mariusz's profile - activity

Do yo know when latest build tools 27.0.3 and gradle will be supported?

triangulation for image Hi, How can I generate triangulation similar to below files: C:\fakepath\doberman.jpg C:\fake

triangulation for image Hi, How can I generate triangulation similar to below files: (/upfiles/15323659009392009.png) (

Hi,

Below my implementation of function countPixels. Does exist better OpenCv/matrix way? cv::countNonZero works only for on channel image.

int countPixels(const cv::Mat &image, cv::Scalar color) {
  int result = 0;
  for (int y = 0; y < image.rows; y++) {
    const cv::Vec4b *rowImage = image.ptr<cv::Vec4b>(y);
    for (int x = 0; x < image.cols; x++) {
      if (rowImage[x][0] == color[0] && rowImage[x][1] == color[1] &&
          rowImage[x][2] == color[2] && rowImage[x][3] == color[3]) {
        ++result;
      }
    }
  }
  return result;
}

Thanks Mariusz

Hi,

How to create 3d button from rectangle? My goal is to have a function with output similar to: http://www.imagemagick.org/Usage/adva...

Could you send me any ideas how to do it in OpenCV?

Thank you in advance, Mariusz

Below my implementation

void join(cv::Mat& image1, const cv::Mat& image2)
{
    assert(image1.rows == image2.rows);
    assert(image1.cols == image2.cols);

    std::vector<cv::Mat> channels;
    std::vector<cv::Mat> channels2;
    cv::split(image1, channels);
    cv::split(image2, channels2);

    cv::Mat c1 = (255.0 - channels2[3]) / 255.0;
    cv::Mat c2 = channels2[3] / 255.0;
    for (size_t i = 0; i < 3; i++)
    {
        channels[i] = channels[i].mul(c1) + channels2[i].mul(c2);
    }
    cv::merge(channels, image1);
}

Could you help me write it as matrix operation?

Hi,

Performance analysis shows me that below function is the slowest function in my program. Is it possible to optimize performance of this gradient function? (i.e. by some matrix operation)

void gradient(cv::Mat& image, cv::Scalar c1, cv::Scalar c2)
{
    auto alphaStep = 1.0 / image.rows;
    auto alpha = 0.0;
    for (int y = 0; y < image.rows; y++) {
        cv::Vec4b* rowImage = image.ptr<cv::Vec4b>(y);
        cv::Scalar color(c1(0)*(1 - alpha) + c2(0)*(alpha), c1(1)*(1 - alpha) + c2(1)*(alpha), c1(2)*(1 - alpha) + c2(2)*(alpha), 255);
        for (int x = 0; x < image.cols; x++) {
            rowImage[x][0] = color[0];
            rowImage[x][1] = color[1];
            rowImage[x][2] = color[2];
            rowImage[x][3] = color[3];
        }
        alpha += alphaStep;
    }
}

I do not know how to use operators instead of below three lines. Could you write it for me?

double c1 = (255 - (*it2)[3]) / 255.0;
double c2 = (*it2)[3] / 255.0;
(*it)[0] = (*it)[0] * c1 + (*it2)[0] * c2;

Thank you in advance.

Thank you for answer. Sorry I provided probably but example. I know that we have also converTo image.convertTo(new_image, -1, alpha, beta);

But What about below code. Join two images base on alpha channel of image2.

    void join(cv::Mat& image, const cv::Mat& image2)
    {
        assert(image.rows == image2.rows);
        assert(image.cols == image2.cols);

        auto it = image.begin<cv::Vec4b>();
        auto it2 = image2.begin<cv::Vec4b>();
        const auto itEnd = image.end<cv::Vec4b>();
        for (; it != itEnd; ++it, ++it2)
        {
            double c1 = (255 - (*it2)[3]) / 255.0;
            double c2 = (*it2)[3] / 255.0;
            (*it)[0] = (*it)[0] * c1 + (*it2)[0] * c2;
            (*it)[1] = (*it)[1] * c1 + (*it2)[1] * c2;
            (*it)[2] = (*it)
(*it)[3] = 255;
    }
    }

Hi,

Is there any generic OpenCV function/algorithm (like C++ std::transform) to perform pixel modification. I know that I can write i.e. below code. But is neither generic nor efficient.

cv::Mat image;
cv::Mat new_image;

for( int y = 0; y < image.rows; y++ )
   { for( int x = 0; x < image.cols; x++ )
        { for( int c = 0; c < 3; c++ )
             { new_image.at<Vec3b>(y,x)[c] =
                         saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta ); }
   }
}

I would like to use it like i.e.

cv::Mat src;
cv::Mat dst;
transform(src, dst, pixelUnaryFunctor);

cv::Mat src1;
cv::Mat src2;
cv::Mat dst;
transform(src1, src2, dst, pixelBinaryFunctor);