I'm working with a Ximea Camera, programming in c++ and using Ubuntu 14.04. I have a XI_IMG image and with the next conversion I'm creating an OpenCV image, copying data from xiAPI buffer to OpenCV buffer.
stat = xiGetImage(xiH, 5000, &image);
HandleResult(stat,"xiGetImage");
XI_IMG* imagen = ℑ
IplImage * Ima = NULL;
char fname_jpg[MAX_PATH] = "";
Ima = cvCreateImage(cvSize(imagen->width, imagen->height), IPL_DEPTH_8U, 1);
memcpy(Ima->imageData, imagen->bp, imagen->width * imagen->height);
imwrite("image1", Ima);
After doing that I should be able to save or show the image, but the next error is shown:
program.cpp:76:24:error:invalid initialization of reference of type 'cv::InputArray {aka const cv::_InputArray&}' from expression of type 'IplImage* {aka IplImage*}'
Is there any other way to obtain or save the image? What else can I do to save a jpg image?
You are mixing old (and obsolete) C syntax like IplImage*, cv<SomeFunction>(), etc... with current C++ syntax.
To make it work be consistent and use only one style.
Using IplImage
int main()
{
IplImage* img = NULL;
img = cvCreateImage(...);
// Save
cvSaveImage("myimage.png", img);
// Show
cvShowImage("Image", img);
cvWaitKey();
return 0;
}
Or using new syntax (much better):
int main()
{
Mat img(...);
// Save
imwrite("myimage.png", img);
// Show
imshow("Image", img);
waitKey();
return 0;
}
Note that you don't need to memcpy the data after you initialize your Mat, but you can call one of these constructors:
C++: Mat::Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP)
C++: Mat::Mat(Size size, int type, void* data, size_t step=AUTO_STEP)
C++: Mat::Mat(int ndims, const int* sizes, int type, void* data, const size_t* steps=0)
Last trick, you can wrap your IplImage in a Mat and then use imwrite:
Mat mat(Ima);
imwrite("name.ext", mat);
Related
I am trying to convert this c api to c++
IplImage* hbm0 = cvCreateImage(cvSize(hbmp->width,hbmp->height),hbmp->depth, hbmp->nChannels );
I tried doing like this,
cv::Mat hbm0 = cv::Mat(hbmp.cols,hbmp.rows,hbmp.depth(), hbmp.channels() )
since mat constuctor doesnot seem to have parameters for depth and channels
Mat (int rows, int cols, int type, void *data, size_t step=AUTO_STEP)
what could be the best way to convert,as i am not directly using channels they are in a Mat object itself.
Thanks
I have a C++ function that is to be called from someone else's C# application. As input my function is given an array of signed short integers, the dimensions of the image it represents, and memory allocated for the returning data, namely another array of signed short integers. This would represent my function's header:
my_function (short* input, int height, int width, short* output)
Inside my function I create a cv::Mat from input, like this:
cv::Mat mat_in = cv::Mat (height, width, CV_16S, input);
This mat_in is then converted to CV_32F and processed by OpenCV's cv::bilateralFilter. After it returns cv::Mat mat_out, I convert the data back to CV_16S (bilateralFilter only accepts CV_8U and CV_32F). Now I need to convert this cv::Mat mat_out back to an array of short integers so that it may be returned to the calling function. This is my code:
my_function (short* input, int height, int width, short* output)
{
Mat mat_in_16S = Mat (height, width, CV_16S, input);
Mat mat_in_32F = Mat (height, width, CV_32F);
Mat mat_out_CV_32F = Mat (height, width, CV_32F);
mat_in_16S.convertTo (mat_in_32F, CV_32F);
bilateralFilter (mat_in_32F, mat_out_32F, 5, 160, 2);
Mat mat_out_16S = Mat (mat_in_16S.size(), mat_in_16S.type());
mat_out_32F.convertTo (mat_out_16S, CV_16S);
return 0;
}
Obviously, somewhere there at the end I need to get the data that is in mat_out_16S into output. My first try was to return a reference:
output = &mat_out_16S.at<short>(0,0);
but of course I realised that this was a silly idea, as mat_out_16S goes out of scope as soon as the function returns, leaving output pointing at emptiness. Currently my best attempt is as follows (from this question):
memcpy ((short*)output, (short*)mat_out_16S.data, height*width*sizeof(short));
Now I would like to know, is there a better way? It feels kind of inefficient to copy all this data, but I don't see what else I can do. I can't return a cv::Mat unfortunately. If there is no better way, is my current memcpy method safe at least? My data are all 2-byte signed short integers, so I don't think there should be issues with padding, but I don't want to run into any unpleasant surprises.
You can use this constructor for your mat_out_16S:
Mat::Mat(Size size, int type, void* data, size_t step=AUTO_STEP)
So your function will be:
my_function (short* input, int height, int width, short* output)
{
Mat mat_in_16S = Mat (height, width, CV_16S, input);
Mat mat_in_32F = Mat (height, width, CV_32F);
Mat mat_out_CV_32F = Mat (height, width, CV_32F);
mat_in_16S.convertTo (mat_in_32F, CV_32F);
bilateralFilter (mat_in_32F, mat_out_32F, 5, 160, 2);
Mat mat_out_16S = Mat (mat_in_16S.size(), mat_in_16S.type(), output);
mat_out_32F.convertTo (mat_out_16S, CV_16S);
return 0;
}
void doCorrectIntensityVariation(Mat& image)
{
Mat kernel = getStructuringElement(MORPH_ELLIPSE, Size(19,19));
Mat closed;
morphologyEx(image, closed, MORPH_CLOSE, kernel);
image.convertTo(image, CV_32F); // divide requires floating-point
divide(image, closed, image, 1, CV_32F);
normalize(image, image, 0, 255, NORM_MINMAX);
image.convertTo(image, CV_8UC1); // convert back to unsigned int
}
inline void correctIntensityVariation(IplImage *img)
{
//Mat imgMat(img); copy the img
Mat imgMat;
imgMat = img; //no copy is done, imgMat is a header of img
doCorrectIntensityVariation(imgMat);
imshow("gamma corrected",imgMat); cvWaitKey(0);
}
When I call
cvShowImage ("normal", n_im); cvWaitKey (0);
correctIntensityVariation(n_im);//here n_im is IplImage*
cvShowImage ("After processed", n_im); cvWaitKey (0);
// here I require n_im for further processing
I wanted "After processed" to be same as that of "gamma corrected" but what I found "After processed" was not the same as that of "gamma corrected" but same as that of "normal" . Why?? What is going wrong??
A very simple wrapper should do the job
Cheetsheet of openCV
I rarely use the old api, because Mat are much more easier to deal with, and
they do not have performance penalty when compare with the old c api.Like the openCV
tutorial page say The main downside of the C++ interface is that many embedded development systems at the moment support only C. Therefore, unless you are targeting embedded platforms, there’s no point to using the old methods (unless you’re a masochist programmer and you’re asking for trouble).
openCV tutorial
cv::Mat to Ipl
Ipl to cv::Mat and Mat to Ipl
IplImage* pImg = cvLoadImage(“lena.jpg”);
cv::Mat img(pImg,0); //transform Ipl to Mat, 0 means do not copy
IplImage qImg; //not pointer, it is impossible to overload the operator of raw pointer
qImg = IplImage(img); //transform Mat to Ipl
Edit : I did a mistake earlier, if the Mat would be reallocated in the function, you need
to copy or try to steal the resource(I don't know how to do it yet) from the Mat.
Copy the data
void doCorrectIntensityVariation(cv::Mat& image)
{
cv::Mat kernel = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(19,19));
cv::Mat closed;
cv::morphologyEx(image, closed, cv::MORPH_CLOSE, kernel);
image.convertTo(image, CV_32F); // divide requires floating-point
cv::divide(image, closed, image, 1, CV_32F);
cv::normalize(image, image, 0, 255, cv::NORM_MINMAX);
image.convertTo(image, CV_8UC1); // convert back to unsigned int
}
//don't need to change the name of the function, the compiler treat
//these as different function in c++
void doCorrectIntensityVariation(IplImage **img)
{
cv::Mat imgMat;
imgMat = *img; //no copy is done, imgMat is a header of img
doCorrectIntensityVariation(imgMat);
IplImage* old = *img;
IplImage src = imgMat;
*img = cvCloneImage(&src);
cvReleaseImage(&old);
}
int main()
{
std::string const name = "onebit_31.png";
cv::Mat mat = cv::imread(name);
if(mat.data){
doCorrectIntensityVariation(mat);
cv::imshow("gamma corrected mat",mat);
cv::waitKey();
}
IplImage* templat = cvLoadImage(name.c_str(), 1);
if(templat){
doCorrectIntensityVariation(&templat);
cvShowImage("mainWin", templat);
// wait for a key
cvWaitKey(0);
cvReleaseImage(&templat);
}
return 0;
}
you could write a small function to alleviate the chores
void copy_mat_Ipl(cv::Mat const &src, IplImage **dst)
{
IplImage* old = *dst;
IplImage temp_src = src;
*dst = cvCloneImage(&temp_src);
cvReleaseImage(&old);
}
and call it in the function
void doCorrectIntensityVariation(IplImage **img)
{
cv::Mat imgMat;
imgMat = *img; //no copy is done, imgMat is a header of img
doCorrectIntensityVariation(imgMat);
copy_mat_to_Ipl(imgMat, img);
}
I will post how to "steal" the resource from Mat rather than copy after
I figure out a solid solution.Anyone know how to do it?
I'm using OpenCV to extract a subimage of a scanned document and would like to use tesseract to perform OCR over this subimage.
I found out that I can use two methods for text recognition in tesseract, but so far I wasn't able to find a working solution.
A.) How can I convert a cv::Mat into a PIX*?
(PIX* is a datatype of leptonica)
Based on vasiles code below, this is essentially my current code:
cv::Mat image = cv::imread("c:/image.png");
cv::Mat subImage = image(cv::Rect(50, 200, 300, 100));
int depth;
if(subImage.depth() == CV_8U)
depth = 8;
//other cases not considered yet
PIX* pix = pixCreateHeader(subImage.size().width, subImage.size().height, depth);
pix->data = (l_uint32*) subImage.data;
tesseract::TessBaseAPI tess;
STRING text;
if(tess.ProcessPage(pix, 0, 0, &text))
{
std::cout << text.string();
}
While it doesn't crash or anything, the OCR result still is wrong. It should recognize one word of my sample image, but instead it returns some non-readable characters.
The method PIX_HEADER doesn't exist, so I used pixCreateHeader, but it doesn't take the number of channels as an argument. So how can I set the number of channels?
B.) How can I use cv::Mat for TesseractRect() ?
Tesseract offers another method for text recognition with this signature:
char * TessBaseAPI::TesseractRect (
const UINT8 * imagedata,
int bytes_per_pixel,
int bytes_per_line,
int left,
int top,
int width,
int height
)
Currently I am using the following code, but it also returns non-readable characters (although different ones than from the code above.
char* cr = tess.TesseractRect(
subImage.data,
subImage.channels(),
subImage.channels() * subImage.size().width,
0,
0,
subImage.size().width,
subImage.size().height);
tesseract::TessBaseAPI tess;
cv::Mat sub = image(cv::Rect(50, 200, 300, 100));
tess.SetImage((uchar*)sub.data, sub.size().width, sub.size().height, sub.channels(), sub.step1());
tess.Recognize(0);
const char* out = tess.GetUTF8Text();
For Anybody using the JavaCPP presets of OpenCV/Tesseract, here is what works
Mat img = imread("file.jpg");
Mat gray = new Mat();
cvtColor(img, gray, CV_BGR2GRAY);
// api is a Tesseract client which is initialised
api.SetImage(gray.data().asBuffer(),gray.size().width(),gray.size().height(),gray.channels(),gray.size1())
cv::Mat image = cv::imread(argv[1]);
cv::Mat gray;
cv::cvtColor(image, gray, CV_BGR2GRAY);
PIX *pixS = pixCreate(gray.size().width, gray.size().height, 8);
for(int i=0; i<gray.rows; i++)
for(int j=0; j<gray.cols; j++)
pixSetPixel(pixS, j,i, (l_uint32) gray.at<uchar>(i,j));
First, make a deep copy of your subImage, so that it will be stored in a coninuous memory block:
cv::Mat subImage = image(cv::Rect(50, 200, 300, 100)).clone();
Then, init a PIX headed (I don't know how) with the correct parameters.
// ???? Put your own constructor here.
PIX* pix = new PIX_HEADER(width, height, channels, depth);
OR, create it manually:
PIX pix;
pix.width = subImage.width;
...
Then set the pix data pointer to the subImage data pointer
pix.data = subImage.data;
Finally, make sure your subImage objects does not go out of scope before you finish your work with pix.
I am wondering how would I convert the OpenCV C++ standard cv::Mat type to QImage. I have been searching around, but have no luck. I have found some code that converts the IPlimage to QImage, but that is not what I want. Thanks.
Michal Kottman's answer is valid and give expected result for some images but it'll fail on some cases. Here is a solution i found to that problem.
QImage imgIn= QImage((uchar*) img.data, img.cols, img.rows, img.step, QImage::Format_RGB888);
Difference is adding img.step part. qt won't complain without it but some images won't show properly without it. Hope this will help.
To convert from cv::Mat to QImage, you could try to use the QImage(uchar * data, int width, int height, Format format) constructor as follows (mat is a cv::Mat) :
QImage img((uchar*)mat.data, mat.cols, mat.rows, QImage::Format_RGB32);
It is more efficient than manually converting the pixels to the QImage, but you have to keep the original cv::Mat image in memory. It can be easily converted to a QPixmap and displayed using a QLabel:
QPixmap pixmap = QPixmap::fromImage(img);
myLabel.setPixmap(pixmap);
Update
Because OpenCV uses BGR order by default, you should first use cvtColor(src, dst, CV_BGR2RGB) to get an image layout that Qt understands.
Update 2:
If the image you are trying to show has nonstandard stride (when it is non-continuous, submatrix), the image may appeard distorted. In this case, it is better to explicitly specify the stride using cv::Mat::step1():
QImage img((uchar*)mat.data, mat.cols, mat.rows, mat.step1(), QImage::Format_RGB32);
Here is code for 24bit RGB and grayscale floating point. Easily adjustable for other types. It is as efficient as it gets.
QImage Mat2QImage(const cv::Mat3b &src) {
QImage dest(src.cols, src.rows, QImage::Format_ARGB32);
for (int y = 0; y < src.rows; ++y) {
const cv::Vec3b *srcrow = src[y];
QRgb *destrow = (QRgb*)dest.scanLine(y);
for (int x = 0; x < src.cols; ++x) {
destrow[x] = qRgba(srcrow[x][2], srcrow[x][1], srcrow[x][0], 255);
}
}
return dest;
}
QImage Mat2QImage(const cv::Mat_<double> &src)
{
double scale = 255.0;
QImage dest(src.cols, src.rows, QImage::Format_ARGB32);
for (int y = 0; y < src.rows; ++y) {
const double *srcrow = src[y];
QRgb *destrow = (QRgb*)dest.scanLine(y);
for (int x = 0; x < src.cols; ++x) {
unsigned int color = srcrow[x] * scale;
destrow[x] = qRgba(color, color, color, 255);
}
}
return dest;
}
OpenCV loads images into a Mat in Blue-Green-Red (BGR) format by default, while QImage expects RGB. This means that if you convert a Mat to QImage, the blue and red channels will be swapped. To fix this, before constructing the QImage, you need to change the BRG format of your Mat to RGB, via the cvtColor method using argument CV_BGR2RGB, like so:
Mat mat = imread("path/to/image.jpg");
cvtColor(mat, mat, CV_BGR2RGB);
QImage image(mat.data, mat.cols, mat.rows, QImage::Format_RGB888);
Alternatively, use rgbSwapped() on the QImage
QImage image = QImage(mat.data, mat.cols, mat.rows, QImage::Format_RGB888).rgbSwapped());
Mat opencv_image = imread("fruits.jpg", CV_LOAD_IMAGE_COLOR);
Mat dest;
cvtColor(opencv_image, dest,CV_BGR2RGB);
QImage image((uchar*)dest.data, dest.cols, dest.rows,QImage::Format_RGB888);
This is what worked for me. I modified Michal Kottman's code above.
I have the same problem as you too, so I develop four functions to alleviate my pain, they are
QImage mat_to_qimage_cpy(cv::Mat const &mat, bool swap = true);
QImage mat_to_qimage_ref(cv::Mat &mat, bool swap = true);
cv::Mat qimage_to_mat_cpy(QImage const &img, bool swap = true);
cv::Mat qimage_to_mat_ref(QImage &img, bool swap = true);
These functions can handle the images with 1, 3, 4 channels, every pixel must occupy one byte only(CV_8U->Format_Indexed8, CV_8UC3->QImage::Format_RGB888, CV_8UC4->QImage::Format_ARGB32), I do not deal with other types yet(QImage::Format_RGB16, QImage::Format_RGB666 and so on). The codes are located
at github.
The key concepts of **transform mat to Qimage ** are
/**
* #brief copy QImage into cv::Mat
*/
struct mat_to_qimage_cpy_policy
{
static QImage start(cv::Mat const &mat, QImage::Format format)
{
//The fourth parameters--mat.step is crucial, because
//opencv may do padding on every row, you need to tell
//the qimage how many bytes per row
//The last thing is if you want to copy the buffer of cv::Mat
//to the qimage, you need to call copy(), else the qimage
//will share the buffer of cv::Mat
return QImage(mat.data, mat.cols, mat.rows, mat.step, format).copy();
}
};
struct mat_to_qimage_ref_policy
{
static QImage start(cv::Mat &mat, QImage::Format format)
{
//every thing are same as copy policy, but this one share
//the buffer of cv::Mat but not copy
return QImage(mat.data, mat.cols, mat.rows, mat.step, format);
}
};
The key concepts of transform cv::Mat to Qimage are
/**
* #brief copy QImage into cv::Mat
*/
struct qimage_to_mat_cpy_policy
{
static cv::Mat start(QImage const &img, int format)
{
//same as convert mat to qimage, the fifth parameter bytesPerLine()
//indicate how many bytes per row
//If you want to copy the data you need to call clone(), else QImage
//cv::Mat will share the buffer
return cv::Mat(img.height(), img.width(), format,
const_cast<uchar*>(img.bits()), img.bytesPerLine()).clone();
}
};
/**
* #brief make Qimage and cv::Mat share the same buffer, the resource
* of the cv::Mat must not deleted before the QImage finish
* the jobs.
*/
struct qimage_to_mat_ref_policy
{
static cv::Mat start(QImage &img, int format)
{
//same as copy policy, but this one will share the buffer
return cv::Mat(img.height(), img.width(), format,
img.bits(), img.bytesPerLine());
}
};
If would be good if some one can extend these functions and make them support more types, please inform me if there are any bugs.
cv::Mat has a conversion operator to IplImage, so if you have something that converts the IplImage to a QImage, just use that (or make the - probably minor - adjustments to take the cv::Mat directly, the memory layout is the same, it's "just" the header that is different.)
This post shows how to convert a QImage to OpenCV's IplImage and vise-versa.
After that, if you need help to convert between IplImage* to cv::Mat:
// Assume data is stored by:
// IplImage* image;
cv::Mat mat(image, true); // Copies the data from image
cv::Mat mat(image, false); // Doesn't copy the data!
It's a hack, but will get the job done.
Use the static function convert16uc1 for the depth image:
QPixmap Viewer::convert16uc1(const cv::Mat& source)
{
quint16* pSource = (quint16*) source.data;
int pixelCounts = source.cols * source.rows;
QImage dest(source.cols, source.rows, QImage::Format_RGB32);
char* pDest = (char*) dest.bits();
for (int i = 0; i < pixelCounts; i++)
{
quint8 value = (quint8) ((*(pSource)) >> 8);
*(pDest++) = value; // B
*(pDest++) = value; // G
*(pDest++) = value; // R
*(pDest++) = 0; // Alpha
pSource++;
}
return QPixmap::fromImage(dest);
}
QPixmap Viewer::convert8uc3(const cv::Mat& source)
{
quint8* pSource = source.data;
int pixelCounts = source.cols * source.rows;
QImage dest(source.cols, source.rows, QImage::Format_RGB32);
char* pDest = (char*) dest.bits();
for (int i = 0; i < pixelCounts; i++)
{
*(pDest++) = *(pSource+2); // B
*(pDest++) = *(pSource+1); // G
*(pDest++) = *(pSource+0); // R
*(pDest++) = 0; // Alpha
pSource+=3;
}
return QPixmap::fromImage(dest);
}
QPixmap Viewer::convert16uc3(const cv::Mat& source)
{
quint16* pSource = (quint16*) source.data;
int pixelCounts = source.cols * source.rows;
QImage dest(source.cols, source.rows, QImage::Format_RGB32);
char* pDest = (char*) dest.bits();
for (int i = 0; i < pixelCounts; i++)
{
*(pDest++) = *(pSource+2); // B
*(pDest++) = *(pSource+1); // G
*(pDest++) = *(pSource+0); // R
*(pDest++) = 0; // Alpha
pSource+=3;
}
return QPixmap::fromImage(dest);
}
This did the trick for me. It's a little dodgy, has terrible performance (as pointed out in the comments), but works with all color formats I have thrown at it so far, and it is also very simple to do.
The procedure is as follows:
cv::Mat image = //...some image you want to display
// 1. Save the cv::Mat to some temporary file
cv::imwrite("../Images/tmp.jpg",image);
// 2. Load the image you just saved as a QImage
QImage img;
img.load("../Images/tmp.jpg");
Done!
If you, say, want to display it in a QLabel, then continue with:
// Set QImage as content of MyImageQLabel
ui-> MyImageQLabel->setPixmap(QPixmap::fromImage(img, Qt::AutoColor));
I personally use this for a simple image editor.