C++ 从3.2升级到openCV 3.4.1后出现分段故障
从openCV 3.2升级到openCV 3.4.1后，我在运行程序时出现分段错误 下面是完整的源代码我不是C专家 正在运行程序。/txtbin input.png output.png 希望有人能帮忙： 错误 input.png txtbin.cpp txtbin.hpp 回溯C++ 从3.2升级到openCV 3.4.1后出现分段故障,c++,opencv,C++,Opencv,从openCV 3.2升级到openCV 3.4.1后，我在运行程序时出现分段错误 下面是完整的源代码我不是C专家 正在运行程序。/txtbin input.png output.png 希望有人能帮忙： 错误 input.png txtbin.cpp txtbin.hpp 回溯 以下Txtbin:：binarize实现不会出现segfault 使用先前的Txtbin:：binarize定义，cv:：imwrite将类型视为_InputArray:：EXPR而不是_InputArray:：MAT
以下Txtbin:：binarize实现不会出现segfault 使用先前的Txtbin:：binarize定义，cv:：imwrite将类型视为_InputArray:：EXPR而不是_InputArray:：MAT，并将img_vec的未初始化值传递给cv:：imwrite。segfault是由于尝试取消引用该未初始化值而导致的。_InputArray:：EXPR值来自MatExpr运算符*的返回值，cv:：MatExpr被传递给_InputArray:：_InputArray 通过修改Txtbin:：binarize的定义，MatExpr运算符*的返回值被传递给MatExpr:：operator Mat const，后者将其传递给MatOp_AddEx:：assign，传递给_InputArray:：_InputArray的值是cv:：Mat，而不是cv:：MatExpr。简言之，MatExpr运算符*返回值的赋值似乎可以防止不正确的类型转换cv:：imwrite的第二个参数需要cv:：InputArray，而不是cv:Mat 新版本的opencv似乎不易受此崩溃的影响。在此之前，cv:：imwrite调用了getMat方法，并将该调用恢复为else子句的默认行为，以替换过于特定的条件。我确认，即使使用先前版本的Txtbin:：binarize，通过对cv:：imwrite的更改重新编译opencv也可以防止崩溃，并且MatExpr操作符*的返回值会传递给MatExpr:：operator Mat const，就像由于赋值而修改的Txtbin:：binarize定义一样
简而言之，您可以解决这个问题，也可以安装它的修复程序。下面的Txtbin:：binarize实现不会出现segfault 使用先前的Txtbin:：binarize定义，cv:：imwrite将类型视为_InputArray:：EXPR而不是_InputArray:：MAT，并将img_vec的未初始化值传递给cv:：imwrite。segfault是由于尝试取消引用该未初始化值而导致的。_InputArray:：EXPR值来自MatExpr运算符*的返回值，cv:：MatExpr被传递给_InputArray:：_InputArray 通过修改Txtbin:：binarize的定义，MatExpr运算符*的返回值被传递给MatExpr:：operator Mat const，后者将其传递给MatOp_AddEx:：assign，传递给_InputArray:：_InputArray的值是cv:：Mat，而不是cv:：MatExpr。简言之，MatExpr运算符*返回值的赋值似乎可以防止不正确的类型转换cv:：imwrite的第二个参数需要cv:：InputArray，而不是cv:Mat 新版本的opencv似乎不易受此崩溃的影响。在此之前，cv:：imwrite调用了getMat方法，并将该调用恢复为else子句的默认行为，以替换过于特定的条件。我确认，即使使用先前版本的Txtbin:：binarize，通过对cv:：imwrite的更改重新编译opencv也可以防止崩溃，并且MatExpr操作符*的返回值会传递给MatExpr:：operator Mat const，就像由于赋值而修改的Txtbin:：binarize定义一样
简而言之，您可以解决这个问题，也可以安装它的修复程序。错误是什么？我的意思是运行它时会显示完整的错误消息。当然会有一条诊断消息。在调试器下运行seg故障时，在seg故障点的调用堆栈是什么？您能搜索发生seg故障的代码行吗？通过调试器或简单地在代码中添加一个单独的couts直到找到行。尝试运行以下命令：gdb-args./txtbin input.png output.png，然后当gdb抱怨segfault时，您将进入gdb shell类型“run”来运行程序，键入“bt”以显示回溯。错误是什么？我的意思是运行它时完整的错误消息。当然会有一条诊断消息。在调试器下运行seg故障时，在seg故障点的调用堆栈是什么？您能搜索发生seg故障的代码行吗？通过调试器或简单地在代码中添加单个couts直到找到行。尝试运行以下命令：gdb-args./txtbin input.png output.png，然后当gdb抱怨segfault时，您将进入gdb shell类型“run”来运行程序，键入“bt”来显示回溯。
> Error: signal 11:
> #1 ./txtbin(_Z6bTracei+0x1c) [0x5596628d8e68]
> #2 /lib/x86_64-linux-gnu/libc.so.6(+0x33060) [0x7fa1b8481060]
> #3 /usr/local/lib/libopencv_world.so.3.4(+0xa3f7da) [0x7fa1b9ac97da]
> #4 /usr/local/lib/libopencv_world.so.3.4(+0xa2782d) [0x7fa1b9ab182d]
> #5 /usr/local/lib/libopencv_world.so.3.4(_ZN2cv7imwriteERKNS_6StringERKNS_11_InputArrayERKSt6vectorIiSaIiEE+0x8e) [0x7fa1b9ab4a4e]
> #6 ./txtbin(_ZN6Txtbin8binarizeEv+0x12d) [0x5596628d67c3]
> #7 ./txtbin(_ZN6Txtbin3runEv+0x698) [0x5596628d8c10]
> #8 ./txtbin(main+0x3fa) [0x5596628d92db]
> #9 /lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf1) [0x7fa1b846e2e1]
/*
* Compile
* # g++ -rdynamic -std=c++11 txtbin.cpp -o txtbin `pkg-config opencv --cflags --libs`
*
* Get opencv version
* # pkg-config --modversion opencv
*/
#include <signal.h>
#include "../backtrace/backtrace.h"
#include "txtbin.hpp"
Backtrace b;
void bTrace(int sig){
b.trace(sig);
}
void usage(const std::string VERSION){
std::cout << "txtbin: " << VERSION << "\nOpenCV: " << CV_VERSION << "\n\nUsage: txtbin input [options] output\n"
"Options:\n"
"\t-w <number> -- Set max width (keeps aspect ratio)\n"
"\t-h <number> -- Set max height (keeps aspect ratio)\n"
"\t-c -- Crop text contours\n"
"\t-r -- Rotate contents (deskew)\n"
"\t-m <number> -- Set margins (%)\n"
"\t-b <number> -- Set blockside (pixel)\n"
"\t Default: 9 pixel\n"
"\t-t <number> -- Set threshold (%)\n"
"\t Default: 85 %\n"
"\t-v -- Verbose\n" << std::endl;
}
int main(int argc, char* argv[]){
signal(SIGSEGV, &bTrace);
Txtbin a;
try{
// Parse arguments
for(int i = 1; i < argc; i++){
std::string arg = std::string(argv[i]);
if(i == 1){
a.set_input(arg);
}
else if(arg == "-w"){
a.set_width(atoi(argv[++i]));
}
else if(arg == "-h"){
a.set_height(atoi(argv[++i]));
}
else if(arg == "-c"){
a.set_crop(true);
}
else if(arg == "-r"){
a.set_rotate(true);
}
else if(arg == "-m"){
a.set_margin(atoi(argv[++i]));
}
else if(arg == "-b"){
a.set_blockside(atoi(argv[++i]));
}
else if(arg == "-t"){
a.set_threshold(atoi(argv[++i]));
}
else if(arg == "-v"){
a.set_verbose(true);
}
else if(i == argc - 1){
a.set_output(arg);
}
else{
throw std::runtime_error("Argument '"+arg+"' is invalid");
}
}
a.run();
}
catch(std::exception& e){
std::cerr << "Error: " << e.what() << "\n" << std::endl;
usage(a.VERSION);
return 1;
}
return 0;
}
struct textblock{
int left = 0;
int top = 0;
int right = 0;
int bottom = 0;
};
class Txtbin{
private:
std::string input = "";
std::string output = "output.png";
int max_width = 0;
int max_height = 0;
bool is_crop = false;
bool is_rotate = false;
float margin = 0;
int blockside = 9; // set greater for larger fonts in image and vice versa
bool is_verbose = false;
float contrast = 0.01; // set smaller for lower contrast image
float thresholding = 0.85;
void binarize ();
cv::Mat src;
cv::Mat calc_block_mean_variance(cv::Mat& img);
textblock detect_text_block (bool test_output);
void downsize ();
void crop (textblock coords);
void error (const std::string& s);
public:
Txtbin();
const std::string VERSION = "0.3.6";
void set_input (const std::string& s);
void set_output (const std::string& s);
void set_height (int h);
void set_width (int w);
void set_crop (bool c);
void set_rotate (bool r);
void set_margin (float m);
void set_blockside (int b);
void set_threshold (int t);
void set_verbose (bool v);
void run ();
};
#include <iostream>
#include <fstream>
#include <chrono>
#include <boost/algorithm/string.hpp>
#include "/usr/local/include/opencv2/opencv.hpp"
#include "txtbin.h"
Txtbin::Txtbin(){}
void Txtbin::set_input(const std::string& s){
input = s;
}
void Txtbin::set_output(const std::string& s){
output = s;
}
void Txtbin::set_height(int h){
max_height = h;
}
void Txtbin::set_width(int w){
max_width = w;
}
void Txtbin::set_crop(bool c){
is_crop = c;
}
void Txtbin::set_rotate(bool r){
is_rotate = r;
}
void Txtbin::set_margin(float m){
margin = m;
}
void Txtbin::set_blockside(int b){
blockside = b;
}
void Txtbin::set_threshold(int t){
thresholding = t / 100;
}
void Txtbin::set_verbose(bool v){
is_verbose = v;
}
void Txtbin::error(const std::string& s){
throw std::runtime_error(s);
}
void Txtbin::binarize(){
src.convertTo(src, CV_32FC1, 1.0 / 255.0);
cv::Mat res = calc_block_mean_variance(src);
imwrite(output, res * 255);
}
void Txtbin::crop(textblock coords){
if(coords.left < coords.right && coords.top < coords.bottom){
if(coords.left < 0){
coords.left = 0;
}
int crop_width = coords.right - coords.left;
int trim_width = coords.left + crop_width - src.cols;
if(trim_width > 0){
crop_width -= trim_width;
}
if(coords.top < 0){
coords.top = 0;
}
int crop_height = coords.bottom - coords.top;
int trim_height = coords.top + crop_height - src.rows;
if(trim_height > 0){
crop_height -= trim_height;
}
cv::Rect cut_rect = cv::Rect(coords.left, coords.top, crop_width, crop_height);
src = src(cut_rect);
}
else{
std::cout << "Warning: Invalid text block coordinates. Cropping is omitted!" << std::endl;
}
}
void Txtbin::downsize(){
float
width = src.cols,
height = src.rows,
scale = 0;
bool resized = false;
if(max_width > 0 && width > max_width){
scale = width / max_width;
width /= scale;
height /= scale;
resized = true;
}
if(max_height > 0 && height > max_height){
scale = height / max_height;
width /= scale;
height /= scale;
resized = true;
}
if(resized){
resize(src, src, cv::Size(round(width), round(height)));
}
}
textblock Txtbin::detect_text_block(bool test_output){
cv::Mat img = src.clone();
// downsample image and use it for processing
int multiplier = 2;
pyrDown(img, img);
textblock block;
block.left = img.cols;
block.top = img.rows;
int
rect_bottom,
rect_right;
// morphological gradient
cv::Mat grad;
cv::Mat morphKernel = getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(3, 3));
morphologyEx(img, grad, cv::MORPH_GRADIENT, morphKernel);
// binarize
cv::Mat bw;
threshold(grad, bw, 0.0, 255.0, cv::THRESH_BINARY | cv::THRESH_OTSU);
// connect horizontally oriented regions
cv::Mat connected;
morphKernel = getStructuringElement(cv::MORPH_RECT, cv::Size(9, 1));
morphologyEx(bw, connected, cv::MORPH_CLOSE, morphKernel);
// find contours
cv::Mat mask = cv::Mat::zeros(bw.size(), CV_8UC1);
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
findContours(connected, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0));
cv::Scalar color = cv::Scalar(0, 255, 0);
cv::Scalar color2 = cv::Scalar(0, 0, 255);
int thickness = 2;
if(test_output){
cv::cvtColor(img, img, CV_GRAY2BGR);
}
// filter contours
if(!hierarchy.empty()){
for(int idx = 0; idx >= 0; idx = hierarchy[idx][0]){
cv::Rect rect = boundingRect(contours[idx]);
cv::Mat maskROI(mask, rect);
maskROI = cv::Scalar(0, 0, 0);
// fill the contour
drawContours(mask, contours, idx, cv::Scalar(255, 255, 255), CV_FILLED);
// ratio of non-zero pixels in the filled region
double r = (double)countNonZero(maskROI) / (rect.width * rect.height);
// assume at least 25% of the area is filled if it contains text
if (r > 0.25 &&
(rect.height > 8 && rect.width > 8) // constraints on region size
// these two conditions alone are not very robust. better to use something
//like the number of significant peaks in a horizontal projection as a third condition
){
if(test_output){
rectangle(img, rect, color, thickness);
}
//rectangle(src, cv::Rect(rect.x * multiplier, rect.y * multiplier, rect.width * multiplier, rect.height * multiplier), color, thickness);
if(rect.y < block.top){
block.top = rect.y;
}
rect_bottom = rect.y + rect.height;
if(rect_bottom > block.bottom){
block.bottom = rect_bottom;
}
if(rect.x < block.left){
block.left = rect.x;
}
rect_right = rect.x + rect.width;
if(rect_right > block.right){
block.right = rect_right;
}
}
}
}
if(test_output){
rectangle(img, cv::Point(block.left, block.top), cv::Point(block.right, block.bottom), color2, thickness);
imwrite("test_text_contours.jpg", img);
}
//rectangle(src, cv::Point(block.left * multiplier, block.top * multiplier), cv::Point(block.right * multiplier, block.bottom * multiplier), color2, thickness);
block.left *= multiplier;
block.top *= multiplier;
block.right *= multiplier;
block.bottom *= multiplier;
return block;
}
cv::Mat Txtbin::calc_block_mean_variance(cv::Mat& img){
cv::Mat res;
cv::Mat I;
img.convertTo(I, CV_32FC1);
res = cv::Mat::zeros(img.rows / blockside, img.cols / blockside, CV_32FC1);
cv::Mat inpaintmask;
cv::Mat patch;
cv::Mat small_img;
cv::Scalar m, s;
for(int i = 0; i < img.rows - blockside; i += blockside){
for(int j = 0; j < img.cols - blockside; j += blockside){
patch = I(cv::Range(i, i + blockside + 1), cv::Range(j, j + blockside + 1));
meanStdDev(patch, m, s);
if(s[0] > contrast){
res.at<float>(i / blockside, j / blockside) = m[0];
}
else{
res.at<float>(i / blockside, j / blockside) = 0;
}
}
}
resize(I, small_img, res.size());
threshold(res, inpaintmask, 0.02, 1.0, cv::THRESH_BINARY);
cv::Mat inpainted;
small_img.convertTo(small_img, CV_8UC1, 255);
inpaintmask.convertTo(inpaintmask, CV_8UC1);
inpaint(small_img, inpaintmask, inpainted, 5, cv::INPAINT_TELEA);
resize(inpainted, res, img.size());
res.convertTo(res, CV_32FC1, 1.0 / 255.0);
res = 1.0 - res;
res = img + res;
threshold(res, res, thresholding, 1, cv::THRESH_BINARY);
return res;
}
void Txtbin::run(){
// Return error if input file is not defined
if(input == ""){
error("Input file not defined");
}
// Return error if input file is not found
else{
std::ifstream stream(input.c_str());
if(!stream.good()){
error("Input file not found");
}
}
// Return error if output file is not defined
if(output == ""){
error("Output file not defined");
}
// Return error if output file is not PNG
else{
std::string output_lc = output;
boost::to_lower(output_lc);
if(output_lc.substr(output_lc.find_last_of(".") + 1) != "png"){
error("Output file must be PNG");
}
}
bool test_output = false;
auto start = std::chrono::high_resolution_clock::now();
src = cv::imread(input, CV_LOAD_IMAGE_GRAYSCALE);
if(is_crop || is_verbose){
textblock coords = detect_text_block(test_output);
if(is_verbose){
std::cout << "Image dimensions: " << src.cols << " x " << src.rows << std::endl;
std::cout << "Text block coordinates: Left|Top " << coords.left << "," << coords.top << " Right|Bottom " << coords.right << "," << coords.bottom << std::endl;
}
if(is_crop){
crop(coords);
}
}
if(margin){
int border = src.cols * margin / 100;
copyMakeBorder(src, src, border, border, border, border, cv::BORDER_CONSTANT, cv::Scalar(255, 255, 255));
}
downsize();
binarize();
auto elapsed = std::chrono::high_resolution_clock::now() - start;
if(is_verbose){
std::cout << "Execution time: " << (std::chrono::duration_cast<std::chrono::microseconds>(elapsed).count() / 1000) << " ms" << std::endl;
}
}
#include <stdio.h>
#include <execinfo.h>
#include <stdlib.h>
class Backtrace {
public:
Backtrace();
void trace(int sig);
};
Backtrace::Backtrace(){}
void Backtrace::trace(int sig){
void *trace[10];
char **messages = (char **)NULL;
int i, trace_size = 0;
trace_size = backtrace(trace, 10);
messages = backtrace_symbols(trace, trace_size);
fprintf(stderr, "Error: signal %d:\n", sig);
for(i=1; i<trace_size; ++i){
fprintf(stderr, "#%d %s\n", i, messages[i]);
}
exit(1);
}
void Txtbin::binarize(){
src.convertTo(src, CV_32FC1, 1.0 / 255.0);
cv::Mat res = calc_block_mean_variance(src) * 255;
imwrite(output, res);
}