怎么把matlab 训练的model 保存下来 然后在opencv 中调用

主要参考：

http://www.tuicool.com/articles/QvAr22

成功的标志:

1. 在我的电脑：

     D:\搜狗高速下载\libsvm-dense-3.20\libsvm-dense-3.20\matlab

     出现：svm_savemodel.mexw64

遇到的错误：前面几次执行make 一直不出现svm_savemodel.mexw64的原因是我开了两个matlab 

其中一个matlab 在使用svmtrain的程序 所以在 D:\搜狗高速下载\libsvm-dense-3.20\libsvm-dense-3.20\matlab

下面发现只更新了libsvmread.mexw64 和libsvmwrite.mexw64。

所以在make的时候：把：

mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims svm_savemodel.c ../svm.cpp svm_model_matlab.c

加在

                mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims libsvmread.c
mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims libsvmwrite.c
                mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims svm_savemodel.c ../svm.cpp svm_model_matlab.c
mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims svmtrain.c ../svm.cpp svm_model_matlab.c
mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims svmpredict.c ../svm.cpp svm_model_matlab.c

这个只是偶然的错误，不具有普遍性。

2. 使用方法：

    model = svmtrain( double(Train_label), double(Feature_train_norm), '-c 0.1649 -g 9.7656e-04');
    svm_savemodel(model,'model.model');

    在当前的目录下生成：

  

svm_type c_svckernel_type rbfgamma 0.00097656nr_class 2total_sv 4292rho 0.939511label 0 1nr_sv 2146 2146SV0.1649 1:0.046779478 2:0.0040677807 3:0.0040677807 4:0.012203342 5:0.0040677807 7:0.0081355614 8:0.034576136 9:0.065084491 10:0.028474465 12:0.1057623 13:0.0040677807 14:0.0020338904 15:0.0040677807 16:0.20338904 17:0.095592847 18:0.0020338904 19:0.0040677807 20:0.0020338904 21:0.040677807 23:0.13423676 24:0.66711604 25:0.020338904 26:0.0061016711 27:0.0020338904 28:0.0020338904 29:0.0061016711 30:0.0061016711 31:0.0040677807 32:0.12813509 33:0.0061016711 39:0.0020338904 40:0.0020338904 41:0.018305013 42:0.061016711 43:0.0040677807 44:0.17084679 48:0.091525066 55:0.0040677807 56:0.034576136 58:0.0020338904 60:0.0040677807 64:0.018305013 65:0.0040677807 66:0.0020338904 72:0.0020338904 76:0.0081355614 87:0.0020338904 88:0.0020338904 96:0.0020338904 97:0.022372794 100:0.0020338904 101:0.0020338904 104:0.0020338904 105:0.11593175 106:0.20745682 107:0.0040677807 108:0.14237233 109:0.0020338904 112:0.061016711 119:0.0040677807 120:0.030508355 121:0.0020338904 122:0.0020338904 124:0.0020338904 125:0.0020338904 127:0.0020338904 128:0.012203342 137:0.0020338904 140:0.0061016711 145:0.014237233 147:0.0020338904 148:0.0020338904 149:0.032542246 151:0.19321958 152:0.18305013 153:0.0061016711 157:0.0040677807 159:0.0020338904 160:0.022372794 169:0.0040677807 185:0.0020338904 189:0.0020338904 192:0.0061016711 193:0.028474465 194:0.0040677807 200:0.0061016711 201:0.0040677807 202:0.0061016711 208:0.010169452 209:0.05491504 210:0.0020338904 211:0.0020338904 213:0.034576136 215:0.022372794 216:0.046779478 217:0.0020338904 218:0.0040677807 223:0.0020338904 224:0.018305013 225:0.077287834 229:0.0061016711 231:0.0061016711 232:0.016271123 233:0.34982914 234:0.15254178 236:0.014237233 237:0.020338904 239:0.018305013 240:0.10169452 241:0.13423676 242:0.0061016711 244:0.0020338904 245:0.061016711 246:0.0020338904 247:0.016271123 248:0.095592847 249:0.148474 250:0.05694893 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256:0.12878239 0.1649 1:0.099513219 2:0.027139969 3:0.0090466563 5:0.0090