我想要做的黃金是將矩陣從images1左側改爲右側。從我所知道的是,我們不能用基本的轉化方法來改變。如何將圖像從不規則矩形更改爲矩形?
image1. change matrix from left to right
真正的問題是,我有以下圖像中的矩形。我需要將不規則矩形更改爲常規矩形。
我想要做的黃金是將矩陣從images1左側改爲右側。從我所知道的是,我們不能用基本的轉化方法來改變。如何將圖像從不規則矩形更改爲矩形?
image1. change matrix from left to right
真正的問題是,我有以下圖像中的矩形。我需要將不規則矩形更改爲常規矩形。
所以,第一個問題是爲了角落。它們必須在兩個向量中都是相同的順序。因此,如果在第一個向量中,您的順序是:(左上角,左下角,右下角,右上角),它們必須在另一個向量中處於相同的順序。
其次,要生成的圖像只包含感興趣的對象,您必須將其寬度和高度設置爲與生成的矩形寬度和高度相同。別擔心,warpPerspective中的src和dst圖片可能大小不同。
三,性能問題。雖然你的方法是絕對準確的,因爲你只用仿射變換(旋轉,調整大小,去偏斜),在數學上,你可以使用函數的仿射函數。他們要快得多。
getAffineTransform() warpAffine().
重要提示:getAffine變換的需要和期望只有3分,結果矩陣是2×3,而不是3×3。
如何使結果圖像有不同的大小比輸入:
cv::warpPerspective(src, dst, dst.size(), ...);
use
cv::Mat rotated;
cv::Size size(box.boundingRect().width, box.boundingRect().height);
cv::warpPerspective(src, dst, size, ...);
所以你在這裏,和你的編程任務已經結束了。
void main()
{
cv::Mat src = cv::imread("r8fmh.jpg", 1);
// After some magical procedure, these are points detect that represent
// the corners of the paper in the picture:
// [408, 69] [72, 2186] [1584, 2426] [1912, 291]
vector<Point> not_a_rect_shape;
not_a_rect_shape.push_back(Point(408, 69));
not_a_rect_shape.push_back(Point(72, 2186));
not_a_rect_shape.push_back(Point(1584, 2426));
not_a_rect_shape.push_back(Point(1912, 291));
// For debugging purposes, draw green lines connecting those points
// and save it on disk
const Point* point = ¬_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;
Point2f pts[4];
box.points(pts);
// 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?
cv::Point2f src_vertices[3];
src_vertices[0] = pts[0];
src_vertices[1] = pts[1];
src_vertices[2] = pts[3];
//src_vertices[3] = not_a_rect_shape[3];
Point2f dst_vertices[3];
dst_vertices[0] = Point(0, 0);
dst_vertices[1] = Point(box.boundingRect().width-1, 0);
dst_vertices[2] = Point(0, box.boundingRect().height-1);
Mat warpAffineMatrix = getAffineTransform(src_vertices, dst_vertices);
cv::Mat rotated;
cv::Size size(box.boundingRect().width, box.boundingRect().height);
warpAffine(src, rotated, warpAffineMatrix, size, INTER_LINEAR, BORDER_CONSTANT);
imwrite("rotated.jpg", rotated);
}
查看http://stackoverflow.com/a/37381666/5294258 – sturkmen
這也許可以幫助你:[鏈接](http://stackoverflow.com/questions/7838487/executing-cvwarpperspective-for-a-fake-deskewing-on-a-set-of-cvpoint) – s1h
@ s1h非常感謝你。 [鏈接](http://stackoverflow.com/questions/7838487/executing-cvwarpperspective-for-a-fake-deskewing-on-a-set-of-cvpoint)是我的答案。 –