Deep learning on Raspberry Pi Squeezenet example unable to find opencv library
2 次查看(过去 30 天)
显示 更早的评论
I'm trying to execute this example: https://www.mathworks.com/help/coder/ug/code-generation-for-deep-learning-on-raspberry-pi.html and deploy it on a Raspberry Pi 3 Model B on which i have installed the Raspbian image provided by Mathworks. I followed the setup instructions to write the SD card with the Raspbian image. I connected the Raspberry Pi directly to the PC.
I have succesfully installed the ARM COMPUTE Library and correctly set-up the path on the Raspberry. I tried to do the same with opencv library: in this case I installed the library version 4.2.0 since the installation of the previous versions (3.1.0 and 3.2.0) failed. Also in this case I tried to set-up the path as specified here: https://www.mathworks.com/matlabcentral/answers/455591-matlab-coder-how-do-i-setup-the-environment-variables-on-arm-targets-to-point-to-the-arm-compute-li but probably I'm doing something wrong because I'm obtaining this error:
Error executing command "touch -c /home/pi/remoteBuildDir/MATLAB_ws/R2019b/C/Users/matte/Documents/MATLAB/Examples/R2019b/deeplearning_shared/CodeGenerationForDeepLearningOnRaspberryPiExample/codegen/exe/squeezenet_raspi_predict/*.*;make -f squeezenet_raspi_predict_rtw.mk all MATLAB_WORKSPACE="/home/pi/remoteBuildDir/MATLAB_ws/R2019b" -C /home/pi/remoteBuildDir/MATLAB_ws/R2019b/C/Users/matte/Documents/MATLAB/Examples/R2019b/deeplearning_shared/CodeGenerationForDeepLearningOnRaspberryPiExample/codegen/exe/squeezenet_raspi_predict". Details:
STDERR: /home/pi/remoteBuildDir/MATLAB_ws/R2019b/C/Users/matte/Documents/MATLAB/Examples/R2019b/deeplearning_shared/CodeGenerationForDeepLearningOnRaspberryPiExample/main_squeezenet_raspi.cpp:9:31: fatal error: /opencv2/opencv.hpp: No such file or directory
#include "/opencv2/opencv.hpp"
^
compilation terminated.
make: *** [main_squeezenet_raspi.cpp.o] Error 1
Has anyone had this problem? How did you solve?
Thank you.
0 个评论
采纳的回答
Hariprasad Ravishankar
2020-3-9
Hi Matteo,
It is likely that the compiler is unable to find the headers for opencv.
You can add the include path to opecv by using coder.updateBuildInfo as follows.
If opencv is installed under ~/opencv3.4 , you may include coder.updateBuildInfo('addIncludePaths', '~/opencv3.4/include')
function out = squeezenet_raspi_predict(in)
%#codegen
% A persistent object mynet is used to load the DAGNetwork object.
% At the first call to this function, the persistent object is constructed and
% set up. When the function is called subsequent times, the same object is reused
% to call predict on inputs, avoiding reconstructing and reloading the
% network object.
persistent net;
opencv_linkflags = '`pkg-config --cflags --libs opencv`';
coder.updateBuildInfo('addLinkFlags',opencv_linkflags);
coder.updateBuildInfo('addIncludePaths', '~/opencv3.4/include');
if isempty(net)
net = coder.loadDeepLearningNetwork('squeezenet', 'squeezenet');
end
out = net.predict(in);
end
Hari
0 个评论
更多回答(1 个)
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!