OpenCV里面的一些常用函数

找出图片变换后的映射关系

    for (...)
    {
      cv::Point tmppt;
　　　　...
      ptarr1.push_back(tmppt);
    }for (...)
    {
     　　cv::Point tmppt;
　　　　 ...
        ptarr2.push_back(tmppt);
    }

    cv::Mat homo = cv::findHomography(ptarr1, ptarr2, CV_RANSAC);

ptarr1的点经过homo的映射关系会得到ptarr2的点  homo 就是其中的映射关系

使用映射关系

    warpPerspective(srcImageMat,imageTransform1,homo,readBackImageMat.size());

srcImageMat经过homo的映射关系，按照readBackImageMat的尺寸，计算出imageTransform1

提取图片的某个区域

    cv::Rect roi_rect = cv::Rect(nleft, ntop, width, height);
    Mat roi= imageTransform1(roi_rect);//提出背景区域
    Mat roi2 = readBackImageMat(roi_rect);

拷贝一个图片到另一个图片的对应区域

outpt.copyTo(readBackImageMat(roi_rect));

outpt拷贝到readBackImageMat的roi_rect区域


松柏克隆

    Mat roi= imageTransform1(roi_rect);//提出背景区域
    Mat roi2 = readBackImageMat(roi_rect);
    
    Mat mask(roi.size(), CV_8UC1,255);
    cv::Size center = mask.size() / 2;

    cv::Mat outpt;
    seamlessClone(roi, roi2, mask, center, outpt, NORMAL_CLONE);

https://blog.csdn.net/hjimce/article/details/45716603

像素融合

    cv::Mat outpt;
    seamlessClone(roi, roi2, mask, center, outpt, NORMAL_CLONE);

    mask.setTo(0);
    mask(cv::Rect(15,30, mask.cols-30,mask.rows-60)).setTo(255);
    cv::blur(mask, mask, cv::Size(15, 30));

    cv::Mat rcMat = readBackImageMat(roi_rect);
    for (int i = 0; i < rcMat.rows; i++)
    {
        uchar* cc = rcMat.ptr<uchar>(i);
        uchar* ss = outpt.ptr<uchar>(i);
        uchar* mm = mask.ptr<uchar>(i);
        for (int j = 0; j < rcMat.cols; j++)
        {
            float falpha = mm[j] / 255.0f;

            cc[j * 3] = ss[j * 3] * falpha + cc[j * 3] * (1 - falpha);
            cc[j * 3+1] = ss[j * 3+1] * falpha + cc[j * 3+1] * (1 - falpha);
            cc[j * 3+2] = ss[j * 3+2] * falpha + cc[j * 3+2] * (1 - falpha);
        }
    }

Mat转bitmap

Bitmap* CPublicFunction::CopyMatToBmp(Mat& i_Mat)
{
    //assert(mb_InitDone);

    PixelFormat e_Format;
    switch (i_Mat.channels())
    {
    case 1: e_Format = PixelFormat8bppIndexed; break;
    case 3: e_Format = PixelFormat24bppRGB;    break;
    case 4: e_Format = PixelFormat32bppARGB;   break;
    default: throw L"Image format not supported.";
    }

    // Create Bitmap with own memory
    Bitmap* pi_Bmp = new Bitmap(i_Mat.cols, i_Mat.rows, e_Format);

    BitmapData i_Data;
    Gdiplus::Rect k_Rect(0, 0, i_Mat.cols, i_Mat.rows);
    if (Ok != pi_Bmp->LockBits(&k_Rect, ImageLockModeWrite, e_Format, &i_Data))
    {
        delete pi_Bmp;
        throw L"Error locking Bitmap.";
    }

    if (i_Mat.elemSize1() == 1) // 1 Byte per channel (8 bit gray scale palette)
    {
        BYTE* u8_Src = i_Mat.data;
        BYTE* u8_Dst = (BYTE*)i_Data.Scan0;

        int s32_RowLen = i_Mat.cols * i_Mat.channels(); // != i_Mat.step !!

                                                        // The Windows Bitmap format requires all rows to be DWORD aligned (always!)
                                                        // while OpenCV by default stores bitmap data sequentially.
        for (int R = 0; R<i_Mat.rows; R++)
        {
            memcpy(u8_Dst, u8_Src, s32_RowLen);
            u8_Src += i_Mat.step;    // step may be e.g 3729
            u8_Dst += i_Data.Stride; // while Stride is 3732
        }
    }
    else // i_Mat may contain e.g. float data (CV_32F -> 4 Bytes per pixel grayscale)
    {
        int s32_Type;
        switch (i_Mat.channels())
        {
        case 1: s32_Type = CV_8UC1; break;
        case 3: s32_Type = CV_8UC3; break;
        default: throw L"Image format not supported.";
        }

        CvMat i_Dst;
        cvInitMatHeader(&i_Dst, i_Mat.rows, i_Mat.cols, s32_Type, i_Data.Scan0, i_Data.Stride);

        CvMat i_Img = i_Mat;
        cvConvertImage(&i_Img, &i_Dst, 0);
    }

    pi_Bmp->UnlockBits(&i_Data);

    // Add the grayscale palette if required.
    if (e_Format == PixelFormat8bppIndexed)
    {
        CByteArray i_Arr;
        i_Arr.SetSize(sizeof(ColorPalette) + 256 * sizeof(ARGB));
        ColorPalette* pk_Palette = (ColorPalette*)i_Arr.GetData();

        pk_Palette->Count = 256;
        pk_Palette->Flags = PaletteFlagsGrayScale;

        ARGB* pk_Color = &pk_Palette->Entries[0];
        for (int i = 0; i<256; i++)
        {
            pk_Color[i] = Color::MakeARGB(255, i, i, i);
        }

        if (Ok != pi_Bmp->SetPalette(pk_Palette))
        {
            delete pi_Bmp;
            throw L"Error setting grayscale palette.";
        }
    }
    return pi_Bmp;
}

展示图片的时候控制窗口属性

        cv::namedWindow("head", CV_WINDOW_NORMAL);
        cv::resizeWindow("head", 150, 120);  //控制窗口大小
        cv::moveWindow("head", 1000, 100);//控制窗口起始坐标
        cv::imshow("head", imageROI);

 提取某个矩形区域的图片

cv::Mat mMat = m_findfacethread->GetImage();
cv::Mat imageROI = mMat(cv::Rect(x1, y, x2 - x1, y12 - y));