VlKDForest * kdtreebuild(int verbose, vl_size dimension, vl_size numTrees, int thresholdingMethod, vl_size numData, float *data) { vl_type dataType = VL_TYPE_FLOAT; VlKDForest * forest; forest = vl_kdforest_new (dataType, dimension, numTrees) ; vl_kdforest_set_thresholding_method (forest, thresholdingMethod) ; if (verbose) { char const * str = 0 ; printf("vl_kdforestbuild: data %s [%d x %d]\n", vl_get_type_name (dataType), dimension, numData) ; switch (vl_kdforest_get_thresholding_method(forest)) { case VL_KDTREE_MEAN : str = "mean" ; break ; case VL_KDTREE_MEDIAN : str = "median" ; break ; default: abort() ; } printf("vl_kdforestbuild: threshold selection method: %s\n", str) ; printf("vl_kdforestbuild: number of trees: %d\n", vl_kdforest_get_num_trees(forest)) ; } /* ----------------------------------------------------------------- * Do job * -------------------------------------------------------------- */ vl_kdforest_build (forest, numData, data) ; if (verbose) { vl_uindex ti ; for (ti = 0 ; ti < vl_kdforest_get_num_trees(forest) ; ++ ti) { printf("vl_kdforestbuild: tree %d: depth %d, num nodes %d\n", ti, vl_kdforest_get_depth_of_tree(forest, ti), vl_kdforest_get_num_nodes_of_tree(forest, ti)) ; } } return(forest); }
void LLC::SetUp() { if (base_.get() == NULL || dim_ == 0 || num_base_ == 0) { cerr << "ERROR: must set the base before." << endl; exit(-1); } if (kdforest_model_ != NULL) vl_kdforest_delete(kdforest_model_); kdforest_model_ = vl_kdforest_new(VL_TYPE_FLOAT, dim_, num_tree_, dist_method_); vl_kdforest_set_thresholding_method(kdforest_model_, thrd_method_); vl_kdforest_set_max_num_comparisons(kdforest_model_, max_comp_); vl_kdforest_build(kdforest_model_, num_base_, base_.get()); has_setup_ = true; }
void mexFunction(int nout, mxArray *out[], int nin, const mxArray *in[]) { enum {IN_DATA = 0, IN_END} ; enum {OUT_TREE = 0} ; int verbose = 0 ; int opt ; int next = IN_END ; mxArray const *optarg ; VlKDForest * forest ; void * data ; vl_size numData ; vl_size dimension ; mxClassID dataClass ; vl_type dataType ; int thresholdingMethod = VL_KDTREE_MEDIAN ; vl_size numTrees = 1 ; VL_USE_MATLAB_ENV ; /* ----------------------------------------------------------------- * Check the arguments * -------------------------------------------------------------- */ if (nin < 1) { vlmxError(vlmxErrInvalidArgument, "At least one argument required") ; } else if (nout > 2) { vlmxError(vlmxErrInvalidArgument, "Too many output arguments"); } dataClass = mxGetClassID(IN(DATA)) ; if (! vlmxIsMatrix (IN(DATA), -1, -1) || ! vlmxIsReal (IN(DATA))) { vlmxError(vlmxErrInvalidArgument, "DATA must be a real matrix ") ; } switch (dataClass) { case mxSINGLE_CLASS : dataType = VL_TYPE_FLOAT ; break ; case mxDOUBLE_CLASS : dataType = VL_TYPE_DOUBLE ; break ; default: vlmxError(vlmxErrInvalidArgument, "DATA must be either SINGLE or DOUBLE") ; } while ((opt = vlmxNextOption (in, nin, options, &next, &optarg)) >= 0) { char buffer [1024] ; switch (opt) { case opt_threshold_method : mxGetString (optarg, buffer, sizeof(buffer)/sizeof(buffer[0])) ; if (! vlmxIsString(optarg, -1)) { vlmxError(vlmxErrInvalidOption, "THRESHOLDMETHOD must be a string") ; } if (vl_string_casei_cmp(buffer, "median") == 0) { thresholdingMethod = VL_KDTREE_MEDIAN ; } else if (vl_string_casei_cmp(buffer, "mean") == 0) { thresholdingMethod = VL_KDTREE_MEAN ; } else { vlmxError(vlmxErrInvalidOption, "Unknown thresholding method %s", buffer) ; } break ; case opt_num_trees : if (! vlmxIsScalar(optarg) || (numTrees = mxGetScalar(optarg)) < 1) { vlmxError(vlmxErrInvalidOption, "NUMTREES must be not smaller than one") ; } break ; case opt_verbose : ++ verbose ; break ; } } data = mxGetData (IN(DATA)) ; numData = mxGetN (IN(DATA)) ; dimension = mxGetM (IN(DATA)) ; forest = vl_kdforest_new (dataType, dimension, numTrees) ; vl_kdforest_set_thresholding_method (forest, thresholdingMethod) ; if (verbose) { char const * str = 0 ; mexPrintf("vl_kdforestbuild: data %s [%d x %d]\n", vl_get_type_name (dataType), dimension, numData) ; switch (vl_kdforest_get_thresholding_method(forest)) { case VL_KDTREE_MEAN : str = "mean" ; break ; case VL_KDTREE_MEDIAN : str = "median" ; break ; default: abort() ; } mexPrintf("vl_kdforestbuild: threshold selection method: %s\n", str) ; mexPrintf("vl_kdforestbuild: number of trees: %d\n", vl_kdforest_get_num_trees(forest)) ; } /* ----------------------------------------------------------------- * Do job * -------------------------------------------------------------- */ vl_kdforest_build (forest, numData, data) ; if (verbose) { vl_uindex ti ; for (ti = 0 ; ti < vl_kdforest_get_num_trees(forest) ; ++ ti) { mexPrintf("vl_kdforestbuild: tree %d: depth %d, num nodes %d\n", ti, vl_kdforest_get_depth_of_tree(forest, ti), vl_kdforest_get_num_nodes_of_tree(forest, ti)) ; } } out[OUT_TREE] = new_array_from_kdforest (forest) ; vl_kdforest_delete (forest) ; }