DPM（voc-release5）|DPM（voc-release5） Matlab模型文件 Mat转XML DPM（voc-release5）Matlab模型文件

（转载请注明作者和出处楼燚(yì)航的blog ：http://www.cnblogs.com/louyihang loves baiyan/ 未经允许请勿用于商业用途）
由于目前DPM模型训练的代码没有C++版本，至少我没看见opencv ccv conrib等一些库中都没有看到相关训练的部分倒都是有detector的部分），大部分人都是基于Matlab来做训练的，放到wnidows下用一些别的DPM的库或者自己C++实现，那么这些模型的文件类型大多都是XML的，网上现成的都比较混乱，看到opencv contrib库中的作者在他的另一个Git库中放了这个转换文件，没有公开说明。这个转换的文件可以达到目的，亲测可用。

function mat2opencvxml(fname_in, fname_out) % Convert DPM (2007) model to cascade model and % save in OpenCV file storage format (.xml) %mat2opencvxml(fname_in, fname_out) % %e.g., mat2opencvxml('./INRIA/inriaperson_final.mat', 'inriaperson_cascade_cv.xml' % %Arguments %fname_inFile name of the DPM VOC 2007 model %fname_outFile name of the OpenCV file storage model (.xml)% load VOC2007 DPM model load(fname_in); thresh = model.thresh; pca = 5; csc_model = cascade_model(model, '2007', pca, thresh); num_feat = 32; rootfilters = []; for i = 1:length(csc_model.rootfilters) rootfilters{i} = csc_model.rootfilters{i}.w; end partfilters = []; for i = 1:length(csc_model.partfilters) partfilters{i} = csc_model.partfilters{i}.w; end for c = 1:csc_model.numcomponents ridx{c} = csc_model.components{c}.rootindex; oidx{c} = csc_model.components{c}.offsetindex; root{c} = csc_model.rootfilters{ridx{c}}.w; root_pca{c} = csc_model.rootfilters{ridx{c}}.wpca; offset{c} = csc_model.offsets{oidx{c}}.w; loc{c} = csc_model.loc{c}.w; rsize{c} = [size(root{c},1) size(root{c},2)]; numparts{c} = length(csc_model.components{c}.parts); for j = 1:numparts{c} pidx{c,j} = csc_model.components{c}.parts{j}.partindex; didx{c,j} = csc_model.components{c}.parts{j}.defindex; part{c,j} = csc_model.partfilters{pidx{c,j}}.w; part_pca{c,j} = csc_model.partfilters{pidx{c,j}}.wpca; psize{c,j} = [size(part{c,j},1) size(part{c,j},2)]; end endmaxsizex = ceil(csc_model.maxsize(2)); maxsizey = ceil(csc_model.maxsize(1)); pca_rows = size(csc_model.pca_coeff, 1); pca_cols = size(csc_model.pca_coeff, 2); f = fopen(fname_out, 'wb'); fprintf(f, '\n'); fprintf(f, '\n'); fprintf(f, '%d\n', csc_model.sbin); fprintf(f, '%d\n', csc_model.numcomponents); fprintf(f, '%d\n', num_feat); fprintf(f, '%d\n', csc_model.interval); fprintf(f, '%d\n', maxsizex); fprintf(f, '%d\n', maxsizey); %the pca coeff fprintf(f, '\n'); fprintf(f,'\t%d\n', pca_rows); fprintf(f,'\t%d\n', pca_cols); fprintf(f,'\td\n'); fprintf(f,'\t\n'); for i=1:pca_rows fprintf(f,'\t'); for j=1:pca_cols fprintf(f,'%f ', csc_model.pca_coeff(i, j)); end fprintf(f,'\n'); end fprintf(f,'\t\n'); fprintf(f, '\n'); fprintf(f, '%d\n', pca_cols); fprintf(f, '%.16f\n', csc_model.thresh); fprintf(f, '\n'); for c = 1:csc_model.numcomponents fprintf(f,'%f ', offset{c}); end fprintf(f, '\n\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents rootfilter = root{c}; rows = size(rootfilter,1); cols = size(rootfilter,2); depth = size(rootfilter,3); fprintf(f, '\t<_ type_id="opencv-matrix">\n'); fprintf(f,'\t%d\n', rows); fprintf(f,'\t%d\n', cols*depth); fprintf(f,'\td\n'); fprintf(f,'\t\n'); for i=1:rows fprintf(f,'\t'); for j=1:cols for k=1:depth fprintf(f,'%f ', rootfilter(i, j, k)); end end fprintf(f,'\n'); end fprintf(f,'\t\n'); fprintf(f, '\t\n'); end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents rootfilter_pca = root_pca{c}; rows = size(rootfilter_pca,1); cols = size(rootfilter_pca,2); depth = size(rootfilter_pca,3); fprintf(f, '\t<_ type_id="opencv-matrix">\n'); fprintf(f,'\t%d\n', rows); fprintf(f,'\t%d\n', cols*depth); fprintf(f,'\td\n'); fprintf(f,'\t\n'); for i=1:rows fprintf(f,'\t'); for j=1:cols for k=1:depth fprintf(f,'%f ', rootfilter_pca(i, j, k)); end end fprintf(f,'\n'); end fprintf(f,'\t\n'); fprintf(f, '\t\n'); end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents for p=1:numparts{c} partfilter = part{c,p}; rows = size(partfilter,1); cols = size(partfilter,2); depth = size(partfilter,3); fprintf(f, '\t<_ type_id="opencv-matrix">\n'); fprintf(f,'\t%d\n', rows); fprintf(f,'\t%d\n', cols*depth); fprintf(f,'\td\n'); fprintf(f,'\t\n'); for i=1:rows fprintf(f,'\t'); for j=1:cols for k=1:depth fprintf(f,'%f ', partfilter(i, j, k)); end end fprintf(f,'\n'); end fprintf(f,'\t\n'); fprintf(f, '\t\n'); end end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents for p=1:numparts{c} partfilter = part_pca{c,p}; rows = size(partfilter,1); cols = size(partfilter,2); depth = size(partfilter,3); fprintf(f, '\t<_ type_id="opencv-matrix">\n'); fprintf(f,'\t%d\n', rows); fprintf(f,'\t%d\n', cols*depth); fprintf(f,'\td\n'); fprintf(f,'\t\n'); for i=1:rows fprintf(f,'\t'); for j=1:cols for k=1:depth fprintf(f,'%f ', partfilter(i, j, k)); end end fprintf(f,'\n'); end fprintf(f,'\t\n'); fprintf(f, '\t\n'); end end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents fprintf(f, '\t<_>\n'); fprintf(f,'\t'); t = csc_model.cascade.t{ridx{c}}; for j=1:length(t) fprintf(f,'%f ', t(j)); end fprintf(f, '\n\t\n'); end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents for p=1:numparts{c} fprintf(f, '\t<_>\n'); fprintf(f,'\t'); anchor = csc_model.defs{didx{c,p}}.anchor; for j=1:length(anchor) fprintf(f,'%f ', anchor(j)); end fprintf(f, '\n\t\n'); end end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents for p=1:numparts{c} fprintf(f, '\t<_>\n'); fprintf(f,'\t'); def = csc_model.defs{didx{c,p}}.w; for j=1:length(def) fprintf(f,'%f ', def(j)); end fprintf(f, '\n\t\n'); end end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents fprintf(f,'%f ', numparts{c}); end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents fprintf(f, '\t<_>\n'); fprintf(f,'\t'); order = csc_model.cascade.order{c}; for i=1:length(order) fprintf(f,'%f ', order(i)); end fprintf(f, '\n\t\n'); end fprintf(f, '\n'); fprintf(f, '\n'); for c = 1:csc_model.numcomponents fprintf(f, '\t<_>\n'); fprintf(f,'\t'); loc_w = loc{c}; for i=1:length(loc_w) fprintf(f,'%f ', loc_w(i)); end fprintf(f, '\n\t\n'); end fprintf(f, '\n'); fprintf(f, ''); fclose(f);