shreya's profile - activity

thanks a lot

http://answers.opencv.org/question/12... please help here

i tried that too that doesn't work either and even if that was the problem green blobs would be detected as red and red as green ones but all the blobs were detected as red

somehow all the blobs are detected as red even green ones

I am making a project that detects circles in a real time image and then classifies the circle as red or green. My approach towards the problem is that first i make a saliency map of the original image then i apply simple blob detector on that saliency map by setting suitable parameters.Hence the circles are detected as blobs .Then i extract the coordinates of the centre of th blob and go to that coordinate in the original 3 channel image , if the pixel value in the red channel is more than that in green it is classified as red otherwise green,but this logic fails to work i dont get why my code:

 int main()
 {


// Read image
Mat org=imread("32.jpg");
Mat im = imread( "sal12.jpg", IMREAD_GRAYSCALE );
Size s(400,300);
resize(im,im,s);
resize(org,org,s);
imshow("original",org);
imshow("saliency map",im);





// Setup SimpleBlobDetector parameters.
SimpleBlobDetector::Params params;

// Change thresholds
params.minThreshold = 10;
params.maxThreshold = 256;

// Filter by Area.
params.filterByArea = true;
params.minArea =70;
params.maxArea=1000;

// filter my min distance
//params.minDistBetweenBlobs=100;

// Filter by Circularity
params.filterByCircularity = true;
params.minCircularity = 0.8;

// Filter by Convexity
params.filterByConvexity = true;
params.minConvexity = 0.5;

// Filter by Inertia
params.filterByInertia = false;
params.minInertiaRatio = 0.01;

//filter by colour
params.filterByColor=false;
params.blobColor=255;

// Storage for blobs
vector<KeyPoint> keypoints;



// Set up detector with params
Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create(params);   

// Detect blobs
detector->detect( im, keypoints);

//the total no of blobs detected are:
int x=keypoints.size();
cout<<"total no of circles detected are:"<< x <<endl;
cout<<endl;
        int green=0;
    int red=0;
for(int i=0;i<x;i++)
{  

   //location of first blob
    Point2f point1=keypoints.at(i).pt;
    int x1=point1.x;
    int y1=point1.y;

    float R=(float)org.at<Vec3b>(x1,y1)[1];
    float B=(float)org.at<Vec3b>(x1,y1)[0];
    float G=(float)org.at<Vec3b>(x1,y1)[2];
    cout<<"location of "<<i+1<<" blob is "<<x1<<","<<y1<<endl;
    cout<<" blue channel pixel value at the location is"<<(float)org.at<Vec3b>(x1,y1)[0]<<endl;
    cout<<" green channel pixel value at the location is"<<(float)org.at<Vec3b>(x1,y1)[2]<<endl;
    cout<<" red channel pixel value at the location is"<<(float)org.at<Vec3b>(x1,y1)[1]<<endl;
    if (R>G)
    {
            cout<<" THE BLOB IS RED"<<endl;
           red++;
    }
    if(G>R)
    {
        cout<<"THE BLOB IS GREEN"<<endl;
        green++;
    }
    //cout<<"hue value : "<<(int)hsv.at<Vec3b>(x1,y1)[0]<<endl;
    float size=keypoints.at(i).size;
    cout<<"size of the blob is : "<<size<<cout<<endl;
    cout<<endl;



}

cout<<"no of green circles: "<<green<<endl;
cout<<"no of red circles :"<<red <<endl;
 //Draw detected blobs as red circles.
//DrawMatchesFlags::DRAW_RICH_KEYPOINTS flag ensures
// the size of the circle corresponds to the size of blob
Mat im_with_keypoints;
drawKeypoints(org, keypoints, im_with_keypoints, Scalar(0,0,255), DrawMatchesFlags::DRAW_RICH_KEYPOINTS );

}

how can i print the diameter of blob detected? and what does the octave parameter of the keypoint return?

i am running the sample code for simple blob detector in open cv 3 in c++ i want to print the x and y cordinate of the keypoints that are detected , here is the code:

using namespace cv; using namespace std;

int main() {

 // Read image
 Mat im = imread( "24.jpg", IMREAD_GRAYSCALE );
Size s(400,300);
resize(im,im,s);
imshow("original",im);




// Setup SimpleBlobDetector parameters.
SimpleBlobDetector::Params params;

// Change thresholds
params.minThreshold = 10;
params.maxThreshold = 256;

// Filter by Area.
params.filterByArea = true;
params.minArea =50;
params.maxArea=700;

// filter my min distance
//params.minDistBetweenBlobs=100;

// Filter by Circularity
params.filterByCircularity = true;
params.minCircularity = 0.8;

// Filter by Convexity
params.filterByConvexity = true;
params.minConvexity = 0.5;

// Filter by Inertia
params.filterByInertia = false;
params.minInertiaRatio = 0.01;

//filter by colour
params.filterByColor=true;
params.blobColor=255;

// Storage for blobs
vector<KeyPoint> keypoints;



// Set up detector with params
Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create(params);   

// Detect blobs
detector->detect( im, keypoints);

//the total no of blobs detected are:
size_t x=keypoints.size();
cout<<"total no of circles detected are:"<<x<<endl;


//location of first blob
Point2f point1=keypoints.at(0).pt;
float x1=point1.x;
float y1=point1.y;
cout<<"location of the first blob is "<<x1<<","<<y1;


// Draw detected blobs as red circles.
// DrawMatchesFlags::DRAW_RICH_KEYPOINTS flag ensures
// the size of the circle corresponds to the size of blob

Mat im_with_keypoints;
drawKeypoints( im, keypoints, im_with_keypoints, Scalar(0,0,255), DrawMatchesFlags::DRAW_RICH_KEYPOINTS );

// Show blobs
imshow("keypoints", im_with_keypoints );

waitKey();

}

thanks a lot sir and i just started using open cv 2 months back so i am new to the library and how it works the only way i learn is through internet i didnt write this code i found this code online only and was trying to understand and run it to learn how kmeans can be used to posterize an image

i am trying to write a code to posterize an image using kmeans in open 3.0 (c++) the code is as follows :

int main()
{
  Mat src = imread("1.jpg", 1 );
  Mat samples(src.rows * src.cols, 3, CV_32F);
  //Mat samples(3,src.rows*src.cols,CV_32F);
  for( int y = 0; y < src.rows; y++ )
    for( int x = 0; x < src.cols; x++ )
      for( int z = 0; z < 3; z++)
        samples.at<float>(y + x*src.rows, z) = src.at<Vec3b>(y,x)[z];


  int clusterCount = 3;
  Mat labels;
  int attempts = 5;
  Mat centers;
  //kmeans(samples, clusterCount, labels, TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10000, 0.0001), attempts, KMEANS_PP_CENTERS, centers );

kmeans(samples,clusterCount, labels,TermCriteria( TermCriteria::EPS+TermCriteria::COUNT, 10, 1.0),3, KMEANS_RANDOM_CENTERS, centers);
  Mat new_image(src.rows * src.cols, 3, CV_32S);
  for( int y = 0; y < src.rows; y++ )
    for( int x = 0; x < src.cols; x++ )
    { 
      int cluster_idx = labels.at<int>(y + x*src.rows,0);
      new_image.at<Vec3b>(y,x)[0] = centers.at<int>(cluster_idx, 0);
      new_image.at<Vec3b>(y,x)[1] = centers.at<int>(cluster_idx, 1);
      new_image.at<Vec3b>(y,x)[2] = centers.at<int>(cluster_idx, 2);
    }
  imshow( "clustered image", new_image );
  waitKey();
}

i am getting an assertion failed error : OpenCV Error: Assertion failed (N >= K) in cv::kmeans, file C:\buildslave64\win64_amdocl\master_PackSlave-win64-vc11-shared\opencv\modules\core\src\kmeans.cpp, line 231 how should i resolve this ?

can you explain me the what nnPtr->setBackpropWeightScale(0.5f); nnPtr->setBackpropMomentumScale(0.5f); this will implement

no its not the previous error i was debugging somehow if i cout<<trainLabels.rows; it gives me 4 instead of 35591 (which is equal to the no examples)

read this paper and try applying the method described i think it will solve your problem :http://cmp.felk.cvut.cz/~cernyad2/TextCaptchaPdf/Detecting%20Text%20in%20Natural%20Scenes%20with%20Stroke%20Width%20Transform.pdf

you should search for stroke width transform for text detection and try to segment characters by that method and then use ocr. can you provide a link to theinput image

yes sir you are right i considered the no of rows instead of column i changed the code and made it 784 instead of 35591 but i am still getting errors that i am trying to resolve actually i am new to open cv and its confused

https://www.kaggle.com/c/digit-recogn... this is the link from where i downloaded the data

here is a screen shot i am unable to attach the csv file itself http://answers.opencv.org/upfiles/148...

the text version: OpenCV Error Assertion failed (nvars==(int)rowvals.size()) in cv ml TrainDataImpl::loadCSV,file(then the path till ml/src/data.cpp,line 587

are you unable to view the images ? if so next time i will give the text version

i edited my code but i am still getting the following error: http://answers.opencv.org/upfiles/148... most probably because of the load command

what method should be used for model selection of ann? like the no of layers and nodes? is it hit and trial method and see maximum accuracy?

vector<int> layerSizes; layerSizes[0]=35591; layerSizes[1]=1000; layerSizes[2]=10; most probably something wrong here

http://answers.opencv.org/upfiles/148...

I downloaded training set for digit recognition. The training set is in csv format , the first column contains the responses and pixel value of the following response is stored the corresponding row. I am trying to write a c++ code in visual studio that uses the ml module of open cv 3.00 to train from the data. I can load the data using the TrainData::loadFromCSV function but i am unable to understand how will it generate the samples and responses matrix that is required to feed into the TrainData::create command my code:

void main()
{
    TrainData::loadFromCSV("C:/Users/Shreya Srivastava/Desktop/train.csv",0,1,10);
    Mat samples ( 28,28, CV_32FC1 );
    Mat responses(35591,0,CV_32F);
    TrainData::create(samples,ROW_SAMPLE,responses);
    imshow("samples",samples);

    waitKey();
}

http://answers.opencv.org/question/12... can you please help resolve this error

[C:\fakepath\csv file.png] (/upfiles/1483124022567734.png)C:\fakepath\error.png C:\fakepath\error.pngthis related to the previous question i had asked: http://answers.opencv.org/question/12... i am trying to build digit recognition project using ANN_MLP open cv 3.0 and the code is as follows:

C:\fakepath\csv file.png

void main()
{

int inputLayerSize = 1;
int outputLayerSize = 1;
int numSamples = 2;
Mat layers = Mat(3, 1, CV_32S);
layers.row(0) =Scalar(35591) ;
layers.row(1) = Scalar(100);
layers.row(2) = Scalar(10);
vector<int> layerSizes;
layerSizes[0]=35591;
layerSizes[1]=1000;
layerSizes[2]=10;

Ptr<ANN_MLP> nnPtr =ANN_MLP::create();


//nnPtr->setLayerSizes(3);
nnPtr->setLayerSizes(layers);
nnPtr->setTrainMethod(ANN_MLP::BACKPROP);

nnPtr->setTermCriteria(TermCriteria(cv::TermCriteria::COUNT | cv::TermCriteria::EPS, 1000, 0.00001f));

nnPtr->setActivationFunction(ANN_MLP::SIGMOID_SYM, 1, 1);
nnPtr->setBackpropWeightScale(0.5f);
nnPtr->setBackpropMomentumScale(0.5f);

Ptr<TrainData> tdata = TrainData::loadFromCSV("C:/Users/Shreya Srivastava/Desktop/train.csv",
       0, // lines to skip
       0, // 1st elem is the label
      -1); // only 1 response per line


Mat trainData = tdata->getTrainSamples();
Mat trainLabels = tdata->getTrainResponses();
int numClasses = 10; // assuming mnist
Mat hot(trainLabels.rows, numClasses, CV_32F, 0.0f); // all zero, initially
for (int i=0; i<trainLabels.rows; i++)
{
        int id = (int)trainLabels.at<float>(i);
        hot.at<float>(i, id) = 1.0f; 
}
nnPtr->train(trainData,0,hot);

bool m = nnPtr->isTrained();
if (m)
    std::cout << "training complete\n\n";


Ptr<TrainData> mdata = TrainData::loadFromCSV("C:/Users/Shreya Srivastava/Desktop/test.csv", 0,0,-1);
Mat testData = mdata->getTrainSamples();
Mat testLabels = mdata->getTrainResponses();
Mat testResults;
nnPtr->predict(testData, testResults);
float accuracy = float(countNonZero(testResults == testLabels)) / testLabels.rows;

printf("the accuracy is %f",accuracy);
}

i dont understand why i am getting assertion failed error