I have a pretty solidly-functioning Kivy app, written in python and using the OpenCV2 library. having gotten it working on my laptop (windows) I then tried to convert it into an android APK using the python-for-android VM. after some issues (including adding more space to the VM and installing OpenCV on it) I managed to compile the APK successfully.
however, when running the app on android, the opencv part doesn't seem to be working. the kivy menus and such work fine, but loading the video - the job that opencv handles - simply doesn't happen. I'm going to try and connect the android device to the VM directly in order to try and get some debug information, but for now, can anyone think of any reasons why I might be having these issues?
thanks.
I'm interested in incorporating TensorFlow into a C++ server application built in Visual Studio on Windows 10 and I need to know if that's possible.
Google recently announced Windows support for TensorFlow: https://developers.googleblog.com/2016/11/tensorflow-0-12-adds-support-for-windows.html
but from what I can tell this is just a pip install for the more commonly used Python package, and to use the C++ API you need to build the repo from source yourself: How to build and use Google TensorFlow C++ api
I tried building the project myself using bazel, but ran into issues trying to configure the build.
Is there a way to get TensorFlow C++ to work in native Windows (not using Docker or the new Windows 10 Linux subsystem, as I've seen others post about)?
Thanks,
Ian
It is certainly possible to use TensorFlow's C++ API on Windows, but it is not currently very easy. Right now, the easiest way to build against the C++ API on Windows would be to build with CMake, and adapt the CMake rules for the tf_tutorials_example_trainer project (see the source code here). Building with CMake will give you a Visual Studio project in which you can implement your C++ TensorFlow program.
Note that the tf_tutorials_example_trainer project builds a Console Application that statically links all of the TensorFlow runtime into your program. At present we have not written the necessary rules to create a reusable TensorFlow DLL, although this would be technially possible: for example, the Python extension is a DLL that includes the runtime, but does not export the necessary symbols to use TensorFlow's C or C++ APIs directly.
There is a detailed guide by Joe Antognini and a similar TensorFlow ReadMe at GitHub explaining the building of TensorFlow source via CMake. You also need to have SWIG installed on your machine which allows connecting C/C++ source with the Python scripting language. I did use Visual CMAKE (cmake-gui) with the screen capture shown below.
In the CMake configuration, I used Visual Studio 15 2017 compiler. Once this stage successfully completes, you can click on the Generate button to go ahead with the actual build process.
However, on Visual Studio 2015, when I attempted building via the "ALL_BUILD" project, the setup gave me "build tools for v141 cannot be found" error. This did not go away even when I attempted to retarget my solution. Finally, the solution got built successfully with Visual Studio 2017. You also need to manually set the SWIG_EXECUTABLE path in CMake before it successfully configures.
As indicated in the Antognini link, for me the build took about half an hour on a 16GB RAM, Core i7 machine. Once done, you might want to validate your build by attempting to run the tf_tutorials_example_trainer.exe file.
Hope this helps!
For our latest work on building TensorFlow C++ API on Windows, please look at this github page. This works on Windows 10, currently without CUDA support (only CPU).
PS:
Only the bazel build method works, because CMake is not supported and not maintained anymore, resulting in CMake configuration errors.
I had to use a downgraded version of my Visual Studio 2017 (from 15.7.5 to 15.4) by adding "VC++ 2017 version 15.4 v14.11 toolset" through the installer (Individual Components tab).
The cmake command which worked for me was:
cmake .. -A x64 -DCMAKE_BUILD_TYPE=Release ^
-T "v141,version=14.11" ^
-DSWIG_EXECUTABLE="C:/Program Files/swigwin-3.0.12/swig.exe" ^
-DPYTHON_EXECUTABLE="C:/Program Files/Python/python.exe" ^
-DPYTHON_LIBRARIES="C:/Program Files/Python/libs/python27.lib" ^
-Dtensorflow_ENABLE_GPU=ON ^
-DCUDNN_HOME="C:/Program Files/cudnn-9.2-windows10-x64-v7.1/cuda" ^
-DCUDA_TOOLKIT_ROOT_DIR="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v9.0"
After the build, open tensorflow.sln in Visual Studio and build ALL_BUILD.
If you want to enable GPU computation, do check your Graphics Card here (Compute Capability > 3.5). Do remember to install all the packages (Cuda Toolkit 9.0, cuDNN, Python 3.7, SWIG, Git, CMake...) and add the paths to the environment variable in the beginning.
I made a README detailing how to I built the Tensorflow dll and .lib file for the C++ API on Windows with GPU support building from source with Bazel. Tensorflow version 1.14
The tutorial is step by step and starts at the very beginning, so you may have to scroll down past steps you have already done, like checking your hardware, installing Bazel etc.
Here is the url: https://github.com/sitting-duck/stuff/tree/master/ai/tensorflow/build_tensorflow_1.14_source_for_Windows
Probably you will want to scroll all the way down to this part:
https://github.com/sitting-duck/stuff/tree/master/ai/tensorflow/build_tensorflow_1.14_source_for_Windows#step-7-build-the-dll
It shows how to pass command to create .lib and .dll.
Then to test your .lib you should link it into your c++ project,
Then it will show you how to identify and fix the missing symbols using the TF_EXPORT macro
I am actively working on making this tutorial better so feel free to leave comments on this answer if you are having problems.
I'm trying to write a program that uses SURF algorithm and I know that the nonfree module must be installed separately. I've downloaded and installed the latest version of CMake(3.5.2) and I'm following the instructions from:
https://github.com/itseez/opencv_contrib/ . I'm using the GUI and I run Visual Studio 2015 on a 64 bit Windows 10.
Since I know that for SURF you must include xfeatures2d when it asked me the source of the code I only specified the xfeatures2d folder. When I first pressed the configure button I had some errors(I've attached an image of them). I managed to get rid of one of the errors, the one that said to write a line of code at the top of the file
cmake_minimum_required(VERSION 3.5), but I still have one error:
CMake Error at CMakeLists.txt:4 (ocv_define_module):
Unknown CMake command "ocv_define_module".
I'm also attaching a picture of the CMakeLists.txt. Please help me find the problem.
Also, if you could help my install all modules at once, I would be grateful. Or do I have to set as input every folder in the modules folder?
GUI error and CMakeLists.txt
Try using Visual Studio 12 2013 for compilation, this has worked for me, but not the other (newer) versions of Visual Studio.
I'm trying (with no success) to cross-compile OpenCV on a embedded board.
I followed this: http://docs.opencv.org/doc/tutorials/introduction/crosscompilation/arm_crosscompile_with_cmake.html.
To summarize I installed the cross compilation tools for ARM, the I ran the cmake (providing the proper toolchain file), the make and the make install commands.
I next copied the lib/ include and bin/ directories with the opencv installation in the embedded board.
However, when I try to compile a simple hello world with opencv I get undefined reference to __gnu_thumb1_case_uqi and other similar symbols.
Does anybody faced this problem and know how to solve it?
Alternative approach
Just take some embedded distro like Buildroot, OpenEmbedded or Debian. They all provide OpenCV.
As I'm mostly experienced in Buildroot, I'd like to point to the newly introduced feature to keep your project separate from BR: http://nightly.buildroot.org/manual.html#outside-br-custom. This will give you a main idea on how to compile your software against BR's OpenCV.
cloned openCV and modified the build script to include 64bit arm according to suggested answer
But getting many errors and it is not building.
Any work around for this?
I can post the log if needed.