I'm using OpenCV master branch (3.0.0. dev) with CUDA on Ubuntu 12.04, and trying to compile the following opencv with gpu code:
#include <iostream>
#include "opencv2/opencv.hpp"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/gpu/gpu.hpp"
using namespace cv;
int main (int argc, char* argv[])
{
try
{
cv::Mat src_host = cv::imread("file.png", CV_LOAD_IMAGE_GRAYSCALE);
cv::gpu::GpuMat dst, src;
src.upload(src_host);
cv::gpu::threshold(src, dst, 128.0, 255.0, CV_THRESH_BINARY);
cv::Mat result_host = dst;
cv::imshow("Result", result_host);
cv::waitKey();
}
catch(const cv::Exception& ex)
{
std::cout << "Error: " << ex.what() << std::endl;
}
return 0;
}
The compiling command is:
g++ testgpu.cpp -o test `pkg-config --cflags --libs opencv` -lopencv_gpu
It has the following compiling errors:
testgpu.cpp: In function ‘int main(int, char**)’:
testgpu.cpp:13:51: error: ‘CV_LOAD_IMAGE_GRAYSCALE’ was not declared in this scope
cv::Mat src_host = cv::imread("file.png", CV_LOAD_IMAGE_GRAYSCALE);
^
testgpu.cpp:17:52: error: ‘CV_THRESH_BINARY’ was not declared in this scope
cv::gpu::threshold(src, dst, 128.0, 255.0, CV_THRESH_BINARY);
^
testgpu.cpp:19:31: error: conversion from ‘cv::gpu::GpuMat’ to non-scalar type ‘cv::Mat’ requested
cv::Mat result_host = dst;
^
It is something wrong with the installation of OpenCV, or the API change in Opencv 3.0.0?
The gpu module was redesigned in OpenCV 3.0. It was splitted onto several modules, it was renamed to cuda and gpu:: namespace was renamed to cuda::. The correct code for OpenCV 3.0:
#include <iostream>
#include "opencv2/opencv.hpp"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/cudaarithm.hpp"
using namespace cv;
int main (int argc, char* argv[])
{
try
{
cv::Mat src_host = cv::imread("file.png", cv::IMREAD_GRAYSCALE);
cv::cuda::GpuMat dst, src;
src.upload(src_host);
cv::cuda::threshold(src, dst, 128.0, 255.0, cv::THRESH_BINARY);
cv::Mat result_host(dst);
cv::imshow("Result", result_host);
cv::waitKey();
}
catch(const cv::Exception& ex)
{
std::cout << "Error: " << ex.what() << std::endl;
}
return 0;
}
Ah, they've been playing with the constants in master. Expect the CV_* prefix removed almost anywhere ( except the types, CV_8U and such are still alive).
So it's cv::THRESH_BINARY, cv::LOAD_IMAGE_GRAYSCALE, but .... cv::COLOR_BGR2GRAY (you didn't use it now, but i'll spare you the searching ;) )
Sorry, I've no experience with GPU stuff, so i can't solve the last riddle there.
Related
i tried to change code ipl to mat
but failed
i use opencv 4.1.2
this sample uses opencv 2.4.13
https://jadeshin.tistory.com/entry/cvAcc에-의한-배경-영상-계산
i can't use ipl
so i changed
#include <opencv2\opencv.hpp>
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\core\mat.hpp>
#include <opencv2\imgproc.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main()
{
VideoCapture cap("ball.avi");
if (!cap.isOpened())
{
cout << "file not found." << endl;
return 0;
}
Mat image;
Size size = Size((int)CAP_PROP_FRAME_WIDTH, (int)CAP_PROP_FRAME_HEIGHT);
Mat grayImage(size, CV_8UC1);
Mat sumImage(size, CV_32FC1);
sumImage.setTo(Scalar::all(0));
int nFrameCount = 0;
for (;;)
{
cap.read(image);
if (image.empty())
{
cout << "could'nt capture" << endl;
break;
}
cvtColor(image, grayImage, COLOR_BGR2GRAY);
accumulate(grayImage, sumImage, NULL); //here is error
imshow("grayImage", grayImage);
char chKey = waitKey(50);
if (chKey == 27)
break;
nFrameCount++;
}
convertScaleAbs(sumImage, sumImage, 1.0 / nFrameCount);
imwrite("ballBkg.jpg", sumImage);
destroyAllWindows();
return 0;
}
nothing wrong to compile but wrong to excute
i did also try, catch
but also failed
what's wrong with accumulate?
C++ version of accumulate void accumulate(InputArray src, InputOutputArray dst, InputArray mask=noArray() )
your are passing NULL instead of noArray() . so just do :
accumulate(grayImage, sumImage);
cv::noArray() is an empty Mat not NULL.
Edit :
Also change
Size size = Size((int)CAP_PROP_FRAME_WIDTH, (int)CAP_PROP_FRAME_HEIGHT);
to
Size size = Size((int)cap.get(CV_CAP_PROP_FRAME_WIDTH), (int)cap.get(CV_CAP_PROP_FRAME_HEIGHT));
I am new to SVM. I used to do object detection using HAAR Cascading. Now I am trying to implement SVM for object detection. I searched online and got to know about the basics.
I wanted to use libsvm while coding for c++. I am getting lots of problems.
Can anyone please explain step by step process of using it for object detection.
BTW I looked into opencv documentation of svm. But I am not able to do anything further.
Also I got this code for training my SVM and saving it into an xml file.
Now I want a code which can take this xml and detect objects in test cases.
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <cv.h>
#include <highgui.h>
#include <cvaux.h>
#include <iostream>
#include <vector>
#include<string.h>
using namespace std;
using namespace cv;
int main ( int argc, char** argv )
{
cout << "OpenCV Training SVM Automatic Number Plate Recognition\n";
cout << "\n";
char* path_Plates;
char* path_NoPlates;
int numPlates;
int numNoPlates;
int imageWidth=150;
int imageHeight=150;
//Check if user specify image to process
if(1)
{
numPlates= 11;
numNoPlates= 90 ;
path_Plates= "/home/kaushik/opencv_work/Manas6/Pics/Positive_Images/";
path_NoPlates= "/home/kaushik/opencv_work/Manas6/Pics/Negative_Images/i";
}else{
cout << "Usage:\n" << argv[0] << " <num Plate Files> <num Non Plate Files> <path to plate folder files> <path to non plate files> \n";
return 0;
}
Mat classes;//(numPlates+numNoPlates, 1, CV_32FC1);
Mat trainingData;//(numPlates+numNoPlates, imageWidth*imageHeight, CV_32FC1 );
Mat trainingImages;
vector<int> trainingLabels;
for(int i=1; i<= numPlates; i++)
{
stringstream ss(stringstream::in | stringstream::out);
ss<<path_Plates<<i<<".jpg";
try{
const char* a = ss.str().c_str();
printf("\n%s\n",a);
Mat img = imread(ss.str(), CV_LOAD_IMAGE_UNCHANGED);
img= img.clone().reshape(1, 1);
//imshow("Window",img);
//cout<<ss.str();
trainingImages.push_back(img);
trainingLabels.push_back(1);
}
catch(Exception e){;}
}
for(int i=0; i< numNoPlates; i++)
{
stringstream ss(stringstream::in | stringstream::out);
ss << path_NoPlates<<i << ".jpg";
try
{
const char* a = ss.str().c_str();
printf("\n%s\n",a);
Mat img=imread(ss.str(), 0);
//imshow("Win",img);
img= img.clone().reshape(1, 1);
trainingImages.push_back(img);
trainingLabels.push_back(0);
//cout<<ss.str();
}
catch(Exception e){;}
}
Mat(trainingImages).copyTo(trainingData);
//trainingData = trainingData.reshape(1,trainingData.rows);
trainingData.convertTo(trainingData, CV_32FC1);
Mat(trainingLabels).copyTo(classes);
FileStorage fs("SVM.xml", FileStorage::WRITE);
fs << "TrainingData" << trainingData;
fs << "classes" << classes;
fs.release();
return 0;
}
Any help would be greatly appreciated.
Also I would love to have suggestions on how to implement libsvm for object detection.
This is a simple code which you could take a test with your xml file:
#include "highgui.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "cv.h"
#include <vector>
#include <string.h>
#include <ml.h>
#include <iostream>
#include <io.h>
using namespace cv;
using namespace std;
int main()
{
FileStorage fs;
fs.open("SVM.xml", FileStorage::READ);
Mat trainingData;
Mat classes;
fs["TrainingData"] >> trainingData;
fs["classes"] >> classes;
CvSVMParams SVM_params;
SVM_params.svm_type = CvSVM::C_SVC;
SVM_params.kernel_type = CvSVM::LINEAR; //CvSVM::LINEAR;
SVM_params.degree = 1;
SVM_params.gamma = 1;
SVM_params.coef0 = 0;
SVM_params.C = 1;
SVM_params.nu = 0;
SVM_params.p = 0;
SVM_params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 1000, 0.01);
CvSVM svm(trainingData, classes, Mat(), Mat(), SVM_params);
Mat src = imread("D:\\SVM\\samples\\\pos\\10.jpg");
Mat gray;
cvtColor(src, gray, CV_BGR2GRAY);
Mat p = gray.reshape(1, 1);
p.convertTo(p, CV_32FC1);
int response = (int)svm.predict( p );
if(response ==1 )
{
cout<<"this is a object!"<<endl;
cout<<endl;
}
else
{
cout<<"no object detected!"<<endl;
cout<<endl;
}
return 0;
}
by the way,it seems that there is little problem when runing your offered code,the result shows that:"opencv errror,Image step is wrongin cv::Mat::reshape".Had you met such situation before?Thank you.
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I am getting the following error when trying to compile my code:
/usr/lib/gcc/x86_64-linux-gnu/4.7/../../../x86_64-linux-gnu/crt1.o: In function `_start':
(.text+0x20): undefined reference to `main'
collect2: error: ld returned 1 exit status
I am using the following command:
g++ detectTemplatePoints.cpp -o SURF_TemplatePoints `pkg-config --cflags --libs opencv`
From what I can find online this seems to happen when you do not have a main entry point included but I do have that, my code below:
#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/nonfree/nonfree.hpp"
using namespace cv;
void readme();
int main (int argc, char* argv[]) {
if( argc != 2 ) {
readme(); return -1;
}
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
if( !img_1.data ) {
std::cout<< " --(!) Error reading images " << std::endl; return -1;
}
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1;
detector.detect( img_1, keypoints_1 );
Mat img_keypoints_1;
drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
imshow("Keypoints 1", img_keypoints_1 );
waitKey(0);
return 0;
}
void readme() {
std::cout << " Usage: ./detectTemplatePoints <img1>" << std::endl;
}
What is causing this error?
As the error message says: you have no main function. They have to have one of the following signatures:
int main()
or
int main(int, char**)
First of all, you should use g++ detectTemplatePoints.cpp -o SURF_TemplatePoints $(pkg-config --cflags --libs opencv ) in order to link opencv libraries.
Also, you haven't shown us the libraries you are including.
I can get it compiled so:
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp>
using namespace std;
using namespace cv;
void readme();
int main (int argc, char** argv) {
if( argc != 2 ) {
readme(); return -1;
}
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
if( !img_1.data ) {
std::cout<< " --(!) Error reading images " << std::endl; return -1;
}
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1;
detector.detect( img_1, keypoints_1 );
Mat img_keypoints_1;
drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
imshow("Keypoints 1", img_keypoints_1 );
waitKey(0);
return 0;
}
void readme() {
std::cout << " Usage: ./detectTemplatePoints <img1>" << std::endl;
}
I'm using opencv3.0.0 dev version with cmake.I installed opencv following this tutorial
http://docs.opencv.org/trunk/doc/tutorials/introduction/linux_install/linux_install.html#linux-installation
After that I'm use the following cmake file to compile a simple face-detector:
cmake_minimum_required(VERSION 2.8)
project( face-detect )
find_package( OpenCV 3.0.0 EXACT REQUIRED )
add_executable( face-detect face-detect.cpp )
target_link_libraries( face-detect ${OpenCV_LIBS} )
Makefile is generated succefully, but when I compile the code there're missing classes under namespace cv:
face-detect.cpp:15: error: 'CommandLineParser' is not a member of 'cv'
cv::CommandLineParser parser(argc, argv, keys);
^
face-detect.cpp:23: error: invalid initialization of reference of type 'cv::InputArray {aka const cv::_InputArray&}' from expression of type 'const char*'
std::cout << cv::format("Error: cannot load cascade file!\n");
However it does find cv::CascadeClassifier. How to fix this problem?
This is the code for face-detect, I took it from internet:
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
const char* keys =
{
"{i|input| |The source image}"
"{o|outdir| |The output directory}"
};
int main(int argc, const char** argv)
{
cv::CommandLineParser parser(argc, argv, keys);
std::string infile = parser.get<std::string>("input");
std::string outdir = parser.get<std::string>("outdir");
std::string cascade_file = "haarcascade_frontalface_alt.xml";
cv::CascadeClassifier cascade;
if (cascade_file.empty() || !cascade.load(cascade_file))
{
std::cout << cv::format("Error: cannot load cascade file!\n");
return -1;
}
cv::Mat src = cv::imread(infile);
if (src.empty())
{
std::cout << cv::format("Error: cannot load source image!\n");
return -1;
}
cv::Mat gray;
cv::cvtColor(src, gray, CV_BGR2GRAY);
cv::equalizeHist(gray, gray);
std::vector<cv::Rect> faces;
cascade.detectMultiScale(gray, faces, 1.2, 3);
std::cout << cv::format("0, %s (%dx%d)\n", infile.c_str(), src.cols, src.rows);
cv::Mat src_copy = src.clone();
for (int i = 0; i < faces.size(); i++)
{
std::string outfile(cv::format("%s/face-%d.jpg", outdir.c_str(), i+1));
cv::Rect r = faces[i];
cv::rectangle(src, r, CV_RGB(0,255,0), 2);
cv::imwrite(outfile, src_copy(r));
cv::imwrite(infile, src);
std::cout << cv::format("%d, %s (%dx%d)\n", i+1, outfile.c_str(), r.width, r.height);
}
return 0;
}
When I compile this example:
#include <iostream>
#include "opencv2/opencv.hpp"
#include "opencv2/gpu/gpu.hpp"
int main (int argc, char* argv[])
{
try
{
cv::Mat src_host = cv::imread("file.png", CV_LOAD_IMAGE_GRAYSCALE);
cv::gpu::GpuMat dst, src;
src.upload(src_host);
cv::gpu::threshold(src, dst, 128.0, 255.0, CV_THRESH_BINARY);
cv::Mat result_host = dst;
cv::imshow("Result", result_host);
cv::waitKey();
}
catch(const cv::Exception& ex)
{
std::cout << "Error: " << ex.what() << std::endl;
}
return 0;
}
I got the following error:
threshold.cpp: In function ‘int main(int, char**)’:
threshold.cpp:19: error: conversion from ‘cv::gpu::GpuMat’ to non-scalar type ‘cv::Mat’ requested
Does anybody knows why?
In the current versions of OpenCV, the cv::Mat class has no overloaded assignment operator or copy constructor which takes argument of type cv::gpu::GpuMat. So the following line of your code will not compile.
cv::Mat result_host = dst;
There are 2 alternatives to this.
First you can pass the dst as the argument of the constructor of result_host.
cv::Mat result_host(dst);
Second is that you can call the download function of dst
cv::Mat result_host;
dst.download(result_host);
It seems that you should use download method of gpuMat to convert it to cv::Mat:
//! downloads data from device to host memory. Blocking calls.
void download(cv::Mat& m) const;
See this doc.