9
12
2013
1

LibSVM如何从matlab模型转化为C的模型

如何从model.mat转换为model.model?

一个看似小的东西，折腾了一个晚上才弄好

心路历程：

最开始认为libsvm没有提供直接从model.mat转化为mdoel.model的函数，网上几乎搜不到相关信息，打算自己动手写一个转换函数，参考matlab的example里面的explore.c，写的时候发现其他参数读取都没有问题，唯独model.totalSV怎么都读不正确，抓狂的是VS2012在此处还没法调试，一边想着解决方案，一边继续搜索能否直接将model.mat转化为model.model，终于在StackOverFlow上搜到了lib-svm-how-to-convert-mymodel-mat-to-mymodel-model，在http://ick.mech.kumamoto-u.ac.jp/kumon/ja/node/26 Japanese给出了一个代码，answer里面加以了改进。

将程序拷进来直接放到libsvm下用mex编译，mex svm_savemodel.c出现错误“Error using mex (line 206) Unable to complete successfully.”仔细检查了代码，发现没有什么问题，后来看到这个函数里面调用了定义在svm_save_model.c中的matlab_matrix_to_model()函数，联想到svmpredict和svmtrain的编译，再看make.m文件，找到了问题来源，将编译语句改为：：mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims svm_savemodel.c ../svm.cpp svm_model_matlab.c 即可成功通过编译。

用heart_scale进行测试，没有问题，输出标准的model

然而，当用我所需要的model测试时，却出现错误：

“number of return field is not correct”

原因在于需要的model相比于标准的model结构体少了一个域，少了这个域并不会影响用模型进行测试，但是在这个函数里面却需要检查域的数量是否为11（svm_node结构体里面最后一项free_sv不考虑），再进一步看，该函数的核心函数是libsvm自带的函数svm_model_matlab.c，该函数实现了标准的model.model和model.mat之间的相互转换，注意，是“标准”的，要求model.mat结构体里面域必须是11个，贴代码如下：

#include <stdlib.h>
#include <string.h>
#include "../svm.h"

#include "mex.h"

#ifdef MX_API_VER
#if MX_API_VER < 0x07030000
typedef int mwIndex;
#endif
#endif

#define NUM_OF_RETURN_FIELD 11

#define Malloc(type,n) (type *)malloc((n)*sizeof(type))

static const char *field_names[] = {
	"Parameters",
	"nr_class",
	"totalSV",
	"rho",
	"Label",
	"sv_indices",
	"ProbA",
	"ProbB",
	"nSV",
	"sv_coef",
	"SVs"
};
struct svm_model *matlab_matrix_to_model(const mxArray *matlab_struct, const char **msg)
{
	int i, j, n, num_of_fields;
	double *ptr;
	int id = 0;
	struct svm_node *x_space;
	struct svm_model *model;
	mxArray **rhs;

	num_of_fields = mxGetNumberOfFields(matlab_struct);
	if(num_of_fields != NUM_OF_RETURN_FIELD) 
	{
		*msg = "number of return field is not correct";
		return NULL;
	}
	rhs = (mxArray **) mxMalloc(sizeof(mxArray *)*num_of_fields);

	for(i=0;i<num_of_fields;i++)
		rhs[i] = mxGetFieldByNumber(matlab_struct, 0, i);

	model = Malloc(struct svm_model, 1);
	model->rho = NULL;
	model->probA = NULL;
	model->probB = NULL;
	model->label = NULL;
	model->sv_indices = NULL;
	model->nSV = NULL;
	model->free_sv = 1; // XXX

	ptr = mxGetPr(rhs[id]);
	model->param.svm_type = (int)ptr[0];
	model->param.kernel_type  = (int)ptr[1];
	model->param.degree	  = (int)ptr[2];
	model->param.gamma	  = ptr[3];
	model->param.coef0	  = ptr[4];
	id++;

	ptr = mxGetPr(rhs[id]);
	model->nr_class = (int)ptr[0];
	id++;

	ptr = mxGetPr(rhs[id]);
	model->l = (int)ptr[0];
	id++;

	// rho
	n = model->nr_class * (model->nr_class-1)/2;
	model->rho = (double*) malloc(n*sizeof(double));
	ptr = mxGetPr(rhs[id]);
	for(i=0;i<n;i++)
		model->rho[i] = ptr[i];
	id++;

	// label
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->label = (int*) malloc(model->nr_class*sizeof(int));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<model->nr_class;i++)
			model->label[i] = (int)ptr[i];
	}
	id++;

	// sv_indices
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->sv_indices = (int*) malloc(model->l*sizeof(int));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<model->l;i++)
			model->sv_indices[i] = (int)ptr[i];
	}
	id++;

	// probA
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->probA = (double*) malloc(n*sizeof(double));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<n;i++)
			model->probA[i] = ptr[i];
	}
	id++;

	// probB
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->probB = (double*) malloc(n*sizeof(double));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<n;i++)
			model->probB[i] = ptr[i];
	}
	id++;

	// nSV
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->nSV = (int*) malloc(model->nr_class*sizeof(int));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<model->nr_class;i++)
			model->nSV[i] = (int)ptr[i];
	}
	id++;

	// sv_coef
	ptr = mxGetPr(rhs[id]);
	model->sv_coef = (double**) malloc((model->nr_class-1)*sizeof(double));
	for( i=0 ; i< model->nr_class -1 ; i++ )
		model->sv_coef[i] = (double*) malloc((model->l)*sizeof(double));
	for(i = 0; i < model->nr_class - 1; i++)
		for(j = 0; j < model->l; j++)
			model->sv_coef[i][j] = ptr[i*(model->l)+j];
	id++;

	// SV
	{
		int sr, sc, elements;
		int num_samples;
		mwIndex *ir, *jc;
		mxArray *pprhs[1], *pplhs[1];

		// transpose SV
		pprhs[0] = rhs[id];
		if(mexCallMATLAB(1, pplhs, 1, pprhs, "transpose")) 
		{
			svm_free_and_destroy_model(&model);
			*msg = "cannot transpose SV matrix";
			return NULL;
		}
		rhs[id] = pplhs[0];

		sr = (int)mxGetN(rhs[id]);
		sc = (int)mxGetM(rhs[id]);

		ptr = mxGetPr(rhs[id]);
		ir = mxGetIr(rhs[id]);
		jc = mxGetJc(rhs[id]);

		num_samples = (int)mxGetNzmax(rhs[id]);

		elements = num_samples + sr;

		model->SV = (struct svm_node **) malloc(sr * sizeof(struct svm_node *));
		x_space = (struct svm_node *)malloc(elements * sizeof(struct svm_node));

		// SV is in column
		for(i=0;i<sr;i++)
		{
			int low = (int)jc[i], high = (int)jc[i+1];
			int x_index = 0;
			model->SV[i] = &x_space[low+i];
			for(j=low;j<high;j++)
			{
				model->SV[i][x_index].index = (int)ir[j] + 1; 
				model->SV[i][x_index].value = ptr[j];
				x_index++;
			}
			model->SV[i][x_index].index = -1;
		}

		id++;
	}
	mxFree(rhs);

	return model;
}

这样对于域并不完全的model，就完全没有办法。

于是我将此代码稍作修改，以适应我的需要，我的情况是没有sv_indice域，因此修改如下：

struct svm_model *matlab_matrix_to_model(const mxArray *matlab_struct, const char **msg)
{
	int i, j, n, num_of_fields;
	double *ptr;
	int id = 0;
	struct svm_node *x_space;
	struct svm_model *model;
	mxArray **rhs;

	num_of_fields = mxGetNumberOfFields(matlab_struct);
	printf("%d\n",num_of_fields);
	//允许10个的也可以
	if(num_of_fields != NUM_OF_RETURN_FIELD&&num_of_fields!=NUM_OF_RETURN_FIELD-1) 
	{
		*msg = "number of return field is not correct";
		
		return NULL;
	}
	rhs = (mxArray **) mxMalloc(sizeof(mxArray *)*num_of_fields);

	for(i=0;i<num_of_fields;i++)
		rhs[i] = mxGetFieldByNumber(matlab_struct, 0, i);

	model = Malloc(struct svm_model, 1);
	model->rho = NULL;
	model->probA = NULL;
	model->probB = NULL;
	model->label = NULL;
	model->sv_indices = NULL;
	model->nSV = NULL;
	model->free_sv = 1; // XXX

	ptr = mxGetPr(rhs[id]);
	model->param.svm_type = (int)ptr[0];
	model->param.kernel_type  = (int)ptr[1];
	model->param.degree	  = (int)ptr[2];
	model->param.gamma	  = ptr[3];
	model->param.coef0	  = ptr[4];
	id++;

	ptr = mxGetPr(rhs[id]);
	model->nr_class = (int)ptr[0];
	id++;

	ptr = mxGetPr(rhs[id]);
	model->l = (int)ptr[0];
	id++;

	// rho
	n = model->nr_class * (model->nr_class-1)/2;
	model->rho = (double*) malloc(n*sizeof(double));
	ptr = mxGetPr(rhs[id]);
	for(i=0;i<n;i++)
		model->rho[i] = ptr[i];
	id++;

	// label
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->label = (int*) malloc(model->nr_class*sizeof(int));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<model->nr_class;i++)
			model->label[i] = (int)ptr[i];
	}
	id++;

	if(num_of_fields==NUM_OF_RETURN_FIELD)
	{
		// sv_indices
		if(mxIsEmpty(rhs[id]) == 0)
		{
			model->sv_indices = (int*) malloc(model->l*sizeof(int));
			ptr = mxGetPr(rhs[id]);
			for(i=0;i<model->l;i++)
				model->sv_indices[i] = (int)ptr[i];
		}
		id++;
	}
	// probA
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->probA = (double*) malloc(n*sizeof(double));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<n;i++)
			model->probA[i] = ptr[i];
	}
	id++;

	// probB
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->probB = (double*) malloc(n*sizeof(double));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<n;i++)
			model->probB[i] = ptr[i];
	}
	id++;

	// nSV
	if(mxIsEmpty(rhs[id]) == 0)
	{
		model->nSV = (int*) malloc(model->nr_class*sizeof(int));
		ptr = mxGetPr(rhs[id]);
		for(i=0;i<model->nr_class;i++)
			model->nSV[i] = (int)ptr[i];
	}
	id++;

	// sv_coef
	ptr = mxGetPr(rhs[id]);
	model->sv_coef = (double**) malloc((model->nr_class-1)*sizeof(double));
	for( i=0 ; i< model->nr_class -1 ; i++ )
		model->sv_coef[i] = (double*) malloc((model->l)*sizeof(double));
	for(i = 0; i < model->nr_class - 1; i++)
		for(j = 0; j < model->l; j++)
			model->sv_coef[i][j] = ptr[i*(model->l)+j];
	id++;

	// SV
	{
		int sr, sc, elements;
		int num_samples;
		mwIndex *ir, *jc;
		mxArray *pprhs[1], *pplhs[1];

		// transpose SV
		pprhs[0] = rhs[id];
		if(mexCallMATLAB(1, pplhs, 1, pprhs, "transpose")) 
		{
			svm_free_and_destroy_model(&model);
			*msg = "cannot transpose SV matrix";
			return NULL;
		}
		rhs[id] = pplhs[0];

		sr = (int)mxGetN(rhs[id]);
		sc = (int)mxGetM(rhs[id]);

		ptr = mxGetPr(rhs[id]);
		ir = mxGetIr(rhs[id]);
		jc = mxGetJc(rhs[id]);

		num_samples = (int)mxGetNzmax(rhs[id]);

		elements = num_samples + sr;

		model->SV = (struct svm_node **) malloc(sr * sizeof(struct svm_node *));
		x_space = (struct svm_node *)malloc(elements * sizeof(struct svm_node));

		// SV is in column
		for(i=0;i<sr;i++)
		{
			int low = (int)jc[i], high = (int)jc[i+1];
			int x_index = 0;
			model->SV[i] = &x_space[low+i];
			for(j=low;j<high;j++)
			{
				model->SV[i][x_index].index = (int)ir[j] + 1; 
				model->SV[i][x_index].value = ptr[j];
				x_index++;
			}
			model->SV[i][x_index].index = -1;
		}

		id++;
	}
	mxFree(rhs);

	return model;
}

svm_savemodel.c   

svm_model_matlab.c

 

如果你情况类似，缺乏哪个域可以用相应类似的方式，感兴趣的话可以将所有异常的情况都考虑了。急着去做下一步，暂时现弄一个项目适用的。

这样就可以有两种方案：

1.将修改后的代码用于我的程序之中，仍然读取mat文件，用修改后的函数进行转换。

2.对修改后的代码mex编译，在matlab上面转化.mat到.model

load('model.mat');

svm_savemodel(model,'model.model');

尝试第一种方案，结果在调用matlab转置函数mexCallMATLAB(1, pplhs, 1, pprhs, "transpose")的时候出错，原因没有细究，猜测是路劲配置的问题。

尝试第二种方案，成功！

其实相比第一种方案，第二种方案更加的方便和高效。

结果如图所示：

model.mat

model.model

结论：

1.不同的情况适用性不同，libsvm的库仍有不完善的地方

2.善用mex编程可以方便地实现C++和matlab混合编程

Category: C/C++ | Tags: libsvm | Read Count: 4226
Small_feed 评论 (1)
1
[回复]
seo service london 说:
Feb 21, 2024 02:07:32 AM

Thanks again for the article post.Thanks Again. Really Great


登录 *


loading captcha image...
(输入验证码)
or Ctrl+Enter

| Theme: Aeros 2.0 by TheBuckmaker.com