win10下caffe+gpu使用问题总结

环境：

gtx 1080Ti

i7

32g内存

三星sm951，256g固态NVME硬盘

vs2013+win10+cuda9.0+cudnn5.1

NVME的硬盘只支持win10的固态硬盘，无法安装linux系统，因此后续的问题都是基于windows环境下的

x64 无法调试，出现“调试监视器(MSVSMON.EXE)未能启动”错误

解决方案：打开vs2013后，从文件-->打开->项目里重新打开caffe，只能是暂时的解决方案

使用社区版2013，专业版装时不知道是什么问题Nuget使用不了，在编译过程中protobuf调用出现1083的错误码，读取dll错误的问题，不清楚是什么原因。



opencv、glog、gflafs在配置gpu版本时出现以下错误

error：NuGet Error:未知命令:“overlay”

error：MSB4062 加载任务“NuGetPackageOverlay”失败问题



反正使用Nuget怎么配都有问题


解决方案：手动配置，工程下的packages.config文件写了依赖库的版本，按这个去下载对应的库，然后在属性文件CommonSettings.props中

去配置：

<PropertyGroup Label="UserMacros">
<!-- opencv 2.4.10 supported -->
<OpencvPath>D:\wxf\opencv\build</OpencvPath>
<OpencvDependencies></OpencvDependencies>

<!-- Glog supported -->
<GlogPath>F:\caffe\NugetPackages\glog.0.3.3.0\build\native</GlogPath>
<!-- Gflags supported -->
<GflagsPath>F:\caffe\NugetPackages\gflags.2.1.2.1\build\native</GflagsPath>
</PropertyGroup>

<PropertyGroup>
<LibraryPath>$(OpencvPath)\x64\vc12\lib;$(LibraryPath)</LibraryPath>
<IncludePath>$(OpencvPath)\include;$(OpencvPath)\include\opencv;$(OpencvPath)\include\opencv2;$(IncludePath)</IncludePath>
</PropertyGroup>

<PropertyGroup>
<LibraryPath>$(GflagsPath)\x64\v120\dynamic\Lib;$(LibraryPath)</LibraryPath>
<IncludePath>$(GflagsPath)\include;$(IncludePath)</IncludePath>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">

<LibraryPath>$(GlogPath)\lib\x64\v120\Release\dynamic;$(LibraryPath)</LibraryPath>
<IncludePath>$(GlogPath)\include;$(IncludePath)</IncludePath>

<CudaDependencies>
opencv_objdetect2410.lib;
opencv_ts2410.lib;
opencv_video2410.lib;
opencv_nonfree2410.lib;
opencv_ocl2410.lib;
opencv_photo2410.lib;
opencv_stitching2410.lib;
opencv_superres2410.lib;
opencv_videostab2410.lib;
opencv_calib3d2410.lib;
opencv_contrib2410.lib;
opencv_core2410.lib;
opencv_features2d2410.lib;
opencv_flann2410.lib;
opencv_gpu2410.lib;
opencv_highgui2410.lib;
opencv_imgproc2410.lib;
opencv_legacy2410.lib;
opencv_ml2410.lib;
libglog.lib;
gflags.lib;
gflags_nothreads.lib;
$(CudaDependencies)
</CudaDependencies>
</PropertyGroup>

<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
<LibraryPath>$(GlogPath)\lib\x64\v120\Debug\dynamic;$(LibraryPath)</LibraryPath>
<IncludePath>$(GlogPath)\include;$(IncludePath)</IncludePath>
<CudaDependencies>
opencv_ml2410d.lib;
opencv_calib3d2410d.lib;
opencv_contrib2410d.lib;
opencv_core2410d.lib;
opencv_features2d2410d.lib;
opencv_flann2410d.lib;
opencv_gpu2410d.lib;
opencv_highgui2410d.lib;
opencv_imgproc2410d.lib;
opencv_legacy2410d.lib;
opencv_objdetect2410d.lib;
opencv_ts2410d.lib;
opencv_video2410d.lib;
opencv_nonfree2410d.lib;
opencv_ocl2410d.lib;
opencv_photo2410d.lib;
opencv_stitching2410d.lib;
opencv_superres2410d.lib;
opencv_videostab2410d.lib;
libglog.lib;
gflagsd.lib;
gflags_nothreadsd.lib;
$(CudaDependencies)
</CudaDependencies>
</PropertyGroup>

然后在项目的附加依赖项中添加$(OpencvDependencies)，这样编译基本就没问题了。

数据类型不匹配，把数据转为LMDB，但还是报错，反正就是其他地方都没问题了，但还是报错估计就是路径问题了，‘/’，‘\’是不一样的，路径最好都用‘/’。

设置数据层为：

name: "LeNet"

layer {

name: "data"

type: "Input"

top: "data"

input_param { shape: { dim: 1 dim: 1 dim: 28 dim: 28 } }

}

错误：Check failed: labels_.size() == output_layer->channels() (1 vs. 10) Number of labels is different from the output layer dimension.

分类的标签文件不对，在label.txt中只写了个0，应该是0,1,2,3,4,5,6,7,8,9

[b]设置：input_param { shape: { dim: 1 dim: 3 dim: 28 dim: 28 } }时出现：Cannot copy param 0 weights from layer 'conv1'; shape mismatch. Source param shape is 20 1 5 5 (500); target param shape is 20 3 5 5 (1500). To learn this layer's parameters from scratch rather than copying from a saved net, rename the layer.[/b]

设置训练模型时的通道数的地方没找到，后面回来补充下。

关于MNIST数据集测试不准确的问题



之前感觉是均值文件的问题，因为训练LeNet时没加减均值的过程，但应该不至于有很高的错误率，后面在知乎上 https://www.zhihu.com/question/52047327 原来训练集是黑底白字的！将测试样本改为黑底白字后就ok了