Php::Value FastImage::crop(Php::Parameters ¶meters)
{
Php::Value self(this);
int x = parameters[0];
int y = parameters[1];
int w = parameters[2];
int h = parameters[3];
if (x < 0) throwMustBePositiveOrNilException("1", "FastImage::crop", parameters[0].stringValue());
if (y < 0) throwMustBePositiveOrNilException("2", "FastImage::crop", parameters[1].stringValue());
if (w <= 0) throwMustBePositiveException("3", "FastImage::crop", parameters[2].stringValue());
if (h <= 0) throwMustBePositiveException("4", "FastImage::crop", parameters[3].stringValue());
if ((x + w) > cvImage.size().width) {
throwOutOfBoundException("FastImage::crop");
}
if ((y +h) > cvImage.size().height) {
throwOutOfBoundException("FastImage::crop");
}
cv::Rect roi(x, y, w, h);
cv::Mat croppedImage = cvImage(roi);
cvImage = croppedImage;
croppedImage.release();
return self;
}
void process( FrameData &frameData ) {
vector< vector< FrameData::Cluster> > &clusters = frameData.clusters;
vector< vector< FrameData::Match > > matches = frameData.matches;
Image *img = frameData.images[0].get();
cv::Mat cvImage( img->height, img->width, CV_8UC1 );
for (int y = 0; y < img->height; y++) {
for (int x = 0; x < img->width; x++) {
cvImage.at<uchar>(y, x) = (float) img->data[img->width*y+x];
}
}
vector<int> modelSize;
foreach( model, *models )
modelSize.push_back(model->IPs["SIFT"].size());
for ( int model = 0; model < (int)clusters.size(); model ++ ) {
int featNum = modelSize[model];
for ( int cluster = 0; cluster < (int)clusters[model].size(); cluster ++ ) {
// Unify the observation features
list<int>::iterator it;
int count = 0;
vector<Node> nodes;
map<Pt<3>, int> usedObsPts;
vector<int> obsPts;
for ( it = clusters[model][cluster].begin(); it != clusters[model][cluster].end(); it ++ ) {
int idx = *it;
Pt<3> obsPt = matches[model][idx].cloud3D;
Pt<3> mdlPt = matches[model][idx].coord3D;
Pt<2> imgPt = matches[model][idx].coord2D;
int mdlIdx = matches[model][idx].featIdx;
if ( usedObsPts[obsPt] == 0 ) {
usedObsPts[obsPt] = count;
Node node;
node.obsPos = obsPt;
node.mdlPos.push_back(mdlPt);
node.imgPos.push_back(imgPt);
node.obsIdx = idx;
node.obsIdxs.push_back( idx );
node.mdlIdxs.push_back( mdlIdx );
nodes.push_back( node );
count ++;
}
else {
int tmp = usedObsPts[obsPt];
nodes[tmp].mdlPos.push_back(mdlPt);
nodes[tmp].imgPos.push_back(imgPt);
nodes[tmp].mdlIdxs.push_back( mdlIdx );
nodes[tmp].obsIdxs.push_back( idx );
}
}
map<int, int> usedMdlPts;
// Weighted vertex cover
/*
for ( int node = 0; node < nodes.size(); node ++ ) {
int matchNum = nodes[node].obsIdxs.size();
if ( matchNum != 1 ) {
// multiple matches for 1 observed feature
double minDist = INT_MAX;
int minIdx;
for ( int i = 0; i < nodes[node].obsIdxs.size(); i ++ ) {
int matchIdx = nodes[node].obsIdxs[i];
double matchDist = matches[model][matchIdx].dist;
if ( dist < minDist ) {
minDist = dist;
minIdx = i;
}
}
for ( int i = 0; i < nodes[node].obsIdxs.size(); i ++ ) {
if ( i != minIdx ) {
nodes[node].obsIdxs.erase( nodes[node].obsIdxs.begin() + i );
nodes[node].mdlIdxs.erase( nodes[node].mdlIdxs.begin() + i );
}
}
}
int mdlSize = nodes[node].mdlIdxs.size();
if ( mdlSize == 1 ) {
int mdlIdx = nodes[node].mdlIdxs[0];
if ( usedMdlPts[mdlIdx] == 0 ) {
usedMdlPts[mdlIdx] = node;
}
else {
// compare the matched distances
int preNode = usedMdlPts[mdlIdx];
int preMatch = nodes[preNode].obsIdx;
int curMatch = nodes[node].obsIdx;
}
}
}
*/
// Unweighted vertex cover
for ( int it = 0; it < nodes.size(); it ++ ) {
for ( int i = 0; i < nodes[it].mdlIdxs.size(); i ++ ) {
int mdlIdx = nodes[it].mdlIdxs[i];
if ( usedMdlPts[mdlIdx] == 0 ) {
usedMdlPts[mdlIdx] = it;
}
else {
nodes.erase( nodes.begin() + it );
}
}
}
// resetting cluster data
clusters[model][cluster].clear();
for ( int it = 0; it < nodes.size(); it ++ )
clusters[model][cluster].push_back( nodes[it].obsIdx );
// for ( map<Pt<3>, int>::iterator it = usedObsPts.begin(); it != usedObsPts.end(); ++ it )
// cout << it->first << " => " << it->second << '\n';
}
}
}
