-b));
pt1.y = cvRound(y0 + 1000*(a));
pt2.x = cvRound(x0 - 1000*(-b));
pt2.y = cvRound(y0 - 1000*(a));
cvLine(&lines_img_ipl, pt1, pt2, cv::Scalar(100), 2, 8 );
}
//delete[] lines;
for(uint32_t i=0;i<theta_bins.size();i++) {
theta_bins[i] /= count_bins[i];
rho_bins[i] /= count_bins[i];
}
vector<float> posesx, posesy, poses_theta, dists_obj;
vector<uint32_t> pose_inds;
for(uint32_t i=0;i<theta_bins.size();i++) {
double theta = theta_bins[i];
double rho = rho_bins[i];
double a1 = cos(theta-CV_PI/2), b1 = sin(theta-CV_PI/2);
double a2 = cos(theta-CV_PI), b2 = sin(theta-CV_PI);
double vvcl = a2*b1-b2*a1, deltpx = cos(theta)*rho-objcenty, deltpy = sin(theta)*rho-objcentx;
double pvcr = deltpx*b1 - deltpy*a1;
double t = pvcr/vvcl;
double posey = objcenty + t*a2, posex = objcentx + t*b2;
printf("\naPose %d: (t: %f, %f, %f)[%f, %f](%f, %f)[%f, %f](1 %f, %f)(2 %f, %f)[theta %f, %f]\n", i, t, posex, posey, t*a2, t*b2, a1*rho, b1*rho, objcentx, objcenty, a1, b1, a2, b2, theta, rho);
if(posex == posex && posey == posey &&
posex >= 0 && posey >= 0 &&
posex < imgx && posey < imgy) {
posesx.push_back(posex); posesy.push_back(posey); poses_theta.push_back(theta);
pose_inds.push_back(posesx.size()-1);
float dist = (posex-objcentx)*(posex-objcentx)+(posey-objcenty)*(posey-objcenty);
dists_obj.push_back(dist);
}
//lines_img.at<uint8_t>(posex, posey)
}
boost::function<bool(uint32_t, uint32_t)> sortind = boost::bind(&compind, _1, _2, dists_obj);
sort(pose_inds.begin(), pose_inds.end(), sortind);
vector<float> retposesx, retposesy, retposesr;
grasp_points.poses.clear();
for(uint32_t i=0;i<pose_inds.size();i++) {
float posex = posesx[pose_inds[i]], posey = posesy[pose_inds[i]];
float poser = -poses_theta[pose_inds[i]] + 3*CV_PI/2;
bool same_found = false;
for(int32_t j=((int)retposesx.size())-1;j>=0;j--) {
if(fabs(posex - retposesx[j]) < xgran &&
fabs(posey - retposesy[j]) < ygran) {
same_found = true;
}
}
if(!same_found) {
retposesx.push_back(posex);
retposesy.push_back(posey);
retposesr.push_back(poser);
geometry_msgs::Pose cpose;
cpose.position.x = posex/imgx*(maxx-minx) + minx;
cpose.position.y = posey/imgy*(maxy-miny) + miny;
cpose.position.z = table_height/256.0*(maxz-minz) + minz;
btMatrix3x3 quatmat; btQuaternion quat;
quatmat.setEulerZYX(poser, 0 , 0);
quatmat.getRotation(quat);
cpose.orientation.x = quat.x(); cpose.orientation.y = quat.y();
cpose.orientation.z = quat.z(); cpose.orientation.w = quat.w();
grasp_points.poses.push_back(cpose);
}
}
grasp_points.header.stamp = ros::Time::now();
grasp_points.header.frame_id = base_frame;
pose_arr_pub.publish(grasp_points);
printf("\nCenter (%f, %f)\n", objcentx, objcenty);
for(uint32_t i=0;i<retposesx.size();i++) {
//for(uint32_t i=0;i<1;i++) {
printf("\nPose %d: (%f, %f, r: %f)\n", i, retposesx[i], retposesy[i], retposesr[i]);
//CvPoint centerpt; centerpt.x = objcenty; centerpt.y = objcentx;
CvPoint centerpt; centerpt.x = retposesy[i]; centerpt.y = retposesx[i];
cvCircle(&lines_img_ipl, centerpt, 3, cv::Scalar(200), 2);
}
//cv::Mat obj_feats(xfeats.size(), 1, CV_32S, cv::Scalar(0));
//for(uint32_t i=0;i<xfeats.size();i++) {
// obj_feats.at<uint32_t>(i,0) = xfeats[i]; obj_feats.at<uint32_t>(i,1) = yfeats[i]; obj_feats.at<uint32_t>(i,2) = zfeats[i];
//}
//cvflann::KMeansIndexParams kmips;
//kmips.branching = 32;
//kmips.iterations = 11;
//kmips.centers_init = cvflann::CENTERS_RANDOM;
//kmips.cb_index = 0.2;
//cv::Mat obj_centers;
//CvMat obj_feats_mat = obj_feats;
////cvflann::Matrix<uint32_t> obj_feats_mat;
////cvflann::Matrix<cvflann::EUCLIDEAN> obj_centers_mat;
//int num_clust = cvflann::hierarchicalClustering<CV_32S,CV_32S>(obj_feats_mat, obj_centers, kmips);
//printf("\nNum clust: %d \n", num_clust);
cv::Mat table_edge2 = table_edge.clone();
IplImage table_edge_ipl2 = table_edge2;
cvMorphologyEx(&table_edge_ipl2, &table_edge_ipl2, NULL, element, CV_MOP_DILATE, 3);
BOOST_FOREACH(const pcl::PointXYZRGB& pt, pc_full_frame.points) {
if(pt.x != pt.x || pt.y != pt.y || pt.z != pt.z)
continue;
int32_t x, y, z;
x = (pt.x - minx)/(maxx-minx) * imgx;
y = (pt.y - miny)/(maxy-miny) * imgy;
z = (pt.z - minz)/(maxz-minz) * 256;
if(x < 0 || y < 0) continue;
if(x >= imgx || y >= imgy) continue;
if(z < 0 || z >= 256) continue;
if(table_blob.at<uint8_t>(x,y) == 255 &&
std::fabs(table_height - z) < stddev*2) {
uint32_t red = 0xFFFF0000;
((uint32_t*) &pt.rgb)[0] = red;
}
if(table_edge2.at<uint8_t>(x,y) == 255 &&
std::fabs(table_height - z) < stddev*4) {
uint32_t blue = 0xFF0000FF;
((uint32_t*) &pt.rgb)[0] = blue;
}
}
cv_bridge::CvImage cvb_height_img;
//cvb_height_img.image = height_img_avg;
//cvb_height_img.image = height_img_max;
//cvb_height_img.image = height_morph;
//cvb_height_img.image = obj_img;
cvb_height_img.image = lines_img;
//cvb_height_img.image = height_img_thresh_blob;
//cvb_height_img.image = table_blob;
//cvb_height_img.image = height_img_thresh;
//cvb_height_img.image = above_table;
//cvb_height_img.image = table_edge;
cvb_height_img.header.stamp = ros::Time::now();
cvb_height_img.header.frame_id = base_frame;
cvb_height_img.encoding = enc::MONO8;
height_pub.publish(cvb_height_img.toImageMsg());
pc_full_frame.header.stamp = ros::Time::now();
pc_full_frame.header.frame_id = base_frame;
pc_pub.publish(pc_full_frame);
if(grasp_points.poses.size() > 0)
grasp_points_found = true;
//delete element;
pc_lock.unlock();
}
int main() {
CvPoint pt1,pt2;
CvRect regt;
CvPoint cir_center;
CvPoint frame_center;
CvPoint A,B,C,D;
CvPoint temp;
double angle,spinsize;
int cir_radius=1;
int frame_width=160, frame_height=120;
CvCapture* capture = cvCaptureFromCAM( CV_CAP_ANY );
if ( !capture ) {
fprintf(stderr, "ERROR: capture is NULL \n" );
getchar();
return -1;
}
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH,frame_width);// 120x160
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT,frame_height);
//cvSetCaptureProperty(capture, CV_CAP_PROP_FPS,10);
// cvSetCaptureProperty(capture,CV_CAP_PROP_POS_FRAMES,5);
// Create a window in which the captured images will be presented
cvNamedWindow( "mywindow", CV_WINDOW_AUTOSIZE );
// Show the image captured from the camera in the window and repeat
while ( 1 ) {
// Get one frame
IplImage* frame = cvQueryFrame( capture );
if ( !frame ) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
int modfheight, modfwidth;
modfheight = frame->height;
modfwidth = frame->width;
// create modified frame with 1/4th the original size
IplImage* modframe = cvCreateImage(cvSize((int)(modfwidth/4),(int)(modfheight/4)),frame->depth,frame->nChannels); //cvCreateImage(size of frame, depth, noofchannels)
cvResize(frame, modframe,CV_INTER_LINEAR);
// create HSV(Hue, Saturation, Value) frame
IplImage* hsvframe = cvCreateImage(cvGetSize(modframe),8, 3);
cvCvtColor(modframe, hsvframe, CV_BGR2HSV); //cvCvtColor(input frame,outputframe,method)
// create a frame within threshold.
IplImage* threshframe = cvCreateImage(cvGetSize(hsvframe),8,1);
cvInRangeS(hsvframe,cvScalar(15, 100, 100),cvScalar(60, 220, 220),threshframe); //cvInRangeS(input frame, cvScalar(min range),cvScalar(max range),output frame)
// created dilated image
IplImage* dilframe = cvCreateImage(cvGetSize(threshframe),8,1);
cvDilate(threshframe,dilframe,NULL,2); //cvDilate(input frame, output frame, mask, number of times to dilate)
CBlobResult blobs;
blobs = CBlobResult(dilframe,NULL,0); // CBlobresult(inputframe, mask, threshold) Will filter all white parts of image
blobs.Filter(blobs,B_EXCLUDE,CBlobGetArea(),B_LESS,50);//blobs.Filter(input, cond, criteria, cond, const) Filter all images whose area is less than 50 pixels
CBlob biggestblob;
blobs.GetNthBlob(CBlobGetArea(),0,biggestblob); //GetNthBlob(criteria, number, output) Get only the largest blob based on CblobGetArea()
// get 4 points to define the rectangle
pt1.x = biggestblob.MinX()*4;
pt1.y = biggestblob.MinY()*4;
pt2.x = biggestblob.MaxX()*4;
pt2.y = biggestblob.MaxY()*4;
cir_center.x=(pt1.x+pt2.x)/2;
cir_center.y=(pt1.y+pt2.y)/2;
frame_center.x=frame_width/2;
frame_center.y=frame_height/2;
A.x=frame_center.x-4;
A.y=frame_center.y;
B.x=frame_center.x+4;
B.y=frame_center.y;
C.y=frame_center.y-4;
C.x=frame_center.x;
D.y=frame_center.y+4;
D.x=frame_center.x;
cvRectangle(frame,pt1,pt2,cvScalar(255,0,0),1,8,0); // draw rectangle around the biggest blob
cvCircle( frame, cir_center, cir_radius, cvScalar(0,255,255), 1, 8, 0 ); // center point of the rectangle
cvLine(frame, A, B,cvScalar(255,0,255),2,8,0);
cvLine(frame, C, D,cvScalar(255,0,255),2,8,0);
if (cir_center.x!=0&&cir_center.y!=0){
spinsize=sqrt((cir_center.x-frame_center.x)*(cir_center.x-frame_center.x) +(cir_center.y-frame_center.y)*(cir_center.y-frame_center.y));
angle = atan2((double)cir_center.y-frame_center.y,(double)cir_center.x-frame_center.x);
temp.x=(int)(frame_center.x+spinsize/5*cos(angle+3.1416/4));
temp.y=(int)(frame_center.y+spinsize/5*sin(angle+3.1415/4));
cvLine(frame, temp, frame_center,cvScalar(0,255,0),1,8,0);
temp.x=(int)(frame_center.x+spinsize/5*cos(angle-3.1416/4));
temp.y=(int)(frame_center.y+spinsize/5*sin(angle-3.1415/4));
cvLine(frame, temp, frame_center,cvScalar(0,255,0),1,8,0);
cvLine(frame, cir_center, frame_center,cvScalar(0,255,0),1,8,0);
//cvCircle( frame, frame_center, cir_radius, cvScalar(0,255,255), 2, 8, 0 );
}
cvShowImage( "mywindow", frame); // show output image
// Do not release the frame!
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
if ( (cvWaitKey(10) & 255) == 27 ) break;
}
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
return 0;
}
float thresholdSegmentation(Rect r, ntk::RGBDImage* current_frame, Mat& dst){
Mat depth = current_frame->depth();
Rect& rr = r;
Mat depthROI = depth(rr), maskROI;
Mat& rDepthROI = depthROI, &rMaskROI = maskROI;
double var = 0.3;
// maskROI for nonZero values in the Face Region
inRange(depthROI, Scalar::all(0.001), Scalar::all(255), maskROI);
// Mean depth of Face Region
Scalar mFace = cv::mean(rDepthROI, rMaskROI);
//mFace[0] = mFace[0] - mFace[0] * var;
inRange(depthROI, Scalar::all(0.001), mFace, maskROI);
mFace = cv::mean(rDepthROI, rMaskROI);
//inRange(depthROI, Scalar::all(0.001), mFace, maskROI);
//mFace = cv::mean(rDepthROI, rMaskROI);
// Mask for nearer than the mean of face.
inRange(depth, Scalar::all(0.001), mFace, dst);
Mat rgbImage = current_frame->rgb();
Mat outFrame = cvCreateMat(rgbImage.rows, rgbImage.cols, CV_32FC3);
rgbImage.copyTo(outFrame, dst);
Mat outFrameROI;
outFrameROI = outFrame(rr);
//cvCopy(&rgbImage, &outFrame, &dst);
//rgbImageROI = rgbImageROI(rr);
imshow("ROI", outFrameROI);
//imshow("thresholdSeg", dst);
// For debug of cvblobslib
// Display the color image
//imshow("faceRIO", maskROI);
imshow("faceRIO", outFrameROI);
bool iswrite;
const int nchannel = 1;
vector<Rect> faces;
//iswrite = imwrite("faceROI.png", maskROI);
iswrite = imwrite("faceROI.png", outFrameROI);
//iswrite = cvSaveImage("faceROI.jpeg", pOutFrame, &nchannel);
// ---- blob segmentation on maskROI by using cvblobslib ----
// --- Third Trial ---
//visualizeBlobs("faceROI.png", "faceRIO");
// --- First Trial Not Successful ---
//Mat maskROIThr=cvCreateMat(maskROI.rows, maskROI.cols, CV_8UC1);
//maskROIThr = maskROI;
//IplImage imgMaskROIThr = maskROIThr;
//IplImage* pImgMaskROIThr = &imgMaskROIThr;
//cvThreshold(pImgMaskROIThr, pImgMaskROIThr, 0.1, 255, CV_THRESH_BINARY_INV);
// --- Second Trial ---
IplImage* original = cvLoadImage("faceROI.png", 0);
IplImage* originalThr = cvCreateImage(cvGetSize(original), IPL_DEPTH_8U, 1);
IplImage* displayBiggestBlob = cvCreateImage(cvGetSize(original), IPL_DEPTH_8U, 3);
CBlobResult blobs;
CBlob biggestBlob;
//IplImage source = maskROIThr; IplImage* pSource = &source;
//blobs = CBlobResult(
cvThreshold(original, originalThr, 0.1, 255, CV_THRESH_BINARY_INV);
blobs = CBlobResult( originalThr, NULL, 255);
printf("%d blobs \n", blobs.GetNumBlobs());
blobs.GetNthBlob(CBlobGetArea(), 0, biggestBlob);
biggestBlob.FillBlob(displayBiggestBlob, CV_RGB(255, 0, 0));
// Drawing the eclipse and Rect on the blob
Mat mat(displayBiggestBlob);
cv::RotatedRect blobEllipseContour;
cv::Rect blobRectContour;
//RotatedRect blobEllipseContour;
blobEllipseContour = biggestBlob.GetEllipse();
blobRectContour = biggestBlob.GetBoundingBox();
//cv::ellipse(
cv::ellipse(mat, blobEllipseContour, cv::Scalar(0,255, 0), 3, CV_AA);
cv::rectangle(mat, blobRectContour, cv::Scalar(255, 0, 0), 3, CV_AA);
//cv::ellipse(mat, blobEllipseContour);
float headOritation = blobEllipseContour.angle;
if (headOritation <= 180)
headOritation = headOritation - 90;
else
headOritation = headOritation - 270;
cv::putText(mat,
cv::format("%f degree", headOritation),
Point(10,20), 0, 0.5, Scalar(255,0,0,255));
cv::imshow("faceRIO", mat);
return(headOritation);
}
/*
* thread for displaying the opencv content
*/
void *cv_threadfunc (void *ptr) {
IplImage* timg = cvCloneImage(rgbimg); // Image we do our processing on
IplImage* dimg = cvCloneImage(rgbimg); // Image we draw on
CvSize sz = cvSize( timg->width & -2, timg->height & -2);
IplImage* outimg = cvCreateImage(sz, 8, 3);
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* squares; // Sequence for squares - sets of 4 points
CvSeq* contours; // Raw contours list
CvSeq* result; // Single contour being processed
CBlobResult blobs;
CBlob *currentBlob;
IplImage *pyr = cvCreateImage(cvSize(sz.width/2, sz.height/2), 8, 1);
// Set region of interest
cvSetImageROI(timg, cvRect(0, 0, sz.width, sz.height));
cvSetImageROI(dimg, cvRect(0, 0, sz.width, sz.height));
// Processing and contours
while (1) {
squares = cvCreateSeq(0, sizeof(CvSeq), sizeof(CvPoint), storage);
pthread_mutex_lock( &mutex_rgb );
cvCopy(rgbimg, dimg, 0);
cvCopy(rgbimg, timg, 0);
pthread_mutex_unlock( &mutex_rgb );
// BLUR TEST
// cvPyrDown(dimg, pyr, 7);
// cvPyrUp(pyr, timg, 7);
// DILATE TEST
IplConvKernel* element = cvCreateStructuringElementEx(5, 5, 2, 2, 0);
IplConvKernel* element2 = cvCreateStructuringElementEx(3, 3, 1, 1, 0);
cvDilate(timg, timg, element, 2);
cvErode(timg, timg, element2, 3);
// THRESHOLD TEST
cvThreshold(timg, timg, 200, 255, CV_THRESH_BINARY);
// Output processed or raw image.
cvCvtColor(timg, outimg, CV_GRAY2BGR);
// BLOB TEST
blobs = CBlobResult( timg, (IplImage*)NULL, 0, true );
// blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_LESS, 50 );
printf("Blobs: %d\n", blobs.GetNumBlobs());
CBlob biggestBlob;
blobs.GetNthBlob( CBlobGetArea(), 1, biggestBlob );
biggestBlob.FillBlob( outimg, CV_RGB(255, 0, 0) );
CvSeq* dest;
biggestBlob.GetConvexHull(dest);
// for (int i = 0; i < blobs.GetNumBlobs(); i++ )
// {
// currentBlob = blobs.GetBlob(i);
// currentBlob->FillBlob( outimg, CV_RGB(255,0,0) );
// }
// // CONTOUR FINDING
// cvFindContours(timg, storage, &contours, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));
//
// while (contours)
// {
// // Approximate contour, accuracy proportional to perimeter of contour; may want to tune accuracy.
// result = cvApproxPoly(contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours) * 0.02, 0);
// // Filter small contours and contours w/o 4 vertices (filters noise, finds rectangles)
// if (result->total == 4 &&
// fabs(cvContourArea(result, CV_WHOLE_SEQ)) > 600 &&
// cvCheckContourConvexity(result))
// {
// // Skipped checking whether angles were close to 90 degrees here; may want to implement.
// // Probably also want to check if it's square enough to filter out ex. long windows.
//
// for (int i = 0; i < 4; i++)
// {
// // Write vertices to output sequence
// cvSeqPush(squares, (CvPoint*)cvGetSeqElem(result, i));
// }
// }
//
// // Take next contour
// contours = contours->h_next;
// }
//
//
// // DRAW RECTANGLES
// CvSeqReader reader;
// cvStartReadSeq(squares, &reader, 0);
//
// // Read 4 points at a time
// CvPoint pt[4];
// CvPoint *rect = pt;
// CvRect out[4];
// CvRect *outrect = out;
// for (int i = 0; i < squares->total; i += 4)
// {
// int count = 4;
//
// // Which point is which corner is unpredictable.
// CV_READ_SEQ_ELEM(pt[0], reader);
// CV_READ_SEQ_ELEM(pt[1], reader);
// CV_READ_SEQ_ELEM(pt[2], reader);
// CV_READ_SEQ_ELEM(pt[3], reader);
// // Draw rectangle on output
// cvPolyLine(outimg, &rect, &count, 1, 1, CV_RGB(0,255,0), 1, CV_AA, 0);
// // Make rectangles
// // Print (temporary)
// printf("Rect[0]: %d, %d\n", pt[0].x, pt[0].y);
// printf("Rect[1]: %d, %d\n", pt[1].x, pt[1].y);
// printf("Rect[2]: %d, %d\n", pt[2].x, pt[2].y);
// printf("Rect[3]: %d, %d\n\n", pt[3].x, pt[3].y);
// fflush(stdout);
//
// }
//
// Print on order
if( cvWaitKey( 15 )==27 )
{
}
cvShowImage (FREENECTOPENCV_WINDOW_N,outimg);
cvClearMemStorage(storage);
}
pthread_exit(NULL);
}
int main() {
CvPoint pt1,pt2;
CvRect regt;
CvCapture* capture = cvCaptureFromCAM( CV_CAP_ANY );
if ( !capture ) {
fprintf(stderr, "ERROR: capture is NULL \n" );
getchar();
return -1;
}
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT,144);
cvSetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH,216);
// Create a window in which the captured images will be presented
cvNamedWindow( "mywindow", CV_WINDOW_AUTOSIZE );
// Show the image captured from the camera in the window and repeat
while ( 1 ) {
// Get one frame
IplImage* frame = cvQueryFrame( capture );
if ( !frame ) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
int modfheight, modfwidth;
modfheight = frame->height;
modfwidth = frame->width;
// create modified frame with 1/4th the original size
IplImage* modframe = cvCreateImage(cvSize((int)(modfwidth/4),(int)(modfheight/4)),frame->depth,frame->nChannels); //cvCreateImage(size of frame, depth, noofchannels)
cvResize(frame, modframe,CV_INTER_LINEAR);
// create HSV(Hue, Saturation, Value) frame
IplImage* hsvframe = cvCreateImage(cvGetSize(modframe),8, 3);
cvCvtColor(modframe, hsvframe, CV_BGR2HSV); //cvCvtColor(input frame,outputframe,method)
// create a frame within threshold.
IplImage* threshframe = cvCreateImage(cvGetSize(hsvframe),8,1);
cvInRangeS(hsvframe,cvScalar(30, 25, 150),cvScalar(60, 60, 220),threshframe); //cvInRangeS(input frame, cvScalar(min range),cvScalar(max range),output frame)
// created dilated image
IplImage* dilframe = cvCreateImage(cvGetSize(threshframe),8,1);
cvDilate(threshframe,dilframe,NULL,2); //cvDilate(input frame, output frame, mask, number of times to dilate)
CBlobResult blobs;
blobs = CBlobResult(dilframe,NULL,0); // CBlobresult(inputframe, mask, threshold) Will filter all white parts of image
blobs.Filter(blobs,B_EXCLUDE,CBlobGetArea(),B_LESS,50);//blobs.Filter(input, cond, criteria, cond, const) Filter all images whose area is less than 50 pixels
CBlob biggestblob;
blobs.GetNthBlob(CBlobGetArea(),0,biggestblob); //GetNthBlob(criteria, number, output) Get only the largest blob based on CblobGetArea()
// get 4 points to define the rectangle
pt1.x = biggestblob.MinX()*4;
pt1.y = biggestblob.MinY()*4;
pt2.x = biggestblob.MaxX()*4;
pt2.y = biggestblob.MaxY()*4;
cvRectangle(frame,pt1,pt2,cvScalar(255,0,0),1,8,0); // draw rectangle around the biggest blob
cvShowImage( "mywindow", frame); // show output image
// Do not release the frame!
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
if ( (cvWaitKey(10) & 255) == 27 ) break;
}
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
return 0;
}
void blobbing( IplImage *hi, char * win1, char * win2, int check ) {
cvCvtColor(hi,hi2,CV_BGR2HSV);
uchar *itemp=(uchar *)(hi2->imageData);
uchar *itemp1=(uchar *)(hitemp->imageData);
// binary conversion
for(int i=0;i<hi2->height;i++){
for(int j=0;j<hi2->width;j++){
if((itemp[i*hi2->widthStep+j*hi2->nChannels] <hh)
&&
(itemp[i*hi2->widthStep+j*hi2->nChannels]>hl)
&&
(itemp[i*hi2->widthStep+j*hi2->nChannels+1]<sh)
&&
(itemp[i*hi2->widthStep+j*hi2->nChannels+1]>sl)
&&
( itemp[i*hi2->widthStep+j*hi2->nChannels+2]<vh)
&&
( itemp[i*hi2->widthStep+j*hi2->nChannels+2]>vl) //previous 124
)
{
itemp1[i*hitemp->widthStep+j]=0; //dark regions black rest white
}
else
itemp1[i*hitemp->widthStep+j]=255;
}}
cvErode( hitemp, hitemp1, NULL, 3);
cvDilate(hitemp1, hitemp1, NULL, 3);
hitemp=hitemp1;
CBlobResult blob;
CBlob *currentBlob=NULL;
blob=CBlobResult(hitemp1,NULL,255);
blob.Filter(blob,B_EXCLUDE,CBlobGetArea(),B_LESS,500);
cvMerge(hitemp1,hitemp1,hitemp1,NULL,out);
CBlob hand1,hand2; //two blobs,one for each hand
blob.GetNthBlob( CBlobGetArea(), 0, (hand2));
blob.GetNthBlob( CBlobGetArea(), 1, (hand1 ));
hand1.FillBlob(out,CV_RGB(0,0,255)); //fill the color of blob of hand one with blue
hand2.FillBlob(out,CV_RGB(0,255,0)); //fill the color of blob of hand two with green
coordinates (out,check); //to find the coordinates of the hands we pass the image onto the function coordinates
int greater1,greater2,lesser1,lesser2;
if(x>X) {
greater1=x,greater2=y;
lesser1=X,lesser2=Y;
}
else {
greater1=X,greater2=Y;
lesser1=x,lesser2=y;
}
/*cvCircle ( hi, cvPoint(greater1,greater2), 10,
cvScalar(0,0,255), -1, 8 );
cvCircle ( hi, cvPoint(lesser1,lesser2), 10,
cvScalar(0,255,255), -1, 8 );
*/
cvResizeWindow(win2,280,280);
cvMoveWindow(win2,0,0);
cvShowImage(win2,out);
return ;
}
