This is currently set up to expect a grayscale image as input. I think that you are asking how to adapt it to accept a colour input image and return a colour output image. You don't need to change much:

cv::Mat CVCircles::detectedCirclesInImage(cv::Mat img, double dp, double minDist, double  param1, double param2, int min_radius, int max_radius) {

  if(img.empty())
        {
        cout << "can not open image " << endl;
        return img;
        }
  Mat img;

  if (img.type()==CV_8UC1) {
              //input image is grayscale
    cvtColor(img, cimg, CV_GRAY2RGB);

  } else {
              //input image is colour
    cimg = img;
    cvtColor(img, img, CV_RGB2GRAY);
  }

the rest stays as is.

If your input image is colour, you are converting it to gray for processing by HoughCircles, and applying the found circles to the original colour image for output.