Keep Coding

I have the following image:
I would like to detect the red rectangle using cv::inRange method and HSV color space.
int H_MIN = 0;
int H_MAX = 10;
int S_MIN = 70;
int S_MAX = 255;
int V_MIN = 50;
int V_MAX = 255;
cv::cvtColor( input, imageHSV, cv::COLOR_BGR2HSV );
cv::inRange( imageHSV, cv::Scalar( H_MIN, S_MIN, V_MIN ), cv::Scalar( H_MAX, S_MAX, V_MAX ), imgThreshold0 );
I already created dynamic trackbars in order to change the values for HSV, but I can't get the desired result.
Any suggestion for best values (and maybe filters) to use?

In HSV space, the red color wraps around 180. So you need the H values to be both in [0,10] and [170, 180].
Try this:
#include <opencv2\opencv.hpp>
using namespace cv;
int main()
{
Mat3b bgr = imread("path_to_image");
Mat3b hsv;
cvtColor(bgr, hsv, COLOR_BGR2HSV);
Mat1b mask1, mask2;
inRange(hsv, Scalar(0, 70, 50), Scalar(10, 255, 255), mask1);
inRange(hsv, Scalar(170, 70, 50), Scalar(180, 255, 255), mask2);
Mat1b mask = mask1 | mask2;
imshow("Mask", mask);
waitKey();
return 0;
}
Your previous result:
Result adding range [170, 180]:
Another interesting approach which needs to check a single range only is:
invert the BGR image
convert to HSV
look for cyan color
This idea has been proposed by fmw42 and kindly pointed out by Mark Setchell. Thank you very much for that.
#include <opencv2\opencv.hpp>
using namespace cv;
int main()
{
Mat3b bgr = imread("path_to_image");
Mat3b bgr_inv = ~bgr;
Mat3b hsv_inv;
cvtColor(bgr_inv, hsv_inv, COLOR_BGR2HSV);
Mat1b mask;
inRange(hsv_inv, Scalar(90 - 10, 70, 50), Scalar(90 + 10, 255, 255), mask); // Cyan is 90
imshow("Mask", mask);
waitKey();
return 0;
}