Awesome
MenohSharp
C# binding for Menoh DNN inference library.
This project is for 64 bit only.
Requirements
To execute an example, please put binaries in ./bin/
Windows
Visual Studio 2015 or later
Mac
mono or Visual Studio For Mac
Linux(Experiment)
mono
Build
Windows
Double click retrieve_data.bat or execute below command in root directory .
retrieve_data.bat
Open MenohSharp.sln and compile with Visual Studio 2015 or later.
Mac, Linux
Execute below command in root directory.
sh retrieve_data.sh
xbuild MenohSharp/MenohSharp.csproj /t:build /p:Configuration=Release /p:Platform=x64
Running VGG16 example
Windows
Execute ./bin/MenohSharpExample.exe
Mac, Linux
Execute below command in root directory.
xbuild MenohSharp/MenohSharp.csproj /t:build /p:Configuration=Release /p:Platform=x64
cd menoh
mono MenohSharpExample.exe
If libgdiplus.dylib is not found on Mac, please execute below command (brew and cask are required)
brew cask install mono-mdk
Result is below
-22.45651 -34.58567 -10.29389 24.40432 -0.2879904 -7.913781...
top 5 categories are
8 0.9613832 categories aren01514859 hen
7 0.03693673 categories aren01514668 cock
86 0.001228112 categories aren01807496 partridge
82 0.000224892 categories aren01797886 ruffed grouse, partridge, Bonasa umbellus
97 3.720724E-05 categories aren01847000 drake
Licence
Note: retrieve_data.sh downloads data/VGG16.onnx. data/VGG16.onnx is generated by onnx-chainer from pre-trained model which is uploaded
at http://www.robots.ox.ac.uk/%7Evgg/software/very_deep/caffe/VGG_ILSVRC_16_layers.caffemodel
That pre-trained model is released under Creative Commons Attribution License.
The library license is as follows.