blocks|key|140397|text|另一种选择。Ubuntu+14.04、GTX+Titan+X、opencv-2.4.10|type|unstyled|depth|inlineStyleRanges|entityRanges|data|140398|cmake+-D+CMAKE_BUILD_TYPE=Release+-D+CMAKE_INSTALL_PREFIX=/usr/local+-D+BUILD_TIFF=ON+-D+BUILD_EXAMPLES=ON+-D+CUDA_GENERATION=Auto+-D+BUILD_NEW_PYTHON_SUPPORT=ON++..+|code-block|syntax|javascript|140399|我也申请了patch，但我不确定最终是否需要它。我尝试过使用和不使用CUDA_GENERATION=Maxwell，但是没有检测到Maxwell。在打补丁之前我没有尝试过CUDA_GENERATION=Auto，这就是为什么我不确定的原因。|offset|length|style|CODE|140400|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/Itseez/opencv/pull/3886/files^0|0|0|Y|N|2D|K|5|5|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|W|8|@$I|X|J|Y|K|L]|$I|Z|J|10|K|L]]|9|@$I|11|J|12|1|13]]|A|$]]|$1|M|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|N|$O|$5|P|Q|R|A|$S|T]]]]

Another option.
Ubuntu 14.04, GTX Titan X, opencv-2.4.10

<pre><code>cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D BUILD_TIFF=ON -D BUILD_EXAMPLES=ON -D CUDA_GENERATION=Auto -D BUILD_NEW_PYTHON_SUPPORT=ON .. 
</code></pre>

I also applied the <a href="https://github.com/Itseez/opencv/pull/3886/files" rel="noreferrer">patch</a>,
but I'm not sure whether it ended up being needed. I had tried with and without<code>CUDA_GENERATION=Maxwell</code> but Maxwell isn't detected. I did not try <code>CUDA_GENERATION=Auto</code> prior to the patch, that's why I don't know for sure.

blocks|key|140327|text|当使用cmake进行配置时，请设置选项CUDA_GENERATION以指定您的GPU架构。我遇到了同样的错误，并尝试解决这个问题。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|140328|entityMap^0|J|F|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|K|8|@]|D|@]|E|$]]]|G|$]]

When using cmake to do configurations, set the option CUDA_GENERATION to specific your GPU architecture. I ran across the same error and tried this to work out the problem.

blocks|key|2715390|text|跟随云的回答(无法留下评论)，这对我很有效，并显示了CUDA_GENERATION的可能价值|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|2715391|cmake+-D+CMAKE_BUILD_TYPE=RELEASE+-D+CMAKE_INSTALL_PREFIX=/usr/local+-D+CUDA_GENERATION=Kepler+..|code-block|syntax|javascript|2715392|(Ubuntu12.04和14.04、GTX和OpenCV+2.4.11和3.0.0。)|2715393|entityMap^0|Q|F|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@]|D|@]|E|$]]|$1|M|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|N|$]]

Following up on Yun's answer (could not leave comment), this worked for me and shows a possible value for CUDA_GENERATION:

<pre><code>cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D CUDA_GENERATION=Kepler ..
</code></pre>

(Ubuntu 12.04 and 14.04, GTX Titan, and OpenCV 2.4.11 and 3.0.0.)

blocks|key|2715673|text|您可以使用CUDA_GENERATION为您的GPU架构指定相应的代码名。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2715674|下面是解析CUDA_GENERATION值的相关opencv+cmake+code：|2715675|++set(__cuda_arch_ptx+"")
++if(CUDA_GENERATION+STREQUAL+"Fermi")
++++set(__cuda_arch_bin+"2.0")
++elseif(CUDA_GENERATION+STREQUAL+"Kepler")
++++set(__cuda_arch_bin+"3.0+3.5+3.7")
++elseif(CUDA_GENERATION+STREQUAL+"Maxwell")
++++set(__cuda_arch_bin+"5.0+5.2")
++elseif(CUDA_GENERATION+STREQUAL+"Pascal")
++++set(__cuda_arch_bin+"6.0+6.1")
++elseif(CUDA_GENERATION+STREQUAL+"Volta")
++++set(__cuda_arch_bin+"7.0")
++elseif(CUDA_GENERATION+STREQUAL+"Auto")
++++execute_process(+COMMAND+"${CUDA_NVCC_EXECUTABLE}"+${CUDA_NVCC_FLAGS}+"${OpenCV_SOURCE_DIR}/cmake/checks/OpenCVDetectCudaArch.cu"+"--run"
+++++++++++++++++++++WORKING_DIRECTORY+"${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/"
+++++++++++++++++++++RESULT_VARIABLE+_nvcc_res+OUTPUT_VARIABLE+_nvcc_out
+++++++++++++++++++++ERROR_QUIET+OUTPUT_STRIP_TRAILING_WHITESPACE)
++++if(NOT+_nvcc_res+EQUAL+0)
++++++message(STATUS+"Automatic+detection+of+CUDA+generation+failed.+Going+to+build+for+all+known+architectures.")
++++else()
++++++set(__cuda_arch_bin+"${_nvcc_out}")
++++++string(REPLACE+"2.1"+"2.1(2.0)"+__cuda_arch_bin+"${__cuda_arch_bin}")
++++endif()
endif()|code-block|syntax|javascript|2715676|wikipedia+CUDA页面有一个很好的表，用于将您的视频卡映射到正确的微体系结构代码名(抱歉，它太大了，无法在此处重现)：|2715677|https://en.wikipedia.org/wiki/CUDA#GPUs_supported|2715678|例如，我的middling-2012+Macbook+Pro有一台古董的GeForce+GT+650M，维基百科表显示它使用的是开普勒微体系结构。因此，我在cmake命令行中使用了以下代码：|2715679|cmake+-D+CUDA_GENERATION="Kepler"+...|2715680|当opencv脚本显示配置摘要时，它会将其转换为“3.03.53.7”，并将相应的标志传递给nvcc。|2715681|在我的例子中，在正确设置它之前，我得到了关于compute_70不受支持的错误。显然，截至今天(2017-10-07)，仍有一个open+issue+in+the+opencv+tracker关于自动检测不能正常工作。|2715682|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/opencv/opencv/blob/master/cmake/OpenCVDetectCUDA.cmake#L64-L86|1|2|https://github.com/opencv/opencv/issues/8781^0|5|F|0|5|F|O|H|0|0|0|0|0|1D|1|0|0|0|11|0|1A|4|0|M|A|1S|W|2|0^^$0|@$1|2|3|4|5|6|7|19|8|@$9|1A|A|1B|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1C|8|@$9|1D|A|1E|B|C]]|D|@$9|1F|A|1G|1|1H]]|E|$]]|$1|H|3|I|5|J|7|1I|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1J|8|@]|D|@]|E|$]]|$1|O|3|P|5|6|7|1K|8|@]|D|@$9|1L|A|1M|1|1N]]|E|$]]|$1|Q|3|R|5|6|7|1O|8|@]|D|@]|E|$]]|$1|S|3|T|5|6|7|1P|8|@$9|1Q|A|1R|B|C]]|D|@]|E|$]]|$1|U|3|V|5|6|7|1S|8|@$9|1T|A|1U|B|C]]|D|@]|E|$]]|$1|W|3|X|5|6|7|1V|8|@$9|1W|A|1X|B|C]]|D|@$9|1Y|A|1Z|1|20]]|E|$]]|$1|Y|3|-4|5|6|7|21|8|@]|D|@]|E|$]]]|Z|$10|$5|11|12|13|E|$14|15]]|16|$5|11|12|13|E|$14|P]]|17|$5|11|12|13|E|$14|18]]]]

You can use <code>CUDA_GENERATION</code> to specify the corresponding generation code name for your GPU architecture. 

Here's the relevant <a href="https://github.com/opencv/opencv/blob/master/cmake/OpenCVDetectCUDA.cmake#L64-L86" rel="noreferrer">opencv cmake code</a> that parses the <code>CUDA_GENERATION</code> value:

<pre class="lang-c prettyprint-override"><code> set(__cuda_arch_ptx "")
 if(CUDA_GENERATION STREQUAL "Fermi")
 set(__cuda_arch_bin "2.0")
 elseif(CUDA_GENERATION STREQUAL "Kepler")
 set(__cuda_arch_bin "3.0 3.5 3.7")
 elseif(CUDA_GENERATION STREQUAL "Maxwell")
 set(__cuda_arch_bin "5.0 5.2")
 elseif(CUDA_GENERATION STREQUAL "Pascal")
 set(__cuda_arch_bin "6.0 6.1")
 elseif(CUDA_GENERATION STREQUAL "Volta")
 set(__cuda_arch_bin "7.0")
 elseif(CUDA_GENERATION STREQUAL "Auto")
 execute_process( COMMAND "${CUDA_NVCC_EXECUTABLE}" ${CUDA_NVCC_FLAGS} "${OpenCV_SOURCE_DIR}/cmake/checks/OpenCVDetectCudaArch.cu" "--run"
 WORKING_DIRECTORY "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/CMakeTmp/"
 RESULT_VARIABLE _nvcc_res OUTPUT_VARIABLE _nvcc_out
 ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
 if(NOT _nvcc_res EQUAL 0)
 message(STATUS "Automatic detection of CUDA generation failed. Going to build for all known architectures.")
 else()
 set(__cuda_arch_bin "${_nvcc_out}")
 string(REPLACE "2.1" "2.1(2.0)" __cuda_arch_bin "${__cuda_arch_bin}")
 endif()
endif()
</code></pre>

And the wikipedia CUDA page has a nice table for mapping your video card to the right microarchitecture code name (sorry, it's too large to reproduce here):

<a href="https://en.wikipedia.org/wiki/CUDA#GPUs_supported" rel="noreferrer">https://en.wikipedia.org/wiki/CUDA#GPUs_supported</a>

For example, my middling-2012 Macbook Pro has an antique GeForce GT 650M, which the wikipedia table indicates uses the Kepler microarchitecture. Therefore, I use this in my cmake command line:

<code>cmake -D CUDA_GENERATION="Kepler" ...</code>

and the opencv script converts that to "3.0 3.5 3.7" when it displays the config summary, and passes on the corresponding flags to <code>nvcc</code>.

In my case, before setting this properly, I was getting errors about <code>compute_70</code> not supported. Apparently, there is still an <a href="https://github.com/opencv/opencv/issues/8781" rel="noreferrer">open issue in the opencv tracker</a> as of today (2017-10-07) about auto-detection not working properly.

blocks|key|2928115|text|谢谢,|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2928116|cmake+-D+CMAKE_BUILD_TYPE=RELEASE+-D+CMAKE_INSTALL_PREFIX=/usr/local+-D+CUDA_GENERATION=Kepler+..|code-block|syntax|javascript|2928117|这让我可以安装opencv-2.4.9。|2928118|如果您想了解更多细节，请查看此link。|offset|length|2928119|entityMap|0|LINK|mutability|MUTABLE|url|http://vinayhacks.blogspot.com.es/2011/11/installing-opencv-231-with-ffmpeg-on-64.html^0|0|0|0|F|4|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|W|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|X|8|@]|9|@$K|Y|L|Z|1|10]]|A|$]]|$1|M|3|-4|5|6|7|11|8|@]|9|@]|A|$]]]|N|$O|$5|P|Q|R|A|$S|T]]]]

Thank you,

<pre><code>cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D CUDA_GENERATION=Kepler ..
</code></pre>

This let me install opencv-2.4.9. 

If you want to know more detaills check this <a href="http://vinayhacks.blogspot.com.es/2011/11/installing-opencv-231-with-ffmpeg-on-64.html" rel="nofollow">link</a>.

blocks|key|2715645|text|这是因为您的gpu类型不匹配。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2715646|您必须显式定义CUDA_GENERATION。|2715647|在我这里，我可以找到三种类型的CUDA_GENERATION:自动，开普勒，费米。|2715648|当我将CUDA_GENERATION设置为Kepler时，compute_11更改为compute_30并构建成功。|2715649|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

This is because of your gpu type is mismatching.

You have to define CUDA_GENERATION explicitly.

In my side, I could find 3 types of CUDA_GENERATION; Auto, Kepler, Fermi.

When I set CUDA_GENERATION as Kepler, compute_11 changed to compute_30 and build successful.

blocks|key|140402|text|您应该使用cmake设置这些条目CUDA_ARCH_BIN+=+3.2和CUDA_ARCH_PTX+=+3.2|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|140403|希望能有所帮助。|140404|问候|140405|entityMap^0|5|5|G|J|10|J|0|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@$9|M|A|N|B|C]|$9|O|A|P|B|C]|$9|Q|A|R|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|S|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|T|8|@]|D|@]|E|$]]|$1|J|3|-4|5|6|7|U|8|@]|D|@]|E|$]]]|K|$]]

You should set with <code>cmake</code> these entries <code>CUDA_ARCH_BIN = 3.2</code> and <code>CUDA_ARCH_PTX = 3.2</code> 

Hope it helps.

Regards

blocks|key|144071|text|cmake+-D+CMAKE_BUILD_TYPE=Release+-D+CMAKE_INSTALL_PREFIX=/usr/local+-D+BUILD_TIFF=ON+-D+BUILD_EXAMPLES=ON+-D+CUDA_GENERATION=Kepler+-D+BUILD_NEW_PYTHON_SUPPORT=ON+..|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|144072|适用于我的OpenCV+2.4.11|144073|entityMap^0|0|4M|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|M|8|@]|D|@]|E|$]]|$1|H|3|-4|5|6|7|N|8|@]|D|@]|E|$]]]|I|$]]

<code>cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D BUILD_TIFF=ON -D BUILD_EXAMPLES=ON -D CUDA_GENERATION=Kepler -D BUILD_NEW_PYTHON_SUPPORT=ON .. </code>

worked for me for OpenCV 2.4.11

Im use CMake to generate visual studio 2013 solution. Next im try to build it, but get follow error:
<blockquote>
Building NVCC (Device) object modules/core/CMakeFiles/cuda_compile.dir/src/cuda/Debug/cuda_compile_generated_gpu_mat.cu.obj
nvcc fatal : Unsupported gpu architecture 'compute_11'
</blockquote>
Im try version 2.10 and 3.0 with cuda 6.5 and 7.0.
CUDA_ARCH_BIN set to : 1.1 1.2 1.3 2.0 2.1(2.0) 3.0 3.5

Build OpenCV with CUDA support

Ubuntu

即时通信工具使用CMake生成visual studio 2013解决方案。下一步，我尝试构建它，但得到了以下错误：构建NVCC (设备)对象modules/core/CMakeFiles/cuda_compile.dir/src/cuda/Debug/cuda_compile_generated_gpu_mat.cu.objnvcc致命:不支持的图形处理器架构'compute_11‘我尝试使用c

问构建支持CUDA的OpenCV
EN

回答 8

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