Qt c++图片更换背景

#include "qalgorithm.h"
#include <iostream>

#include <stdio.h>
#include <stdlib.h>

QAlgorithm::QAlgorithm()
{

}

Mat QAlgorithm::ImageAlgorithm(Mat &src)
{
    // 组装数据
    int w1 = src.cols;
    int h = src.rows;
    int samplecount = w1*h;
    int dims = src.channels();
    Mat points(samplecount, dims, CV_32F, Scalar(10));
    int index1 = 0;
    for (int row = 0; row < h; row++) {
        for (int col = 0; col < w1; col++) {
            index1 = row*w1 + col;
            Vec3b bgr = src.at<Vec3b>(row, col);
            points.at<float>(index1, 0) = static_cast<int>(bgr[0]);
            points.at<float>(index1, 1) = static_cast<int>(bgr[1]);
            points.at<float>(index1, 2) = static_cast<int>(bgr[2]);
        }
    }
    // 运行KMeans
    int numCluster = 4;
    TermCriteria criteria = TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 10, 0.1);
    kmeans(points, numCluster, labels, criteria, 3, KMEANS_PP_CENTERS, centers);
    //我觉得没有必要用这个，毕竟这个的价值只是为了找到背景的标记罢了，
    //用那么多的时间换取这个，成本太大而收益太低了
    //去背景+遮罩生成
    Mat mask = Mat::zeros(src.size(), CV_8UC1);
    int index = src.rows * 2 + 2;
    int cindex = labels.at<int>(index, 0);
    int height = src.rows;
    int width = src.cols;
    for (int row = 0; row < height; row++) {
        for (int col = 0; col < width; col++) {
            index = row*width + col;
            int label = labels.at<int>(index, 0);
            if (label == cindex) {
                mask.at<uchar>(row, col) = 0;
            }
            else {
                mask.at<uchar>(row, col) = 255;
            }
        }
    }
    //imshow("mask", mask);

    // 腐蚀 + 高斯模糊
    Mat mask_morph, mask_blur;
    Mat k = getStructuringElement(MORPH_RECT, Size(7, 7), Point(-1, -1));
    erode(mask, mask_morph, k);                 //腐蚀操作后的图像白色边界少了一个边界像素，是全部的轮廓边界
    //imshow("erode-mask", mask);
    //更新一个骚操作，以前不知道，原来3X3的内核去掉的是广义上的一个边界像素，5X5去掉的是两个边界像素，真香哈哈哈~
    GaussianBlur(mask_morph, mask_blur, Size(3, 3), 0, 0);
    //imshow("Blur Mask", mask);                //使得边界高斯模糊了原本的0跟255变成0，64，191，255
    /*
    为什么要进行这步操作呢？
    1.羽化边界，先通过形态学腐蚀，为了是轮廓边界在”腐蚀 + 高斯模糊“ 操作后，轮廓边缘的像素保持不变
    高斯模糊的原因在于将原本的0跟255的像素变成0，64，191，255，使得边界不会发生突变，可以起到羽化的作用
    */
    // 通道混合
    RNG rng(12345);
    Vec3b color;

    uchar t_r = mcolor.red();
    uchar t_g = mcolor.green();
    uchar t_b = mcolor.blue();
    color[0] = t_r;//rng.uniform(0, 255);
    color[1] = t_g; // rng.uniform(0, 255);
    color[2] = t_b;// rng.uniform(0, 255);
    Mat result(src.size(), src.type());
    double w = 0.0;
    int b = 0, g = 0, r = 0;
    int b1 = 0, g1 = 0, r1 = 0;
    int b2 = 0, g2 = 0, r2 = 0;
    for (int row = 0; row < height; row++) {
        for (int col = 0; col < width; col++) {
            int m = mask_blur.at<uchar>(row, col);
            if (m == 255) {
                result.at<Vec3b>(row, col) = src.at<Vec3b>(row, col); // 前景
            }
            else if (m == 0) {
                result.at<Vec3b>(row, col) = color; // 背景
            } else {
                w = m / 255.0;
                b1 = src.at<Vec3b>(row, col)[0];
                g1 = src.at<Vec3b>(row, col)[1];
                r1 = src.at<Vec3b>(row, col)[2];
                b2 = color[0];
                g2 = color[1];
                r2 = color[2];
                b = b1*w + b2*(1.0 - w);
                g = g1*w + g2*(1.0 - w);
                r = r1*w + r2*(1.0 - w);
                result.at<Vec3b>(row, col)[0] = b;
                result.at<Vec3b>(row, col)[1] = g;
                result.at<Vec3b>(row, col)[2] = r;
            }
        }
    }
    return result;
}


void QAlgorithm::setColor(QColor pcolor)
{
    mcolor = pcolor;
}