TEST(greedy_algorithms_test, GPGA)
{
// load the MATLAB MAT file
MatlabIO matio;
string file_path = "/home/xiejianhe/Pycharm/SPDA/csgpda/data/temp_20160322.mat";
bool ok = matio.open(file_path, "r");
if (!ok) {
EXPECT_TRUE(false);
} else {
// read all of the variables in the file
std::vector<MatlabIOContainer> variables;
variables = matio.read();
matio.close();
// load the matrix by name in OpenCV style
Mat D = matio.find<Mat>(variables, "D");
Mat DTY = matio.find<Mat>(variables, "DTY");
Mat Y = matio.find<Mat>(variables, "Y");
// convert cvMat to Eigen
// and call pga_newton function
MatrixXd dict, y_eigen, dty_eigen;
cv2eigen(D, dict);
cv2eigen(Y, y_eigen);
cv2eigen(DTY, dty_eigen);
int dict_row = dict.rows(), dict_col = dict.cols(), patch_num = y_eigen.cols();
const int k = 2;
MatrixXd alphahat = MatrixXd::Zero(dict_col, patch_num);
MatrixXd xhat = MatrixXd::Zero(dict_row, patch_num);
double diver_error = GPGA(dict, dty_eigen, y_eigen, k, xhat, alphahat);
}
}
/*! @brief deserialize a Matlab .Mat file into memory
*
* deserialize a valid version 5 .Mat file using the underlying
* MatlabIO parser, and populate the model fields. If any of the fields
* do not exist, or a bad type cast is attempted, an exception will be thrown
*
* @param filename the path to the model file
* @return true if the file was found, opened and verified to be a valid Matlab
* version 5 file
* @throws boost::bad_any_cast, exception
*/
bool MatlabIOModel::deserialize(const std::string& filename) {
// open the Mat File for reading
MatlabIO cvmatio;
bool ok = cvmatio.open(filename, "r");
if (!ok) return false;
// read all of the variables from the file
vectorMatlabIOContainer variables;
variables = cvmatio.read();
// populate the model, one variable at a time
try {
name_ = cvmatio.find<std::string>(variables, "name");
} catch (...) {
name_ = boost::filesystem::path(filename).stem().c_str();
}
/*
cv::Mat pa = cvmatio.find<cv::Mat>(variables, "pa");
for (unsigned int n = 0; n < pa.cols*pa.rows; ++n) conn_.push_back(pa.at<double>(n));
zeroIndex(conn_);
*/
//model
vectorMatlabIOContainer model = cvmatio.find<vector2DMatlabIOContainer>(variables, "model")[0];
nscales_ = cvmatio.find<double>(model, "interval");
thresh_ = cvmatio.find<double>(model, "thresh");
binsize_ = cvmatio.find<double>(model, "sbin");
norient_ = 18;
// ------------------------------
// get the filters
vector2DMatlabIOContainer filters = cvmatio.find<vector2DMatlabIOContainer>(model, "filters");
for (unsigned int f = 0; f < filters.size(); ++f) {
// flatten the filters to 2D
cv::Mat filter = cvmatio.find<cv::Mat>(filters[f], "w");
const unsigned int M = filter.rows;
const unsigned int N = filter.cols;
vectorMat filter_vec;
cv::split(filter, filter_vec);
const unsigned int C = filter_vec.size();
flen_ = C;
cv::Mat filter_flat(cv::Size(N * C, M), cv::DataType<double>::type);
for (unsigned int m = 0; m < M; ++m) {
for (unsigned int c = 0; c < C; ++c) {
for (unsigned int n = 0; n < N; ++n) {
filter_flat.at<double>(m,n*C+c) = filter_vec[c].at<double>(m,n);
}
}
}
filtersw_.push_back(filter_flat);
//filtersi_.push_back(cvmatio.find<double>(filters[f], "i"));
}
// ------------------------------
// get the components
vectorMatlabIOContainer components = cvmatio.find<vectorMatlabIOContainer>(model, "components");
const unsigned int ncomponents = components.size();
biasid_.resize(ncomponents);
filterid_.resize(ncomponents);
defid_.resize(ncomponents);
parentid_.resize(ncomponents);
for (unsigned int c = 0; c < ncomponents; ++c) {
// a single component is a struct array
vector2DMatlabIOContainer component = components[c].data<vector2DMatlabIOContainer>();
const unsigned int nparts = component.size();
biasid_[c].resize(nparts);
filterid_[c].resize(nparts);
defid_[c].resize(nparts);
parentid_[c].resize(nparts);
// for each element, add to the component indices
for (unsigned int p = 0; p < nparts; ++p) {
cv::Mat defid = cvmatio.find<cv::Mat>(component[p], "defid");
cv::Mat filterid = cvmatio.find<cv::Mat>(component[p], "filterid");
int parentid = cvmatio.find<double>(component[p], "parent");
// the biasid type can change, depending on the number of elements saved
cv::Mat biasid = cvmatio.find<cv::Mat>(component[p], "biasid");
biasid_[c][p] = vectori(biasid.begin<double>(), biasid.end<double>());
zeroIndex(biasid_[c][p]);
parentid_[c][p] = parentid;
filterid_[c][p] = vectori(filterid.begin<double>(), filterid.end<double>());
defid_[c][p] = vectori(defid.begin<double>(), defid.end<double>());
// re-index from zero (Matlab uses 1-based indexing)
zeroIndex(parentid_[c][p]);
zeroIndex(filterid_[c][p]);
zeroIndex(defid_[c][p]);
}
}
// ------------------------------
// get the defs
vector2DMatlabIOContainer defs = cvmatio.find<vector2DMatlabIOContainer>(model, "defs");
const unsigned int ndefs = defs.size();
for (unsigned int n = 0; n < ndefs; ++n) {
defw_.push_back(cvmatio.find<cv::Mat>(defs[n], "w"));
//defi_.push_back(cvmatio.find<double>(defs[n], "i"));
cv::Mat anchor = cvmatio.find<cv::Mat>(defs[n], "anchor");
anchors_.push_back(cv::Point(anchor.at<double>(0), anchor.at<double>(1)));
}
zeroIndex(anchors_);
// ------------------------------
// get the bias
vector2DMatlabIOContainer bias = cvmatio.find<vector2DMatlabIOContainer>(model, "bias");
const unsigned int nbias = bias.size();
for (unsigned int n = 0; n < nbias; ++n) {
biasw_.push_back(cvmatio.find<double>(bias[n], "w"));
//biasi_.push_back(cvmatio.find<double>(bias[n], "i"));
}
return true;
}