Hello, im trying to install caffe on windows. Setps to reproduce: C: Projects >git clone C: Projects >cd caffe C: Projects caffe >git checkout windows:: Edit any of the options inside build_win.cmd to suit your needs C: Projects caffe >scripts build_win. Cmd my build_win config: msvs_version=12 with_ninja=0 cpu_only=0 CMAKE_CONFIG=Release CMAKE_BUILD_SHARED_LIBS=0 BUILD_PYTHON=1 BUILD_PYTHON_LAYER=1 BUILD_MATLAB=0 PYTHON_EXE=python RUN_TESTS=0 RUN_LINT=0 RUN_INSTALL=1 also using cudnn,so i added '-DCUDNN_ROOT=D:/cuda ^' on cmake. After a while, the process completes, with tons of warning, but 0 errors.

So i tried 'C: Projects caffe >call build libraries prependpath.bat' next, but nothing happened, it didnt set any env variables on my path. So i added myself. Also im trying to install DIGITS, but DIGITS doesnt seem to find where caffe is, and i belive its because i've set the env variables wrong. Screenshot attached.

To speed up your Caffe models, install cuDNN then uncomment the USE_CUDNN:= 1 flag in Makefile.config when installing Caffe. Acceleration is automatic. CPU-only Caffe: for cold-brewed CPU-only Caffe uncomment the CPU_ONLY:= 1 flag in Makefile.config to configure and build Caffe without CUDA. Jan 11, 2015 Caffe is a deep learning framework popular in Linux with Python or Matlab interface. I just managed to compile Caffe in Windows, and I think it's worth.

$CAFFE_ROOT=D: Projects caffe build $PYTHONPATH=D: Projects caffe python if someone could figure out what im doing wrong, i would really apreciate. Thank you Tiago Silva 28.12.16 3:58.

README.md Windows Installation This is not the original but an installation guide for windows version. Want to run first before build by yourself? You can download the windows x64 and run directly on MNIST dataset. Prerequisites You may need the followings to build the code: • Windows 64-bit • MS Visual Studio 2012 • CUDA toolkit 6.5 • Other dependencies which you can directly download from. Build Steps Currently it can be built by VS2012 for x64 flatform only. This is because the dependencies mentioned above is cross-compiled to support x64 only. If you want to build on 32bit windows, you need to rebuild your own 3rd-party libraries.

• Check out the code and switch to windows branch • Download the dependency file and extract the folders inside to project root directory. • Open the solution file in./build/MSVC • Switch build target to x64 platform (Both debug and release are OK). • Include any.cpp you want to build in the. Stickman Game For Pc on this page. /tools directory to MainCaller.cpp.

• Build the code and you may find the./bin/MainCaller.exe Train MNIST dataset • Suppose you choose to build train_net.cpp which is the default one in MainCaller.cpp • If you do not have GPU, please change it to CPU in lenet_solver.prototxt • Goto directory./examples/mnist • Double click get_mnist_leveldb.bat to download the dataset in leveldb format. • Double click train_lenet.bat to see the training progress. Tips • It takes obvious longer time when you compile for the first time.

Therefore please refrain from using clean & rebuild. • To support different, the code is built for several compute capability versions. If you know the exact version of your GPU device, you may remove the support to other versions to speed up the compiling procedure. You may wish to take a look at #25 for more details. Known Issues • Because I am very busy doing my own project (may or may not be deep learning related), I am sorry that I do not have time to update the code to keep pace with the official Caffe development.

As for the same reason, I will not be able to answer all the questions or solve the issues for some time. • I have trained on ImageNet with this windows porting as well. Frontline Solver there.

The speed is much slower than the one built on Ubuntu. 20 iterations take 79s on Windows, whereas same number of iterations take about 30s on Ubuntu (on GTX Titan). • The above issue has been solved since the upgrade of GPU driver to 340.62 and CUDA to 6.5.