在圖片不被裁剪時opencv繞圖片中任意點旋轉任意角度

opencv繞圖片中任意角度旋轉任意角度

  最近在做專案需要把把圖片繞圖片中任意點旋轉任意角度，考慮到自己旋轉需要編寫插值演演算法，所以想到了用opencv，但是網上都是圍繞圖片中點旋轉任意角度的，都是向下面這樣寫的：

#include"opencv.hpp"
#include<iostream>
using namespace std;
using namespace cv;
int main() {
	Mat src = imread("timg.jpg");
	Mat des,m;
	Point2f center = Point(src.cols / 2, src.rows / 2);
	double angle = 50,scale=0.5;
	int w = src.cols, h = src.rows;
	int bound_w = (h * fabs(sin(angle * CV_PI / 180)) + w * fabs(cos(angle * CV_PI / 180))) * scale;
	int bound_h = (h * fabs(cos(angle * CV_PI / 180)) + w * fabs(sin(angle * CV_PI / 180))) * scale;
	m = getRotationMatrix2D(center, angle, scale);
	m.at<double>(0, 2) += (bound_w - src.cols) / 2;
	m.at<double>(1, 2) += (bound_h - src.rows) / 2;
	
	warpAffine(src,des,m,Size2i(bound_h,bound_w));
	imshow("image",des);
	waitKey();
	return 0;

旋轉之後的效果: 

但是遇到繞任意點旋轉時，會產生問題，用這種方式還是會存在裁剪，如果要理解繞任意點旋轉，需要先理解函數getRotationMatrix2D，這個函數處理過程如下面矩陣表示所示：

具體實現程式碼如下：

    Mat src = imread("/home/sss/1111.jpg", IMREAD_GRAYSCALE);
    Mat des, m;
//旋轉的任意角度
    double angle = 45;
    int w = src.cols, h = src.rows;
    Point2f rorate_center;
//旋轉的任意中心
    rorate_center.x = w;
    rorate_center.y = h;
//重新計算旋轉後的寬和高
    int bound_w = ceil(h * fabs(sin(angle * CV_PI / 180.0)) + w * fabs(cos(angle * CV_PI / 180.0)));
    int bound_h = ceil(h * fabs(cos(angle * CV_PI / 180.0)) + w * fabs(sin(angle * CV_PI / 180.0)));
    m = getRotationMatrix2D(rorate_center, angle, 1.0);

//通過eigen計算旋轉矩陣
    Eigen::Matrix3d T1;
    T1 << 1, 0, -rorate_center.x,
            0, 1, -rorate_center.y,
            0, 0, 1;
    Eigen::Matrix3d T2;
    T2 <<   1, 0, rorate_center.x,
            0, 1, rorate_center.y,
            0, 0, 1;
    Eigen::Matrix3d rorate;
    rorate << cos(angle * CV_PI / 180.0), sin(angle * CV_PI / 180.0), 0,
            -sin(angle * CV_PI / 180.0), cos(angle * CV_PI / 180.0), 0,
            0, 0, 1;
    Eigen::Matrix3d T = T2 * rorate * T1;
//計算原來矩陣的四個頂點經過變換後的頂點
    Eigen::Matrix<double,3, 1> left_top_p, right_top_p, right_bottom_p, left_botoom_p;
    left_top_p << 0, 0, 1;
    right_top_p << w, 0, 1;
    right_bottom_p << w, h, 1;
    left_botoom_p << 0, h , 1;
    left_top_p = T * left_top_p;
    right_top_p = T * right_top_p;
    right_bottom_p = T * right_bottom_p;
    left_botoom_p = T * left_botoom_p;

//找到經過變換過定位的最大最小值
    double min_x = 10000, min_y = 10000;
    //min_x
    if(left_top_p[0] < min_x){
        min_x = left_top_p[0];
    }
    if(right_top_p[0] < min_x){
        min_x = right_top_p[0];
    }
    if(right_bottom_p[0] < min_x)
    {
        min_x = right_bottom_p[0];
    }
    if(left_botoom_p[0] < min_x){
        min_x = left_botoom_p[0];
    }

    //min_y
    if(left_top_p[1] < min_y){
        min_y = left_top_p[1];
    }
    if(right_top_p[1] < min_y){
        min_y = right_top_p[1];
    }
    if(right_bottom_p[1] < min_y)
    {
        min_y = right_bottom_p[1];
    }
    if(left_botoom_p[1] < min_y){
        min_y = left_botoom_p[1];
    }

    double max_x = -1000, max_y = -1000;
    //max_x
    if(left_top_p[0] > max_x){
        max_x = left_top_p[0];
    }
    if(right_top_p[0] > max_x){
        max_x = right_top_p[0];
    }
    if(right_bottom_p[0] > max_x)
    {
        max_x = right_bottom_p[0];
    }
    if(left_botoom_p[0] > max_x){
        max_x = left_botoom_p[0];
    }

    //max_y
    if(left_top_p[1] > max_y){
        max_y = left_top_p[1];
    }
    if(right_top_p[1] > max_y){
        max_y = right_top_p[1];
    }
    if(right_bottom_p[1] > max_y)
    {
        max_y = right_bottom_p[1];
    }
    if(left_botoom_p[1] > max_y){
        max_y = left_botoom_p[1];
    }

    //將偏置新增到矩陣中
    m.at<double>(0, 2) += -min_x;
    m.at<double>(1, 2) += -min_y;

//變換，最後不會存在裁剪
    warpAffine(src, des , m , Size2i(bound_w , bound_h),
               INTER_LINEAR, 0, Scalar(100, 100, 100));
    imwrite("/home/sss/222.jpg", des);
    return 0;

經過變換過的圖片不會存在裁剪：