I would like to know how to draw semi-transparent shapes in OpenCV, similar to those in the image below (from http://tellthattomycamera.wordpress.com/)
I don't need those fancy circles, but I would like to be able to draw a rectangle, e.g, on a 3 channel color image and specify the transparency of the rectangle, something like
rectangle (img, Point (100,100), Point (300,300), Scalar (0,125,125,0.4), CV_FILLED);
where 0,125,125 is the color of the rectangle and 0.4 specifies the transparency.
However OpenCV doesn't have this functionality built into its drawing functions. How can I draw shapes in OpenCV so that the original image being drawn on is partially visible through the shape?
The image below illustrates transparency using OpenCV. You need to do an alpha blend between the image and the rectangle. Below is the code for one way to do this.
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
int main( int argc, char** argv )
{
cv::Mat image = cv::imread("IMG_2083s.png");
cv::Mat roi = image(cv::Rect(100, 100, 300, 300));
cv::Mat color(roi.size(), CV_8UC3, cv::Scalar(0, 125, 125));
double alpha = 0.3;
cv::addWeighted(color, alpha, roi, 1.0 - alpha , 0.0, roi);
cv::imshow("image",image);
cv::waitKey(0);
}
In OpenCV 3 this code worked for me:
cv::Mat source = cv::imread("IMG_2083s.png");
cv::Mat overlay;
double alpha = 0.3;
// copy the source image to an overlay
source.copyTo(overlay);
// draw a filled, yellow rectangle on the overlay copy
cv::rectangle(overlay, cv::Rect(100, 100, 300, 300), cv::Scalar(0, 125, 125), -1);
// blend the overlay with the source image
cv::addWeighted(overlay, alpha, source, 1 - alpha, 0, source);
Source/Inspired by: http://bistr-o-mathik.org/2012/06/13/simple-transparency-in-opencv/
Adding to Alexander Taubenkorb's answer, you can draw random (semi-transparent) shapes by replacing the cv::rectangle line with the shape you want to draw.
For example, if you want to draw a series of semi-transparent circles, you can do it as follows:
cv::Mat source = cv::imread("IMG_2083s.png"); // loading the source image
cv::Mat overlay; // declaring overlay matrix, we'll copy source image to this matrix
double alpha = 0.3; // defining opacity value, 0 means fully transparent, 1 means fully opaque
source.copyTo(overlay); // copying the source image to overlay matrix, we'll be drawing shapes on overlay matrix and we'll blend it with original image
// change this section to draw the shapes you want to draw
vector<Point>::const_iterator points_it; // declaring points iterator
for( points_it = circles.begin(); points_it != circles.end(); ++points_it ) // circles is a vector of points, containing center of each circle
circle(overlay, *points_it, 1, (0, 255, 255), -1); // drawing circles on overlay image
cv::addWeighted(overlay, alpha, source, 1 - alpha, 0, source); // blending the overlay (with alpha opacity) with the source image (with 1-alpha opacity)
For C++, I personally like the readability of overloaded operators for scalar multiplication and matrix addition:
... same initial lines as other answers above ...
// blend the overlay with the source image
source = source * (1.0 - alpha) + overlay * alpha;
Related
How is it possible to calculate the black / white ratio of the pixels inside the outline of a contour (not the bounding box)?
The image is pre-processed with cv::threshold(src, img, 0, 255, cv::THRESH_BINARY | cv::THRESH_OTSU); and then inverted img = 255 - img;
I look for the retangular outline of the table (contour) via cv::RETR_EXTERNAL.. I want to calculate the black pixels inside the contour
There can be other components in the image so I can't just count all non-zero pixels
This is the original image before binarized and inverted
I think there's some confusion about terminology. A contour is simply a sequence of points. If you draw them as a closed polygon (e.g. with cv::drawContours), all the points inside the polygon will be white.
You can however use this mask to count the white or black pixels on your thresholded image:
cv::Mat1b bw_image = ...
std::vector<std::vector<cv::Point>> contours;
cv::findContours(bw_image, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
for(size_t i=0; i<contours.size(); ++i)
{
cv::Mat1b contour_mask(bw_image.rows, bw_image.cols, uchar(0));
cv::drawContours(contour_mask, contours, i, Scalar(255), cv::FILLED);
int total_white_inside_contour = cv::countNonZero(mask);
int white_on_image_inside_contour = cv::countNonZero(bw_image & mask);
int black_on_image_inside_contour = total_white_inside_contour - white_on_image_inside_contour;
}
You cannot calculate the white and black ratio of a contour, because what is a contour? A group of white pixels which are connected which each other calls contour, so a contour does not contain any black pixel if it does, it calls hole inside the contour.
And also a contour does not have a specific shape.
So you can do it by Bounding Rectangle the rectangle around the contour then you will be to calculate the black and white ratio inside the rectangle.
I have jpg image and polygon which I want to use as mask in this way: image inside this polygon should be displayed, and all outside this polygon should be 100% transparent. Now I achieved only first goal - I can display image inside polygon, but all outside of it is black:
cv::Mat image;
//load image
image.convertTo(image, CV_8UC3, 255.0);
std::vector<cv::Point> contour;
//load polygon
const cv::Point* elementPoints[1] = { &contour[0] };
int numberOfPoints = (int)contour.size();
cv::Mat mask = cv::Mat::zeros(image.size(), image.type());
cv::fillPoly(mask, elementPoints, &numberOfPoints, 1, cv::Scalar( 255, 255, 255), 8);
cv::Mat dstImage = cv::Mat::zeros(image.size(), image.type());
cv::bitwise_and(image, mask, dstImage);
imwrite("test.jpg", dstImage);
I know that I need to use alpha channel, but it's unclear what I need to do next and how to implement this.
How can I get transparent background outside the mask?
First, create your image with four channels as described in this answer. Use negative source for fourth channel to get it zeroed out already. You now have a totally transparent image.
Create your mask just as you did before, just using different RGBA values (be aware that Scalar has a fourth constructor parameter for alpha values):
cv::fillPoly(mask, elementPoints, &numberOfPoints, 1, cv::Scalar(0, 0, 0, 255), 8);
Finally, apply the mask to set the region in question to totally opaque:
cv::bitwise_or(image, mask, dstImage);
You might want to retain the RGB values of the original image (so you can operate on later) or you might clear them out (which will result in higher compression and thus smaller file size). If the latter, use an inverted mask with RGBA set to 0, 0, 0, 0 and apply that with bitwise_and...
Currently I am using OpenCV to process images from an AVCaptureSession. The app right now takes these images and draws cv::Circles on the blobs. The tracking is working but when I draw the circle, it comes out as this gray, distorted circle when it should be green. Is it that OpenCV drawing functions don't work properly with iOS apps? Or is there something I can do to fix it?
Any help would be appreciated.
Here is a screen shot: (Ignore that giant green circle on the bottom)
The cv::Circle is around the outside of the black circle.
Here is where I converted the CMSampleBuffer into a cv::Mat:
enter code here CVImageBufferRef pixelBuff = CMSampleBufferGetImageBuffer(sampleBuffer);
cv::Mat cvMat;
CVPixelBufferLockBaseAddress(pixelBuff, 0);
int bufferWidth = CVPixelBufferGetWidth(pixelBuff);
int bufferHeight = CVPixelBufferGetHeight(pixelBuff);
unsigned char *pixel = (unsigned char *)CVPixelBufferGetBaseAddress(pixelBuff);
cvMat = cv::Mat(bufferHeight, bufferWidth, CV_8UC4, pixel);
cv::Mat grayMat;
cv::cvtColor(cvMat, grayMat, CV_BGR2GRAY);
CVPixelBufferUnlockBaseAddress(pixelBuff, 0);
This is the cv::Circle command:
if (keypoints.size() > 0) {
cv::Point p(keypoints[0].pt.x, keypoints[0].pt.y);
printf("x: %f, y: %f\n",keypoints[0].pt.x, keypoints[0].pt.y);
cv::circle(cvMat, p, keypoints[0].size/2, cv::Scalar(0,255,0), 2, 8, 0);
}
Keypoints is the vector of blobs that have been detected.
I'm new to image processing and development. I have used opencv, There I need to extract circle from a given image. That circle given x, y coordinates are (radius) in Oder to do that I used following code. But my problem is I have to take black rectangle. So the image patch having unwanted black pixels. How do I save just only circle?
my code
double save_key_points(Mat3b img, double x, double y, double radius, string
filename, string foldername)
{
// print image height and width first and check.
Vec3f circ(x, y, radius);
// Draw the mask: white circle on black background
Mat1b mask(img.size(), uchar(0));
circle(mask, Point(circ[0], circ[1]), circ[2], Scalar(255), CV_FILLED);
// Compute the bounding box
Rect bbox(circ[0] - circ[2], circ[1] - circ[2], 2 * circ[2], 2 * circ[2]);
// Create a black image
Mat3b res(img.size(), Vec3b(0, 0, 0));
// Copy only the image under the white circle to black image
img.copyTo(res, mask);
// Crop according to the roi
res = res(bbox);
//remove black but doesn't work.
Mat tmp, alpha;
threshold(res, alpha, 100, 255, THRESH_BINARY);
// Save the image
string path = "C:\\Users\\bb\\Desktop\\test_results\\test_case8\\" + foldername + filename + ".png";
imwrite(path, res);
Mat keypointimg = imread(path, CV_LOAD_IMAGE_GRAYSCALE);
//print the cordinate of one patch.
cordinate_print(keypointimg, radius);
}
(Here i want without black background)
If I understand what you are asking correctly you could remove the black from an image you can use a mask. The mask can highlight anything that is of a certain colour or in your case the shade of black. Check out the link for this implementation and see if it is what you are looknig for. It is in python but can be easily adapted.
Image Filtering
I was wondering how it is possible to create effects like a glowing ball or a glowing line in my video frames in OpenCV. Any tips on where I can start or what can I use so I can create simple animations in my output?
Thanks in advance!
These effects are simple to accomplish with primitive OpenCV pixel operations. Let's say you have your ball identified as a white region in a separate mask image mask. Blur this mask with GaussianBlur and then combine the result with your source image img. For a glow effect, you probably want something like Photoshop's Screen blending mode, which will only brighten the image:
Result Color = 255 - [((255 - Top Color)*(255 - Bottom Color))/255]
The real key to the "glow" effect is using the pixels in the underlying layer as the screen layer. This translates to OpenCV:
cv::Mat mask, img;
...
mask = mask * img; //fill the mask region with pixels from the original image
cv::GaussianBlur(mask, mask, cv::Size(0,0), 4); //blur the mask, 4 pixels radius
mask = mask * 0.50; //a 50% opacity glow
img = 255 - ((255 - mask).mul(255 - img) / 255); //mul for per-element multiply
I did not test this code, so I might have something wrong here. Color Dodge is also a useful blending mode for glows.
More here: How does photoshop blend two images together?
I wrote a version of the effect that can run both on the CPU and on HW acceleration devices (e.g. GPU). If src is a cv::UMat and you have OpenCL support it will run using OpenCL otherwise if src is a cv::Mat it will run good old CPU code.
template<typename Tmat>
void glow_effect(Tmat& src, int ksize = 100) {
static Tmat resize;
static Tmat blur;
static Tmat src16;
cv::bitwise_not(src, src);
//Resize for some extra performance
cv::resize(src, resize, cv::Size(), 0.5, 0.5);
//Cheap blur
cv::boxFilter(resize, resize, -1, cv::Size(ksize, ksize), cv::Point(-1, -1), true, cv::BORDER_REPLICATE);
//Back to original size
cv::resize(resize, blur, cv::Size(VIDEO_WIDTH, VIDEO_HEIGHT));
//Multiply the src image with a blurred version of itself
cv::multiply(src, blur, src16, 1, CV_16U);
//Normalize and convert back to CV_8U
cv::divide(src16, cv::Scalar::all(255.0), src, 1, CV_8U);
cv::bitwise_not(src, src);
}