I used the rectangle array below to loop faces detected by Haar Classifier:
for( int i = 0; i < (objects ? objects->total : 0 ); i++ )
{
CvRect* r = ( CvRect* )cvGetSeqElem( objects, i );
cvRectangle( frame, cvPoint( r->x, r->y ), cvPoint( r->x + r->width, r->y + r->height ),colors[i%1]);
}
But I want to change the pixel data of each face detected in the classifier i.e. change the values of pixels of each rectangle in:
CvRect* r;
I tried:
for( int i = 0; i < (objects ? objects->total : 0 ); i++ )
{
r[i];
for(int j = r->y; j < r->y + r->height; j++)
{
for(int k = r->x; k < r->x + r->width; k++)
{
frame->imageData[k*3] = 0;
frame->imageData[k*3+2] = 0;
}
}
}
to keep only G channel of the face but it is saying that the variable 'r' is not declared.
In this loop:
for( int i = 0; i < (objects ? objects->total : 0 ); i++ )
{
CvRect* r = ( CvRect* )cvGetSeqElem( objects, i );
cvRectangle( frame, cvPoint( r->x, r->y ), ... );
}
properly initialized temporary local variable r is being used, while in this code:
CvRect* r;
for( int i = 0; i < (objects ? objects->total : 0 ); i++ )
{
r[i];
for(int j = r->y; j < r->y + r->height; j++)
{
for(int k = r->x; k < r->x + r->width; k++)
{
frame->imageData[k*3] = 0;
frame->imageData[k*3+2] = 0;
}
}
}
uninitialized pointer r is treated as an array and even within the nonsense expression making this code invalid.
Try to replace r[i] with r = ( CvRect* )cvGetSeqElem( objects, i );
Use a new image instance as a roi pointer. Example:
Mat myimage(500,500,CV_8U,Scalar(255));
imshow("image",myimage); //white image
cvWaitKey();
//Reference matrix
Mat roi_img(myimage(cvRect(25,25,100,100)));
roi_img.setTo(Scalar(0));
imshow("image",myimage); //image has a black rect area.
cvWaitKey();
Related
I have this C++ function to create an image from multiple images:
Mat imageCollage(vector<Mat> & array_of_images, int M, int N )
{
// All images should be the same size
const Size images_size = array_of_images[0].size();
// Create a black canvas
Mat image_collage( images_size.height * M, images_size.width * N, CV_8UC3, Scalar( 0, 0, 0 ) );
for( int i = 0; i < M; ++i )
{
for( int j = 0; j < N; ++j )
{
if( ( ( i * N ) + j ) >= array_of_images.size() )
break;
Rect roi( images_size.width * j, images_size.height * i, images_size.width, images_size.height );
array_of_images[ ( i * N ) + j ].copyTo( image_collage( roi ) );
}
}
return image_collage;
}
My program is supposed to create an image collage from multiple images and it works for RGB images but not when I convert them to grayscale. I tested separately the functions and I think it's this one that creates the problem. This is the error I get:
OpenCV(4.5.0-dev) /home/csimage/Documents/opencv-repos/opencv/modules/core/src/copy.cpp:254: error: (-215:Assertion failed) channels() == CV_MAT_CN(dtype) in function 'copyTo'
Aborted (core dumped)
I have an image 800x800 which is broken down to 16 blocks of 200x200.
(you can see previous post here)
These blocks are : vector<Mat> subImages;
I want to use float pointers on them , so I am doing :
float *pdata = (float*)( subImages[ idxSubImage ].data );
1) Now, I want to be able to get again the same images/blocks, going from float array to Mat data.
int Idx = 0;
pdata = (float*)( subImages[ Idx ].data );
namedWindow( "Display window", WINDOW_AUTOSIZE );
for( int i = 0; i < OriginalImgSize.height - 4; i+= 200 )
{
for( int j = 0; j < OriginalImgSize.width - 4; j+= 200, Idx++ )
{
Mat mf( i,j, CV_32F, pdata + 200 );
imshow( "Display window", mf );
waitKey(0);
}
}
So , the problem is that I am receiving an
OpenCV Error: Assertion failed
in imshow.
2) How can I recombine all the blocks to obtain the original 800x800 image?
I tried something like:
int Idx = 0;
pdata = (float*)( subImages[ Idx ].data );
Mat big( 800,800,CV_32F );
for( int i = 0; i < OriginalImgSize.height - 4; i+= 200 )
{
for( int j = 0; j < OriginalImgSize.width - 4; j+= 200, Idx++ )
{
Mat mf( i,j, CV_32F, pdata + 200 );
Rect roi(j,i,200,200);
mf.copyTo( big(roi) );
}
}
imwrite( "testing" , big );
This gives me :
OpenCV Error: Assertion failed (!fixedSize()) in release
in mf.copyTo( big(roi) );.
First, you need to know where are your subimages into the big image. To do this, you can save the rect of each subimage into the vector<Rect> smallImageRois;
Then you can use pointers (keep in mind that subimages are not continuous), or simply use copyTo to the correct place:
Have a look:
#include <opencv2\opencv.hpp>
#include <vector>
using namespace std;
using namespace cv;
int main()
{
Mat3b img = imread("path_to_image");
resize(img, img, Size(800, 800));
Mat grayImg;
cvtColor(img, grayImg, COLOR_BGR2GRAY);
grayImg.convertTo(grayImg, CV_32F);
int N = 4;
if (((grayImg.rows % N) != 0) || ((grayImg.cols % N) != 0))
{
// Error
return -1;
}
Size graySize = grayImg.size();
Size smallSize(grayImg.cols / N, grayImg.rows / N);
vector<Mat> smallImages;
vector<Rect> smallImageRois;
for (int i = 0; i < graySize.height; i += smallSize.height)
{
for (int j = 0; j < graySize.width; j += smallSize.width)
{
Rect rect = Rect(j, i, smallSize.width, smallSize.height);
smallImages.push_back(grayImg(rect));
smallImageRois.push_back(rect);
}
}
// Option 1. Using pointer to subimage data.
Mat big1(800, 800, CV_32F);
int big1step = big1.step1();
float* pbig1 = big1.ptr<float>(0);
for (int idx = 0; idx < smallImages.size(); ++idx)
{
float* pdata = (float*)smallImages[idx].data;
int step = smallImages[idx].step1();
Rect roi = smallImageRois[idx];
for (int i = 0; i < smallSize.height; ++i)
{
for (int j = 0; j < smallSize.width; ++j)
{
pbig1[(roi.y + i) * big1step + (roi.x + j)] = pdata[i * step + j];
}
}
}
// Option 2. USing copyTo
Mat big2(800, 800, CV_32F);
for (int idx = 0; idx < smallImages.size(); ++idx)
{
smallImages[idx].copyTo(big2(smallImageRois[idx]));
}
return 0;
}
For concatenating the sub-images into a single squared image, you can use the following function:
// Important: all patches should have exactly the same size
Mat concatPatches(vector<Mat> &patches) {
assert(patches.size() > 0);
// make it square
const int patch_width = patches[0].cols;
const int patch_height = patches[0].rows;
const int patch_stride = ceil(sqrt(patches.size()));
Mat image = Mat::zeros(patch_stride * patch_height, patch_stride * patch_width, patches[0].type());
for (size_t i = 0, iend = patches.size(); i < iend; i++) {
Mat &patch = patches[i];
const int offset_x = (i % patch_stride) * patch_width;
const int offset_y = (i / patch_stride) * patch_height;
// copy the patch to the output image
patch.copyTo(image(Rect(offset_x, offset_y, patch_width, patch_height)));
}
return image;
}
It takes a vector of sub-images (or patches as I refer them to) and concatenates them into a squared image. Example usage:
vector<Mat> patches;
vector<Scalar> colours = {Scalar(255, 0, 0), Scalar(0, 255, 0), Scalar(0, 0, 255)};
// fill vector with circles of different colours
for(int i = 0; i < 16; i++) {
Mat patch = Mat::zeros(100,100, CV_32FC3);
circle(patch, Point(50,50), 40, colours[i % 3], -1);
patches.push_back(patch);
}
Mat img = concatPatches(patches);
imshow("img", img);
waitKey();
Will produce the following image
print the values of i and j before creating Mat mf and I believe you will soon be able to find the error.
Hint 1: i and j will be 0 the first time
Hint 2: Use the copyTo() with a ROI like:
cv::Rect roi(0,0,200,200);
src.copyTo(dst(roi))
Edit:
Hint 3: Try not to do such pointer fiddling, you will get in trouble. Especially if you're ignoring the step (like you seem to do).
Hi everyone i tried using kmeans clustering to group the objects. So that i can use this clustering method to detect objects. I get output but the problem is its too slow{How can i solve this?? } and i get the output window is as shown in the below link. Three output images are displayed instead of one how can i solve this. I don't know where exactly the error lies.
http://tinypic.com/view.php?pic=30bd7dc&s=8#.VgkSIPmqqko
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
int main( )
{
Mat src = imread( "Light.jpg", 0 );
// imshow("fff",src);
// cvtColor(src,src,COLOR_BGR2GRAY);
Mat dst;
// pyrDown(src,src,Size( src.cols/2, src.rows/2 ),4);
// src=dst;
resize(src,src,Size(128,128),0,0,1);
Mat samples(src.rows * src.cols, 3, CV_32F);
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
// for( int z = 0; z < 3; z++)
samples.at<float>(y + x*src.rows) = src.at<uchar>(y,x);
cout<<"aaa"<<endl;
int clusterCount = 15;
Mat labels;
int attempts = 2;
Mat centers;
cout<<"aaa"<<endl;
kmeans(samples, clusterCount, labels, TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10000, 0.0001), attempts, KMEANS_PP_CENTERS, centers );
Mat new_image( src.size(), src.type() );
cout<<"aaa"<<endl;
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
{
int cluster_idx = labels.at<int>(y + x*src.rows,0);
new_image.at<uchar>(y,x) = centers.at<float>(cluster_idx,0);
//new_image.at<Vec3b>(y,x)[1] = centers.at<float>(cluster_idx, 1);
// new_image.at<Vec3b>(y,x)[2] = centers.at<float>(cluster_idx, 2);
}
imshow( "clustered image", new_image );
waitKey( 0 );
}
In your initial code you have to change the intermedia Mat sample from 3 channels to 1 channel if you use grayscale images.
In addition, if you change the memory ordering, it might be faster (changed to (y*src.cols + x, 0) in both places):
int main( )
{
clock_t start = clock();
Mat src = imread( "Light.jpg", 0 );
Mat dst;
resize(src,src,Size(128,128),0,0,1);
Mat samples(src.rows * src.cols, 1, CV_32F);
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
samples.at<float>(y*src.cols + x, 0) = src.at<uchar>(y,x);
int clusterCount = 15;
Mat labels;
int attempts = 2;
Mat centers;
kmeans(samples, clusterCount, labels, TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10000, 0.0001), attempts, KMEANS_PP_CENTERS, centers );
Mat new_image( src.size(), src.type() );
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
{
int cluster_idx = labels.at<int>(y*src.cols + x,0);
new_image.at<uchar>(y,x) = centers.at<float>(cluster_idx,0);
}
imshow( "clustered image", new_image );
clock_t end = clock();
std::cout << "time: " << (end - start)/(float)CLOCKS_PER_SEC << std::endl;
waitKey( 0 );
}
I'm attempting to convert a MATLAB .mat file to openCV MAT and then applying several masks to those files. I am building from cvmatio source code. I am receiving the following error:
OpenCV Error: Assertion failed (A.size == arrays[i0]->size) in init,
file
/home/derek/Documents/Libraries/opencv-3.0.0-beta/modules/core/src/matrix.cpp,
line 4279 terminate called after throwing an instance of
'cv::Exception' what():
/home/derek/Documents/Libraries/opencv-3.0.0-beta/modules/core/src/matrix.cpp:4279:
error: (-215) A.size == arrays[i0]->size in function init
Here is the source file I've written. It occurs at the line with MixChannels. Note that SrcImage is a 3 channel Mat. lower and upper are the threshold values in an array who's length is equal to the number of channels.
/*
* Mask.cpp
*
* Created on: Mar 16, 2015
* Author: derek
*/
#include <cv.h>
#include <highgui.h>
#include "imgcodecs.hpp"
#include "highgui.hpp"
#include "imgproc.hpp"
using namespace cv;
Mat Mask(Mat SrcImage, double lower[], double upper[]){
int height=SrcImage.rows;
int width=SrcImage.cols;
int depth=SrcImage.depth();
Mat B2d = Mat::ones(height, width,depth);
Mat out(height, width, depth);
Mat outL(height, width, depth);
Mat outU(height,width, depth);
for (int i=1; i< SrcImage.channels(); i=i+1){
int from_to[]={i,1};
mixChannels(&SrcImage, 3, &out, 1, from_to, 1 );
threshold(out, outL, lower[i], 1, THRESH_BINARY);
threshold(out, outU, upper[i], 1, THRESH_BINARY);
bitwise_and(B2d, outL, B2d);
bitwise_and(B2d, outU, B2d);
}
return B2d;
}
Also, here is an excerpt of the actual CV_Assertion error location. As indicated in the error, it occurs at "(A.size == arrays[i0]->size)".
void NAryMatIterator::init(const Mat** _arrays, Mat* _planes, uchar** _ptrs, int _narrays)
{
CV_Assert( _arrays && (_ptrs || _planes) );
int i, j, d1=0, i0 = -1, d = -1;
arrays = _arrays;
ptrs = _ptrs;
planes = _planes;
narrays = _narrays;
nplanes = 0;
size = 0;
if( narrays < 0 )
{
for( i = 0; _arrays[i] != 0; i++ )
;
narrays = i;
CV_Assert(narrays <= 1000);
}
iterdepth = 0;
for( i = 0; i < narrays; i++ )
{
CV_Assert(arrays[i] != 0);
const Mat& A = *arrays[i];
if( ptrs )
ptrs[i] = A.data;
if( !A.data )
continue;
if( i0 < 0 )
{
i0 = i;
d = A.dims;
// find the first dimensionality which is different from 1;
// in any of the arrays the first "d1" step do not affect the continuity
for( d1 = 0; d1 < d; d1++ )
if( A.size[d1] > 1 )
break;
}
else
CV_Assert( A.size == arrays[i0]->size );
if( !A.isContinuous() )
{
CV_Assert( A.step[d-1] == A.elemSize() );
for( j = d-1; j > d1; j-- )
if( A.step[j]*A.size[j] < A.step[j-1] )
break;
iterdepth = std::max(iterdepth, j);
}
}
if( i0 >= 0 )
{
size = arrays[i0]->size[d-1];
for( j = d-1; j > iterdepth; j-- )
{
int64 total1 = (int64)size*arrays[i0]->size[j-1];
if( total1 != (int)total1 )
break;
size = (int)total1;
}
iterdepth = j;
if( iterdepth == d1 )
iterdepth = 0;
nplanes = 1;
for( j = iterdepth-1; j >= 0; j-- )
nplanes *= arrays[i0]->size[j];
}
else
iterdepth = 0;
idx = 0;
if( !planes )
return;
for( i = 0; i < narrays; i++ )
{
CV_Assert(arrays[i] != 0);
const Mat& A = *arrays[i];
if( !A.data )
{
planes[i] = Mat();
continue;
}
planes[i] = Mat(1, (int)size, A.type(), A.data);
}
}
Well it's obviously too late of an answer, but here is the reason why your code failed:
Since your SrcImage is a single Mat with multiple channels, you should'we written:
mixChannels(&SrcImage, 1, &out, 1, from_to, 1 );
(The assert error was related to this, since mixChannels expected 3 Mats, which is 3 times bigger than your Mat.)
Also opencv MixChannels labels channels from 0, not sure if the i=1 was intended, or just a typo.
Cheers!
So I'm trying to erode a binary matrix.
I create the matrix using this code:
cv::Mat tmp = cv::Mat::zeros( IMG->width, IMG->height, CV_8U );
for( auto i = 0 ; i < IMG->width ; i++)
{
for ( auto j = 0 ; j < IMG->height ; j++)
{
if( cv::pointPolygonTest(cv::Mat(contour),cv::Point(i,j),true) < 0 )
{
tmp.at<double>(i,j) = 255;
}
}
}
Here is the source picture I'm using:
And this what I get with my loop (it's the tmp matrix):
So after I'm trying to erode the picture using this code:
int erosion_elem = 1;
int erosion_size = 8;
int erosion_type;
if( erosion_elem == 0 ){ erosion_type = MORPH_RECT; }
else if( erosion_elem == 1 ){ erosion_type = MORPH_CROSS; }
else if( erosion_elem == 2) { erosion_type = MORPH_ELLIPSE; }
Mat element = getStructuringElement( erosion_type,
Size( 2*erosion_size + 1, 2*erosion_size+1 ),
Point( erosion_size, erosion_size ) );
/// Apply the erosion operation
erode( binary, erosion_dst, element );`
So it compiles well but I get an exception on this line:
erode( binary, erosion_dst, element );`
It says it's an unsupported data type.
Does anyone have an idea why do I get this exception?
I tried to change the data type of the matrix tmp but I have the same error.
Thanks for your help !
Your binary image pixels are stored as unsigned char (CV_8U -> on 8bits -> 1 byte),
you should store your pixels' value as unsigned char too
cv::Mat tmp = cv::Mat::zeros( IMG->width, IMG->height, CV_8U );
for( auto i = 0 ; i < IMG->width ; i++)
{
for ( auto j = 0 ; j < IMG->height ; j++)
{
if( cv::pointPolygonTest(cv::Mat(contour),cv::Point(i,j),true) < 0 )
{
tmp.at<unsigned char>(i,j) = 255;
}
}
}
(made answer from comment)