I have a trivial problem but I don't know how to solve it. I just wanna do a simple "foreach" of a Mat to view rgb values. I have next code:
for(int i=0; i<mat.rows; i++)
{
for(int j=0; j<mat.cols; j++)
{
int value_rgb = mat.at<uchar>(i,j);
cout << "(" << i << "," << j << ") : " << value_rgb <<endl;
}
}
The mat is 200 rows x 200 cols. When I print on console the results, just in the final the programs fails with next error:
**OpenCV Error: Assertion failed (dims <= 2 && data && (unsigned)i0 <(unsigned)size.p[0] && (unsigned)(i1*DataType<_Tp>::channels) < (unsigned)(size.p[1]*channels()) && ((((sizeof(size_t)<<28)|0x8442211) >> ((DataType<_Tp>::depth) & ((1 << 3) - 1))*4) & 1 5) == elemSize1()) in unknown function, file c:\opencv\build\include\opencv2\core\mat.hpp, line 537**
Anyone can help me?
Thanks.
The below piece of code will help you in accessing the rgb pixel values.You have to access three channels to view RGB values.
for(int i = 0; i < i<mat.rows; i++)
{
for(int j = 0; j < mat.cols; j++)
{
int b = mat.at<cv::Vec3b>(i,j)[0];
int g = mat.at<cv::Vec3b>(i,j)[1];
int r = mat.at<cv::Vec3b>(i,j)[2];
cout << r << " " << g << " " << b << value_rgb <<endl ;
}
}
To read pixel value from a grayscale image
#include <opencv\cv.h>
#include <highgui\highgui.hpp>
using namespace std;
using namespace cv;
int main()
{
cv::Mat img = cv::imread("5.jpg",0);
for(int j=0;j<img.rows;j++)
{
for (int i=0;i<img.cols;i++)
{
int a;
a=img.at<uchar>(j,i);
cout<<a<<endl;
}
}
cv::imshow("After",img);
waitKey(0);
}
Updated
This code reads all the grayscale values from an image and results in frequent occurring vales (Number of times the value as occurred). i.e
Number of times pixel value '0' as appeared,
Number of times pixel value '1' as appeared, ... & so on till 256.
#include <opencv\cv.h>
#include <highgui\highgui.hpp>
using namespace std;
using namespace cv;
int main()
{
cv::Mat img = cv::imread("5.jpg",0);
//for(int j=0;j<img.rows;j++)
//{
// for (int i=0;i<img.cols;i++)
// {
// int a;
// a=img.at<uchar>(j,i);
// cout<<a<<endl;
// }
//}
vector<int> values_rgb;
for(int i=0; i<20; i++)
{
for(int j=0; j<20; j++)
{
int value_rgb = img.at<uchar>(i,j);
values_rgb.push_back(value_rgb);
//cout << "(" << i << "," << j << ") : " << value_rgb <<endl;
}
}
// Sorting of values in ascending order
vector<int> counter_rg_values;
for(int l=0; l<256; l++)
{
for(int k=0; k<values_rgb.size(); k++)
{
if(values_rgb.at(k) == l)
{
counter_rg_values.push_back(l);
}
}
}
//for(int m=0;m<counter_rg_values.size();m++)
//cout<<m<<" "<< counter_rg_values[m] <<endl;
int m=0;
for(int n=0;n<256;n++)
{
int c=0;
for(int q=0;q<counter_rg_values.size();q++)
{
if(n==counter_rg_values[q])
{
//int c;
c++;
m++;
}
}
cout<<n<<"= "<< c<<endl;
}
cout<<"Total number of elements "<< m<<endl;
cv::imshow("After",img);
waitKey(0);
}
Related
I'm trying to create a char matrix using dynamic allocation (char**). It represents a board where the margins are '#' character and in the middle is the ASCII 32 (blank space). When I run the code this massage appear: "Exception thrown at 0x00007FFD9ABF024E (ucrtbased.dll) in myapp.exe: 0xC0000005: Access violation reading location " in some cpp file.
Here's my code:
#include <iostream>
using namespace std;
char** allocateBoard(int n)
{
char** Board = 0;
Board = new char* [n+2];
int i;
for (i = 0; i < n + 2; i++)
{
Board[i] = new char[n * 2 + 2];
}
return Board;
}
void initBoard(char**& Board, int n)
{
int i, j;
for (i = 0; i < n; i++)
{
for (j = 0; j < n * 2; j++)
{
if (i == 0 || i == n - 1) Board[i][j] = '#';
else if (j == 0 || j == n * 2 - 1) Board[i][j] = '#';
else Board[i][j] = 32;
}
}
}
void showBoard(char** Board, int n)
{
int i, j;
for (i = 0; i < n; i++)
{
for (j = 0; j < n * 2; j++)
{
cout << Board[i][j];
}
cout << endl;
}
}
int main()
{
int n = 4;
char** Board = 0;
Board = allocateBoard(n);
initBoard(Board, n);
showBoard(Board, n);
cout << endl;
showBoard(Board, n);
for (int i = 0; i < n * 2 + 4; i++)
{
delete[] Board[i];
}
delete[] Board;
return 0;
}
Does anyone know where is the problem? As a very beginner I can't see where is the mistake. I've allocated more space in the matrix than I'm actually using so I can't figure why this message appears. Is the deallocation the problem?
Thanks!
I'm new in OpenCV, and I want to thresholding the image by myself without using Threshold function in opencv, because the time spend on function threshold is to high for me.
Here is my code:
Mat src = imread("D:\\DataBox\\7.jpg", 0);
for (int i = 0; i < src.cols; i++) {
cout << i << endl;
for (int j = 0; j < src.rows; j++) {
if (src.at<uchar>(i, j) > 70) {
src.at<uchar>(i, j) = 0;
cout << j << endl;
}
else
src.at<uchar>(i, j) = 255;
}
}
but it still says:
"OpenCV Error: Assertion failed (dims <= 2 && data && (unsigned)i0 < (unsigned)size.p[0] && (unsigned)(i1 * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels()) && ((((sizeof(size_t)<<28)|0x8442211) >> ((DataType<_Tp>::depth) & ((1 << 3) - 1))*4) & 15) == elemSize1()) in cv::Mat::at, file C:\Program Files\opencv\build\include\opencv2/core/mat.inl.hpp, line 894"
I can print j from 0~719(since the size of the image is 720*960), but as long as the parameter i want to become 2 from 1, the error occurs.
You mixed up rows and cols:
Try this:
Mat src = imread("path_to_image", IMREAD_GRAYSCALE);
for (int i = 0; i < src.rows; i++)
{
//cout << i << endl;
for (int j = 0; j < src.cols; j++)
{
if (src.at<uchar>(i, j) > 70) {
src.at<uchar>(i, j) = 0;
//cout << j << endl;
}
else
src.at<uchar>(i, j) = 255;
}
}
This is, however very unlikely to perform better than OpenCV implementation. You can gain a little speed working on raw pointers, with a little trick to work on continuous data when possible:
#include <opencv2\opencv.hpp>
using namespace cv;
int main()
{
Mat src = imread("D:\\SO\\img\\nice.jpg", IMREAD_GRAYSCALE);
int rows = src.rows;
int cols = src.cols;
if (src.isContinuous())
{
cols = rows * cols;
rows = 1;
}
for (int i = 0; i < rows; i++)
{
uchar* pdata = src.ptr<uchar>(i);
int base = i*cols;
for (int j = 0; j < cols; j++)
{
if (pdata[base + j] > 70)
{
pdata[base + j] = 0;
}
else
{
pdata[base + j] = 255;
}
}
}
return 0;
}
Actually, on my PC my version is a little bit faster than OpenCV one:
Time #HenryChen (ms): 2.83266
Time #Miki (ms): 1.09597
Time #OpenCV (ms): 2.10727
You can test on your PC with the following code, since time depends on many factor, e.g. optimizations enabled in OpenCV:
#include <opencv2\opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main()
{
Mat1b src(720,960);
randu(src, 0, 256);
Mat1b src1 = src.clone();
Mat1b src2 = src.clone();
Mat1b src3 = src.clone();
double tic1 = double(getTickCount());
// Method #HenryChen (corrected)
for (int i = 0; i < src1.rows; i++)
{
//cout << i << endl;
for (int j = 0; j < src1.cols; j++)
{
if (src1.at<uchar>(i, j) > 70) {
src1.at<uchar>(i, j) = 0;
//cout << j << endl;
}
else
src1.at<uchar>(i, j) = 255;
}
}
double toc1 = (double(getTickCount()) - tic1) * 1000.0 / getTickFrequency();
cout << "Time #HenryChen (ms): \t" << toc1 << endl;
//-------------------------------------
double tic2 = double(getTickCount());
// Method #Miki
int rows = src2.rows;
int cols = src2.cols;
if (src2.isContinuous())
{
cols = rows * cols;
rows = 1;
}
for (int i = 0; i < rows; i++)
{
uchar* pdata = src2.ptr<uchar>(0);
int base = i*cols;
for (int j = 0; j < cols; j++)
{
pdata[base + j] = (pdata[base + j] > 70) ? uchar(0) : uchar(255);
}
}
double toc2 = (double(getTickCount()) - tic2) * 1000.0 / getTickFrequency();
cout << "Time #Miki (ms): \t" << toc2 << endl;
//-------------------------------------
double tic3 = double(getTickCount());
// Method #OpenCV
threshold(src3, src3, 70, 255, THRESH_BINARY_INV);
double toc3 = (double(getTickCount()) - tic3) * 1000.0 / getTickFrequency();
cout << "Time #OpenCV (ms): \t" << toc3 << endl;
getchar();
return 0;
}
Use test.at<uchar>(cv::Point(i, j)) instead. I always get lost when accessing cv::Mat directly - cv::Point clears it up a little bit.
Anyway, I agree with Miki - it is very unlikely to create a function that performs better that a library one.
I am trying to train my own detector based on HOG features and i trained a detector with CvSVM utility of opencv. Now to use this detector in HOGDescriptor.SetSVM(myDetector), i need to get trained detector in row-vector (primal) form to feed. For this i am using this code. my implementation is like given below:
vector<float>primal;
void LinearSVM::getSupportVector(std::vector<float>& support_vector) {
CvSVM svm;
svm.load("Classifier.xml");
cin.get();
int sv_count = svm.get_support_vector_count();
const CvSVMDecisionFunc* df = decision_func;
const double* alphas = df[0].alpha;
double rho = df[0].rho;
int var_count = svm.get_var_count();
support_vector.resize(var_count, 0);
for (unsigned int r = 0; r < (unsigned)sv_count; r++) {
float myalpha = alphas[r];
const float* v = svm.get_support_vector(r);
for (int j = 0; j < var_count; j++,v++) {
support_vector[j] += (-myalpha) * (*v);
}
}
support_vector.push_back(rho);
}
int main()
{
LinearSVM s;
s.getSupportVector(primal);
return 0;
}
When i use built-in CvSVM, it shows me SV as 3 bec i have only 3 SV in my saved file but since the decision_func is in protected mode, hence i can not access it. That's why i tried to use that wrapper but still of no use. Perhaps you guys can help me out here... Thanks alot!
Answer with a test harness. I put in new answer as it would add allot of clutter to the original answer, possibly making it a bit confusing.
//dummy features
std:: vector<float>
dummyDerReaderForOneDer(const vector<float> &pattern)
{
int i = std::rand() % pattern.size();
int j = std::rand() % pattern.size();
vector<float> patternPulNoise(pattern);
std::random_shuffle(patternPulNoise.begin()+std::min(i,j),patternPulNoise.begin()+std::max(i,j));
return patternPulNoise;
};
//extend CvSVM to get access to weights
class mySVM : public CvSVM
{
public:
vector<float>
getWeightVector(const int descriptorSize);
};
//get the weights
vector<float>
mySVM::getWeightVector(const int descriptorSize)
{
vector<float> svmWeightsVec(descriptorSize+1);
int numSupportVectors = get_support_vector_count();
//this is protected, but can access due to inheritance rules
const CvSVMDecisionFunc *dec = CvSVM::decision_func;
const float *supportVector;
float* svmWeight = &svmWeightsVec[0];
for (int i = 0; i < numSupportVectors; ++i)
{
float alpha = *(dec[0].alpha + i);
supportVector = get_support_vector(i);
for(int j=0;j<descriptorSize;j++)
{
*(svmWeight + j) += alpha * *(supportVector+j);
}
}
*(svmWeight + descriptorSize) = - dec[0].rho;
return svmWeightsVec;
}
// main harness entry point for detector test
int main (int argc, const char * argv[])
{
//dummy variables for example
int posFiles = 10;
int negFiles = 10;
int dims = 1000;
int randomFactor = 4;
//setup some dummy data
vector<float> dummyPosPattern;
dummyPosPattern.assign(int(dims/randomFactor),1.f);
dummyPosPattern.resize(dims );
random_shuffle(dummyPosPattern.begin(),dummyPosPattern.end());
vector<float> dummyNegPattern;
dummyNegPattern.assign(int(dims/randomFactor),1.f);
dummyNegPattern.resize(dims );
random_shuffle(dummyNegPattern.begin(),dummyNegPattern.end());
// the labels and lables mat
float posLabel = 1.f;
float negLabel = 2.f;
cv::Mat cSvmLabels;
//the data mat
cv::Mat cSvmTrainingData;
//dummy linear svm parmas
SVMParams cSvmParams;
cSvmParams.svm_type = cv::SVM::C_SVC;
cSvmParams.C = 0.0100;
cSvmParams.kernel_type = cv::SVM::LINEAR;
cSvmParams.term_crit = cv::TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 1000000, FLT_EPSILON);
cout << "creating training data. please wait" << endl;
int i;
for(i=0;i<posFiles;i++)
{
//your feature for one box from file
vector<float> d = dummyDerReaderForOneDer(dummyPosPattern);
//push back a new mat made from the vectors data, with copy data flag on
//this shows the format of the mat for a single example, (1 (row) X dims(col) ), as training mat has each **row** as an example;
//the push_back works like vector add adds each example to the bottom of the matrix
cSvmTrainingData.push_back(cv::Mat(1,dims,CV_32FC1,d.data(),true));
//push back a pos label to the labels mat
cSvmLabels.push_back(posLabel);
}
//do same with neg files;
for(i=0;i<negFiles;i++)
{
float a = rand();
vector<float> d = dummyDerReaderForOneDer(dummyNegPattern);
cSvmTrainingData.push_back(cv::Mat(1,dims,CV_32FC1,d.data(),true));
cSvmLabels.push_back(negLabel);
}
//have a look
cv::Mat viz;
cSvmTrainingData.convertTo(viz,CV_8UC3);
viz = viz*255;
cv::imshow("svmData", viz);
cv::waitKey(10);
cout << "press any key to continue" << endl;
getchar();
viz.release();
//create the svm;
cout << "training, please wait" << endl;
mySVM svm;
svm.train(cSvmTrainingData,cSvmLabels,cv::Mat(),cv::Mat(),cSvmParams);
cout << "get weights" << endl;
vector<float> svmWeights = svm.getWeightVector(dims);
for(i=0; i<dims+1; i++)
{
cout << svmWeights[i] << ", ";
if(i==dims)
{
cout << endl << "bias: " << svmWeights[i] << endl;
}
}
cout << "press any key to continue" << endl;
getchar();
cout << "testing, please wait" << endl;
//test the svm with a large amount of new unseen fake one at a time
int totExamples = 10;
int k;
for(i=0;i<totExamples; i++)
{
cout << endl << endl;
vector<float> dPos = dummyDerReaderForOneDer(dummyPosPattern);
cv::Mat dMatPos(1,dims,CV_32FC1,dPos.data(),true);
float predScoreFromDual = svm.predict(dMatPos,true);
float predScoreBFromPrimal = svmWeights[dims];
for( k = 0; k <= dims - 4; k += 4 )
predScoreBFromPrimal += dPos[k]*svmWeights[k] + dPos[k+1]*svmWeights[k+1] +
dPos[k+2]*svmWeights[k+2] + dPos[k+3]*svmWeights[k+3];
for( ; k < dims; k++ )
predScoreBFromPrimal += dPos[k]*svmWeights[k];
cout << "Dual Score:\t" << predScoreFromDual << "\tPrimal Score:\t" << predScoreBFromPrimal << endl;
}
cout << "press any key to continue" << endl;
getchar();
return(0);
}
Hello again :) please extend the cvsm class rather than encapsulating it, as you need access to protected member.
//header
class mySVM : public CvSVM
{
public:
vector<float>
getWeightVector(const int descriptorSize);
};
//cpp
vector<float>
mySVM::getWeightVector(const int descriptorSize)
{
vector<float> svmWeightsVec(descriptorSize+1);
int numSupportVectors = get_support_vector_count();
//this is protected, but can access due to inheritance rules
const CvSVMDecisionFunc *dec = CvSVM::decision_func;
const float *supportVector;
float* svmWeight = &svmWeightsVec[0];
for (int i = 0; i < numSupportVectors; ++i)
{
float alpha = *(dec[0].alpha + i);
supportVector = get_support_vector(i);
for(int j=0;j<descriptorSize;j++)
{
*(svmWeight + j) += alpha * *(supportVector+j);
}
}
*(svmWeight + descriptorSize) = - dec[0].rho;
return svmWeightsVec;
}
something like that.
credits:
Obtaining weights in CvSVM, the SVM implementation of OpenCV
Alright, i have a hw assignment to check if an inserted string is a palindrome. The string must first be inserted into a stack, a queue, and then compared. I have the program up and running, for me that is. My teacher, when trying to grade it experience(d) a run time error. Also, getline portable is a requirement of the assignment and came with the file and instructions.
This is the note from the teacher:
Check if a line is a palindrome. Ignore spaces? y/n y (her running the code)
Input line to check
(where she gets the runtime error)
175 [main] csc240Summer2014PE8Student 10060 open_stackdumpfile: Dumping stack trace to csc240Summer2014PE8Student.exe.stackdump
#include <iostream>
#include <stack>
#include <queue>
#include <string>
using namespace std;
istream& getline_portable( istream& is, string& str ) {
istream& ris = std::getline(is,str);
if ( str.size() && str[str.size()-1] == '\r' )
str.resize(str.size()-1);
return ris;
}
int main()
{
stack<char> s;
queue<char> q;
char c, choice, b;
string str;
int i = 0;
int count = 0;
do
{
cout<<"Check if a line is a palindrome. Ignore spaces? y/n ";
cin >> b;
cin.ignore();
tolower(b);
cout<<"Input line to check\n";
getline_portable(cin,str);
for(int j = 0; j < str.size(); j++)
str[j] = tolower(str[j]);
if(b == 'n')
{
for(int j = 0; j < str.size(); j++)
{
c = str[j];
q.push(c);
s.push(c);
}
}
else if (b == 'y')
{
for(int j = 0; j < str.size() - count; j++)
{
c = str[j];
if(isspace(c))
{
}
else if(!isspace(c))
{
q.push(c);
s.push(c);
}
}
}
do
{
if(q.front() != s.top())
{
i = false;
break;
}
else
{
i = true;
s.pop();
q.pop();
}
}while(!q.empty() && !s.empty());
if (i == true)
cout << str << " is a pallindrom.\n";
else if (i == false)
cout << "Your input of " << str << " is not a pallindrome.\n";
cout << "Would you like to test another string? y/n ";
cin >> choice;
tolower(choice);
cin.ignore();
}while (choice == 'y');
cout << "Press enter to continue...";
cin.get();
return 0;
}
Basically I've got a loop which goes through all the kinects depth pixels. If they are greater than 3000mm it sets the pixel value to black.
For some reason this works only at a close range while pointed to a wall. If I pull the kinect back (giving it a larger area to scan) I get a Bad Memory allocation error. My code can be found below. I get the bad memory allocation error inside that try catch statement. Most of the code is from the opencv kinect sample here and here.
i figured out the problem, its because the depth values are stored in an array instead of matrix, i need a better way of finding out which location in the array, the x.y of the pixels which start from 1,1 point to instead of the (i = x+y*640)
#include <opencv.hpp>
#include <iostream>
#include <string>
#include <stdio.h>
#include <OpenNI.h>
using namespace std;
using namespace cv;
int main()
{
openni::Device device;
openni::VideoStream depth;
const char* device_uri = openni::ANY_DEVICE;
openni::Status ret = openni::OpenNI::initialize();
// Open
ret =device.open( device_uri );
ret = depth.create( device, openni::SENSOR_DEPTH );
if ( ret == openni::STATUS_OK )
{
// Start Depth
depth.start();
}
// Get Depth Stream Min-Max Value
int minDepthValue = depth.getMinPixelValue();
int maxDepthValue = depth.getMaxPixelValue();
//cout << "Depth min-Max Value : " << minDepthValue << "-" << maxDepthValue << endl;
// Frame Information Reference
openni::VideoFrameRef depthFrame;
// Get Sensor Resolution Information
int dImgWidth = depth.getVideoMode().getResolutionX();
int dImgHeight = depth.getVideoMode().getResolutionY();
// Depth Image Matrix
cv::Mat dImg = cv::Mat( dImgHeight, dImgWidth, CV_8UC3 );
Mat grey= cvCreateImage(cvSize(640, 480), 8, 1); ;
for(;;)
{
depth.readFrame( &depthFrame );
openni::DepthPixel* depthImgRaw = (openni::DepthPixel*)depthFrame.getData();
for ( int i = 0 ; i < ( depthFrame.getDataSize() / sizeof( openni::DepthPixel ) ) ; i++ )
{
int idx = i * 3; // Grayscale
unsigned char* data = &dImg.data[idx];
int gray_scale = ( ( depthImgRaw[i] * 255 ) / ( maxDepthValue - minDepthValue ) );
data[0] = (unsigned char)~gray_scale;
data[1] = (unsigned char)~gray_scale;
data[2] = (unsigned char)~gray_scale;
}
openni::DepthPixel* depthpixels = (openni::DepthPixel*)depthFrame.getData();
cvtColor(dImg, grey, CV_RGB2GRAY);
int i ;
try{
for( int y =0; y < 480 ; y++){
//getting in to each pixel in a row
for(int x = 0; x < 640; x++){
//getting out the corresponding pixel value from the array
i = x+y*640;
if (depthpixels[i] >3000)
{
grey.at<unsigned char>(x,y) = 0;
}
}
}
}catch(exception e)
{cout << e.what() <<endl ;
cout <<depthpixels[i] <<endl ;
cout << i <<endl ;
}
// cv:imshow( "depth", dImg );
imshow("dpeth2", grey);
int k = cvWaitKey( 30 ); // About 30fps
if ( k == 0x1b )
break;
}
// Destroy Streams
depth.destroy();
// Close Device
device.close();
// Shutdown OpenNI
openni::OpenNI::shutdown();
return 0;
}
solved the problem simply by swapping my x and y around
for( y =0; y < 480 ; y++)
{
//getting in to each pixel in a row
for( x = 0; x < 640; x++)
{
if (depthpixels[i]>1500)
{
grey.at<unsigned char >(y,x) = 0;
}
if (depthpixels[i] <500)
{
grey.at<unsigned char >(y,x) = 0;
}
i++;
}
}