Hi I am trying to extract the lighting and the shadow from one surface and apply it to another type of surface. I convert the image to HSV and extract the Hue component and plot it which seems to give me a good indication of where the lighting and shadows are. However when I swap the hue component of the original image with my final image I get all sorts of greens and blues that are not desired. Are there any other techniques that can be used to project shadow and lighting?
cvtColor( img0, hsv, CV_BGR2HSV );
components[0].create( hsv.size(), 1);
components[1].create( hsv.size(), 1);
components[2].create( hsv.size(), 1);
split(hsv, components);
...
cvtColor( drawing, hsv_output, CV_BGR2HSV );
components_output[0].create( hsv.size(), 1);
components_output[1].create( hsv.size(), 1);
components_output[2].create( hsv.size(), 1);
split(hsv_output, components_output);
components_output[0] = 0.5 * components_output[0] + 0.5 * components[0];
int ch[] = {0 , 0};
mixChannels(&components_output[0], 1, &hsv_output, 1, ch, 1);
cvtColor( hsv_output, drawing, CV_HSV2BGR );
Related
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 am working on some "Face Normalization" Project.
What I did till now is:
Face detection
Facial Landmark detection (68)
Split the face is a few triangles by connecting the several landmarks (Delaunay Triangulation -->AAM)
Create some 3D Model of a generic face (consists of 68 (same as Landmarks) Points) in 3D and also did some Delaunay Triangulation
Now what i need to do now:
I know all the Landmark coordinates and all the 3D coordinates so i want to crop each triangle in 2D and put it on its right place on the 3D generic model to generate a 3D Model of the detected face.
Question:
1.)Does anyone know a way to crop a single Triangle by knowing all three coords?
2.)And what kind of transformation do i have to use to "copy" the cropped triangle on its right place on the generic 3D model?
I am programming in c++ and took dlib and openCV for the facial landmark detection and on the 3D side I am working with openGL
EDIT:
Maybe it is better to "see" the problem. This is what i have already
and now i just want to crop all these triangles separately. So how can I crop a triangle (when i know all 3 coords) from a picture and safe it in another window?
In order to crop a triangle, we need to use warpaffine method.
http://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.html
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace cv;
using namespace std;
/// Global variables
char* source_window = "Source image";
char* warp_window = "Warp";
char* warp_rotate_window = "Warp + Rotate";
/** #function main */
int main( int argc, char** argv )
{
Point2f srcTri[3];
Point2f dstTri[3];
Mat rot_mat( 2, 3, CV_32FC1 );
Mat warp_mat( 2, 3, CV_32FC1 );
Mat src, warp_dst, warp_rotate_dst;
/// Load the image
src = imread( argv[1], 1 );
/// Set the dst image the same type and size as src
warp_dst = Mat::zeros( src.rows, src.cols, src.type() );
/// Set your 3 points to calculate the Affine Transform
srcTri[0] = Point2f( 0,0 );
srcTri[1] = Point2f( src.cols - 1, 0 );
srcTri[2] = Point2f( 0, src.rows - 1 );
dstTri[0] = Point2f( src.cols*0.0, src.rows*0.33 );
dstTri[1] = Point2f( src.cols*0.85, src.rows*0.25 );
dstTri[2] = Point2f( src.cols*0.15, src.rows*0.7 );
/// Get the Affine Transform
warp_mat = getAffineTransform( srcTri, dstTri );
/// Apply the Affine Transform just found to the src image
warpAffine( src, warp_dst, warp_mat, warp_dst.size() );
/** Rotating the image after Warp */
/// Compute a rotation matrix with respect to the center of the image
Point center = Point( warp_dst.cols/2, warp_dst.rows/2 );
double angle = -50.0;
double scale = 0.6;
/// Get the rotation matrix with the specifications above
rot_mat = getRotationMatrix2D( center, angle, scale );
/// Rotate the warped image
warpAffine( warp_dst, warp_rotate_dst, rot_mat, warp_dst.size() );
/// Show what you got
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
imshow( source_window, src );
namedWindow( warp_window, CV_WINDOW_AUTOSIZE );
imshow( warp_window, warp_dst );
namedWindow( warp_rotate_window, CV_WINDOW_AUTOSIZE );
imshow( warp_rotate_window, warp_rotate_dst );
/// Wait until user exits the program
waitKey(0);
return 0;
}
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;
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);
}