Open SineXue opened 5 years ago
1: 安装CUDA 9.2, cuda9.2版已经带有显卡驱动,默认安装,保持cuda和显卡驱动一致,否则会报cuda runtime is inefficient 35号错误。
2:确认各项目的include、lib和第三方库路径的配置,本人在项目中除CUDA使用绝对路径外,其余的include、lib路径均使用相对路径
caffe项目:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include
....\opensource\boost_1_57_0 ....\opensource\opencv\include ....\3rdparty\include ....\include ....\3rdparty\include\lmdb ....\3rdparty\include\hdf5 ....\src\ ....\3rdparty\include\glog ....\3rdparty\include\cudnn ....\src\caffe\proto ....\3rdparty\include\openblas
....\opensource\boost_1_57_0\lib ....\opensource\opencv\lib C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\lib\x64 ....\3rdparty\lib ....\tools_bin
libClassfication项目:
..\..\3rdparty\include\openblas
....\opensource\opencv\include ....\opensource\boost_1_57_0 ....\3rdparty\include ....\include ....\3rdparty\include\lmdb ....\3rdparty\include\hdf5 ....\src\ ....\3rdparty\include\glog ....\3rdparty\include\cudnn ....\src\caffe\proto C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\lib\x64 ....\opensource\boost_1_57_0\lib ....\opensource\opencv\lib ....\3rdparty\lib ....\tools_bin
ocr_test:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include ....\opensource\boost_1_57_0 ....\opensource\opencv\include ..\libClassification ....\include ....\3rdparty\include ....\src\ ....\3rdparty\include\openblas
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\lib\x64 ....\opensource\opencv\lib ....\opensource\boost_1_57_0\lib ....\tools_bin 3:生成时要选择Release,x64格式
4:在项目的cuda生成host代码时,支持一些旧版本的cu伪代码,三个项目都设置成:compute_61,sm_61;compute_52,sm_52;compute_50,sm_50;compute_35,sm_35;compute_30,sm_30,否则会报no kernel image 40号错误
5:整理的3rdparty请使用群文件的3rdparty-20180730.tar
6:在visual studio 2015打开caffe.sln方案时(项目根目录下),如果出现无法加载工程的错误,打开项目根目录下的caffe-vsproj\caffe.sln
7:导入工程后,在ocr_test的项目,右键,选择【生成依赖项】-> 【项目依赖项】,勾选caffe, libClassfication两个项目
8: 项目代码中对路径没有做规范化处理,导致在运行期间报找不到模型文件的错误,为了调试方便,这里把代码中的路径全部修改成绝对路径,如ocr_test.cpp的962行, string modelfolder = "E:\License-Plate-Detect-Recognition\caffe-vsproj\ocr_test\plateCard_test"; 其他的类似修改 但要区分MTCNN模型和ICNNPredict模型的位置
9:启动一个cmd,切换到工程根目录下的tools_bin目录,启动ocr_test.ext
@zhubenfu 您好,我在群里下的3rdparty20180726.7z(没有找到您说的3rdparty-20180730.tar)第三方文件, cuda改成了9.2,cudnn用7.1和3rdparty里边的都说不兼容! 方便的话,您能告知一下用哪个版本的cudnn吗? 十分感谢!
链接:https://pan.baidu.com/s/1nX3CgpTckEOjSXlNvaruNw 提取码:8gls 或者加群 群里有更新
how to test one picture on this project, please