I have a TV capture card that has a feed coming in as a YUV format. I've seen other posts here similar to this question and attempted to try every possible method stated, but neither of them provided a clear image. At the moment the best results were with the OpenCV cvCvtColor(scr, dst, CV_YUV2BGR)
function call.
I am currently unaware of the YUV format and to be honest confuses me a little bit as it looks like it stores 4 channels, but is only 3? I have included an image from the capture card to hope that someone can understand what is possibly going on that I could use to fill in the blanks.
The feed is coming in through a DeckLink Intensity Pro card and being accessed in a C++ application in using OpenCV in a Windows 7 environment.
Update
I have looked at a wikipedia article regarding this information and attempted to use the formula in my application. Below is the code block with the output received from it. Any advice is greatly appreciated.
BYTE* pData;
videoFrame->GetBytes((void**)&pData);
m_nFrames++;
printf("Num Frames executed: %d\n", m_nFrames);
for(int i = 0; i < 1280 * 720 * 3; i=i+3)
{
m_RGB->imageData[i] = pData[i] + pData[i+2]*((1 - 0.299)/0.615);
m_RGB->imageData[i+1] = pData[i] - pData[i+1]*((0.114*(1-0.114))/(0.436*0.587)) - pData[i+2]*((0.299*(1 - 0.299))/(0.615*0.587));
m_RGB->imageData[i+2] = pData[i] + pData[i+1]*((1 - 0.114)/0.436);
}
OpenCV uses BGR image format. So, when we read an image using cv2. imread() it interprets in BGR format by default. We can use cvtColor() method to convert a BGR image to RGB and vice-versa.
When the image file is read with the OpenCV function imread() , the order of colors is BGR (blue, green, red). On the other hand, in Pillow, the order of colors is assumed to be RGB (red, green, blue). Therefore, if you want to use both the Pillow function and the OpenCV function, you need to convert BGR and RGB.
"The reason why the early developers at OpenCV chose BGR color format is probably that back then BGR color format was popular among camera manufacturers and software providers. E.g. in Windows, when specifying color value using COLORREF they use the BGR format 0x00bbggrr.
It may be the wrong path, but many people (I mean, engineers) do mix YUV with YCbCr.
Try to
cvCvtColor(src, dsc, CV_YCbCr2RGB)
or CV_YCrCb2RGB or maybe a more exotic type.
In newer version of OPENCV
there is a built in function can be used to do YUV
to RGB
conversion
cvtColor(src,dst,CV_YUV2BGR_YUY2);
specify the YUV
format after the underscore, like this CV_YUYV2BGR_xxxx
I use the following C++ code using OpenCV to convert yuv data (YUV_NV21) to rgb image (BGR in OpenCV)
int main()
{
const int width = 1280;
const int height = 800;
std::ifstream file_in;
file_in.open("../image_yuv_nv21_1280_800_01.raw", std::ios::binary);
std::filebuf *p_filebuf = file_in.rdbuf();
size_t size = p_filebuf->pubseekoff(0, std::ios::end, std::ios::in);
p_filebuf->pubseekpos(0, std::ios::in);
char *buf_src = new char[size];
p_filebuf->sgetn(buf_src, size);
cv::Mat mat_src = cv::Mat(height*1.5, width, CV_8UC1, buf_src);
cv::Mat mat_dst = cv::Mat(height, width, CV_8UC3);
cv::cvtColor(mat_src, mat_dst, cv::COLOR_YUV2BGR_NV21);
cv::imwrite("yuv.png", mat_dst);
file_in.close();
delete []buf_src;
return 0;
}
and the converted result is like the image yuv.png.
you can find the testing raw image from here and the whole project from my Github Project
It looks to me like you're decoding a YUV422 stream as YUV444. Try this modification to the code you provided:
for(int i = 0, j=0; i < 1280 * 720 * 3; i+=6, j+=4)
{
m_RGB->imageData[i] = pData[j] + pData[j+3]*((1 - 0.299)/0.615);
m_RGB->imageData[i+1] = pData[j] - pData[j+1]*((0.114*(1-0.114))/(0.436*0.587)) - pData[j+3]*((0.299*(1 - 0.299))/(0.615*0.587));
m_RGB->imageData[i+2] = pData[j] + pData[j+1]*((1 - 0.114)/0.436);
m_RGB->imageData[i+3] = pData[j+2] + pData[j+3]*((1 - 0.299)/0.615);
m_RGB->imageData[i+4] = pData[j+2] - pData[j+1]*((0.114*(1-0.114))/(0.436*0.587)) - pData[j+3]*((0.299*(1 - 0.299))/(0.615*0.587));
m_RGB->imageData[i+5] = pData[j+2] + pData[j+1]*((1 - 0.114)/0.436);
}
I'm not sure you've got your constants correct, but at worst your colors will be off - the image should be recognizable.
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