Python版本可參考以下鏈接：
https://github.com/crossin/snippet/tree/master/face_detect

//人臉寬度
//im為原始視頻幀

const std::string strPath = AppPath.substr(0, AppPath.rfind("\\")) + "\\" + "hat8.png";

　Mat m_hatImg = imread(strPath, -1);//帶alpha通道的圖片如果仍要保留alpha通道，imread的第二個參數必須是-1

int faceWidth = face_info_list[best_index].face.right - face_info_list[best_index].face.left;
 
int faceHeight = face_info_list[best_index].face.bottom - face_info_list[best_index].face.top;

//人臉與帽子的比例
float scale = (float)(faceWidth) / (float)m_hatImg.cols * 2.7;

Mat hatScale;
m_hatImg.copyTo(hatScale);
//縮放帽子
resize(hatScale, hatScale, Size(), scale, scale);
//imwrite("F:\\HappyNewYear\\hatImg_new.png", hatScale);
 
//人臉正中位置坐標
int face_mid_x = face_info_list[best_index].face.left + faceWidth / 2;
int face_mid_y = face_info_list[best_index].face.top - hatScale.rows/5;

//帽子左上位置坐標
int hat_offset_x = face_mid_x - hatScale.cols / 2;
int hat_offset_y = face_mid_y - hatScale.rows / 2;

//調整，以免超出邊界
//x1 帽子左上角x坐標
//x2 帽子右上角x坐標
int x1 = max(hat_offset_x, 0
 
);
int x2 = min(hat_offset_x + hatScale.cols, im.cols);
//y1 帽子左上角y坐標
//y2 帽子右上角y坐標
int y1 = max(hat_offset_y, 0);
int y2 = min(hat_offset_y + hatScale.rows, im.rows);

//調整坐標
int hat_x1 = max(0, -hat_offset_x);
int hat_x2 = hat_x1 + x2 - x1;

int hat_y1 = max(0, -hat_offset_y);
int hat_y2 = hat_y1 + y2 - y1;    
Mat ROI = im(cv::Rect(x1, y1, hat_x2- hat_x1, hat_y2 - hat_y1));

 

channels.clear();
src_channels.clear();
Mat hatROI = hatScale(cv::Rect(hat_x1, hat_y1, hat_x2 - hat_x1, hat_y2 - hat_y1));
split(hatROI, channels);
split(ROI, src_channels);

for (int i=0;i<3;i++)
                    {
                        src_channels[i]= src_channels[i].mul(255.0 / 1.0 - channels[3], 1.0 / 255.0);
                        src_channels[i] += channels[i].mul(channels[3], 1.0 / 255.0);
                    }

                    merge(src_channels, ROI);

效果如下：

視頻檢測人臉添加帽子完美方案