更換色罩時遇到麻煩

Question

我正在使用鼠標處理程序從第一幀中選擇顏色。 我正在嘗試將所選顏色替換為背景框。 這對於紅色來說效果很好，但是對於其他任何顏色（例如綠色，藍色等）都無效。我正在使用以下圖形進行顏色選擇：單擊此處 ！

#include "opencv2/opencv.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>

using namespace std;
using namespace cv;

 // structure to be used in mouseHandler function
struct userdata {
Mat im;
vector<Point2f> points;
 };


 void mouseHandler(int event, int x, int y, int flags, void* data_ptr)
 {
if (event == EVENT_LBUTTONDOWN) {
    userdata* data = ((userdata*)data_ptr);
    circle(data->im, Point(x, y), 3, Scalar(0, 0, 255), 5, LINE_AA);
    imshow("Image", data->im);
    if (data->points.size() < 1) {
        data->points.push_back(Point2f(x, y));
       }
   }
}

int main(int argc, char** argv) {

// Take video frame from camera to select color of material
VideoCapture capt(0);
Mat frames;
capt >> frames;
Mat hsvimg;

// Converting image from BGR to HSV
cvtColor(frames, hsvimg, COLOR_BGR2HSV);

    // Set data for mouse event
Mat im_temp = frames.clone();
userdata data;
data.im = im_temp;

cout << "Select the point on image for the color you want to create cloak and than press 'Enter'" << endl;

// Show image and wait for a click.
imshow("Image", im_temp);

// Set the callback function for any mouse event
setMouseCallback("Image", mouseHandler, &data);
waitKey(0);

//defining the HSV values of the point selected
    Vec3b HSV_Color = hsvimg.at<Vec3b>(data.points[0]);
int hue = HSV_Color.val[0];
int saturation = HSV_Color.val[1];
int value = HSV_Color.val[2];

// Create a VideoCapture object and open the input file for demonstrating the cloak working
    // If the input is the web camera, pass 0 instead of the video file name
// In first frame only background should be there, i.e., no person present
VideoCapture cap(0);

// Check if camera opened successfully
if (!cap.isOpened()) {
    cout << "Error opening video stream or file" << endl;
    return -1;
}

Mat background;
for (int i = 0; i < 30; i++)
{
    cap >> background;
}

//Laterally invert the image / flip the image.
flip(background, background, 1);



while (1)
{

    Mat frame;
    // Capture frame-by-frame
    cap >> frame;

    // Laterally invert the image / flip the image
    flip(frame, frame, 1);

    //Converting image from BGR to HSV color space.
    Mat hsv;
    cvtColor(frame, hsv, COLOR_BGR2HSV);

    Mat mask1, mask2;
    // Creating masks to detect the upper and lower red color.
    // Otherwise mask1 and mask2 are same for other colors
    // Making different conditions according to hue values 
    // Take help from this: https://stackoverflow.com/questions/10948589/choosing-the-correct-upper-and-lower-hsv-boundaries-for-color-detection-withcv
    if (saturation > 100) {
        if (hue <= 10 || hue>165) {
            inRange(hsv, Scalar(0, 120, 20), Scalar(10, 255, 255), mask1);
            inRange(hsv, Scalar(170, 120, 20), Scalar(180, 255, 255), mask2);
        }
        else if (10<hue<=25) {
            inRange(hsv, Scalar(10, 120, 20), Scalar(25, 255, 255), mask1);
            inRange(hsv, Scalar(10, 120, 20), Scalar(25, 255, 255), mask2);
        }
        else if (25 < hue <= 38) {
            inRange(hsv, Scalar(25, 120, 20), Scalar(35, 255, 255), mask1);
            inRange(hsv, Scalar(25, 120, 20), Scalar(35, 255, 255), mask2);
        }
        else if (38 < hue <= 71) {
            inRange(hsv, Scalar(38, 100, 20), Scalar(71, 255, 255), mask1);
            inRange(hsv, Scalar(38, 100, 20), Scalar(71, 255, 255), mask2);
        }
        else if (71 < hue <= 100) {
            inRange(hsv, Scalar(71, 120, 20), Scalar(95, 255, 255), mask1);
            inRange(hsv, Scalar(71, 120, 20), Scalar(95, 255, 255), mask2);
        }
        else if (100 < hue <= 140) {
            inRange(hsv, Scalar(100, 150, 20), Scalar(130, 255, 255), mask1);
            inRange(hsv, Scalar(100, 150, 20), Scalar(130, 255, 255), mask2);
        }
        else if (140 < hue <= 165) {
            inRange(hsv, Scalar(140, 120, 20), Scalar(170, 255, 255), mask1);
            inRange(hsv, Scalar(140, 120, 20), Scalar(170, 255, 255), mask2);
        }
    }
    else { 
        cout << "Use colored material." << endl;
        break;
    }

    // Generating the final mask
    mask1 = mask1 + mask2;

    Mat kernel = Mat::ones(3, 3, CV_32F);
    morphologyEx(mask1, mask1, cv::MORPH_OPEN, kernel);
    morphologyEx(mask1, mask1, cv::MORPH_DILATE, kernel);

    // creating an inverted mask to segment out the cloth from the frame
    bitwise_not(mask1, mask2);

    Mat res1, res2, final_output;
            // Segmenting the cloth out of the frame using bitwise and with the inverted mask
    bitwise_and(frame, frame, res1, mask2);

    // creating image showing static background frame pixels only for the masked region
    bitwise_and(background, background, res2, mask1);

    // Generating the final augmented output.
    addWeighted(res1, 1, res2, 1, 0, final_output);
    imshow("magic", final_output);
    waitKey(1);

    // Press  ESC on keyboard to exit
    char c = (char)waitKey(25);
    if (c == 27)
        break;
    // Also relese all the mat created in the code to avoid memory leakage.
    frame.release(), hsv.release(), mask1.release(), mask2.release(), res1.release(), res2.release(), final_output.release();

}

// When everything done, release the video capture object
cap.release();

// Closes all the frames
cv::destroyAllWindows();

return 0;
    }

它對所有主要顏色都應與對紅色相同。

Answer 1

選擇其他顏色時，是否檢查了這兩點的輸出？

Vec3b HSV_Color = hsvimg.at<Vec3b>(data.points[0]);
int hue = HSV_Color.val[0];
int saturation = HSV_Color.val[1];
int value = HSV_Color.val[2];

還有這個

cvtColor(frame, hsv, COLOR_BGR2HSV);