warpperspective 透视变化的opencv实现

warpperspective 透视变化的opencv2.0实现

1st-------2nd | | | | | |3rd-------4th

原始代码

              cv::Mat src= cv::imread( "c://03p.jpg" ,0);

                 if (!src.data)

                                 return 0;

                  vector<Point> not_a_rect_shape;

                not_a_rect_shape.push_back(Point(122,0));

                not_a_rect_shape.push_back(Point(814,0));

                not_a_rect_shape.push_back(Point(22,540));

                not_a_rect_shape.push_back(Point(910,540));

                 // For debugging purposes, draw green lines connecting those points

                 // and save it on disk

                 const Point* point = &not_a_rect_shape[0];

                 int n = ( int )not_a_rect_shape.size();

                Mat draw = src.clone();

                polylines(draw, &point, &n, 1, true , Scalar(0, 255, 0), 3, CV_AA);

                imwrite( "draw.jpg" , draw);

                 // Assemble a rotated rectangle out of that info

                RotatedRect box = minAreaRect(cv::Mat(not_a_rect_shape));

                std::cout << "Rotated box set to (" << box.boundingRect().x << "," << box.boundingRect().y << ") " << box.size.width << "x" << box.size.height << std::endl;

                 // Does the order of the points matter? I assume they do NOT.

                 // But if it does, is there an easy way to identify and order

                 // them as topLeft, topRight, bottomRight, bottomLeft?

                 //(0,0) (960,0) (0,540) (960,540)

                cv::Point2f src_vertices[4];

                src_vertices[0] = not_a_rect_shape[0];

                src_vertices[1] = not_a_rect_shape[1];

                src_vertices[2] = not_a_rect_shape[2];

                src_vertices[3] = not_a_rect_shape[3];

                Point2f dst_vertices[4];

                dst_vertices[0] = Point(0, 0);

                dst_vertices[1] = Point(960,0);

                dst_vertices[2] = Point(0,540);

                dst_vertices[3] = Point(960,540);

                Mat warpMatrix = getPerspectiveTransform(src_vertices, dst_vertices);

                cv::Mat rotated;

                warpPerspective(src, rotated, warpMatrix, rotated.size(), INTER_LINEAR, BORDER_CONSTANT);

                 // Display the image

                cv::namedWindow( "Original Image" );

                cv::imshow( "Original Image" ,src);

                cv::namedWindow( "warp perspective" );

                cv::imshow( "warp perspective" ,rotated);

                imwrite( "03p.jpg" ,src);

                cv::waitKey();

                 return 0;

结果基本是出来了，下一步就是要将其和现有的代码结合起来。

=====================================================2020年4月23日20:25:54===========================================添加Python版本的实现=======================

import cv2

import numpy  as np

src = cv2.imread( "e:/template/steel03.jpg")

rows,cols,ch = src.shape

pts1 = np.float32([[ 122, 0],[ 814, 0],[ 22, 540],[ 910, 540]])

pts2 = np.float32([[ 0, 0],[ 960, 0],[ 0, 540],[ 960, 540]])

M = cv2.getPerspectiveTransform(pts1,pts2)

dst = cv2.warpPerspective(src,M,(cols,rows))

cv2.imshow( "src",dst)

cv2.waitKey( 0)

来自为知笔记(Wiz)