I am working on a C++ function (inside my iOS app) where I have image data in the form uint8_t*.
I obtained the image data using the code using the CVPixelBufferGetBaseAddress() method of the iOS SDK:
uint8_t *bPixels = (uint8_t *)CVPixelBufferGetBaseAddress(imageBuffer);
I have another function (from a third part source) that does some of the image processing functions I would like to use on my image data, but the input for the image data for these functions is double**.
Does anyone have any idea how to go about converting this?
What other information can I provide?
The constructor prototype for the class that use double** look like:
Image(double **iPixels, unsigned int iWidth, unsigned int iHeight);
Your uint8_t *bPixels seems to hold image data as 1-dimensional continuous array of height*width lenght. So to access pixel in the x-th row and y-th column you have to write bPixels[x*width+y].
Image() seems to work on 2-dimensional arrays. To access pixel like above you would have to write iPixels[x][y].
So you need to copy your existing 1-dimensional array to a 2-dimensional:
double **mypixels = new double* [height];
for (int x=0; x<height; x++)
{
mypixels[x] = new double [width];
for (int y=0; y<width; y++)
mypixels[x][y] = bPixels[x*width+y]; // attention here, maybe normalization is necessary
// e.g. mypixels[x][y] = bPixels[x*width+y] / 255.0
}
Because your 1-dimensional array has pixel of type uint8_t and the 2-dimensional one pixel of type double, you must allocate new memory. Otherwise, if both would have same pixel type, the more elegant solution (a simple map) would be:
uint8_t **mypixels = new uint8_t* [height];
for (int x=0; x<height; x++)
mypixels[x] = bPixels+x*width;
Attention: beside the problem of eventually necessary normalization, there is also a problem with the indices-compatibility! My examples assume that the 1-dimensional array is stored row-by-row and that the functions working on 2-dimensional index with [x][y] (that means first-row-then-column). The declaration of Image() however, could lead to the conclusion that it needs its arrays to be indexed with [y][x] maybe.
I'm going to take a giant bunch of guesses here in hopes that this will lead you towards getting at the documentation and answering back. If there's no further documentation, well, here's a starting point.
Guess 1) The Image constructor requires a doubly dimensioned array where each component is an R,G,B,Alpha channel in that order. So iPixels[0] is the red data, iPixels[1] is the green data, etc.
Guess 2) Because it's not integer data, the values range from 0 to 1.
Guess 3) All of this must be pre-allocated.
Guess 4) Image data is row-major
Guess 5) Source data is BRGA
So with that in mind, starting with bPixels
double *redData = new double[width*height];
double *greenData = new double[width*height];
double *blueData = new double[width*height];
double *alphaData = new double[width*height];
double **iPixels = new double*[4];
iPixels[0] = redData;
iPixels[1] = greenData;
iPixels[2] = blueData;
iPixels[3] = alphaData;
for(int y = 0;y < height;y++)
{
for(int x = 0;x < width;x++)
{
int alpha = bPixels[(y*width + x)*4 + 3];
int red = bPixels[(y*width +x)*4 + 2];
int green = bPixels[(y*width + x)*4 + 1];
int blue = bPixels[(y*width + x)*4];
redData[y*width + x] = red/255.0;
greenData[y*width + x] = green/255.0;
blueData[y*width + x] = blue/255.0;
alphaData[y*width + x] = alpha/255.0;
}
}
Image newImage(iPixels,width,height);
some of the things that can go wrong.
Source is not BGRA but RGBA, which will make the colors all wrong.
Not row major or destination is not in slices which will make things look all screwed up and/or seg-fault
Related
I try to extract the region of interest (ROI) in a Matrix in OpenCV. It can be easy to do by cv:Rect, e.g., im_roi = im(Rect(x,y, width, height)). But I prefer to get the data directly from the memory using pointers, which is presumably more efficient. Here below are my codes:
Mat im_roi; //the desired matrix holding ROI of im, uninitialized
uchar* im_roi_data = im_roi.data;
uchar* im_data = im.data;
int xstart = x;
int xend = xstart + width;
int ystart = y;
int yend = ystart + height;
for(ii=ystart; ii<yend; ii++)
{
for(jj=xstart; jj<xend; jj++) //the typo 'jj<xstart' was corrected
{
*im_roi_data++ = *im_data++;
*im_roi_data++ = *im_data++;
*im_roi_data++ = *im_data++;
}
im_data +=3*(im.cols-width);
}
The above for-loop codes however do not proceed. I feel the problem may be due to the uninitialized im_roi.
I think your second for loop needs to be:
for(jj=xstart; jj<xend; jj++)
As Mark Setchell noted it is not the only problem with your code, but yes you must initialize im_roi before accassing its pixels.
Using memcpy to copy content of whole row will be much more effecient then copying data pixel by pixel.
Writing im(Rect(x,y, width, height)).copyTo(im_roi); will be the cleanest AND fastest method of coping ROI (and in that case you don't need to initialize im_roi).
Suppose I have a Mat of indices (locations) called B, We can say that this Mat has dimensions of 1 x 100 and We suppose to have another Mat, called A, full of data of the same dimensions of B.
Now, I would access to the data of A with B. Usually I would create a for loop and I would take for each elements of B, the right elements of A. For the most fussy of the site, this is the code that I would write:
for(int i=0; i < B.cols; i++){
int index = B.at<int>(0, i);
std::cout<<A.at<int>(0, index)<<std:endl;
}
Ok, now that I showed you what I could do, I ask you if there is a way to access the matrix A, always using the B indices, in a more intelligent and fast way. As someone could do in python thanks to the numpy.take() function.
This operation is called remapping. In OpenCV, you can use function cv::remap for this purpose.
Below I present the very basic example of how remap algorithm works; please note that I don't handle border conditions in this example, but cv::remap does - it allows you to use mirroring, clamping, etc. to specify what happens if the indices exceed the dimensions of the image. I also don't show how interpolation is done; check the cv::remap documentation that I've linked to above.
If you are going to use remapping you will probably have to convert indices to floating point; you will also have to introduce another array of indices that should be trivial (all equal to 0) if your image is one-dimensional. If this starts to represent a problem because of performance, I'd suggest you implement the 1-D remap equivalent yourself. But benchmark first before optimizing, of course.
For all the details, check the documentation, which covers everything you need to know to use te algorithm.
cv::Mat<float> remap_example(cv::Mat<float> image,
cv::Mat<float> positions_x,
cv::Mat<float> positions_y)
{
// sizes of positions arrays must be the same
int size_x = positions_x.cols;
int size_y = positions_x.rows;
auto out = cv::Mat<float>(size_y, size_x);
for(int y = 0; y < size_y; ++y)
for(int x = 0; x < size_x; ++x)
{
float ps_x = positions_x(x, y);
float ps_y = positions_y(x, y);
// use interpolation to determine intensity at image(ps_x, ps_y),
// at this point also handle border conditions
// float interpolated = bilinear_interpolation(image, ps_x, ps_y);
out(x, y) = interpolated;
}
return out;
}
One fast way is to use pointer for both A (data) and B (indexes).
const int* pA = A.ptr<int>(0);
const int* pIndexB = B.ptr<int>(0);
int sum = 0;
for(int i = 0; i < Bi.cols; ++i)
{
sum += pA[*pIndexB++];
}
Note: Be carefull with pixel type, in this case (as you write in your code) is int!
Note2: Using cout for each point access put the optimization useless!
Note3: In this article Satya compare four methods for pixel access and fastest seems "foreach": https://www.learnopencv.com/parallel-pixel-access-in-opencv-using-foreach/
EDIT: I will improve this question. I will clarify it right in a little days.
first, I am writing a litlle bmp image analyzer. I have the following problem: The image is stored on plain bytes, without format as an array.
The image is 24 bits, and requires 3 bytes per pixel. I have tried with a solution that I have found on this stackoverflow page, but I can not adapt it for structures.
I have tried but it references invalid areas and bytes. Here's my complete code if you want to see it in TinyPaste (just for a better highlighting): The code in TinyPaste
EDIT 1: This code is in C++, I want to translate it to pure C for portability reasons. This is just the example from I taken the idea of convert a linear array to bidimensional. I have tried to adapt it to pure C for structs but I fail.
This snippet was taken from a stackoverflow question that made me think about this
//The resulting array
unsigned int** array2d;
// Linear memory allocation
unsigned int* temp = new unsigned int[sizeX * sizeY];
// These are the important steps:
// Allocate the pointers inside the array,
// which will be used to index the linear memory
array2d = new unsigned int*[sizeY];
// Let the pointers inside the array point to the correct memory addresses
for (int i = 0; i < sizeY; ++i)
{
array2d[i] = (temp + i * sizeX);
}
// Fill the array with ascending numbers
for (int y = 0; y < sizeY; ++y)
{
for (int x = 0; x < sizeX; ++x)
{
array2d[y][x] = x + y * sizeX;
}
}
I adapt it to reference structs, but it fails. I have tried multiplying by three in this line:
array2d[i] = (temp + i * sizeX /* multiply by 3*/);
But it still without work. I have also done the related castings from char to the struct bmp_pixel(char r, char g, char b).
Can somebody tell me how to adapt it to pure C for structs?? Thanks.
I guess it's such an easy question (I'm coming from Java), but I can't figure out how it works.
I simply want to increment an vector element by one. The reason for this is, that I want to compute a histogram out of image values. But whatever I try I just can accomplish to assign a value to the vector. But not to increment it by one!
This is my histogram function:
void histogram(unsigned char** image, int height,
int width, vector<unsigned char>& histogramArray) {
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
// histogramArray[1] = (int)histogramArray[1] + (int)1;
// add histogram position by one if greylevel occured
histogramArray[(int)image[i][j]]++;
}
}
// display output
for (int i = 0; i < 256; i++) {
cout << "Position: " << i << endl;
cout << "Histogram Value: " << (int)histogramArray[i] << endl;
}
}
But whatever I try to add one to the histogramArray position, it leads to just 0 in the output. I'm only allowed to assign concrete values like:
histogramArray[1] = 2;
Is there any simple and easy way? I though iterators are hopefully not necesarry at this point, because I know the exakt index position where I want to increment something.
EDIT:
I'm so sorry, I should have been more precise with my question, thank you for your help so far! The code above is working, but it shows a different mean value out of the histogram (difference of around 90) than it should. Also the histogram values are way different than in a graphic program - even though the image values are exactly the same! Thats why I investigated the function and found out if I set the histogram to zeros and then just try to increase one element, nothing happens! This is the commented code above:
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
histogramArray[1]++;
// add histogram position by one if greylevel occured
// histogramArray[(int)image[i][j]]++;
}
}
So the position 1 remains 0, instead of having the value height*width. Because of this, I think the correct calculation histogramArray[image[i][j]]++; is also not working properly.
Do you have any explanation for this? This was my main question, I'm sorry.
Just for completeness, this is my mean function for the histogram:
unsigned char meanHistogram(vector<unsigned char>& histogram) {
int allOccurences = 0;
int allValues = 0;
for (int i = 0; i < 256; i++) {
allOccurences += histogram[i] * i;
allValues += histogram[i];
}
return (allOccurences / (float) allValues) + 0.5f;
}
And I initialize the image like this:
unsigned char** image= new unsigned char*[width];
for (int i = 0; i < width; i++) {
image[i] = new unsigned char[height];
}
But there shouldn't be any problem with the initialization code, since all other computations work perfectly and I am able to manipulate and safe the original image. But it's true, that I should change width and height - since I had only square images it didn't matter so far.
The Histogram is created like this and then the function is called like that:
vector<unsigned char> histogramArray(256);
histogram(array, adaptedHeight, adaptedWidth, histogramArray);
So do you have any clue why this part histogramArray[1]++; don't increases my histogram? histogramArray[1] remains 0 all the time! histogramArray[1] = 2; is working perfectly. Also histogramArray[(int)image[i][j]]++; seems to calculate something, but as I said, I think it's wrongly calculating.
I appreciate any help very much! The reason why I used a 2D Array is simply because it is asked for. I like the 1D version also much more, because it's way simpler!
You see, the current problem in your code is not incrementing a value versus assigning to it; it's the way you index your image. The way you've written your histogram function and the image access part puts very fine restrictions on how you need to allocate your images for this code to work.
For example, assuming your histogram function is as you've written it above, none of these image allocation strategies will work: (I've used char instead of unsigned char for brevity.)
char image [width * height]; // Obvious; "char[]" != "char **"
char * image = new char [width * height]; // "char*" != "char **"
char image [height][width]; // Most surprisingly, this won't work either.
The reason why the third case won't work is tough to explain simply. Suffice it to say that a 2D array like this will not implicitly decay into a pointer to pointer, and if it did, it would be meaningless. Contrary to what you might read in some books or hear from some people, in C/C++, arrays and pointers are not the same thing!
Anyway, for your histogram function to work correctly, you have to allocate your image like this:
char** image = new char* [height];
for (int i = 0; i < height; ++i)
image[i] = new char [width];
Now you can fill the image, for example:
for (int i = 0; i < height; ++i)
for (int j = 0; j < width; ++j)
image[i][j] = rand() % 256; // Or whatever...
On an image allocated like this, you can call your histogram function and it will work. After you're done with this image, you have to free it like this:
for (int i = 0; i < height; ++i)
delete[] image[i];
delete[] image;
For now, that's enough about allocation. I'll come back to it later.
In addition to the above, it is vital to note the order of iteration over your image. The way you've written it, you iterate over your columns on the outside, and your inner loop walks over the rows. Most (all?) image file formats and many (most?) image processing applications I've seen do it the other way around. The memory allocations I've shown above also assume that the first index is for the row, and the second is for the column. I suggest you do this too, unless you've very good reasons not to.
No matter which layout you choose for your images (the recommended row-major, or your current column-major,) it is in issue that you should always keep in your mind and take notice of.
Now, on to my recommended way of allocating and accessing images and calculating histograms.
I suggest that you allocate and free images like this:
// Allocate:
char * image = new char [height * width];
// Free:
delete[] image;
That's it; no nasty (de)allocation loops, and every image is one contiguous block of memory. When you want to access row i and column j (note which is which) you do it like this:
image[i * width + j] = 42;
char x = image[i * width + j];
And you'd calculate the histogram like this:
void histogram (
unsigned char * image, int height, int width,
// Note that the elements here are pixel-counts, not colors!
vector<unsigned> & histogram
) {
// Make sure histogram has enough room; you can do this outside as well.
if (histogram.size() < 256)
histogram.resize (256, 0);
int pixels = height * width;
for (int i = 0; i < pixels; ++i)
histogram[image[i]]++;
}
I've eliminated the printing code, which should not be there anyway. Note that I've used a single loop to go through the whole image; this is another advantage of allocating a 1D array. Also, for this particular function, it doesn't matter whether your images are row-major or column major, since it doesn't matter in what order we go through the pixels; it only matters that we go through all the pixels and nothing more.
UPDATE: After the question update, I think all of the above discussion is moot and notwithstanding! I believe the problem could be in the declaration of the histogram vector. It should be a vector of unsigned ints, not single bytes. Your problem seems to be that the value of the vector elements seem to stay at zero when your simplify the code and increment just one element, and are off from the values they need to be when you run the actual code. Well, this could be a symptom of numeric wrap-around. If the number of pixels in your image are a a multiple of 256 (e.g. 32x32 or 1024x1024 image) then it is natural that the sum of their number would be 0 mod 256.
I've already alluded to this point in my original answer. If you read my implementation of the histogram function, you see in the signature that I've declared my vector as vector<unsigned> and have put a comment above it that says this victor counts pixels, so its data type should be suitable.
I guess I should have made it bolder and clearer! I hope this solves your problem.
A function that I am trying to conform to requires three 1-Dimensional arrays of type double[19200]. The following arrays are RGB arrays such that:
double r[19200]; // r
double g[19200]; // g
double b[19200]; // b
So far, I can extract pixel information from a QImage and populate the above arrays.
The problem is with testing. I don't know how to do the inverse: given the three 1-Dimensional arrays how do I create a new QImage from this data?
I would like to verify that I am indeed getting the correct values. (Things like column vs. row major order is giving me doubts). As a result, I am trying to construct an image a QImage from these three 1-D Dimensional arrays.
I don't really understand why you're having a problem if you managed to do it one way. The process is essentially the same:
for (int x=0; x<w; x++)
for (int y=0; y<h; y++)
image.setPixel(x,y, convertToRGB(r[x*w+y], ...);
Where convertToRGB is the inverse transform of what you to to convert and RGB value to your float values, supposing the image has dimension w*h. If you discover this is the wrong row-major/column major variant, just inverse it.
Since you gave no info about how you do the color space conversion, and we don't know if it's row-major or column-major either, can't help you much more than that.
Well it looks like QImage supports a couple of ways to load from pixel arrays.
QImage(const uchar *data, int width, int height, Format format)
bool QImage::loadFromData(const uchar *buf, int len, const char *format=0)
Using the first example, if you have the arrays you mention, then you will likely want to use the format QImage::Format_RGB888 (from qimage.h).
You will need to know the width and height yourself.
Finally you will want to repack your arrays into a single uchar* array
uchar* rgb_array = new uchar[19200+19200+19200];
for( int i = 0, j = 0; j < 19200; ++j )
{
// here we convert from the double range 0..1 to the integer range 0..255
rgb_array[i++] = r[j] * 255;
rgb_array[i++] = g[j] * 255;
rgb_array[i++] = b[j] * 255;
}
{
QImage my_image( rgb_array, width, height, QImage::Format_RGB888 );
// do stuff with my_image...
}
delete[] rgb_array; // note you need to hold onto this array while the image still exists