// load template images
bool OfflineTemplatesLoader::loadTemplateImages(
const ObjectsConfig &objectsConfig,
cv::Ptr<Detector> &detector,
std::map<int, std::vector<cv::Mat> > &images,
std::map<int, std::vector<cv::Rect> > &boundingBoxes)
{
const int objectNum = objectsConfig.object_config_size();
CHECK(objectNum>0) << "No template images.";
#pragma omp parallel for
for(int i=0; i<objectNum; ++i)
{
const ObjectConfig &objectConfig = objectsConfig.object_config(i);
const int classId = objectConfig.id();
const std::string &className = objectConfig.name();
const std::string &imagesDir = objectConfig.img_dir();
//read images
std::vector<std::string> fileName;
CHECK(GetFileNames(imagesDir, fileName))
<< "Cannot get files name in specific directory";
std::vector<cv::Mat> imgs;
std::vector<cv::Rect> bbs;
for(int k=0; k<(int)fileName.size(); ++k)
{
std::string file = imagesDir + "/" + fileName[k];
cv::Mat img=cv::imread( file );
//extract a new template for current image
cv::Rect tmplBoundingBox;
int template_id = detector->addTemplate(img, classId, &tmplBoundingBox);
//save all images, it is not a good idea when template images are large
//but to do matches refinement, there's not good way
imgs.push_back(img);
bbs.push_back(tmplBoundingBox);
}
#pragma omp critical
{
images.insert(std::pair<int, std::vector<cv::Mat> >(classId, imgs));
boundingBoxes.insert(std::pair<int, std::vector<cv::Rect> >(classId, bbs));
}
}
return true;
}
// load template images, poses of images, obj model file
bool OfflineTemplatesLoader::loadTemplateImagesAndPoses(
const ObjectsConfig &objectsConfig,
cv::Ptr<Detector> &detector,
std::map<int, std::vector<cv::Mat> > &images,
std::map<int, std::vector<cv::Rect> > &boundingBoxes,
std::map<int, std::vector<cv::Matx61f> > &poses,
std::map<int, GLMmodel*> &objModels)
{
const int objectNum = objectsConfig.object_config_size();
CHECK(objectNum>0) << "No template images.";
#pragma omp parallel for
for(int i=0; i<objectNum; ++i)
{
const ObjectsConfig_ObjectConfig &objectConfig = objectsConfig.object_config(i);
const int classId = objectConfig.id();
const std::string &className = objectConfig.name();
//const std::string &imagesDir = objectConfig.img_dir();
//const std::string &posePath = objectConfig.pose_path();
const std::string &modelPath = objectConfig.model_path();
//CHECK(!posePath.empty())<< "Please configure the file path of pose file.";
CHECK(!modelPath.empty())<< "Please configure the file path of obj file.";
#if 0
// read images
std::vector<std::string> fileName;
CHECK(GetFileNames(imagesDir, fileName))
<< "Cannot get files name in specific directory";
std::vector<cv::Mat> imgs;
std::vector<cv::Rect> bbs;
for(int k=0; k<(int)fileName.size(); ++k)
{
std::string file = imagesDir + "/" + fileName[k];
cv::Mat img=cv::imread( file );
//extract a new template for current image
cv::Rect tmplBoundingBox;
int template_id = detector->addTemplate(img, classId, &tmplBoundingBox);
//save all images, it is not a good idea when template images are large
//but to do matches refinement, there's not good way
imgs.push_back(img);
bbs.push_back(tmplBoundingBox);
}
// read pose file
std::ifstream poseInFile(posePath.c_str());
CHECK(poseInFile.is_open()) << "Cannot open pose file.";
std::vector<cv::Matx61f> posesParam;
for(int j=0; j<(int)fileName.size(); ++j)
{
cv::Matx61f poseTmp;
// rotation vector and translation vector
poseInFile >> poseTmp.val[0] >> poseTmp.val[1] >> poseTmp.val[2]
>> poseTmp.val[3] >> poseTmp.val[4] >> poseTmp.val[5];
posesParam.push_back(poseTmp);
}
#endif
// read template images and corresponding poses
std::vector<cv::Mat> imgs;
std::vector<cv::Rect> bbs;
std::vector<cv::Matx61f> posesParam;
for(int j=0; j<objectConfig.imagedir_posefile_pair_size(); ++j)
{
const ObjectsConfig_ObjectConfig_ImageDirAndPoseFilePair& imagedir_posefile = objectConfig.imagedir_posefile_pair(j);
const std::string &imagesDir = imagedir_posefile.img_dir();
const std::string &posePath = imagedir_posefile.pose_path();
// read images
std::vector<std::string> fileName;
CV_Assert(GetFileNames(imagesDir, fileName));
for(int k=0; k<(int)fileName.size(); ++k)
{
std::string file = imagesDir + "/" + fileName[k];
cv::Mat img=cv::imread( file );
//extract a new template for current image
cv::Rect tmplBoundingBox;
int template_id = detector->addTemplate(img, classId, &tmplBoundingBox);
//save all images, it is not a good idea when template images are large
//but to do matches refinement, there's not good way
imgs.push_back(img);
bbs.push_back(tmplBoundingBox);
}
// read poses
std::ifstream poseInFile(posePath.c_str());
CV_Assert(poseInFile.is_open());
for(int j=0; j<(int)fileName.size(); ++j)
{
cv::Matx61f poseTmp;
// rotation vector and translation vector
poseInFile >> poseTmp.val[0] >> poseTmp.val[1] >> poseTmp.val[2]
>> poseTmp.val[3] >> poseTmp.val[4] >> poseTmp.val[5];
posesParam.push_back(poseTmp);
}
}
// read obj file
GLMmodel *modelTmp = glmReadOBJ(const_cast<char*>(modelPath.c_str()));
#pragma omp critical
{
images.insert(std::pair<int, std::vector<cv::Mat> >(classId, imgs));
boundingBoxes.insert(std::pair<int, std::vector<cv::Rect> >(classId, bbs));
poses.insert( std::pair<int, std::vector<cv::Matx61f> >(classId, posesParam) );
objModels.insert(std::pair<int, GLMmodel*>(classId, modelTmp));
}
}
return true;
}