Opencv 3.0 SVM火车分类问题 [英] Opencv 3.0 SVM train classification issues

问题描述

这是openCV SVM的新功能.我在Xcode 7.0，openCV 3.0中运行，下面是我的代码

Im new in openCV SVM. Im running in Xcode 7.0, openCV 3.0, Below is my code

MatMat labels(0,1,CV_32FC1);
//Mat labels(0,1,CV_32S);  //I also try this when i saw some posting, But error too.
...
Mat samples_32f; samples.convertTo(samples_32f, CV_32F);
//Mat samples_32f; samples.convertTo(samples_32f, CV_32FC1); //tried!

Ptr<SVM> classifier = SVM::create();
classifier->SVM::train(samples_32f, 0, labels);  <- Here the Error

OpenCV错误:错误的参数(在分类问题中，响应必须是分类的；在创建TrainData时指定varType，或者传递整数响应).

The OpenCV Error: Bad argument (in the case of classification problem the responses must be categorical; either specify varType when creating TrainData, or pass integer responses) in train.

当我搜索一些解决方案时，错误消息似乎来自labels，它们定义的不是整数值.因此，我不得不尝试更改为Mat labels(0,1,CV_32S)，但是问题错误仍然相同.

When I search around some solutions, the error message seem was came from labels that define not integer value. So i had try to changed to Mat labels(0,1,CV_32S), but the issues error still the same.

所以我不知道代码出了什么问题.有人可以帮忙吗?

So i have no idea what going wrong with the code..is anyone can help?

推荐答案

错误是因为标签不包含定义为0行且具有1列的任何值.因此，确保labels具有用于SVM训练的保留行数记录是正确的.

The errors is because labels does not content any value as defined as 0 rows with 1 cols. Therefore, it is correct to make sure labels has holding numbers of rows records for SVM training.

我的解决方案:

Mat labels(0,1,CV_32S); 

/*
for loop to use pushback added value into lables
{...}
*/
/*
or
define another Mat labeled(labels.rows, 1, CV_32S); after the for loop 
and use it in the SVM.train
*/

Mat samples_32f; samples.convertTo(samples_32f, CV_32F);

Ptr<SVM> classifier = SVM::create();
classifier->SVM::train(samples_32f, 0, labels);  <-change the labels names if you define new labels after the for loop.

谢谢，这就是我可以分享的.

Thanks, that's what i can share.

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