Commit ef0d1dae2de0046682e847e56b6fa05e0fb6e565

Authored by Josh Klontz
1 parent 3537050f

dropped RowWisePCATransform

openbr/plugins/classification/lda.cpp
... ... @@ -224,50 +224,6 @@ BR_REGISTER(Transform, PCATransform)
224 224  
225 225 /*!
226 226 * \ingroup transforms
227   - * \brief PCA on each row.
228   - * \author Josh Klontz \cite jklontz
229   - */
230   -class RowWisePCATransform : public PCATransform
231   -{
232   - Q_OBJECT
233   -
234   - void train(const TemplateList &trainingSet)
235   - {
236   - if (trainingSet.first().m().type() != CV_32FC1)
237   - qFatal("Requires single channel 32-bit floating point matrices.");
238   -
239   - originalRows = trainingSet.first().m().rows;
240   - const int dimsIn = trainingSet.first().m().cols;
241   - int instances = 0;
242   - foreach (const Template &t, trainingSet)
243   - instances += t.m().rows;
244   -
245   - // Map into 64-bit Eigen matrix
246   - Eigen::MatrixXd data(dimsIn, instances);
247   - int index = 0;
248   - foreach (const Template &t, trainingSet)
249   - for (int i=0; i<t.m().rows; i++)
250   - data.col(index++) = Eigen::Map<const Eigen::MatrixXf>(t.m().ptr<float>(i), dimsIn, 1).cast<double>();
251   -
252   - PCATransform::trainCore(data);
253   - }
254   -
255   - void project(const Template &src, Template &dst) const
256   - {
257   - dst = cv::Mat(src.m().rows, keep, CV_32FC1);
258   -
259   - for (int i=0; i<src.m().rows; i++) {
260   - Eigen::Map<const Eigen::MatrixXf> inMap(src.m().ptr<float>(i), src.m().cols, 1);
261   - Eigen::Map<Eigen::MatrixXf> outMap(dst.m().ptr<float>(i), keep, 1);
262   - outMap = eVecs.transpose() * (inMap - mean);
263   - }
264   - }
265   -};
266   -
267   -BR_REGISTER(Transform, RowWisePCATransform)
268   -
269   -/*!
270   - * \ingroup transforms
271 227 * \brief Computes Distance From Feature Space (DFFS)
272 228 * \br_paper Moghaddam, Baback, and Alex Pentland.
273 229 * "Probabilistic visual learning for object representation."
... ...