ChatGPT解决这个技术问题 Extra ChatGPT

Executing cv::warpPerspective for a fake deskewing on a set of cv::Point

I'm trying to do a perspective transformation of a set of points in order to achieve a deskewing effect:

http://nuigroup.com/?ACT=28&fid=27&aid=1892_H6eNAaign4Mrnn30Au8d

I'm using the image below for tests, and the green rectangle display the area of interest.

https://i.stack.imgur.com/r8fmh.jpg

I was wondering if it's possible to achieve the effect I'm hoping for using a simple combination of cv::getPerspectiveTransform and cv::warpPerspective. I'm sharing the source code I've written so far, but it doesn't work. This is the resulting image:

https://i.stack.imgur.com/206aG.jpg

So there is a vector<cv::Point> that defines the region of interest, but the points are not stored in any particular order inside the vector, and that's something I can't change in the detection procedure. Anyway, later, the points in the vector are used to define a RotatedRect, which in turn is used to assemble cv::Point2f src_vertices[4];, one of the variables required by cv::getPerspectiveTransform().

My understanding about vertices and how they are organized might be one of the issues. I also think that using a RotatedRect is not the best idea to store the original points of the ROI, since the coordinates will change a little bit to fit into the rotated rectangle, and that's not very cool.

#include <cv.h>
#include <highgui.h>
#include <iostream>

using namespace std;
using namespace cv;

int main(int argc, char* argv[])
{
    cv::Mat src = cv::imread(argv[1], 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 = &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?
    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(0, box.boundingRect().width-1);
    dst_vertices[2] = Point(0, box.boundingRect().height-1);
    dst_vertices[3] = Point(box.boundingRect().width-1, box.boundingRect().height-1);

    Mat warpMatrix = getPerspectiveTransform(src_vertices, dst_vertices);

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

    imwrite("rotated.jpg", rotated);

    return 0;
}

Can someone help me fix this problem?

can you share your magical procedure... for points detect that represent the corners of the paper in the picture, May be it helps me or others?
I've done it here, don't forget to up vote.
Hi can u plz tll me how can i mke ur magical procedure workable for the white paper which is on white color desk ...(i mean how to detect object which has somewhat similar background not exact bt its nt contrast ....it wud b help full if u share smething for ths issue ...
Hello, I don't know. There has to be some contrast between the paper & background for any detection to work. But you can investigate detecting sudoku squares and see if that brings you any ideas. Good luck!
well thnks for the gr8 help :)

k
karlphillip

So, first problem is corner order. They must be in the same order in both vectors. So, if in the first vector your order is:(top-left, bottom-left, bottom-right, top-right) , they MUST be in the same order in the other vector.

Second, to have the resulting image contain only the object of interest, you must set its width and height to be the same as resulting rectangle width and height. Do not worry, the src and dst images in warpPerspective can be different sizes.

Third, a performance concern. While your method is absolutely accurate, because you are doing only affine transforms (rotate, resize, deskew), mathematically, you can use the affine corespondent of your functions. They are much faster.

getAffineTransform()

warpAffine().

Important note: getAffine transform needs and expects ONLY 3 points, and the result matrix is 2-by-3, instead of 3-by-3.

How to make the result image have a different size than the input:

cv::warpPerspective(src, dst, dst.size(), ... );

use

cv::Mat rotated;
cv::Size size(box.boundingRect().width, box.boundingRect().height);
cv::warpPerspective(src, dst, size, ... );

So here you are, and your programming assignment is over.

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 = &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;

    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 warpMatrix = getPerspectiveTransform(src_vertices, dst_vertices);

    cv::Mat rotated;
    cv::Size size(box.boundingRect().width, box.boundingRect().height);
    warpPerspective(src, rotated, warpMatrix, size, INTER_LINEAR, BORDER_CONSTANT);*/
    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);
}

The code automatically reorders the points, which is a mush-have, but you will see the image is upside-down. The solution is the correct combination of points here ` src_vertices[0] = pts[0]; src_vertices[1] = pts[1]; src_vertices[2] = pts[3];`
One property of an affine transformation is: parallel lines remain parallel. In this cases this does not hold. AD is parallel to BC in the end only. So this isn't an affine transform, isn't it?
It's perspective transform, not affine. Affine transforms are a subset of perspective transforms, and have a number of special properties, one of them being the one you mentioned
@sammy: Isn't this prone to not keeping the aspect ratio of the isolated object when corrected? I see you use the width/height of the bounding box as the destination for the transform. So a more skew image of the isolated object would yield aspect-ratio distortions in the resulting image, yes?
k
karlphillip

The problem was the order in which the points were declared inside the vector, and then there was also another issue related to this on the definition of dst_vertices.

The order of the points matter to getPerspectiveTransform() and must be specified in the following order:

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

Therefore, the points of origin needed to be re-ordered to this:

vector<Point> not_a_rect_shape;
not_a_rect_shape.push_back(Point(408, 69));
not_a_rect_shape.push_back(Point(1912, 291));
not_a_rect_shape.push_back(Point(72, 2186));
not_a_rect_shape.push_back(Point(1584, 2426));

and the destination:

Point2f dst_vertices[4];
dst_vertices[0] = Point(0, 0);
dst_vertices[1] = Point(box.boundingRect().width-1, 0); // Bug was: had mistakenly switched these 2 parameters
dst_vertices[2] = Point(0, box.boundingRect().height-1);
dst_vertices[3] = Point(box.boundingRect().width-1, box.boundingRect().height-1);

After this, some cropping need to be done because the resulting image is not just the area within the green rectangle as I thought it would be:

https://i.stack.imgur.com/8qInG.jpg

I don't know if this is a bug of OpenCV or if I'm missing something, but the main issue has been solved.


how I find the corner of paper? ( I already draw lines around rectangle.. already following your answer in stack overflow)I am struggling with find the corner of the paper and crop it. Now I have coordinates rectangle x:507 y:418 1776x1372 when i use cout<< According to your answer. I am doing right? So please provide the way how to determine the corners of paper.
I wish I could upvote this more than once! After hours of pain my document scans beautifully. Thanks
I just came back and had to re-use this for a new Xamarin project!
@Bijington Glad to hear!
C
Community

When working with a quadrangle, OpenCV isn't really your friend. RotatedRect will give you incorrect results. Also you will need a perspective projection instead of a affine projection like others mentioned here..

Basicly what must been done is:

Loop through all polygon segments and connect those which are almost equel.

Sort them so you have the 4 most largest line segments.

Intersect those lines and you have the 4 most likely corner points.

Transform the matrix over the perspective gathered from the corner points and the aspect ratio of the known object.

I implemented a class Quadrangle which takes care of contour to quadrangle conversion and will also transform it over the right perspective.

See a working implementation here: Java OpenCV deskewing a contour


V
VaporwareWolf

UPDATE: RESOLVED

I almost have this working. So close to being usable. It deskews properly but I seem to have a scale or translate issue. I have set the anchor point to zero and also experimented with changing the scale mode (aspectFill, scale to fit, etc...).

https://i.stack.imgur.com/MwFuP.png

https://i.stack.imgur.com/a43LC.png

https://i.stack.imgur.com/RXZAG.png

This is not as simple as translate by -0.5, -0.5 because the original image become a polygon that stretches out very very far (potentially), so it's bounding rect is much bigger than the screen frame.

Does anyone see what I can do to get this wrapped up? I'd like to get it committed and share it here. This is a popular topic but I haven't found a solution that's as simple as copy/paste.

Full source code is here:

git clone https://github.com/zakkhoyt/Quadrilateral.git

git checkout demo

However, I'll paste the relevant parts here. This first method is mine and is where I get the deskew points.

- (IBAction)buttonAction:(id)sender {

    Quadrilateral quadFrom;
    float scale = 1.0;
    quadFrom.topLeft.x = self.topLeftView.center.x / scale;
    quadFrom.topLeft.y = self.topLeftView.center.y / scale;
    quadFrom.topRight.x = self.topRightView.center.x / scale;
    quadFrom.topRight.y = self.topRightView.center.y / scale;
    quadFrom.bottomLeft.x = self.bottomLeftView.center.x / scale;
    quadFrom.bottomLeft.y = self.bottomLeftView.center.y / scale;
    quadFrom.bottomRight.x = self.bottomRightView.center.x / scale;
    quadFrom.bottomRight.y = self.bottomRightView.center.y / scale;

    Quadrilateral quadTo;
    quadTo.topLeft.x = self.view.bounds.origin.x;
    quadTo.topLeft.y = self.view.bounds.origin.y;
    quadTo.topRight.x = self.view.bounds.origin.x + self.view.bounds.size.width;
    quadTo.topRight.y = self.view.bounds.origin.y;
    quadTo.bottomLeft.x = self.view.bounds.origin.x;
    quadTo.bottomLeft.y = self.view.bounds.origin.y + self.view.bounds.size.height;
    quadTo.bottomRight.x = self.view.bounds.origin.x + self.view.bounds.size.width;
    quadTo.bottomRight.y = self.view.bounds.origin.y + self.view.bounds.size.height;

    CATransform3D t = [self transformQuadrilateral:quadFrom toQuadrilateral:quadTo];
//    t = CATransform3DScale(t, 0.5, 0.5, 1.0);
    self.imageView.layer.anchorPoint = CGPointZero;
    [UIView animateWithDuration:1.0 animations:^{
        self.imageView.layer.transform = t;
    }];

}


#pragma mark OpenCV stuff...
-(CATransform3D)transformQuadrilateral:(Quadrilateral)origin toQuadrilateral:(Quadrilateral)destination {

    CvPoint2D32f *cvsrc = [self openCVMatrixWithQuadrilateral:origin];
    CvMat *src_mat = cvCreateMat( 4, 2, CV_32FC1 );
    cvSetData(src_mat, cvsrc, sizeof(CvPoint2D32f));


    CvPoint2D32f *cvdst = [self openCVMatrixWithQuadrilateral:destination];
    CvMat *dst_mat = cvCreateMat( 4, 2, CV_32FC1 );
    cvSetData(dst_mat, cvdst, sizeof(CvPoint2D32f));

    CvMat *H = cvCreateMat(3,3,CV_32FC1);
    cvFindHomography(src_mat, dst_mat, H);
    cvReleaseMat(&src_mat);
    cvReleaseMat(&dst_mat);

    CATransform3D transform = [self transform3DWithCMatrix:H->data.fl];
    cvReleaseMat(&H);

    return transform;
}

- (CvPoint2D32f*)openCVMatrixWithQuadrilateral:(Quadrilateral)origin {

    CvPoint2D32f *cvsrc = (CvPoint2D32f *)malloc(4*sizeof(CvPoint2D32f));
    cvsrc[0].x = origin.topLeft.x;
    cvsrc[0].y = origin.topLeft.y;
    cvsrc[1].x = origin.topRight.x;
    cvsrc[1].y = origin.topRight.y;
    cvsrc[2].x = origin.bottomRight.x;
    cvsrc[2].y = origin.bottomRight.y;
    cvsrc[3].x = origin.bottomLeft.x;
    cvsrc[3].y = origin.bottomLeft.y;

    return cvsrc;
}

-(CATransform3D)transform3DWithCMatrix:(float *)matrix {
    CATransform3D transform = CATransform3DIdentity;

    transform.m11 = matrix[0];
    transform.m21 = matrix[1];
    transform.m41 = matrix[2];

    transform.m12 = matrix[3];
    transform.m22 = matrix[4];
    transform.m42 = matrix[5];

    transform.m14 = matrix[6];
    transform.m24 = matrix[7];
    transform.m44 = matrix[8];

    return transform; 
}

Update: I got it working properly. The coordinates needed to be origin in the center, not the upperleft. I applied xOffset and yOffset and viola. Demo code at the location mentioned above ("demo" branch)


Thanks for the sample code! Helped me solve similar problem. I ended up using getPerspectiveTransform instead of FindHomography and TopLeft rather than ScaleToFit for content mode.
I'm glad I could help you. I'd love to see your code. If it's open please share.
Please find simplified sample code in separate answer.
C
Community

I got the same kind of issue and fixed it using OpenCV's homography extraction function.

You can see how I did in this question: Transforming a rectangle image into a quadrilateral using a CATransform3D


B
Bjørn Egil

Very much inspired by @VaporwareWolf's answer, implemented in C# using Xamarin MonoTouch for iOS. The main difference is that I'm using GetPerspectiveTransform instead of FindHomography and TopLeft rather than ScaleToFit for content mode:

    void SetupWarpedImage(UIImage sourceImage, Quad sourceQuad, RectangleF destRectangle)
    {
        var imageContainerView = new UIView(destRectangle)
        {
            ClipsToBounds = true,
            ContentMode = UIViewContentMode.TopLeft
        };

        InsertSubview(imageContainerView, 0);

        var imageView = new UIImageView(imageContainerView.Bounds)
        {
            ContentMode = UIViewContentMode.TopLeft,
            Image = sourceImage
        };

        var offset = new PointF(-imageView.Bounds.Width / 2, -imageView.Bounds.Height / 2);
        var dest = imageView.Bounds;
        dest.Offset(offset);
        var destQuad = dest.ToQuad();

        var transformMatrix = Quad.GeneratePerspectiveTransformMatrixFromQuad(sourceQuad, destQuad);
        CATransform3D transform = transformMatrix.ToCATransform3D();

        imageView.Layer.AnchorPoint = new PointF(0f, 0f);
        imageView.Layer.Transform = transform;

        imageContainerView.Add(imageView);
    }

Where is ToCATransform3D defined?
@Geoff, is just from my implementation: public static CATransform3D ToCATransform3D( this DoubleMatrix matrix) { CATransform3D transform = CATransform3D.Identity; transform.m11 = (float)matrix[0,0]; transform.m21 = (float)matrix[0,1]; transform.m41 = (float)matrix[0,2]; transform.m12 = (float)matrix[1,0]; transform.m22 = (float)matrix[1,1]; transform.m42 = (float)matrix[1,2]; transform.m14 = (float)matrix[2,0]; transform.m24 = (float)matrix[2,1]; transform.m44 = (float)matrix[2,2]; return transform; } // Sorry about the poor formatting as comment