如何加载以前存储的svm分类器？ [英] How to load previously stored svm classifier?

问题描述

我在Visual Studio中使用openCV SVM。 （OpenCV 2.4.4.0）

我训练它：

  mySVM .train（trainingDataMat，labelsMat，Mat（），Mat（），params）; 
  

已保存：

  mySVM.save（classifier.xml）; 
  

我正在加载它：

  CvSVM mySVM1; 
 mySVM1.load（C：\classifier.xml）; 
 mySVM1.predict（testingDataMat0，result0）; 
  

我想在其他项目中使用。但是当我尝试加载分类器时，这个错误会一直发生：

 错误的参数CvSVM :: predict
  

路径正确，且.xml似乎已正确储存。

有人知道我做错了什么或问题出在哪里？

classifier.xml：

 <？xml version =1.0？> 
< opencv_storage> 
< my_svm type_id =opencv-ml-svm> 
< svm_type> C_SVC< / svm_type> 
< kernel>< type> RBF< / type> 
< gamma> 5.0625000000000009e-001< / gamma>< / kernel> 
< C> 2.5000000000000000e + 000< / C> 
< term_criteria>< epsilon> 2.2204460492503131e-016< / epsilon> 
< iterations> 100< / iterations>< / term_criteria> 
< var_all> 3< / var_all> 
< var_count> 3< / var_count> 
< class_count> 2< / class_count> 
< class_labels type_id =opencv-matrix> 
< rows> 1< / rows> 
< cols> 2< / cols> 
< dt> i< / dt> 
< data> 
 -1 1< / data>< / class_labels> 
< sv_total> 10< / sv_total> 
< support_vectors> 
< _> 
 9.09866020e-002 5.56291997e-001 2.43510995e-002< / _> 
< _> 
 9.46519971e-001 2.94328004e-001 2.08841003e-002< / _> 
< _> 
 1. 3.68389994e-001 1.15272999e-002< / _> 
< _> 
 9.41470027e-001 3.73109013e-001 1.25126000e-002< / _> 
< _> 
 1. 2.23776996e-001 9.57737025e-003< / _> 
< _> 
 4.68845010e-001 3.62690985e-002 9.11400989e-002< / _> 
< _> 
 7.98106015e-001 2.73550004e-002 9.26491022e-002< / _> 
< _> 
 7.02144980e-001 3.98130007e-002 9.00894031e-002< / _> 
< _> 
 4.99359012e-001 4.31513004e-002 8.61563012e-002< / _> 
< _> 
 7.39947975e-001 4.39946018e-002 9.60593969e-002< / _>< / support_vectors> 
< decision_functions> 
< _> 
< sv_count> 10< / sv_count> 
< rho> -5.7845965027809154e-001< / rho> 
< alpha> 
 2.5000000000000000e + 000 2.5000000000000000e + 000 
 1.4641912158132706e + 000 2.5000000000000000e + 000 
 2.5000000000000000e + 000 -1.4641912158132708e + 000 
 -2.5000000000000000e + 000 -2.5000000000000000e + 000 
 -2.5000000000000000e + 000 -2.5000000000000000e + 000& 
< index> 
 0 1 2 3 4 5 6 7 8 9< / index>< / _>< / decision_functions>< / my_svm> 
< / opencv_storage>我有这个问题，并发现在SVM代码中，你可以看到一个问题，至少在OpenCV中，predict函数使用相同的内核witch在train函数中使用来确定输入类。所以当你单独运行预测时，它不知道它应该使用什么样的内核。所以，我认为运行火车功能前预测功能是可以避免的。 
 
I'm working with openCV SVM in Visual Studio. (OpenCV 2.4.4.0) 

I trained it:
mySVM.train(trainingDataMat, labelsMat, Mat(), Mat(), params);
Saved it:
mySVM.save("classifier.xml");
I'm loading it like this:
CvSVM mySVM1;
mySVM1.load("C:\classifier.xml");
mySVM1.predict(testingDataMat0,result0);
And i want to use in other project. But when i try to load classifier this error bumps all the time:
"Bad argument (The SVM should be trained first) in CvSVM::predict"
Path is correct, and .xml seems correctly stored.

Does anybody know what am I doing wrong or where the problem might be?

classifier.xml:
<?xml version="1.0"?>
<opencv_storage>
<my_svm type_id="opencv-ml-svm">
  <svm_type>C_SVC</svm_type>
  <kernel><type>RBF</type>
    <gamma>5.0625000000000009e-001</gamma></kernel>
  <C>2.5000000000000000e+000</C>
  <term_criteria><epsilon>2.2204460492503131e-016</epsilon>
    <iterations>100</iterations></term_criteria>
  <var_all>3</var_all>
  <var_count>3</var_count>
  <class_count>2</class_count>
  <class_labels type_id="opencv-matrix">
    <rows>1</rows>
    <cols>2</cols>
    <dt>i</dt>
    <data>
      -1 1</data></class_labels>
  <sv_total>10</sv_total>
  <support_vectors>
    <_>
      9.09866020e-002 5.56291997e-001 2.43510995e-002</_>
    <_>
      9.46519971e-001 2.94328004e-001 2.08841003e-002</_>
    <_>
      1. 3.68389994e-001 1.15272999e-002</_>
    <_>
      9.41470027e-001 3.73109013e-001 1.25126000e-002</_>
    <_>
      1. 2.23776996e-001 9.57737025e-003</_>
    <_>
      4.68845010e-001 3.62690985e-002 9.11400989e-002</_>
    <_>
      7.98106015e-001 2.73550004e-002 9.26491022e-002</_>
    <_>
      7.02144980e-001 3.98130007e-002 9.00894031e-002</_>
    <_>
      4.99359012e-001 4.31513004e-002 8.61563012e-002</_>
    <_>
      7.39947975e-001 4.39946018e-002 9.60593969e-002</_></support_vectors>
  <decision_functions>
    <_>
      <sv_count>10</sv_count>
      <rho>-5.7845965027809154e-001</rho>
      <alpha>
        2.5000000000000000e+000 2.5000000000000000e+000
        1.4641912158132706e+000 2.5000000000000000e+000
        2.5000000000000000e+000 -1.4641912158132708e+000
        -2.5000000000000000e+000 -2.5000000000000000e+000
        -2.5000000000000000e+000 -2.5000000000000000e+000</alpha>
      <index>
        0 1 2 3 4 5 6 7 8 9</index></_></decision_functions></my_svm>
</opencv_storage>

解决方案
I had this problem and found that in SVM codes ,at least in OpenCV, predict function uses the same kernel witch is used in train function to determine input class. So when you run predict separately it doesn't know what kind of kernel should it uses. So, I think running train function exactly before predict function is avoidable.   

                        
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