我有一个A类和一个B类，它来自A：
class A
{
public :
A() { // Some code }
virtual ~A(){}
// etc
};
这是我的班级B：
class B : public A
{
public :
B():A(){//Some extra code}
~B();
// etc
};
A和B的真实代码很长，所以我不会在那里发布，除非有必要。
我的问题是，在我的主程序中：
仅当我有B的实例时才会出现段错误。
所以，为了找到我的问题的位置，我尝试使用Valgrind，但我很困惑，因为我不明白Valgrind正在展示什么。
Valgrind的输出很长，但是有一个方案，结果如下：
==13512== Invalid read of size 4
==13512== at 0x852EE9D: __tcf_0 (in /usr/local/lib/libeikeotools.so)
==13512== by 0x6AE15E9: __cxa_finalize (cxa_finalize.c:56)
==13512== by 0x84C3E72: ??? (in /usr/local/lib/libeikeotools.so)
==13512== by 0x4010739: _dl_fini (dl-fini.c:252)
==13512== by 0x6AE1258: __run_exit_handlers (exit.c:82)
==13512== by 0x6AE12A4: exit (exit.c:104)
==13512== by 0x6AC6ECB: (below main) (libc-start.c:321)
==13512== Address 0x131e4d00 is 16 bytes inside a block of size 32 free'd
==13512== at 0x4C2C2BC: operator delete(void*) (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==13512== by 0x664536E: std::basic_string<char, std::char_traits<char>, std::allocator<char> >::~basic_string() (in /usr/lib/x86_64-linux-gnu/libstdc++.so.6.0.19)
==13512== by 0x73A3384: __tcf_0 (logwriter.cpp:32)
==13512== by 0x6AE15E9: __cxa_finalize (cxa_finalize.c:56)
==13512== by 0x7301A72: ??? (in /usr/local/lib/libeikeotoolsd.so)
==13512== by 0x4010739: _dl_fini (dl-fini.c:252)
==13512== by 0x6AE1258: __run_exit_handlers (exit.c:82)
==13512== by 0x6AE12A4: exit (exit.c:104)
==13512== by 0x6AC6ECB: (below main) (libc-start.c:321)
==13512==
==13512== Invalid free() / delete / delete[] / realloc()
==13512== at 0x4C2C2BC: operator delete(void*) (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==13512== by 0x852EEB3: __tcf_0 (in /usr/local/lib/libeikeotools.so)
==13512== by 0x6AE15E9: __cxa_finalize (cxa_finalize.c:56)
==13512== by 0x84C3E72: ??? (in /usr/local/lib/libeikeotools.so)
==13512== by 0x4010739: _dl_fini (dl-fini.c:252)
==13512== by 0x6AE1258: __run_exit_handlers (exit.c:82)
==13512== by 0x6AE12A4: exit (exit.c:104)
==13512== by 0x6AC6ECB: (below main) (libc-start.c:321)
==13512== Address 0x131e4cf0 is 0 bytes inside a block of size 32 free'd
==13512== at 0x4C2C2BC: operator delete(void*) (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==13512== by 0x664536E: std::basic_string<char, std::char_traits<char>, std::allocator<char> >::~basic_string() (in /usr/lib/x86_64-linux-gnu/libstdc++.so.6.0.19)
==13512== by 0x73A3384: __tcf_0 (logwriter.cpp:32)
==13512== by 0x6AE15E9: __cxa_finalize (cxa_finalize.c:56)
==13512== by 0x7301A72: ??? (in /usr/local/lib/libeikeotoolsd.so)
==13512== by 0x4010739: _dl_fini (dl-fini.c:252)
==13512== by 0x6AE1258: __run_exit_handlers (exit.c:82)
==13512== by 0x6AE12A4: exit (exit.c:104)
==13512== by 0x6AC6ECB: (below main) (libc-start.c:321)
编辑1：这是我的'B'课程：
HOGpython.hpp：
#ifndef HOGPYTHON_H
#define HOGPYTHON_H
#include "osell/cvaddenda/HOGDescriptor2.h"
#include <opencv2/core/core.hpp>
#include "conversion.hpp"
#define NO_IMPORT_ARRAY
class HOGpython : public eikeotools::CvAddenda::HOGDescriptor2
{
public:
// Constructeurs :
HOGpython();
HOGpython(PyObject* _winSize, PyObject* _blockSize, PyObject* _blockStride, PyObject* _cellSize, int _nbins, double _winSigma);
// Destructeur :
~HOGpython(){ std::cout << " Destroying .." << std::endl;}
// setters :
PyObject* get_winSize() const;
PyObject* get_blockSize() const;
PyObject* get_blockStride() const;
PyObject* get_cellSize() const;
int get_nbins() const;
int get_derivAperture() const;
double get_winSigma() const;
int get_histogramNormType() const;
double get_L2HysThreshold() const;
bool get_gammaCorrection() const;
int get_nlevels() const;
// Setters :
void set_winSize( PyObject* o);
void set_blockSize( PyObject* o);
void set_blockStride( PyObject* o);
void set_cellSize( PyObject* o);
void set_nbins( int o);
void set_derivAperture( int o);
void set_winSigma( double o);
void set_histogramNormType( int o);
void set_L2HysThreshold( double o);
void set_gammaCorrection( bool o);
void set_nlevels( int o);
// Méthodes d'instance :
PyObject* compute(PyObject* img, PyObject* locations);
PyObject* computeSubPix(PyObject* img, PyObject* locations);
PyObject* computeGradient(PyObject* img);
};
#endif
和HOGpython.cpp：
#include "HOGpython.hpp"
// == Constructeur sans paramètres == //
HOGpython :: HOGpython():eikeotools::CvAddenda::HOGDescriptor2()
{}
// == Constructeur avec paramètres == //
HOGpython :: HOGpython(PyObject* _winSize, PyObject* _blockSize, PyObject* _blockStride, PyObject* _cellSize, int _nbins, double _winSigma)
:eikeotools::CvAddenda::HOGDescriptor2( tupleToSize(_winSize),
tupleToSize(_blockSize),
tupleToSize(_blockStride),
tupleToSize(_cellSize),
_nbins,
1,
_winSigma,
eikeotools::CvAddenda::HOGDescriptor2::L2Hys,
0.2,
false,
eikeotools::CvAddenda::HOGDescriptor2::DEFAULT_NLEVELS)
{}
// == Getters == //
PyObject* HOGpython::get_winSize() const {return SizeToTuple(winSize); }
PyObject* HOGpython::get_blockSize() const {return SizeToTuple(blockSize); }
PyObject* HOGpython::get_blockStride() const {return SizeToTuple(blockStride); }
PyObject* HOGpython::get_cellSize() const {return SizeToTuple(cellSize); }
int HOGpython::get_nbins() const {return nbins; }
int HOGpython::get_derivAperture() const {return derivAperture; }
double HOGpython::get_winSigma() const {return winSigma; }
int HOGpython::get_histogramNormType() const {return histogramNormType; }
double HOGpython::get_L2HysThreshold() const {return L2HysThreshold; }
bool HOGpython::get_gammaCorrection() const {return gammaCorrection; }
int HOGpython::get_nlevels() const {return nlevels; }
// == Setters == //
void HOGpython::set_winSize(PyObject* o) {winSize = tupleToSize(o);}
void HOGpython::set_blockSize(PyObject* o) {blockSize = tupleToSize(o);}
void HOGpython::set_blockStride(PyObject* o) {blockStride = tupleToSize(o);}
void HOGpython::set_cellSize(PyObject* o) {cellSize = tupleToSize(o);}
void HOGpython::set_nbins(int o) {nbins = o; return;}
void HOGpython::set_derivAperture(int o) {derivAperture = o; return;}
void HOGpython::set_winSigma(double o) {winSigma = o; return;}
void HOGpython::set_histogramNormType(int o) {histogramNormType = o; return;}
void HOGpython::set_L2HysThreshold(double o) {L2HysThreshold = o; return;}
void HOGpython::set_gammaCorrection(bool o) {gammaCorrection = o; return;}
void HOGpython::set_nlevels(int o) {nlevels = o; return;}
PyObject* HOGpython::compute(PyObject* img, PyObject* locations)
{
// Déclaration d'instances :
cv::Mat im, pt;
PyObject* ret;
// Conversion :
NDArrayConverter cvt;
im = cvt.toMat(img);
pt = cvt.toMat(locations);
// Déclaration de vecteurs :
std::vector<float> desc;
std::vector<cv::Point> pts;
//Py_BEGIN_ALLOW_THREADS;
PyThreadState * m_thread_state;
m_thread_state = PyEval_SaveThread();
for(int i = 0; i < pt.rows; i++)
{
pts.push_back(cv::Point(pt.at<double>(i,0), pt.at<double>(i,1)));
}
eikeotools::CvAddenda::HOGDescriptor2::compute(im,desc,cv::Size(),cv::Size(),pts, false);
PyEval_RestoreThread(m_thread_state);
m_thread_state = NULL;
//Py_END_ALLOW_THREADS;
cv::Mat pointsMat = cv::Mat(desc);
ret = cvt.toNDArray(pointsMat);
return ret;
}
PyObject* HOGpython::computeSubPix(PyObject* img, PyObject* locations)
{
// Déclaration d'instances :
cv::Mat im, pt;
PyObject* ret;
// Conversion :
NDArrayConverter cvt;
im = cvt.toMat(img);
pt = cvt.toMat(locations);
// Déclaration de vecteurs :
std::vector<float> desc;
std::vector<cv::Point2f> pts;
//Py_BEGIN_ALLOW_THREADS;
PyThreadState * m_thread_state;
m_thread_state = PyEval_SaveThread();
for(int i = 0; i < pt.rows; i++)
{
pts.push_back(cv::Point(pt.at<double>(i,0), pt.at<double>(i,1)));
}
eikeotools::CvAddenda::HOGDescriptor2::computeSubPix(im,desc,cv::Size(),cv::Size(),pts, false);
PyEval_RestoreThread(m_thread_state);
m_thread_state = NULL;
//Py_END_ALLOW_THREADS;
cv::Mat pointsMat = cv::Mat(desc);
ret = cvt.toNDArray(pointsMat);
return ret;
}
PyObject* HOGpython::computeGradient(PyObject* img)
{
// Déclaration d'instances :
cv::Mat im, grad, angleOfs;
PyObject* listeRes;
PyObject* grad_;
PyObject* angleOfs_;
// Conversion :
NDArrayConverter cvt;
im = cvt.toMat(img);
//Py_BEGIN_ALLOW_THREADS;
PyThreadState * m_thread_state;
m_thread_state = PyEval_SaveThread();
eikeotools::CvAddenda::HOGDescriptor2::computeGradient(im, grad, angleOfs, cv::Size(), cv::Size());
PyEval_RestoreThread(m_thread_state);
m_thread_state = NULL;
//Py_END_ALLOW_THREADS;
// Conversion :
grad_ = cvt.toNDArray(grad);
angleOfs_ = cvt.toNDArray(angleOfs);
// Création d'une liste Python dans laquelle les deux résultats seront enregistrés :
listeRes = PyList_New(0);
PyList_Append(listeRes, grad_);
PyList_Append(listeRes, angleOfs_);
// Renvoie des données :
return listeRes;
}
不幸的是，我无法展示我的A类（框架的一部分），但我可以说A不会导致任何分段错误。
只是为了总结一下我的代码，我想为我的A类创建一个for python的包装器，并且由于A包含一些OpenCV对象，Boost.Python无法自动转换它们，所以我创建了B派生自A，但是有一些从opencv对象到Python对象的转换。
要进行转换，我有一个工作正常的转换模块。 我想补充一点：这是我的主要代码，它给了我一个段错误：
int main()
{
HOGpython h;
return 0;
}
答案 0 :(得分：1)
这看起来像一个全局对象的析构函数（可能是std::string或与std::string有某种关系的东西）被调用但是该对象被手动删除，要么有人取得了该对象并将其删除。
请与我们分享更多代码，logwriter类的源代码不应包含非常敏感的数据，并且它的存在可能有助于实际识别错误。
顺便说一句，请确保~B();实际上有实施。
答案 1 :(得分：0)
好的，我解决了问题..这与我的代码无关。
问题来自冲突的共享库，我猜的框架安装得不好。 我删除了它，完全重新安装，一切正常。
问题解决了！