i have this image
i want to create a tranigle mask to get only this zone
but with the following code i get this result
Moments mu = moments(red,true);
Point center;
center.x = mu.m10 / mu.m00;
center.y = mu.m01 / mu.m00;
circle(red, center, 2, Scalar(0, 0, 255));
cv::Size sz = red.size();
int imageWidth = sz.width;
int imageHeight = sz.height;
Mat mask3(red.size(), CV_8UC1, Scalar::all(0));
// Create Polygon from vertices
vector<Point> ptmask3(3);
ptmask3.push_back(Point(imageHeight-1, imageWidth-1));
ptmask3.push_back(Point(center.x, center.y));
ptmask3.push_back(Point(0, red.rows - 1));
vector<Point> pt;
approxPolyDP(ptmask3, pt, 1.0, true);
// Fill polygon white
fillConvexPoly(mask3, &pt[0], pt.size(), 255, 8, 0);
// Create new image for result storage
Mat hide3(red.size(), CV_8UC3);
// Cut out ROI and store it in imageDest
red.copyTo(hide3, mask3);
imshow("mask3", hide3);
Updated Version (with the Help of Dan MaĊĦek)
Your Triangle is wrong
This is because you're initializing the vector with size 3, then putting another three points into it, for a total of 6 points of which three have default values. Try this instead:
vector<Point> ptmask3;
Also, make sure that the coordinates of the points are correct. You'll want to have a point in the bottom left corner, but it doesn't seem like your current triangle has one like that.
Your image is gray
You need to initialize hide3 properly, like this:
cv::Mat hide3(img.size(), CV_8UC3, cv::Scalar(0));
Related
My goal is to create yield maps using OpenCV. These yield maps need to be built with coloured rectangles to indicate yield. An example of a Mat built by rectangles here.
So is it possible to create a cv::Mat with coloured rectangles? The amount of rectangles isn't constant, thus changes with every use.
To make the question clear: if I have 4 boxes (2x2 grid) I want to automatically make a Mat which is as big as the 4 boxes. If I have 16 boxes (4x4 grid) I want to make a Mat which is as big as the 16 boxes.
I couldn't find a way to make it work, so I hope somebody here knows if it is possible.
If somebody can help me that would be great, if it is not possible alternatives are also welcome! Thanks
Some info:
OpenCV version:4.5.3
OS: Ubuntu 20.04
Language: C++
You can create rectangle with OpenCV function.
Basic Geometric Drawing OpenCV
int x = 0;
int y = 0;
int width = 10;
int height = 20;
// our rectangle...
cv::Rect rect(x, y, width, height);
// and its top left corner...
cv::Point pt1(x, y);
// and its bottom right corner.
cv::Point pt2(x + width, y + height);
// These two calls...
cv::rectangle(img, pt1, pt2, cv::Scalar(0, 255, 0));
// essentially do the same thing
cv::rectangle(img, rect, cv::Scalar(0, 255, 0))
ref
OpenCV has cv::hconcat and cv::vconcat. Use them like numpy's hstack/vstack.
make sure your parts have the same type (and number of channels).
The documentation has a code example.
cv::Mat matArray[] = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)),
cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)),
cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),};
cv::Mat out;
cv::hconcat( matArray, 3, out );
//out:
//[1, 2, 3;
// 1, 2, 3;
// 1, 2, 3;
// 1, 2, 3]
How can I crop a non rectangular region from image?
Imagine I have four points and I want to crop it, this shape wouldn't be a triangle somehow!
For example I have the following image :
and I want to crop this from image :
How can I do this?
regards..
The procedure for cropping an arbitrary quadrilateral (or any polygon for that matter) part of an image is summed us as:
Generate a "mask". The mask is black where you want to keep the image, and white where you don't want to keep it
Compute the "bitwise_and" between your input image and the mask
So, lets assume you have an image. Throughout this I'll use an image size of 30x30 for simplicity, you can change this to suit your use case.
cv::Mat source_image = cv::imread("filename.txt");
And you have four points you want to use as the corners:
cv::Point corners[1][4];
corners[0][0] = Point( 10, 10 );
corners[0][1] = Point( 20, 20 );
corners[0][2] = Point( 30, 10 );
corners[0][3] = Point( 20, 10 );
const Point* corner_list[1] = { corners[0] };
You can use the function cv::fillPoly to draw this shape on a mask:
int num_points = 4;
int num_polygons = 1;
int line_type = 8;
cv::Mat mask(30,30,CV_8UC3, cv::Scalar(0,0,0));
cv::fillPoly( mask, corner_list, &num_points, num_polygons, cv::Scalar( 255, 255, 255 ), line_type);
Then simply compute the bitwise_and of the image and mask:
cv::Mat result;
cv::bitwise_and(source_image, mask, result);
result now has the cropped image in it. If you want the edges to end up white instead of black you could instead do:
cv::Mat result_white(30,30,CV_8UC3, cv::Scalar(255,255,255));
cv::bitwise_and(source_image, mask, result_white, mask);
In this case we use bitwise_and's mask parameter to only do the bitwise_and inside the mask. See this tutorial for more information and links to all the functions I mentioned.
You may use cv::Mat::copyTo() like this:
cv::Mat img = cv::imread("image.jpeg");
// note mask may be single channel, even if img is multichannel
cv::Mat mask = cv::Mat::zeros(img.rows, img.cols, CV_8UC1);
// fill mask with nonzero values, e.g. as Tim suggests
// cv::fillPoly(...)
cv::Mat result(img.size(), img.type(), cv::Scalar(255, 255, 255));
img.copyTo(result, mask);
I'm playing around with OpenCV and I want to know how you would build a simple version of a perspective transform program. I have a image of a parallelogram and each corner of it consists of a pixel with a specific color, which is nowhere else in the image. I want to iterate through all pixels and find these 4 pixels. Then I want to use them as corner points in a new image in order to warp the perspective of the original image. In the end I should have a zoomed on square.
Point2f src[4]; //Is this the right datatype to use here?
int lineNumber=0;
//iterating through the pixels
for(int y = 0; y < image.rows; y++)
{
for(int x = 0; x < image.cols; x++)
{
Vec3b colour = image.at<Vec3b>(Point(x, y));
if(color.val[1]==245 && color.val[2]==111 && color.val[0]==10) {
src[lineNumber]=this pixel // something like Point2f(x,y) I guess
lineNumber++;
}
}
}
/* I also need to get the dst points for getPerspectiveTransform
and afterwards warpPerspective, how do I get those? Take the other
points, check the biggest distance somehow and use it as the maxlength to calculate
the rest? */
How should you use OpenCV in order to solve the problem? (I just guess I'm not doing it the "normal and clever way") Also how do I do the next step, which would be using more than one pixel as a "marker" and calculate the average point in the middle of multiple points. Is there something more efficient than running through each pixel?
Something like this basically:
Starting from an image with colored circles as markers, like:
Note that is a png image, i.e. with a loss-less compression which preserves the actual color. If you use a lossy compression like jpeg the colors will change a little, and you cannot segment them with an exact match, as done here.
You need to find the center of each marker.
Segment the (known) color, using inRange
Find all connected components with the given color, with findContours
Find the largest blob, here done with max_element with a lambda function, and distance. You can use a for loop for this.
Find the center of mass of the largest blob, here done with moments. You can use a loop also here, eventually.
Add the center to your source vertices.
Your destination vertices are just the four corners of the destination image.
You can then use getPerspectiveTransform and warpPerspective to find and apply the warping.
The resulting image is:
Code:
#include <opencv2/opencv.hpp>
#include <vector>
#include <algorithm>
using namespace std;
using namespace cv;
int main()
{
// Load image
Mat3b img = imread("path_to_image");
// Create a black output image
Mat3b out(300,300,Vec3b(0,0,0));
// The color of your markers, in order
vector<Scalar> colors{ Scalar(0, 0, 255), Scalar(0, 255, 0), Scalar(255, 0, 0), Scalar(0, 255, 255) }; // red, green, blue, yellow
vector<Point2f> src_vertices(colors.size());
vector<Point2f> dst_vertices = { Point2f(0, 0), Point2f(0, out.rows - 1), Point2f(out.cols - 1, out.rows - 1), Point2f(out.cols - 1, 0) };
for (int idx_color = 0; idx_color < colors.size(); ++idx_color)
{
// Detect color
Mat1b mask;
inRange(img, colors[idx_color], colors[idx_color], mask);
// Find connected components
vector<vector<Point>> contours;
findContours(mask, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
// Find largest
int idx_largest = distance(contours.begin(), max_element(contours.begin(), contours.end(), [](const vector<Point>& lhs, const vector<Point>& rhs) {
return lhs.size() < rhs.size();
}));
// Find centroid of largest component
Moments m = moments(contours[idx_largest]);
Point2f center(m.m10 / m.m00, m.m01 / m.m00);
// Found marker center, add to source vertices
src_vertices[idx_color] = center;
}
// Find transformation
Mat M = getPerspectiveTransform(src_vertices, dst_vertices);
// Apply transformation
warpPerspective(img, out, M, out.size());
imshow("Image", img);
imshow("Warped", out);
waitKey();
return 0;
}
Let's say i have the following image:
And my region of interest looks like this:
And i want to have the following result:
How can i achieve this knowing that the ROI is denoted by four points:
Point pt1(129,9);
Point pt2(284,108);
Point pt3(223,205);
Point pt4(67,106);
The idea is to use fillPoly() to fill all the pixels inside the rotated-rectangle/polygon to 0, 255 otherwise:
Mat mask = cv::Mat(img.size(), CV_8UC1, Scalar(255)); // suppose img is your image Mat
vector<vector<Point>> pts = { { pt1, pt2, pt3, pt4 } };
fillPoly(mask, pts, Scalar(0)); // <- do it here
I have the following problem. I'm searching for eyes within an image using HaarClassifiers. Due to the rotation of the head I'm trying to find eyes within different angles. For that, I rotate the image by different angles. For rotating the frame, I use the code (written in C++):
Point2i rotCenter;
rotCenter.x = scaledFrame.cols / 2;
rotCenter.y = scaledFrame.rows / 2;
Mat rotationMatrix = getRotationMatrix2D(rotCenter, angle, 1);
warpAffine(scaledFrame, scaledFrame, rotationMatrix, Size(scaledFrame.cols, scaledFrame.rows));
This works fine and I am able to extract two ROI Rectangles for the eyes. So, I have the top/left coordinates of each ROI as well as their width and height. However, these coordinates are the coordinates in the rotated image. I don't know how I can backproject this rectangle onto the original frame.
Assuming I have the obtaind eye pair rois for the unscaled frame (full_image), but still roated.
eye0_roi and eye1_roi
How can I rotate them back, such that they map their correct position?
Best regards,
Andre
You can use the invertAffineTransform to get the inverse matrix and use this matrix to rotate point back:
Mat RotateImg(const Mat& img, double angle, Mat& invertMat)
{
Point center = Point( img.cols/2, img.rows/2);
double scale = 1;
Mat warpMat = getRotationMatrix2D( center, angle, scale );
Mat dst = Mat(img.size(), CV_8U, Scalar(128));
warpAffine( img, dst, warpMat, img.size(), 1, 0, Scalar(255, 255, 255));
invertAffineTransform(warpMat, invertMat);
return dst;
}
Point RotateBackPoint(const Point& dstPoint, const Mat& invertMat)
{
cv::Point orgPoint;
orgPoint.x = invertMat.at<double>(0,0)*dstPoint.x + invertMat.at<double>(0,1)*dstPoint.y + invertMat.at<double>(0,2);
orgPoint.y = invertMat.at<double>(1,0)*dstPoint.x + invertMat.at<double>(1,1)*dstPoint.y + invertMat.at<double>(1,2);
return orgPoint;
}