I am a new user of JAVA OpenCV, and I am just learning through the official tutorial today about how to convert a Mat object to BufferedImage.
From the demo code, I can understand that the input image source is a Matrix form, and then sourcePixels seems going to be an array of bytes representation of the image, so we need to get the values from the original matrix to the sourcePixels. Here the sourcePixels has the length of the whole image bytes length (with size: w * h * channels), so it would take the whole image byte values at once.
Then it comes this which is not intuitive to me. The System.arraycopy() seems copying the values from the sourcePixels to the targetPixels, but what actaully returns is image. I can guess from the code that targetPixels has relationship with image, but I don't see how we copy values from sourcePixels to targetPixels, but it actually affects values of image?
Here's the demo code. Thanks!
private static BufferedImage matToBufferedImage(Mat original)
{
BufferedImage image = null;
int width = original.width(), height = original.height(), channels = original.channels();
byte[] sourcePixels = new byte[width * height * channels];
original.get(0, 0, sourcePixels);
if (original.channels() > 1)
{
image = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR);
}
else
{
image = new BufferedImage(width, height, BufferedImage.TYPE_BYTE_GRAY);
}
final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
System.arraycopy(sourcePixels, 0, targetPixels, 0, sourcePixels.length);
return image;
}
Each BufferedImage is backed by a byte array just like the Mat class from OpenCV, the call to ((DataBufferByte) image.getRaster().getDataBuffer()).getData(); returns this underlying byte array and assigns it to targetPixels, in other words, targetPixels points to this underlying byte array that the BufferedImage image is currently wrapping around, so when you call System.arraycopy you are actually copying from the source byte array into the byte array of the BufferedImage, that's why the image is being returned, because at that point, the underlying byte array that image encapsulates contains the pixel data from original, it's like this smal example, where after making b points to a, modifications to b will also reflect in a, just like tagetPixels, because it points to the byte array image is encapsulating, copying from sourcePixels into targetPixels will also change the image
int[] a = new int[1];
int[] b = a;
// Because b references the same array that a does
// Modifying b will actually change the array a is pointing to
b[0] = 1;
System.out.println(a[0] == 1);
Related
I am trying to find an efficient way to see if one image is a subset of another (meaning that each unique pixel in one image is also found in the other.) The repetition or ordering of the pixels do not matter.
I am working in Java, so I would like all of my operations to be completed in OpenCV for efficiency's sake.
My first idea was to export a list of unique pixel values, and compare it to the list from the second image.
As there is not a built in function to extract unique pixels, I abandoned this approach.
I also understand that I can find the locations of a particular color with the inclusive inRange, and findNonZero operations.
Core.inRange(image, color, color, tempMat); // inclusive
Core.findNonZero(tempMat, colorLocations);
Unfortunately, this does not provide an adequate answer, as it would need to be executed per color, and would still require extracting unique pixels.
Essentially, I'm asking if there is a clever way to use the built in OpenCV functions to see if an image is comprised of the pixels found in another image.
I understand that this will not work for slight color differences. I am working on a limited dataset, and care about the exact pixel values.
To put the question more mathematically:
Because the only think you are interested in is the pixel values i would suggest to do the following.
Compute the histogram of image 1 using hist1 = calcHist()
Compute the histogram of image 2 using hist2 = calcHist()
Calculate the difference vector diff = hist1 - hist2
Check if each bin of the hist of the subimage is less or equal than the corresponding bin in the hist of the bigger image
Thanks to Miki for the fix.
I will keep Amitay's as the accepted answer, as he absolutely lead me down the correct path. I wanted to also share my exact answer for anyone who finds this in the future.
As I stated in my question, I was looking for an efficient way to see if the RGB values of one image were a subset of the RGB values of another image.
I made a function to the following specification:
The Java code is as follows:
private boolean isSubset(Mat subset, Mat subMask, Mat superset) {
// Get unique set of pixels from both images
subset = getUniquePixels(subset, subMask);
superset = getUniquePixels(superset, null);
// See if the superset pixels encapsulate the subset pixels
// OR the unique pixels together
Mat subOrSuper = new Mat();
Core.bitwise_or(subset, superset, subOrSuper);
//See if the ORed matrix is equal to the superset
Mat notEqualMat = new Mat();
Core.compare(superset, subOrSuper, notEqualMat, Core.CMP_NE);
return Core.countNonZero(notEqualMat) == 0;
}
subset and superset are assumed to be CV_8UC3 matricies, while subMask is assumed to be CV_8UC1.
private Mat getUniquePixels(Mat img, Mat mask) {
if (mask == null) {
mask = new Mat();
}
// int bgrValue = (b << 16) + (g << 8) + r;
img.convertTo(img, CvType.CV_32FC3);
Vector<Mat> splitImg = new Vector<>();
Core.split(img, splitImg);
Mat flatImg = Mat.zeros(img.rows(), img.cols(), CvType.CV_32FC1);
Mat multiplier;
for (int i = 0; i < splitImg.size(); i++) {
multiplier = Mat.ones(img.rows(), img.cols(), CvType.CV_32FC1);
// set powTwo = to 2^i;
int powTwo = (1 << i);
// Set multiplier matrix equal to powTwo;
Core.multiply(multiplier, new Scalar(powTwo), multiplier);
// n<<i == n * 2^i;
// I'm shifting the RGB values into separate parts of the same 32bit
// integer.
Core.multiply(multiplier, splitImg.get(i), splitImg.get(i));
// Add the shifted RGB components together.
Core.add(flatImg, splitImg.get(i), flatImg);
}
// Create a histogram of the pixel values.
List<Mat> images = new ArrayList<>();
images.add(flatImg);
MatOfInt channels = new MatOfInt(0);
Mat hist = new Mat();
// 16777216 == 256*256*256
MatOfInt histSize = new MatOfInt(16777216);
MatOfFloat ranges = new MatOfFloat(0f, 16777216f);
Imgproc.calcHist(images, channels, mask, hist, histSize, ranges);
Mat uniquePixels = new Mat();
Core.inRange(hist, new Scalar(1), new Scalar(Float.MAX_VALUE), uniquePixels);
return uniquePixels;
}
Please feel free to ask questions, or point out problems!
I have tried the cvMatchTemplate function to compare two images(a template and an image).
IplImage img = cvLoadImage("thumbnail.jpg");
IplImage template = cvLoadImage("temp.jpg");
IplImage result = cvCreateImage(cvSize(img.width()-template.width()+1, img.height()-template.height()+1), IPL_DEPTH_32F, 1);
int method = CV_TM_SQDIFF;
cvMatchTemplate(img,template,result,method);
cvShowImage("res",result);
double[] min_val = new double[2];
double[] max_val = new double[2];
//Where are located our max and min correlation points
CvPoint minLoc = new CvPoint();
CvPoint maxLoc = new CvPoint();
cvMinMaxLoc(result, min_val, max_val, minLoc, maxLoc, null); //the last null it's for optional mask mat()
CvPoint point = new CvPoint();
point.x(minLoc.x()+template.width());
point.y(minLoc.y()+template.height());
cvRectangle(img, minLoc, point, CvScalar.WHITE, 2, 8, 0); //Draw the rectangle result in original img.
cvShowImage("Image", img);
cvWaitKey(0);
//Release
cvReleaseImage(img);
cvReleaseImage(template);
cvReleaseImage(result);
I got the desired result but could not find a way of comparing two and more images with a template.
I converted the result image that is obtained to a matrix using asCvMat and got the matrix of probability of match on every pixel of original image.
I came across the determinant function in OpenCv to compare the two matrices to understand which of the images is a closer match to the template but could not find a corresponding function in JavaCv.
Is there any way by which I could compare the results and determine that which image is a closer match. I did come across ObjectFinder but could not find proper documentation of how to use it.
Please point out certain links or examples which may help me solve my problem.
You can compare image matching results by compering the max_val
I would even change the method to CV_TM_SQDIFF_NORMED and then you can set a threshold for max_val that is somewhere between 0 to 1.
Using the new API for OpenCV 2.3, I am having trouble assigning values to a Mat array (or say image) inside a loop. Here is the code snippet which I am using;
int paddedHeight = 256 + 2*padSize;
int paddedWidth = 256 + 2*padSize;
int n = 266; // padded height or width
cv::Mat fx = cv::Mat(paddedHeight,paddedWidth,CV_64FC1);
cv::Mat fy = cv::Mat(paddedHeight,paddedWidth,CV_64FC1);
float value = -n/2.0f;
for(int i=0;i<n;i++)
{
for(int j=0;j<n;j++)
fx.at<cv::Vec2d>(i,j) = value++;
value = -n/2.0f;
}
meshElement = -n/2.0f;
for(int i=0;i<n;i++)
{
for(int j=0;j<n;j++)
fy.at<cv::Vec2d>(i,j) = value;
value++;
}
Now in the first loop as soon as j = 133, I get an exception which seems to be related to depth of the image, I cant figure out what I am doing wrong here.
Please Advise! Thanks!
You are accessing the data as 2-component double vector (using .at<cv::Vec2d>()), but you created the matrices to contain only 1 component doubles (using CV_64FC1). Either create the matrices to contain two components per element (with CV_64FC2) or, what seems more appropriate to your code, access the values as simple doubles, using .at<double>(). This explodes exactly at j=133 because that is half the size of your image and when treated as containing 2-component vectors when it only contains 1, it is only half as wide.
Or maybe you can merge these two matrices into one, containing two components per element, but this depends on the way you are going to use these matrices in the future. In this case you can also merge the two loops together and really set a 2-component vector:
cv::Mat f = cv::Mat(paddedHeight,paddedWidth,CV_64FC2);
float yValue = -n/2.0f;
for(int i=0;i<n;i++)
{
float xValue = -n/2.0f;
for(int j=0;j<n;j++)
{
f.at<cv::Vec2d>(i,j)[0] = xValue++;
f.at<cv::Vec2d>(i,j)[1] = yValue;
}
++yValue;
}
This might produce a better memory accessing scheme if you always need both values, the one from fx and the one from fy, for the same element.
I simply want to convert an Emgu.Cv.Image<,> from a pointer, I am using the following code:
Size img = CvInvoke.cvGetSize(frame);
Image<Bgr, Byte> tImg = new Image<Bgr, byte>(img.Width, img.Height, 0, frame);
I don't know what value to give in 3rd parameter of Image<,> constructor that takes a pointer. It says Size of aligned image row in bytes what does that mean?
Note that image width has to be a multiple of 4 since some OpenCV code optimization is based on this assumption when CVImage is constructed from a memory 1D array.
I'm trying to get information from an image using the function cvGet2D in OpenCV.
I created an array of 10 IplImage pointers:
IplImage *imageArray[10];
and I'm saving 10 images from my webcam:
imageArray[numPicture] = cvQueryFrame(capture);
when I call the function:
info = cvGet2D(imageArray[0], 250, 100);
where info:
CvScalar info;
I got the error:
OpenCV Error: Bad argument (unrecognized or unsupported array type) in cvPtr2D, file /build/buildd/opencv-2.1.0/src/cxcore/cxarray.cpp, line 1824
terminate called after throwing an instance of 'cv::Exception'
what(): /build/buildd/opencv-2.1.0/src/cxcore/cxarray.cpp:1824: error: (-5) unrecognized or unsupported array type in function cvPtr2D
If I use the function cvLoadImage to initialize an IplImage pointer and then I pass it to the cvGet2D function, the code works properly:
IplImage* imagen = cvLoadImage("test0.jpg");
info = cvGet2D(imagen, 250, 100);
however, I want to use the information already stored in my array.
Do you know how can I solve it?
Even though its a very late response, but I guess someone might be still searching for the solution with CvGet2D. Here it is.
For CvGet2D, we need to pass the arguments in the order of Y first and then X.
Example:
CvScalar s = cvGet2D(img, Y, X);
Its not mentioned anywhere in the documentation, but you find it only inside core.h/ core_c.h. Try to go to the declaration of CvGet2D(), and above the function prototypes, there are few comments that explain this.
Yeah the message is correct.
If you want to store a pixel value you need to do something like this.
int value = 0;
value = ((uchar *)(img->imageData + i*img->widthStep))[j*img->nChannels +0];
cout << "pixel value for Blue Channel and (i,j) coordinates: " << value << endl;
Summarizing, to plot or store data you must create an integer value (pixel value varies between 0 and 255). But if you only want to test pixel value (like in an if closure or something similar) you can access directly to pixel value without using an integer value.
I think thats a little bit weird when you start but when you work with it 2 o 3 times you will work without difficulties.
Sorry, cvGet2D is not the best way to obtain pixel value. I know its the shortest and clear way because you in only one line of code and knowing coordinates obtain the pixel value.
I suggest you this option. When you see this code you you wiil think that is so complicated but is more effecient.
int main()
{
// Acquire the image (I'm reading it from a file);
IplImage* img = cvLoadImage("image.bmp",1);
int i,j,k;
// Variables to store image properties
int height,width,step,channels;
uchar *data;
// Variables to store the number of white pixels and a flag
int WhiteCount,bWhite;
// Acquire image unfo
height = img->height;
width = img->width;
step = img->widthStep;
channels = img->nChannels;
data = (uchar *)img->imageData;
// Begin
WhiteCount = 0;
for(i=0;i<height;i++)
{
for(j=0;j<width;j++)
{ // Go through each channel of the image (R,G, and B) to see if it's equal to 255
bWhite = 0;
for(k=0;k<channels;k++)
{ // This checks if the pixel's kth channel is 255 - it can be faster.
if (data[i*step+j*channels+k]==255) bWhite = 1;
else
{
bWhite = 0;
break;
}
}
if(bWhite == 1) WhiteCount++;
}
}
printf("Percentage: %f%%",100.0*WhiteCount/(height*width));
return 0;
This code count white pixels and gives you a percetage of white pixels in the image.