快速梯形到矩形视频 [英] Fast Trapezoid to Rectangle for Video

问题描述

我想将一个梯形区域转换成一个矩形。
示例图片（不完美的梯形，但你得到的想法）：

I want to transform a trapezoid area into a rectangle. Example Picture (not perfectly trapezoid, but you get the idea):

到这里：

to this:

我已经可以标记梯形区域的角，并使用 getPerspectiveTransform 计算 warpPerspective 来转换图像。

I already can mark the corners of the trapezoid area and use getPerspectiveTransform to calculate the correct Matrix for warpPerspective to transform the image.

不幸的是，这种转换真的很慢。在720p网络摄像机流的约80％的面积上使用它导致〜5fps的下降。我怀疑这可能是因为warpPerspective允许更多的变换比我需要。

Unfortunately this transformation is really slow. Using it on ~80% of the area of a 720p webcam stream results in a drop to ~5fps. I suspect this might be because warpPerspective allows more transformation than i need.

有一个更快的方法将图像从梯形变换到矩形？ （最好使用OpenCV）

Is there a faster way to transform an image from a trapezoid to a rectangle? (preferably using OpenCV)

详情：

• warpAffine 可用于进行仿射变换。


• 有些相关，但没有答案：菱形到矩形

• warpAffine can be used to make affine transformations. It is faster than warpPerspective, but (if i got it correctly) you can only change the angle of a Parallelogramm.
• Somewhat related but without an answer: Trapezoid to Rectangle

A最低工作示例（不完全工作）基于AldurDisciple使用我的帖子中的第一张图片的答案。

A Minimum Working Example (not fully working) based on the answer of AldurDisciple using the first picture in my post.

#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp>
#include "opencv2/opencv.hpp"
using namespace cv;
int main() {

    //Mat img = imread("EQ9in.png");
    Mat img = imread("C:\\ss819729\\Aufnahmen\\arbeiten\\EQ9in.png");
    int height = img.rows;
    int width = img.cols;

    vector<Point2f> corners_rectangle, corners_trapezoid;

    corners_rectangle.push_back(Point2f(0, 0));
    corners_rectangle.push_back(Point2f(img.cols, 0));
    corners_rectangle.push_back(Point2f(img.cols, img.rows));
    corners_rectangle.push_back(Point2f(0, img.rows));

    corners_trapezoid.push_back(Point2f(35, 6));
    corners_trapezoid.push_back(Point2f(419, 55));
    corners_trapezoid.push_back(Point2f(404, 44));
    corners_trapezoid.push_back(Point2f(10, 477));

    Mat_<float> H_rectangle_to_trapezoid = cv::getPerspectiveTransform(corners_rectangle, corners_trapezoid);

    cv::Mat_<float> mapx_32f(height, width), mapy_32f(height, width);
    for(int y = 0; y<height; ++y) {
        float *buff_mapx = ((float*) mapx_32f.data)+y*width;
        float *buff_mapy = ((float*) mapy_32f.data)+y*width;
        for(int x = 0; x<width; ++x) {
            cv::Mat_<float> pt(3, 1);
            pt(0) = x;
            pt(1) = y;
            pt(2) = 1;
            pt = H_rectangle_to_trapezoid*pt;
            pt /= pt(2);
            buff_mapx[x] = pt(0);
            buff_mapy[x] = pt(1);
        }
    }
    cv::Mat map1_16u, map2_16u;
    cv::convertMaps(mapx_32f, mapy_32f, map1_16u, map2_16u, CV_16SC2);

    cv::Mat img_rectified;
    cv::remap(img, img_rectified, map1_16u, map2_16u, cv::INTER_LINEAR);

    namedWindow("Rectangle Image", CV_WINDOW_AUTOSIZE);
    while(waitKey(1)!='q') {
        cv::remap(img, img_rectified, map1_16u, map2_16u, cv::INTER_LINEAR);
        imshow("Rectangle Image", img_rectified);
    }
    return 1;
}

推荐答案

，使用函数 remap （ warpPerspective ：//docs.opencv.org/modules/imgproc/doc/geometric_transformations.html？highlight = remap＃remaprel =nofollow>文档链接）。这个函数可以使用如下。

If the warping transformation is constant, there is a much faster way than using warpPerspective at each frame, using function remap (documentation link). This function can be used as follows.

首先，在程序开始时，计算包含（x，y） 源图像中每个像素的坐标：

First, at the begining of your program, compute the transformation maps, containing the (x,y) coordinates in source image for each pixel of the source image:

cv::Mat_<float> corners_rectangle, corners_trapezoid;
// TODO: fill corners_rectangle and corners_trapezoid
cv::Mat_<float> H_rectangle_to_trapezoid = cv::getPerspectiveTransform(corners_rectangle, corners_trapezoid);
cv::Mat_<float> mapx_32f(height,width), mapy_32f(height,width);
for(int y=0; y<height; ++y)
{
    float *buff_mapx=((float*)mapx_32f.data)+y*width;
    float *buff_mapy=((float*)mapy_32f.data)+y*width;
    for(int x=0; x<width; ++x)
    {
        cv::Mat_<float> pt(3,1);
        pt(0) = x;
        pt(1) = y;
        pt(2) = 1;
        pt = H_rectangle_to_trapezoid*pt;
        pt /= pt(2);
        buff_mapx[x] = pt(0);
        buff_mapy[x] = pt(1);
    }
}
cv::Mat map1_16u,map2_16u;
cv::convertMaps(mapx_32f,mapy_32f,map1_16u,map2_16u,CV_16SC2);
// Keep map1_16u & map2_16u, discard the rest

然后在每一帧，你只需要使用 remap 函数：

Then at each frame, you only need to do the interpolation using the remap function:

cv::Mat img_rectified;
cv::remap(img_src, img_rectified, map1_16u, map2_16u, cv::INTER_LINEAR);

由于坐标变换的计算是离线完成的，所以比使用 warpPerspective 。

Since the computation of the coordinate transformation is done offline, this is much faster than using warpPerspective repeatedly.

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