blocks|key|284083|text|这可能是错误的道路，但许多人(我是说，工程师)混合了YUV和YCbCr。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|284084|试着|284085|cvCvtColor(src,+dsc,+CV_YCbCr2RGB)+|code-block|syntax|javascript|284086|或者CV_YCrCb2RGB或者更有异国情调的类型。|284087|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|O|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|P|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

It may be the wrong path, but many people (I mean, engineers) do mix YUV with YCbCr. 

Try to 

<pre><code>cvCvtColor(src, dsc, CV_YCbCr2RGB) 
</code></pre>

or CV_YCrCb2RGB or maybe a more exotic type.

blocks|key|284148|text|BlackMagic强度软件以bmdFormat8BitYUV格式返回YUVY格式，因此2个源像素被压缩为4个字节--我认为openCV的cvtColor无法处理这个问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|284149|您可以自己做，也可以调用强度软件ConvertFrame()函数。|284150|编辑:Y+U+V通常存储为|284151|📷|atomic|offset|length|284152|​|284153|每个像素都有一个Y(亮度)，而行中的每个备用像素只有一个U和V(颜色)。|284154|因此，如果数据是一个无符号字符，指向内存的开始，如上面所示。|284155|像素1，Y=数据U=+data%2B1+V=+data%2B3|284156|像素2，Y=+data%2B2+U=+data%2B1+V=+data%2B3|284157|然后使用您在示例代码中使用的YUV->RGB系数。|284158|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/90fb9b7802b113e12c0748c5fdccc4fd.png|imageAlt^0|0|0|0|0|1|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|15|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|16|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|17|8|@]|9|@]|A|$]]|$1|F|3|G|5|H|7|18|8|@]|9|@$I|19|J|1A|1|1B]]|A|$]]|$1|K|3|L|5|6|7|1C|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|1D|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|1E|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1F|8|@]|9|@]|A|$]]|$1|S|3|T|5|6|7|1G|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1H|8|@]|9|@]|A|$]]|$1|W|3|-4|5|6|7|1I|8|@]|9|@]|A|$]]]|X|$Y|$5|Z|10|11|A|$12|13|14|-4]]]]

The BlackMagic Intensity software return YUVY' format in bmdFormat8BitYUV, so 2 sources pixels are compressed into 4bytes - I don't think openCV's cvtColor can handle this.

You can either do it yourself, or just call the Intensity software ConvertFrame() function

edit: Y U V is normally stored as 
<img src="https://i.stack.imgur.com/d6hFB.png" alt="enter image description here">

There is a Y (brightness) for each pixel but only a U and V (colour) for every alternate pixel in the row.

So if data is an unsigned char pointing to the start of the memory as shown above.

pixel 1, Y = data[0] U = data[+1] V = data[+3] 
pixel 2, Y = data[+2] U = data[+1] V = data[+3]

Then use the YUV->RGB coefficients you used in your sample code.

blocks|key|284191|text|在我看来，您正在将YUV422流解码为YUV444。尝试对您提供的代码进行以下修改：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|284192|for(int+i+=+0,+j=0;+i+<+1280+*+720+*+3;+i%2B=6,+j%2B=4)
{
++++m_RGB->imageData[i]+=+pData[j]+%2B+pData[j%2B3]*((1+-+0.299)/0.615);
++++m_RGB->imageData[i%2B1]+=+pData[j]+-+pData[j%2B1]*((0.114*(1-0.114))/(0.436*0.587))+-+pData[j%2B3]*((0.299*(1+-+0.299))/(0.615*0.587));
++++m_RGB->imageData[i%2B2]+=+pData[j]+%2B+pData[j%2B1]*((1+-+0.114)/0.436);
++++m_RGB->imageData[i%2B3]+=+pData[j%2B2]+%2B+pData[j%2B3]*((1+-+0.299)/0.615);
++++m_RGB->imageData[i%2B4]+=+pData[j%2B2]+-+pData[j%2B1]*((0.114*(1-0.114))/(0.436*0.587))+-+pData[j%2B3]*((0.299*(1+-+0.299))/(0.615*0.587));
++++m_RGB->imageData[i%2B5]+=+pData[j%2B2]+%2B+pData[j%2B1]*((1+-+0.114)/0.436);
}|code-block|syntax|javascript|284193|我不确定你的常量是否正确，但在最坏的情况下，你的颜色将关闭-图像应该是可识别的。|284194|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

It looks to me like you're decoding a YUV422 stream as YUV444. Try this modification to the code you provided:

<pre><code>for(int i = 0, j=0; i &lt; 1280 * 720 * 3; i+=6, j+=4)
{
 m_RGB-&gt;imageData[i] = pData[j] + pData[j+3]*((1 - 0.299)/0.615);
 m_RGB-&gt;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-&gt;imageData[i+2] = pData[j] + pData[j+1]*((1 - 0.114)/0.436);
 m_RGB-&gt;imageData[i+3] = pData[j+2] + pData[j+3]*((1 - 0.299)/0.615);
 m_RGB-&gt;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-&gt;imageData[i+5] = pData[j+2] + pData[j+1]*((1 - 0.114)/0.436);
}
</code></pre>

I'm not sure you've got your constants correct, but at worst your colors will be off - the image should be recognizable.

blocks|key|129807|text|在较新版本的OPENCV中，可以使用内置函数执行YUV到RGB的转换。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|129808|cvtColor(src,dst,CV_YUV2BGR_YUY2);|129809|在下划线后指定YUV格式，如下面的CV_YUYV2BGR_xxxx|129810|entityMap^0|6|6|O|3|S|3|0|0|Y|0|7|3|H|G|0^^$0|@$1|2|3|4|5|6|7|L|8|@$9|M|A|N|B|C]|$9|O|A|P|B|C]|$9|Q|A|R|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|V|8|@$9|W|A|X|B|C]|$9|Y|A|Z|B|C]]|D|@]|E|$]]|$1|J|3|-4|5|6|7|10|8|@]|D|@]|E|$]]]|K|$]]

In newer version of <code>OPENCV</code> there is a built in function can be used to do <code>YUV</code> to <code>RGB</code> conversion

<code>cvtColor(src,dst,CV_YUV2BGR_YUY2);</code>

specify the <code>YUV</code> format after the underscore, like this <code>CV_YUYV2BGR_xxxx</code>

blocks|key|284247|text|也许有人被彩色模型YCbCr和YUV弄糊涂了。Opencv不处理YCbCr。相反，它有YCrCb，的实现方式与opencv中的YUV相同。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|284248|来自opencv源https://github.com/Itseez/opencv/blob/2.4/modules/imgproc/src/color.cpp#L3830|284249|case+CV_BGR2YCrCb:+case+CV_RGB2YCrCb:
case+CV_BGR2YUV:+case+CV_RGB2YUV:
++++//+...
++++//+1+if+it+is+BGR,+0+if+it+is+RGB
++++bidx+=+code+==+CV_BGR2YCrCb+%7C%7C+code+==+CV_BGR2YUV+?+0+:+2;+
++++//...+converting+to+YUV+with+the+only+difference+that+brings+
++++//++++order+of+Blue+and+Red+channels+(variable+bidx)|code-block|syntax|javascript|284250|但还有一件事要说。|284251|目前在转换错误中有一个CV_BGR2YUV，在OpenCV分支中有一个CV_RGB2YUV+.*。|284252|目前，在执行中采用了这一公式：|284253|Y+=+0.299B+%2B+0.587G+%2B+0.114R
U+=+0.492(R-Y)
V+=+0.877(B-Y)|284254|它应该是什么(根据维基百科)：|284255|Y+=+0.299R+%2B+0.587G+%2B+0.114B
U+=+0.492(B-Y)
V+=+0.877(R-Y)|284256|通道红色和蓝色被错误地放置在实现公式中。|284257|可能的解决办法是在错误未修复时转换BGR->YUV：|284258|++cv::Mat+source+=+cv::imread(filename,+CV_LOAD_IMAGE_COLOR);
++cv::Mat+yuvSource;++++
++cvtColor(source,+yuvSource,+cv::COLOR_BGR2RGB);+//+rearranges+B+and+R+in+the+appropriate+order
++cvtColor(yuvSource,+yuvSource,+cv::COLOR_BGR2YUV);
++//+yuvSource+will+contain+here+correct+image+in+YUV+color+space|284259|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/Itseez/opencv/blob/2.4/modules/imgproc/src/color.cpp#L3830|1|http://code.opencv.org/issues/4227|2|http://nl.wikipedia.org/wiki/YUV^0|W|5|17|5|1D|H|0|9|25|0|0|0|0|5|2|1|0|0|0|9|4|2|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1G|8|@$9|1H|A|1I|B|C]|$9|1J|A|1K|B|C]|$9|1L|A|1M|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1N|8|@]|D|@$9|1O|A|1P|1|1Q]]|E|$]]|$1|H|3|I|5|J|7|1R|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1S|8|@]|D|@]|E|$]]|$1|O|3|P|5|6|7|1T|8|@]|D|@$9|1U|A|1V|1|1W]]|E|$]]|$1|Q|3|R|5|6|7|1X|8|@]|D|@]|E|$]]|$1|S|3|T|5|J|7|1Y|8|@]|D|@]|E|$K|L]]|$1|U|3|V|5|6|7|1Z|8|@]|D|@$9|20|A|21|1|22]]|E|$]]|$1|W|3|X|5|J|7|23|8|@]|D|@]|E|$K|L]]|$1|Y|3|Z|5|6|7|24|8|@]|D|@]|E|$]]|$1|10|3|11|5|6|7|25|8|@]|D|@]|E|$]]|$1|12|3|13|5|J|7|26|8|@]|D|@]|E|$K|L]]|$1|14|3|-4|5|6|7|27|8|@]|D|@]|E|$]]]|15|$16|$5|17|18|19|E|$1A|1B]]|1C|$5|17|18|19|E|$1A|1D]]|1E|$5|17|18|19|E|$1A|1F]]]]

Maybe someone is confused by color models YCbCr and YUV.
Opencv does not handle YCbCr. Instead it has YCrCb, and it implemented the same way as YUV in opencv. 

From the opencv sources <a href="https://github.com/Itseez/opencv/blob/2.4/modules/imgproc/src/color.cpp#L3830" rel="nofollow">https://github.com/Itseez/opencv/blob/2.4/modules/imgproc/src/color.cpp#L3830</a>:

<pre><code>case CV_BGR2YCrCb: case CV_RGB2YCrCb:
case CV_BGR2YUV: case CV_RGB2YUV:
 // ...
 // 1 if it is BGR, 0 if it is RGB
 bidx = code == CV_BGR2YCrCb || code == CV_BGR2YUV ? 0 : 2; 
 //... converting to YUV with the only difference that brings 
 // order of Blue and Red channels (variable bidx)
</code></pre>

But there is one more thing to say. 
There is currently a <a href="http://code.opencv.org/issues/4227" rel="nofollow">bug</a> in conversion CV_BGR2YUV and CV_RGB2YUV in OpenCV branch 2.4.* .

At present, this formula is used in implementation:

<pre><code>Y = 0.299B + 0.587G + 0.114R
U = 0.492(R-Y)
V = 0.877(B-Y)
</code></pre>

What it should be (according to <a href="http://nl.wikipedia.org/wiki/YUV" rel="nofollow">wikipedia</a>):

<pre><code>Y = 0.299R + 0.587G + 0.114B
U = 0.492(B-Y)
V = 0.877(R-Y)
</code></pre>

The channels Red and Blue are misplaced in the implemented formula. 

Possible workaround to convert BGR->YUV while the bug is not fixed :

<pre><code> cv::Mat source = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
 cv::Mat yuvSource; 
 cvtColor(source, yuvSource, cv::COLOR_BGR2RGB); // rearranges B and R in the appropriate order
 cvtColor(yuvSource, yuvSource, cv::COLOR_BGR2YUV);
 // yuvSource will contain here correct image in YUV color space
</code></pre>

blocks|key|129125|text|我使用以下C%2B%2B代码使用OpenCV进行，将yuv数据(YUV_NV21)转换为rgb映像(BGR+in+OpenCV)|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|129126|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;
}|code-block|syntax|javascript|129127|转换后的结果类似于图像yuv.png。|129128|您可以从中找到测试原始映像的，从这里找到，从my+Github项目找到整个项目|129129|entityMap|0|LINK|mutability|MUTABLE|url|https://i.stack.imgur.com/cFsyJ.png|1|https://download.csdn.net/download/u011178262/10791506|2|https://github.com/cggos/cgocv/tree/master/cv_libs/opencv/image_convertor^0|K|14|0|0|B|7|0|0|4|A|K|J|G|2|1|P|8|2|0^^$0|@$1|2|3|4|5|6|7|10|8|@$9|11|A|12|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|13|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|14|8|@]|D|@$9|15|A|16|1|17]]|E|$]]|$1|M|3|N|5|6|7|18|8|@$9|19|A|1A|B|C]|$9|1B|A|1C|B|C]]|D|@$9|1D|A|1E|1|1F]|$9|1G|A|1H|1|1I]]|E|$]]|$1|O|3|-4|5|6|7|1J|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]|W|$5|R|S|T|E|$U|X]]|Y|$5|R|S|T|E|$U|Z]]]]

I use the following C++ code using OpenCV to convert yuv data (YUV_NV21) to rgb image (BGR in OpenCV)
<pre><code>int main()
{
 const int width = 1280;
 const int height = 800;

 std::ifstream file_in;
 file_in.open(&quot;../image_yuv_nv21_1280_800_01.raw&quot;, std::ios::binary);
 std::filebuf *p_filebuf = file_in.rdbuf();
 size_t size = p_filebuf-&gt;pubseekoff(0, std::ios::end, std::ios::in);
 p_filebuf-&gt;pubseekpos(0, std::ios::in);

 char *buf_src = new char[size];
 p_filebuf-&gt;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(&quot;yuv.png&quot;, mat_dst);

 file_in.close();
 delete []buf_src;

 return 0;
}
</code></pre>
and the converted result is like the image <a href="https://i.stack.imgur.com/cFsyJ.png" rel="nofollow noreferrer">yuv.png</a>.
you can find the testing raw image from <a href="https://download.csdn.net/download/u011178262/10791506" rel="nofollow noreferrer">here</a> and the whole project from my <a href="https://github.com/cggos/cgocv/tree/master/cv_libs/opencv/image_convertor" rel="nofollow noreferrer">Github Project</a>

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 <code>cvCvtColor(scr, dst, CV_YUV2BGR)</code> 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.

<img src="https://i.stack.imgur.com/RsPNF.png" alt="YUV to BGR converted image">

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.

<pre><code>BYTE* pData;

 videoFrame-&gt;GetBytes((void**)&amp;pData);

 m_nFrames++;

 printf("Num Frames executed: %d\n", m_nFrames);

 for(int i = 0; i &lt; 1280 * 720 * 3; i=i+3)
 {
 m_RGB-&gt;imageData[i] = pData[i] + pData[i+2]*((1 - 0.299)/0.615);
 m_RGB-&gt;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-&gt;imageData[i+2] = pData[i] + pData[i+1]*((1 - 0.114)/0.436);
 }
</code></pre>

<img src="https://i.stack.imgur.com/WBGzS.png" alt="Attempted RGB conversion">

Converting YUV into BGR or RGB in OpenCV

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

文章

问答

视频

学习中心

腾讯云实验室

直播

竞赛

腾讯云架构师技术同盟交流圈

腾讯云数据库专区

腾讯云顾问专区

腾讯云原生专区

腾讯混元专区

腾讯云TCE专区

腾讯云Lighthouse专区

腾讯云HAI专区

腾讯云Edgeone专区

腾讯云存储专区

腾讯云智能专区

腾讯轻联专区 

腾讯云开发专区

TAPD专区

腾讯轻量云游戏服专区

腾讯云最具价值专家

腾讯云架构师技术同盟

腾讯云创作之星

腾讯云开发者先锋 

腾讯云代码助手

CODING DevOps

Cloud Studio

SDK中心

API中心

命令行工具

我有一个电视捕捉卡，有一个输入作为YUV格式。我在这里看到了类似于这个问题的其他帖子，并试图尝试每一种可能的方法，但它们都没有提供一个清晰的图像。目前，最好的结果是使用OpenCV cvCvtColor(scr, dst, CV_YUV2BGR)函数调用。我目前还不知道YUV的格式，老实说，这让我有点困惑，因为它看起来...

问在OpenCV中将YUV转换为BGR或RGB
EN

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问在OpenCV中将YUV转换为BGR或RGBEN