This is not the original Caffe Readme but an installation guide for windows version.
You can download the windows x64 standalone package and run directly on MNIST dataset.
You may need the followings to build the code:
- Windows 64-bit
- MS Visual Studio 2012
- CUDA toolkit 6.0
- Other dependencies which you can directly download from here.
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.
- Include any .cpp you want to build in the
./tools
directory to MainCaller.cpp. - Open the solution file in
./build/MSVC
- Switch build target to x64 platform (Both debug and release are OK).
- Build the code and you may find the
./bin/MainCaller.exe
- 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 .
I have trained on ImageNet with this windows porting as well. And some Issues found are:
- Batch size of 256 exceeds the maximum block number for cuda on my GTX Titan. So using size of 200 is fine.
- The speed is much slower than the one build on Ubuntu. 20 iterations take 79s on Windows, whereas same number of iterations take about 30s on Ubuntu.
- Please create new issues in github if you find any bug.
- If you have new pull requests, they are very welcome.