mexopencv-3.4.1编译好的库matlab直接用

/** Implementation of MxArray. * @file MxArray.cpp * @author Kota Yamaguchi * @date 2012 */ #include "MxArray.hpp" namespace { /// Field names for cv::Moments. const char *cv_moments_fields[24] = { "m00", "m10", "m01", "m20", "m11", "m02","m30", "m21", "m12", "m03", "mu20", "mu11", "mu02", "mu30", "mu21", "mu12", "mu03", "nu20", "nu11", "nu02", "nu30", "nu21", "nu12", "nu03"}; /// Field names for cv::RotatedRect. const char *cv_rotated_rect_fields[3] = {"center", "size", "angle"}; /// Field names for cv::TermCriteria. const char *cv_term_criteria_fields[3] = {"type", "maxCount", "epsilon"}; /// Field names for cv::KeyPoint. const char *cv_keypoint_fields[6] = {"pt", "size", "angle", "response", "octave", "class_id"}; /// Field names for cv::DMatch. const char *cv_dmatch_fields[4] = {"queryIdx", "trainIdx", "imgIdx", "distance"}; /** Translates data type definition used in MATLAB to that of OpenCV. * @param classid data type of MATLAB's mxArray. e.g., \c mxDOUBLE_CLASS. * @return OpenCV's data type. e.g., \c CV_8U. */ const ConstMap<mxClassID, int> DepthOf = ConstMap<mxClassID, int> (mxDOUBLE_CLASS, CV_64F) (mxSINGLE_CLASS, CV_32F) (mxINT8_CLASS, CV_8S) (mxUINT8_CLASS, CV_8U) (mxINT16_CLASS, CV_16S) (mxUINT16_CLASS, CV_16U) (mxINT32_CLASS, CV_32S) (mxUINT32_CLASS, CV_32S) (mxLOGICAL_CLASS, CV_8U); /** Translates data type definition used in OpenCV to that of MATLAB. * @param depth data depth of OpenCV's Mat class. e.g., \c CV_32F. * @return data type of MATLAB's mxArray. e.g., \c mxDOUBLE_CLASS. */ const ConstMap<int,mxClassID> ClassIDOf = ConstMap<int,mxClassID> (CV_64F, mxDOUBLE_CLASS) (CV_32F, mxSINGLE_CLASS) (CV_8S, mxINT8_CLASS) (CV_8U, mxUINT8_CLASS) (CV_16S, mxINT16_CLASS) (CV_16U, mxUINT16_CLASS) (CV_32S, mxINT32_CLASS); /** Comparison operator for sparse matrix elements. * This functor sorts SparseMat nodes in column-major order. * Only meant to be used on arrays with 2 dimensions. */ struct CompareSparseMatNode { /// Comparison functor bool operator () (const cv::SparseMat::Node* rhs, const cv::SparseMat::Node* lhs) const { // sort by column, then by row if (rhs->idx[1] < lhs->idx[1]) return true; if (rhs->idx[1] == lhs->idx[1] && rhs->idx[0] < lhs->idx[0]) return true; return false; } }; /// Inverse TermCriteria type map for option processing. const ConstMap<int, std::string> InvTermCritType = ConstMap<int, std::string> (cv::TermCriteria::COUNT, "Count") (cv::TermCriteria::EPS, "EPS") (cv::TermCriteria::COUNT+cv::TermCriteria::EPS, "Count+EPS"); /// TermCriteria type map for option processing. const ConstMap<std::string, int> TermCritType = ConstMap<std::string, int> ("Count", cv::TermCriteria::COUNT) ("EPS", cv::TermCriteria::EPS) ("Count+EPS", cv::TermCriteria::COUNT+cv::TermCriteria::EPS); } // anonymous namespace int MexErrorHandler(int status, const char *func_name, const char *err_msg, const char *file_name, int line, void * /*userdata*/) { mexErrMsgIdAndTxt("mexopencv:error", "OpenCV Error:\n" " Status : %s (%d)\n" " Message : %s\n" " Function: %s\n" " File : <a href=\"matlab:opentoline('%s',%d)\">%s</a>\n" " Line : %d\n", cvErrorStr(status), status, err_msg, (func_name ? func_name : "(unknown)"), file_name, line, file_name, line); return 0; } MxArray& MxArray::operator=(const MxArray& rhs) { if (this != &rhs) this->p_ = rhs.p_; return *this; } MxArray::MxArray(const int i) : p_(mxCreateDoubleScalar(static_cast<double>(i))) { if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); } MxArray::MxArray(const double d) : p_(mxCreateDoubleScalar(d)) { if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); } MxArray::MxArray(const bool b) : p_(mxCreateLogicalScalar(b)) { if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); } MxArray::MxArray(const std::string& s) : p_(mxCreateString(s.c_str())) { if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); } #if 0 // - works for multi-channel arrays, but doesnt work for ND-arrays because // the order of dimensions is not right (row to column major order) // (the std::swap below only gets it right for 2D arrays). // - There's another bug regarding multi-channel arrays where mat.channels() // is limited because of cv::transpose, which is only implemented for a number // of cases, and asserts that mat.elementSize() <= 32 // (elementSize = sizeof(depth)*nchannels), so for mat.depth()==CV_8U we can // go up to 32 channels, but for mat.depth()==CV_64F we can only go up to a // maximum of 4 channels (8*4 == 32) MxArray::MxArray(const cv::Mat& mat, mxClassID classid, bool transpose) { // handle special case of empty input Mat by creating an empty array classid = (classid == mxUNKNOWN_CLASS) ? ClassIDOf[mat.depth()] : classid; if (mat.empty()) { p_ = mxCreateNumericMatrix(0, 0, classid, mxREAL); if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); return; } // transpose cv::Mat if needed cv::Mat input(mat); if (input.dims == 2 && transpose) input = input.t(); // Create a new mxArray (of the specified classID) equivalent to cv::Mat const mwSize nchannels = input.channels(); const int* dims_ = input.size; std::vector<mwSize> d(dims_, dims_ + input.dims); d.push_back(nchannels); // mxCreate* ignores trailing singleton dimensions std::swap(d[0], d[1]); if (classid == mxLOGICAL_CLASS) { // OpenCV's logical true is any nonzero, while MATLAB's true is 1. cv::compare(input, 0, input, cv::CMP_NE); input.setTo(1, input); p_ = mxCreateLogicalArray(d.size(), &d[0]); } else p_ = mxCreateNumericArray(d.size(), &d[0], classid, mxREAL); if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); // split input cv::Mat into several single-channel arrays std::vector<cv::Mat> channels; channels.reserve(nchannels); cv::split(input, channels); // Copy each channel from Mat to mxArray (converting to specified classid), // as in: p_(:,:,i) <- cast_to_classid_type(channels[i]) std::vector<mwSize> si(d.size(), 0); // subscript index const int type = CV_MAKETYPE(DepthOf[classid], 1); // destination type for (mwIndex i = 0; i < nchannels; ++i) { si[si.size() - 1] = i; // last dim is a channel index void *ptr = reinterpret_cast<void*>( reinterpret_cast<size_t>(mxGetData(p_)) + mxGetElementSize(p_) * subs(si)); // ptr to i-th channel data cv::Mat m(input.dims, dims_, type, ptr); // only creates Mat header channels[i].convertTo(m, type); // Write to mxArray through m } } #else // works for any cv::Mat/cv::MatND (any combination of channels and dimensions) MxArray::MxArray(const cv::Mat& mat, mxClassID classid, bool) { // determine classID of output array classid = (classid == mxUNKNOWN_CLASS) ? ClassIDOf[mat.depth()] : classid; // handle special case of empty input Mat by returning 0x0 array if (mat.empty()) { // TODO: maybe return empty array of same dimensions 0x1, 1x0x2, ... p_ = mxCreateNumericMatrix(0, 0, classid, mxREAL); if (!p_) mexErrMsgIdAndTxt("mexopencv:error", "Allocation error"); return; } // Create output mxArray (of specified type), equivalent to the input Mat const mwSize cn = mat.channels(); const mwSize len = mat.