This code is for 8 bit data to make gray-scale IplImage.
IplImage* img_gray_resize = NULL;
img_gray_resize = cvCreateImage(cvSize(320, 256), IPL_DEPTH_8U, 1);
DWORD dwCount;
LVDS_SetDataMode(0); // o for 8 bit mode and 1 for 16 bit mode
dwCount = (LONG)320 * (LONG)256;
unsigned char* m_pImage = NULL;
m_pImage = new unsigned char[320 * 256];
for (int i=0; i<320 * 256; i++) m_pImage[i] = NULL;
LVDS_GetFrame(&dwCount, m_pImage);
int width = 320;
int height = 256;
int nn = 0;
int ii = 0;
for (int y=0; y<height; y++)
{
for (int x=0; x<width; x++)
{
ii = y * width + x;
if(nn < (height*width))
img_gray_resize->imageData[ii] = m_pImage[nn++];
}
}
delete [] m_pImage;
I need to display 16 bit gray-scale image. If I display 8 bit data, some information is missing from the image. However, LVDS_SetDataMode() can provide both types of data. I am using a library for frame grabber device. Please help me.
16 bit images should be stored in IPL_DEPTH_16U (or CV_16U) mode. This is the correct memory layout.
However, displaying them depends on your display hardware.
Most regular display APIs, e.g. OpenCV's highgui, can only display 8-bit images.
To actually display the image, you will have to convert your image to 8-bits for display.
You will need to decide how to do this. There are many ways to do this, depending on your application and complexity. Some options are:
Show MSB = right-shift the image by 8 pixels.
Show LSB = saturate anything above 255.
In fact, right-shift by any value between 0-8 bits, combined with a cv::saturate_cast to avoid value wrap-around.
HDR->LDR = Apply dynamic range compression algorithms.
as I know,only 8bit data can be displayed,you need to find the best way to convert the 16bit to 8bit to minimize the information you lose. Histogram equalization can be applyed to do this.
Finally, I have solved the problem by following way:
dwCount = (LONG)320 * (LONG)256 * 2;
LVDS_SetDataMode(1);
img_gray_resize->imageData[ii] = m_pImage[nn++] >> 6;
Just shift bits to right (2, 3, 4, 5, 6, ...), where you get good result, use that value.
Related
I would like to perform screenshots (or screen captures) the fastest possible.
Googling this question brings many answeers but my concern is more specific :
I am not interested in the image itself, I would like to grab in near real time the screen brightness, not the hardware one, but the image one, given that, for example, the firefox white google page gives a brighter image than a dark xterm (when both are maximzed).
To make me as clear as possible, here is one way I already managed to implement with X11 and CImg library :
Here is the header :
#include <CImg.h>
using namespace cimg_library;
#include <X11/Xlib.h>
#include <X11/Xutil.h>
#include <X11/Xos.h>
and the core part which extract an X11 image and make a loop on very pixel :
Display *display = XOpenDisplay(NULL);
Window root = DefaultRootWindow(display);
Screen* screen = DefaultScreenOfDisplay(display);
const int W = WidthOfScreen(screen);
const int H = HeightOfScreen(screen);
XImage *image = XGetImage(display, root, 0, 0, W, H, AllPlanes, ZPixmap);
unsigned long red_count(0), green_count(0), blue_count(0), count(0);
const unsigned long red_mask = image->red_mask;
const unsigned long green_mask = image->green_mask;
const unsigned long blue_mask = image->blue_mask;
CImg<unsigned char> screenshot(W, H, 1, 3, 0);
for (int x = 0; x < W; x += pixel_stride)
for (int y = 0; y < H; y += pixel_stride)
{
unsigned long pixel = XGetPixel(image, x, y);
screenshot(x, y, 0) = (pixel & red_mask) >> 16;
screenshot(x, y, 1) = (pixel & green_mask) >> 8;
screenshot(x, y, 2) = pixel & blue_mask;
red_count += (int) screenshot(x, y, 0);
green_count += (int) screenshot(x, y, 1);
blue_count += (int) screenshot(x, y, 2);
count++;
}
As I said, I do not keep the image itself, I just try to compute an average luminance value with respective values of red, green and blue pixels.
XFree(image);
const double luminance_relative = (red_luminance * double(red_count) +
green_luminance * double(green_count) +
blue_luminance * double(blue_count))
/ (double(255) * double(count));
The underlying idea is to adjust the hardware screen brightness depending on the image luminance. In short, the whiter is the screenshot, the more the brightness can be reduced and conversely.
I want to do that because I have sensitive eyes, it usually hurts my eyes when I switch from xterm to firefox.
To do so, the hardware brightness must be adjusted in a very short time, the screenshot, that is to say, the loop on pixels must be as fast as possible.
I began to implement it with X11 methods, but I wonder if there could be faster access methods ? Which comes to the question : what is the fastest way/library to get a screenshot ?
Thanks in advance for your help.
Regards
I have a UIImagePickerViewController where the user takes a photo. My problem is how to know before uploading the photo to the server if the user is sending a dark photo. I mean a totally or nearly black.
I was researching and I found this:
const UInt8 *pixels = CFDataGetBytePtr(imageData);
UInt8 blackThreshold = 10; // or some value close to 0
int bytesPerPixel = 4;
for(int x = 0; x < width1; x++) {
for(int y = 0; y < height1; y++) {
int pixelStartIndex = (x + (y * width1)) * bytesPerPixel;
UInt8 alphaVal = pixels[pixelStartIndex]; // can probably ignore this value
UInt8 redVal = pixels[pixelStartIndex + 1];
UInt8 greenVal = pixels[pixelStartIndex + 2];
UInt8 blueVal = pixels[pixelStartIndex + 3];
if(redVal < blackThreshold && blueVal < blackThreshold && greenVal < blackThreshold) {
//This pixel is close to black...do something with it
}
}
}
However, I don't know how to apply the algorithm.
Yep that's a fairly simple way of doing it. You could, for example, iterate through and see what percentage of the pixels are pure black (i.e. clipped shadows) or nearly black. Or you could average the pixel colors throughout the whole image and see if it falls below a certain threshold. There are lots of approaches and these two might be a tad simplistic, but I'm not sure if this calls for anything particularly sophisticated. What threshold you want to use is up to you.
Also, while it has little practical impact, if I was going to be picky about the algorithm, I might only perform the "brightness" logic if the alphaVal was over a certain threshold, as well, as the color information is meaningless at transparent portions of image. Having said that, real photos rarely have any transparency, so this may be non-issue.
FYI, here is Apple's code for retrieving the pixel buffer. It's an oldie, but a goodie. (If I recall correctly, the only hassle is that the kCGImageAlphaPremultipliedFirst reference in CreateARGBBitmapContext must be cast with (CGBitmapInfo).)
By the way, if you're trying to determine the luminance of a particular pixel, one common algorithm is:
luminance = 0.2126 * red + 0.7152 * green + 0.0722 * blue
I've noticed that using convertTo to convert a matrix from 32-bit to 16-bit "rounds" number to the upper boud. So, values bigger than 0x0000FFFF in the source matrix will be set as 0xFFFF in the destination matrix.
What I want for my application is instead to mask the values, setting in the destination just the 2 LSB of the values.
Here is an example:
Mat mat32;
Mat mat16;
mat32 = Mat(2,2,CV_32SC1);
for(int y = 0; y < 2; y++)
for(int x = 0; x < 2; x++)
mat32.at<unsigned int>(cv::Point(x,y)) = 0x0000FFFE + (y*2+x);
mat32.convertTo(mat16, CV_16UC1);
The matrixes have these values:
32 bits matrix:
0000FFFE 0000FFFF
00010000 00010001
16 bits matrix:
0000FFFE 0000FFFF
0000FFFF 0000FFFF
In the second row of 16-bit matrix I want to have
00000000 00000001
I can do this by scanning the source matrix value-by-value and masking the values, but the performances are low.
Is there an OpenCV function that does this?
Thanks to everyone!
MIX
This can be done, but this requires a somewhat dirty trick, so it is up to you to use this approach or not. So this is how it can be done:
For this example lets create 1000x1000 32-bit matrix and set all its values to 65541 (=256*256+5). So after the conversion we expect to have a matrix filled with fives.
Mat M1(1000, 1000, CV_32S, Scalar(65541));
And here is the trick:
Mat M2(1000, 1000, CV_16SC2, M1.data);
We created matrix M2 over the same memory buffer as M1, but M2 'think' that this is a buffer of 2-channel 16-bit image. Now the last thing to do is to copy the channel you need to the place you need. This can be done by split() or mixChannels() functions. For example:
Mat M3(1000, 1000, CV_16S);
int fromto[] = {0,0};
Mat inpu[] = {M2}, outpu[] = {M3};
mixChannels(inpu, 1, outpu, 1, fromto, 1);
cout << M3.at<short>(10,10) << endl;
Ye I know that the format of mixChannels looks weird and makes the code even less readable, but it works... If you prefer split() function:
vector<Mat> v;
split(M2,v);
cout << v[0].at<short>(10,10) << " " << v[1].at<short>(10,10) << endl;
There is no OpenCV function (that I know of) which does the conversion like you want, so either you code it yourself or like you said you go through a masking step first to remove the 16 high bits.
The mask can be applied using the bitwise_and in C++ or cvAndS in C. See here.
You could also have made your hand-written code more efficient. In general, you should avoid OpenCV pixel accessors in loops because they have bad performance. I don't have an OpenCV install at hand so this could be slighlty off -- the idea is to use the data field directly, and step which is the number of bytes per row:
for(int y = 0; y < mat32.height; ++) {
int* row = (int*)( (char*)mat32.data + y * mat32.step);
for(int x = 0; x < mat32.step/ 4)
row[x] &= 0xffff;
Then, once the mask is applied, all values fit in 16 bits, and convertTo will just truncate the 16 upper bits.
The other solution is to code the conversion by hand:
mat16.resize( mat32.size() );
for(int y = 0; y < mat32.height; ++) {
const int* row32 = (const int*)( (char*)mat32.data + y * mat32.step);
short* row16 = (short*) ( (char*)mat16.data + y * mat16.step);
for(int x = 0; x < mat32.step/ 4)
row16[x] = short(row32[x]);
I'm using Emgu.CV to perform some basic image manipulation and composition. My images are loaded as Image<Bgra,Byte>.
Question #1: When I use the Image<,>.Add() method, the images are always blended together, regardless of the alpha value. Instead I'd like them to be composited one atop the other, and use the included alpha channel to determine how the images should be blended. So if I call image1.Add(image2) any fully opaque pixels in image2 would completely cover the pixels from image1, while semi-transparent pixels would be blended based on the alpha value.
Here's what I'm trying to do in visual form. There's a city image with some "transparent holes" cut out, and a frog behind. This is what it should look like:
And this is what openCV produces.
How can I get this effect with OpenCV? And will it be as fast as calling Add()?
Question #2: is there a way to perform this composition in-place instead of creating a new image with each call to Add()? (e.g. image1.AddImageInPlace(image2) modifies the bytes of image1?)
NOTE: Looking for answers within Emgu.CV, which I'm using because of how well it handles perspective warping.
Before OpenCV 2.4 there was no support of PNGs with alpha channel.
To verify if your current version supports it, print the number of channels after loading an image that you are certain to be RGBA. If it supports, the application will output the number 4, else it will output number 3 (RGB). Using the C API you would do:
IplImage* t_img = cvLoadImage(argv[1], CV_LOAD_IMAGE_UNCHANGED);
if (!t_img)
{
printf("!!! Unable to load transparent image.\n");
return -1;
}
printf("Channels: %d\n", t_img->nChannels);
If you can't update OpenCV:
There are some posts around that try to bypass this limitation but I haven't tested them myself;
The easiest solution would be to use another API to load the image and blend it, check blImageBlending;
Another alternative, not as lightweight, is to use Qt.
If your version already supports PNGs with RGBA:
Take a look at Emulating photoshop’s blending modes in OpenCV. It implements several Photoshop blending modes and I imagine you are capable of converting that code to .Net.
EDIT:
I had to deal with this problem recently and I've demonstrated how to deal with it on this answer.
You'll have to iterate through each pixel. I'm assuming image 1 is the frog image, and image 2 is the city image, with image1 always being bigger than image2.
//to simulate image1.AddInPlace(image2)
int image2w = image2.Width;
int image2h = image2.Height;
int i,j;
var alpha;
for (i = 0; i < w; i++)
{
for (j = 0; j < h; j++)
{
//alpha=255 is opaque > image2 should be used
alpha = image2[3][j,i].Intensity;
image1[j, i]
= new Bgra(
image2[j, i].Blue * alpha + (image1[j, i].Blue * (255-alpha)),
image2[j, i].Green * alpha + (image1[j, i].Green * (255-alpha)),
image2[j, i].Red * alpha + (image1[j, i].Red * (255-alpha)));
}
}
Using Osiris's suggestion as a starting point, and having checked out alpha compositing on Wikipedia, i ended up with the following which worked really nicely for my purposes.
This was used this with Emgucv. I was hoping that the opencv gpu::AlphaComposite methods were available in Emgucv which I believe would have done the following for me, but alas the version I am using didn't appear to have them implemented.
static public Image<Bgra, Byte> Overlay( Image<Bgra, Byte> image1, Image<Bgra, Byte> image2 )
{
Image<Bgra, Byte> result = image1.Copy();
Image<Bgra, Byte> src = image2;
Image<Bgra, Byte> dst = image1;
int rows = result.Rows;
int cols = result.Cols;
for (int y = 0; y < rows; ++y)
{
for (int x = 0; x < cols; ++x)
{
// http://en.wikipedia.org/wiki/Alpha_compositing
double srcA = 1.0/255 * src.Data[y, x, 3];
double dstA = 1.0/255 * dst.Data[y, x, 3];
double outA = (srcA + (dstA - dstA * srcA));
result.Data[y, x, 0] = (Byte)(((src.Data[y, x, 0] * srcA) + (dst.Data[y, x, 0] * (1 - srcA))) / outA); // Blue
result.Data[y, x, 1] = (Byte)(((src.Data[y, x, 1] * srcA) + (dst.Data[y, x, 1] * (1 - srcA))) / outA); // Green
result.Data[y, x, 2] = (Byte)(((src.Data[y, x, 2] * srcA) + (dst.Data[y, x, 2] * (1 - srcA))) / outA); // Red
result.Data[y, x, 3] = (Byte)(outA*255);
}
}
return result;
}
A newer version, using emgucv methods. rather than a loop. Not sure it improves on performance.
double unit = 1.0 / 255.0;
Image[] dstS = dst.Split();
Image[] srcS = src.Split();
Image[] rs = result.Split();
Image<Gray, double> srcA = srcS[3] * unit;
Image<Gray, double> dstA = dstS[3] * unit;
Image<Gray, double> outA = srcA.Add(dstA.Sub(dstA.Mul(srcA)));// (srcA + (dstA - dstA * srcA));
// Red.
rs[0] = srcS[0].Mul(srcA).Add(dstS[0].Mul(1 - srcA)).Mul(outA.Pow(-1.0)); // Mul.Pow is divide.
rs[1] = srcS[1].Mul(srcA).Add(dstS[1].Mul(1 - srcA)).Mul(outA.Pow(-1.0));
rs[2] = srcS[2].Mul(srcA).Add(dstS[2].Mul(1 - srcA)).Mul(outA.Pow(-1.0));
rs[3] = outA.Mul(255);
// Merge image back together.
CvInvoke.cvMerge(rs[0], rs[1], rs[2], rs[3], result);
return result.Convert<Bgra, Byte>();
I found an interesting blog post on internet, which I think is related to what you are trying to do.
Please have a look at the Creating Overlays Method (archive.org link). You can use this idea to implement your own function to add two images in the way you mentioned above, making some particular areas in the image transparent while leaving the rest as it is.
I need to convert an 8-bit IplImage to a 32-bits IplImage. Using documentation from all over the web I've tried the following things:
// general code
img2 = cvCreateImage(cvSize(img->width, img->height), 32, 3);
int height = img->height;
int width = img->width;
int channels = img->nChannels;
int step1 = img->widthStep;
int step2 = img2->widthStep;
int depth1 = img->depth;
int depth2 = img2->depth;
uchar *data1 = (uchar *)img->imageData;
uchar *data2 = (uchar *)img2->imageData;
for(h=0;h<height;h++) for(w=0;w<width;w++) for(c=0;c<channels;c++) {
// attempt code...
}
// attempt one
// result: white image, two red spots which appear in the original image too.
// this is the closest result, what's going wrong?!
// see: http://files.dazjorz.com/cache/conversion.png
((float*)data2+h*step2+w*channels+c)[0] = data1[h*step1+w*channels+c];
// attempt two
// when I change float to unsigned long in both previous examples, I get a black screen.
// attempt three
// result: seemingly random data to the top of the screen.
data2[h*step2+w*channels*3+c] = data1[h*step1+w*channels+c];
data2[h*step2+w*channels*3+c+1] = 0x00;
data2[h*step2+w*channels*3+c+2] = 0x00;
// and then some other things. Nothing did what I wanted. I couldn't get an output
// image which looked the same as the input image.
As you see I don't really know what I'm doing. I'd love to find out, but I'd love it more if I could get this done correctly.
Thanks for any help I get!
The function you are looking for is cvConvertScale(). It automagically does any type conversion for you. You just have to specify that you want to scale by a factor of 1/255 (which maps the range [0...255] to [0...1]).
Example:
IplImage *im8 = cvLoadImage(argv[1]);
IplImage *im32 = cvCreateImage(cvSize(im8->width, im8->height), 32, 3);
cvConvertScale(im8, im32, 1/255.);
Note the dot in 1/255. - to force a double division. Without it you get a scale of 0.
Perhaps this link can help you?
Edit In response to the second edit of the OP and the comment
Have you tried
float value = 0.5
instead of
float value = 0x0000001;
I thought the range for a float color value goes from 0.0 to 1.0, where 1.0 is white.
Floating point colors go from 0.0 to 1.0, and uchars go from 0 to 255. The following code fixes it:
// h is height, w is width, c is current channel (0 to 2)
int b = ((uchar *)(img->imageData + h*img->widthStep))[w*img->nChannels + c];
((float *)(img2->imageData + h*img2->widthStep))[w*img2->nChannels + c] = ((float)b) / 255.0;
Many, many thanks to Stefan Schmidt for helping me fix this!
If you do not put the dot (.), some compilers will understand is as an int division, giving you a int result (zero in this case).
You can create an IplImage wrapper using boost::shared_ptr and template-metaprogramming. I have done that, and I get automatic garbage collection, together with automatic image conversions from one depth to another, or from one-channel to multi-channel images.
I have called the API blImageAPI and it can be found here:
http://www.barbato.us/2010/10/14/image-data-structure-based-shared_ptr-iplimage/
It is very fast, and make code very readable, (good for maintaining algorithms)
It is also can be used instead of IplImage in opencv algorithms without changing anything.
Good luck and have fun writing algorithms!!!
IplImage *img8,*img32;
img8 =cvLoadImage("a.jpg",1);
cvNamedWindow("Convert",1);
img32 = cvCreateImage(cvGetSize(img8),IPL_DEPTH_32F,3);
cvConvertScale(img8,img32,1.0/255.0,0.0);
//For Confirmation Check the pixel values (between 0 - 1)
for(int row = 0; row < img32->height; row++ ){
float* pt = (float*) (img32->imageData + row * img32->widthStep);
for ( int col = 0; col < width; col++ )
printf("\n %3.3f , %3.3f , %3.3f ",pt[3*col],pt[3*col+1],pt[3*col+2]);
}
cvShowImage("Convert",img32);
cvWaitKey(0);
cvReleaseImage(&img8);
cvReleaseImage(&img32);
cvDestroyWindow("Convert");