Hi what I have is a couple of Mat that I want to overlay (in a custom order). The Mat holdes some opencv polygons (which means a lot transparency). This Mat I need to overlay/merge. But not with the classical alpha blending more like with a 100% opacity but with transparency.
This is a simple sample code of what I want to merge.
Mat m1, m2;
m1.create(Point{ 100,100 }, CV_8UC4);
m2.create(Point{ 100,100 }, CV_8UC4);
cv::polylines(m1, std::vector<Point>{ Point{ 2,20 },Point{ 20,40 } }, true, Scalar(6, 6, 255));
cv::polylines(m2, std::vector<Point>{Point{ 100,100 }, Point{ 0,0 } }, true, Scalar(192, 112, 0));
Please note, that I cannot draw the polygons directly in one Mat due to various reasons.
I thought that maybe m1.copyTo(m2); will work, but its overwriting everything (incl. the black background)
Any idea how to get it merged/overlayed without the background? May I construct the mat's wrong?
I suspect you've had a problem looking for black in those images, as they were not initialized (it became apparent in debug mode). If we start with a zeroed out matrix, and draw using a 4-channel colour, so that the lines are visible, we get inputs such as this:
Input 1:
Input 2:
Now, we can use inRange to find all pixels set to (0,0,0,0). Since we want a mask of all non-black pixels, we just invert it by subtracting from 255. (i.e. mask = 255 - mask)
Mask:
Finally, use the mask as the second parameter of copyTo.
Result:
Code:
#include <opencv2/opencv.hpp>
int main()
{
cv::Mat m1(100, 100, CV_8UC4, cv::Scalar(0, 0, 0, 0));
cv::Mat m2(100, 100, CV_8UC4, cv::Scalar(0, 0, 0, 0));
cv::polylines(m1
, std::vector<cv::Point>{cv::Point{2, 20}, cv::Point{20, 40}}
, true, cv::Scalar(6, 6, 255, 255));
cv::polylines(m2
, std::vector<cv::Point>{cv::Point{100, 100}, cv::Point{0, 0}}
, true, cv::Scalar(192, 112, 0, 255));
cv::Mat mask;
cv::inRange(m2, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
mask = 255 - mask; // invert the mask
cv::Mat result(m1.clone());
m2.copyTo(result, mask);
cv::imwrite("transp_in_1.png", m1);
cv::imwrite("transp_in_2.png", m2);
cv::imwrite("transp_mask.png", mask);
cv::imwrite("transp_res.png", result);
return 0;
}
Instead of inverting the mask, you can invert the direction in which you copy. (i.e. overwrite everything black in m2 with stuff from m1)
cv::Mat mask;
cv::inRange(m2, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
cv::Mat result(m2.clone());
m1.copyTo(result, mask);
Related
Using a similar code mentioned here, I detected the red ball like this:
Lower: [0,0,0] Upper[14, 211, 131] (I also tried 1-2 step more-less than this range)
Now I want to detect this red ball from a live capture. So wrote:
cv::medianBlur(image,image,3);
// Convert input image to HSV
cv::Mat hsv_image;
cv::cvtColor(image, hsv_image, cv::COLOR_BGR2HSV);
cv::Mat red_hue_image;
cv::inRange(hsv_image, cv::Scalar(0, 0, 0), cv::Scalar(14, 211, 131), red_hue_image);
But it did not work.
I did exactly the same thing on a yellow ball with this range:
Lower:[15, 162, 0] , Upper[180, 255, 255]
With this code:
cv::medianBlur(image,image,3);
// Convert input image to HSV
cv::Mat hsv_image;
cv::cvtColor(image, hsv_image, cv::COLOR_BGR2HSV);
cv::Mat yellow_hue_image;
cv::inRange(hsv_image, cv::Scalar(15, 162, 0), cv::Scalar(180, 255, 255), yellow_hue_image);
And it worked well for the yellow ball. How to do that on the red one too, what could possibly be wrong?
I draw objects on IplImage like this:
cvLine(image, point_1, point_2, color, thickness, CV_AA); // Line
cvCircle(mage, point, radius, color, thickness, CV_AA); // Circle
// and some others...
How can I draw them translucent? cv::Scalar does not support alpha channel, if I understand correctly. I found something similar, but not quite appropriate: link. Here we are talking about translucenty IplImage, not about the objects on it.
So, I tested it now with IplImage and cv::Mat, and both cvCircle and cv::circle don't support drawing semi-transparent objects. I used OpenCV 3.4.0, since this version still supports the old C API.
Let's have a look at the following code:
// IplImage - doesn't work
IplImage* ipl = cvCreateImage(cvSize(201, 201), IPL_DEPTH_8U, 4);
cvSet(ipl, CvScalar(255, 0, 0, 255));
cvCircle(ipl, CvPoint(100, 100), 50, CvScalar(0, 0, 255, 128), CV_FILLED);
// cv::Mat - doesn't work
cv::Mat img = cv::Mat(201, 201, CV_8UC4, cv::Scalar(255, 0, 0, 255));
cv::circle(img, cv::Point(100, 100), 50, cv::Scalar(0, 0, 255, 128), cv::FILLED);
We create a blue 4-channel image with zero transparency, and draw a red circle with 0.5 transparency. In both cases, we get the following output:
We see, that the part of red circle actually "replaces" the pixel values in the original blue image.
So, for IplImage as well as for cv::Mat we need to use blending, e.g. using addWeighted. Let's have a look at this code:
// IplImage - works
IplImage* iplBG = cvCreateImage(cvSize(201, 201), IPL_DEPTH_8U, 3);
cvSet(iplBG, CvScalar(255, 0, 0));
IplImage* iplFG = cvCreateImage(cvSize(201, 201), IPL_DEPTH_8U, 3);
cvSet(iplFG, CvScalar(0, 0, 0));
cvCircle(iplFG, CvPoint(100, 100), 50, CvScalar(0, 0, 255), CV_FILLED);
IplImage* iplOut = cvCreateImage(cvSize(201, 201), IPL_DEPTH_8U, 3);
cvAddWeighted(iplBG, 1, iplFG, 0.5, 0, iplOut);
// cv::Mat - works
cv::Mat imgBG = cv::Mat(201, 201, CV_8UC3, cv::Scalar(255, 0, 0));
cv::Mat imgFG = cv::Mat(201, 201, CV_8UC3, cv::Scalar(0, 0, 0));
cv::circle(imgFG, cv::Point(100, 100), 50, cv::Scalar(0, 0, 255), cv::FILLED);
cv::Mat imgOut;
cv::addWeighted(imgBG, 1, imgFG, 0.5, 0, imgOut);
In fact, we create a blue 3-channel background image like this:
And, we create a black foreground 3-channel image of the same size with the red circle:
Using addWeighted with alpha = 1 and beta = 0.5, we get the expected output for both versions:
Hi following up on this brillant way of copying polygons to an other Mat in OpenCv overlay two Mat (drawings not images) with transparency I need to advanced this a bit.
Besides just copying Mats with polygons, I need to copy these polygons ONTO a image. Below you can find my MWE of this.
Following the above mentioned answer I load an additional image called bg in this case (as well 100x100px). What I believed is using inRange again on the result gives me the mask of all polygons (which is working). And than using copyTo to copy all that is in the mask. It copies the pixels from the "background image", but colouring the polygons in black insted of its regular colours.
Any ideas what I forgot to consider in this case?
PS: drawing the polygons directly onto the image is not possible. The code below is just a MWE and in the code below I left out an loop for readability reasons.
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
int main(int argc, char **argv)
{
cv::Mat bg = imread("bg.png");
cv::Mat m1(100, 100, CV_8UC4, cv::Scalar(0, 0, 0, 0));
cv::Mat m2(m1);
cv::Mat m3(m1);
cv::Mat m4(m1);
cv::polylines(m1, std::vector<cv::Point>{cv::Point{ 100, 20 }, cv::Point{ 0, 40 }}, true, cv::Scalar(6, 6, 255, 255));
cv::polylines(m2, std::vector<cv::Point>{cv::Point{ 100, 100 }, cv::Point{ 0, 0 }}, true, cv::Scalar(192, 112, 0, 255));
cv::polylines(m3, std::vector<cv::Point>{cv::Point{ 0, 50 }, cv::Point{ 100, 50 }}, true, cv::Scalar(0, 228, 0, 255));
cv::polylines(m4, std::vector<cv::Point>{cv::Point{ 20, 0 }, cv::Point{ 20, 100 }}, true, cv::Scalar(0, 228, 255, 0 ));
cv::Mat mask;
cv::Mat result(m1.clone());
cv::inRange(m2, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
mask = 255 - mask; // invert the mask
m2.copyTo(result, mask);
cv::inRange(result, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
m3.copyTo(result, mask);
cv::inRange(result, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
m4.copyTo(result, mask);
cv::inRange(result, cv::Scalar(0, 0, 0, 0), cv::Scalar(0, 0, 0, 0), mask);
bg.copyTo(result, mask);
namedWindow("result", cv::WINDOW_AUTOSIZE);
imshow("result", result);
}
SSorry for my bad english . I have an image that Show 3 circles of different color, one red, one green and one blue and I can display this image into the 3 channels, but they appear white and in the code I display an image call "copy R" and I dont know how to make this copy R into another image whit any color I want to overlap the original image and changing the red color. How can i do this ???
this is my code, sorry is the first time i make a question and dont know how to publish properly
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#define w 400
using namespace cv;
/// Function headers
void MyFilledCircle(Mat img, Point center);
void MyFilledCircle1(Mat img, Point center);
void MyFilledCircle2(Mat img, Point center);
int main(void) {
//![create_images]
char window[] = "Original";
/// Create black empty images
Mat image = Mat::zeros(w, w, CV_8UC3);
/// 1.b. Creating circles
MyFilledCircle(image, Point(200, 200));
MyFilledCircle1(image, Point(150, 150));
MyFilledCircle2(image, Point(250, 250));
Mat channel[3];
split(image, channel);
//channel[0] = Mat::zeros(image.rows, image.cols, CV_8UC1);
merge(channel, 3, image);
Mat imageHSV;
Mat copy;
imshow(window, image);
//imshow("Color 1", imageHSV);
inRange(image, Scalar(0, 0, 255), Scalar(0, 0, 255), copy);
imshow("copy R", copy);
imshow("B", channel[0]);
imshow("G", channel[1]);
imshow("R", channel[2]);
//imshow("0", canal0);
//imwrite("dest.jpg", image);
waitKey(0);
return(0);
}
/// Function Declaration
//![myfilledcircle]
void MyFilledCircle1(Mat img, Point center)
{
circle(img,
center,
50,
Scalar(0, 255, 0),
FILLED,
LINE_8);
}
void MyFilledCircle(Mat img, Point center)
{
circle(img,
center,
50,
Scalar(0, 0, 255),
FILLED,
LINE_8);
}
void MyFilledCircle2(Mat img, Point center)
{
circle(img,
center,
50,
Scalar(255, 0, 0),
FILLED,
LINE_8);
}
From the looks of it, it looks like copy is a binary mask, and you want to superimpose this mask on image, such that only the non-zero pixels in the mask retain their original color.
If my assumption is correct, then using the subtract method, as shown below, should help you out:
Mat result;
cvtColor(copy,copy,CV_GRAY2BGR);//change copy to a 3 channel image
absdiff(image,image,result);//initialize mask as a black image of img.size()
subtract(copy,image,result);
subtract(copy,result,result);
What I'm basically trying to do is blur an image, and combine it back with the orignal, so that only certain areas in the original image are blurred (the face should be blurred).
My general idea was to mask the parts in the original Iwant to have blurred, then blur the original as a copy and "merge" them together again.
To a certain extend this also worked.
My images:
(1) Original
(2) Original with parts that should be blurred
(3) Blurred
My C++ code that creates these images:
int main(void) {
cv::Mat srcImage = cv::imread(path);
srcImage.convertTo(srcImage, CV_32FC3, 1.0/255.0);
Mat _mask;
Mat img_gray;
cv::Scalar white = cv::Scalar(255, 255, 255);
cv::Scalar black = cv::Scalar(0, 0, 0);
cv::cvtColor(srcImage, img_gray, cv::COLOR_BGR2GRAY);
img_gray.convertTo(_mask, CV_32FC1);
// face
cv::circle(_mask, cv::Point(430, 350), 200, black, -1, 8, 0);
// eyes
cv::circle(_mask, cv::Point(502, 260), 27, white, -1, 8, 0);
cv::circle(_mask, cv::Point(390, 260), 27, white, -1, 8, 0);
// mouth
cv::ellipse(_mask, cv::Point(440, 390), cv::Point(60, 25), 0, 0, 360, white, -1, 8, 0);
cv::threshold(1.0-_mask, _mask, 0.9, 1.0, cv::THRESH_BINARY_INV);
cv::GaussianBlur(_mask,_mask,Size(21,21),11.0);
cv::Mat res;
cv::Mat bg = Mat(srcImage.size(), CV_32FC3);
bg = cv::Scalar(1.0, 1.0 ,1.0);
vector<Mat> ch_img(3);
vector<Mat> ch_bg(3);
cv::split(srcImage, ch_img);
cv::split(bg, ch_bg);
ch_img[0] = ch_img[0].mul(_mask) + ch_bg[0].mul(1.0 - _mask);
ch_img[1] = ch_img[1].mul(_mask) + ch_bg[1].mul(1.0 - _mask);
ch_img[2] = ch_img[2].mul(_mask) + ch_bg[2].mul(1.0 - _mask);
cv::merge(ch_img, res);
cv::merge(ch_bg, bg);
// original but with white mask
res.convertTo(res, CV_8UC3, 255.0);
imwrite("original_with_mask.jpg", res);
// blur original image
cv::Mat blurredImage;
bilateralFilter(srcImage, blurredImage, 10, 20, 5);
GaussianBlur(srcImage, blurredImage, Size(19, 19), 0, 0);
blurredImage.convertTo(blurredImage, CV_8UC3, 255.0);
imwrite("blurred.jpg", blurredImage);
cv::Mat maskedImage;
maskedImage = Mat(srcImage.size(), CV_32FC3);
// now combine blurred image and original using mask
// this fails
cv::bitwise_and(blurredImage, _mask, maskedImage);
cv::imwrite("masked.jpg", maskedImage);
}
My problem is that cv::bitwise_and(blurredImage, _mask, maskedImage); fails with
OpenCV Error: Sizes of input arguments do not match (The operation is neither 'array op array' (where arrays have the same size and type), nor 'array op scalar', nor 'scalar op array') in binary_op
Probably because _mask is a single channel image and blurredImage and maskedImage are 3-channel images.
How can I combine the images I got so that the currently white areas in image (2) are blurred using a transparent mask with "soft" edges?
Instead of float conversion you can just use the linearcombination of byte channel values. See
int main(int argc, char* argv[])
{
cv::Mat srcImage = cv::imread("C:/StackOverflow/Input/transparentMaskInput.jpg");
// blur whole image
cv::Mat blurredImage;
//cv::bilateralFilter(srcImage, blurredImage, 10, 20, 5); // use EITHER bilateral OR Gaússian filter
cv::GaussianBlur(srcImage, blurredImage, cv::Size(19, 19), 0, 0);
// create mask
cv::Scalar white = cv::Scalar(255, 255, 255);
cv::Scalar black = cv::Scalar(0, 0, 0);
cv::Mat mask = cv::Mat::zeros(srcImage.size(), CV_8UC1);
// face
cv::circle(mask, cv::Point(430, 350), 200, black, -1, 8, 0);
// eyes
cv::circle(mask, cv::Point(502, 260), 27, white, -1, 8, 0);
cv::circle(mask, cv::Point(390, 260), 27, white, -1, 8, 0);
// mouth
cv::ellipse(mask, cv::Point(440, 390), cv::Point(60, 25), 0, 0, 360, white, -1, 8, 0);
cv::GaussianBlur(mask, mask, cv::Size(21, 21), 11.0);
// byte inversion:
cv::Mat invertedMask = 255 - mask; // instead of inversion you could just draw the "face" black on a white background!
cv::Mat outputImage = cv::Mat(srcImage.size(), srcImage.type());
// for each pixel, merge blurred and original image regarding the blur-mask
for (int y = 0; y < outputImage.rows; ++y)
for (int x = 0; x < outputImage.cols; ++x)
{
cv::Vec3b pixelOrig = srcImage.at<cv::Vec3b>(y, x);
cv::Vec3b pixelBlur = blurredImage.at<cv::Vec3b>(y, x);
float blurVal = invertedMask.at<unsigned char>(y, x)/255.0f; // value between 0 and 1: zero means 100% orig image, one means 100% blurry image
cv::Vec3b pixelOut = blurVal * pixelBlur + (1.0f - blurVal)* pixelOrig;
outputImage.at<cv::Vec3b>(y, x) = pixelOut;
}
cv::imshow("input", srcImage);
cv::imshow("blurred", blurredImage);
cv::imshow("mask", mask);
cv::imshow("inverted mask", invertedMask);
cv::imshow("output", outputImage);
return 0;
}
using this input image:
computing this blurred and mask:
resulting in this output, by computing (mask/255) * blur + (1-mask/255)*blur (linear combination):
I define a function to do alphaBlend for two images of CV_8UC3 with a mask of CV_8UC1 in OpenCV:
//! 2018.01.16 13:54:39 CST
//! 2018.01.16 14:43:26 CST
void alphaBlend(Mat& img1, Mat&img2, Mat& mask, Mat& blended){
// Blend img1 and img2 (of CV_8UC3) with mask (CV_8UC1)
assert(img1.size() == img2.size() && img1.size() == mask.size());
blended = cv::Mat(img1.size(), img1.type());
for (int y = 0; y < blended.rows; ++y){
for (int x = 0; x < blended.cols; ++x){
float alpha = mask.at<unsigned char>(y, x)/255.0f;
blended.at<cv::Vec3b>(y,x) = alpha*img1.at<cv::Vec3b>(y,x) + (1-alpha)*img2.at<cv::Vec3b>(y,x);
}
}
}
Then, it's easy to do alpha bend on the images, just call alphaBlend(...). Here is an example:
#include <opencv2/opencv.hpp>
using namespace cv;
//! 2018.01.16 13:54:39 CST
//! 2018.01.16 14:43:26 CST
void alphaBlend(Mat& img1, Mat&img2, Mat& mask, Mat& blended){
// Blend img1 and img2 (of CV_8UC3) with mask (CV_8UC1)
assert(img1.size() == img2.size() && img1.size() == mask.size());
blended = cv::Mat(img1.size(), img1.type());
for (int y = 0; y < blended.rows; ++y){
for (int x = 0; x < blended.cols; ++x){
float alpha = mask.at<unsigned char>(y, x)/255.0f;
blended.at<cv::Vec3b>(y,x) = alpha*img1.at<cv::Vec3b>(y,x) + (1-alpha)*img2.at<cv::Vec3b>(y,x);
}
}
}
Mat createMask(Size sz){
// create mask
cv::Mat mask = cv::Mat::zeros(sz, CV_8UC1);
// white and black
cv::Scalar white = cv::Scalar(255, 255, 255);
cv::Scalar black = cv::Scalar(0, 0, 0);
// face
cv::circle(mask, cv::Point(430, 350), 200, black, -1, 8, 0);
// eyes
cv::circle(mask, cv::Point(502, 260), 27, white, -1, 8, 0);
cv::circle(mask, cv::Point(390, 260), 27, white, -1, 8, 0);
// mouth
cv::ellipse(mask, cv::Point(440, 390), cv::Point(60, 25), 0, 0, 360, white, -1, 8, 0);
// Blur
cv::GaussianBlur(mask, mask, cv::Size(21, 21), 11.0);
return mask;
}
int main(){
cv::Mat img = cv::imread("img04.jpg");
// blur whole image
cv::Mat blured;
//cv::bilateralFilter(img, blured, 10, 20, 5); // use EITHER bilateral OR Gaússian filter
cv::GaussianBlur(img, blured, cv::Size(19, 19), 0, 0);
// Create the mask
Mat mask = createMask(img.size());
Mat mask_inv = 255 - mask;
// Alpha blend
Mat blended1, blended2;
alphaBlend(img, blured, mask, blended1);
alphaBlend(img, blured, mask_inv, blended2);
// Display
cv::imshow("source", img);
cv::imshow("blured", blured);
cv::imshow("mask", mask);
cv::imshow("mask_inv", mask_inv);
cv::imshow("blended1", blended1);
cv::imshow("blended2", blended2);
cv::waitKey();
return 0;
}
Source:
Blured:
Mask1:
AlphaBlend 1:
Mask 2:
AlphaBlend 2:
Some useful links:
Alpha Blending in OpenCV C++ : Combining 2 images with transparent mask in opencv
Alpha Blending in OpenCV Python:
Gradient mask blending in opencv python
Probably because _mask is a single channel image and blurredImage and
maskedImage are 3-channel images.
Put this before calling the cv::bitwise_and:
P.S if you do not want to alter your mask becuase you want to use it in another place just do it in a temporary variable:
cv::Mat _mask_temp;
cv::cvtColor(_mask,_mask_temp,cv::COLOR_GRAY2BGR);
cv::bitwise_and(blurredImage, _mask_temp, maskedImage);
_mask_temp.release(); // just in case you do not want it anymore to be in your memory(optional)
EDIT (another problem):
The mask is 32F while the image is 8U. So, you need this:
cv::cvtColor(_mask,_mask,cv::COLOR_GRAY2BGR);
_mask.convertTo(_mask, CV_8UC3);