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tkDNN on Windows

Index

Dependencies-Windows

This branch should work on every NVIDIA GPU supported in windows with the following dependencies:

  • WINDOWS 10 1803 or HIGHER
  • CUDA 10.0 (Recommended CUDA 11.2 )
  • CUDNN 7.6 (Recommended CUDNN 8.1.1 )
  • TENSORRT 6.0.1 (Recommended TENSORRT 7.2.3.4 )
  • OPENCV 3.4 (Recommended OPENCV 4.2.0 )
  • MSVC 16.7
  • YAML-CPP
  • EIGEN3
  • 7ZIP (ADD TO PATH)
  • NINJA 1.10

All the above mentioned dependencies except 7ZIP can be installed using Microsoft's VCPKG . After bootstrapping VCPKG the dependencies can be built and installed using the following command :

opencv4(normal) - vcpkg.exe install opencv4[tbb,jpeg,tiff,opengl,openmp,png,ffmpeg,eigen]:x64-windows yaml-cpp:x64-windows eigen3:x64-windows --x-install-root=C:\opt --x-buildtrees-root=C:\temp_vcpkg_build

opencv4(cuda) - vcpkg.exe install opencv4[cuda,nonfree,contrib,eigen,tbb,jpeg,tiff,opengl,openmp,png,ffmpeg]:x64-windows yaml-cpp:x64-windows eigen3:x64-windows --x-install-root=C:\opt --x-buildtrees-root=C:\temp_vcpkg_build

To build opencv4 with cuda and cudnn version corresponding to your cuda version,vcpkg's cudnn portfile needs to be modified by adding $ENV{CUDA_PATH} at lines 16 and 17 in the portfile.cmake

After VCPKG finishes building and installing all the packages delete C:\temp_vcpkg_build and add C:\opt\x64-windows\bin and C:\opt\x64-windows\debug\bin to path

Compiling tkDNN on Windows

tkDNN is built with cmake(3.15+) on windows along with ninja.Msbuild and NMake Makefiles are drastically slower when compiling the library compared to windows

git clone https://github.com/ceccocats/tkDNN.git
cd tkdnn-windows
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -G"Ninja" ..
ninja -j4

Run the demo on Windows

This example uses yolo4_tiny.
To run the object detection file create .rt file bu running:

.\test_yolo4tiny.exe

Once the rt file has been successfully create,run the demo using the following command:

.\demo.exe yolo4tiny_fp32.rt ..\demo\yolo_test.mp4 y

For general info on more demo paramters,check Run the demo section on top To run the test_all_tests.sh on windows,use git bash or msys2

FP16 inference windows

This is an untested feature on windows.To run the object detection demo with FP16 interference follow the below steps(example with yolo4tiny):

set TKDNN_MODE=FP16
del /f yolo4tiny_fp16.rt
.\test_yolo4tiny.exe
.\demo.exe yolo4tiny_fp16.rt ..\demo\yolo_test.mp4

INT8 inference windows

To run object detection demo with INT8 (example with yolo4tiny):

set TKDNN_MODE=INT8
set TKDNN_CALIB_LABEL_PATH=..\demo\COCO_val2017\all_labels.txt
set TKDNN_CALIB_IMG_PATH=..\demo\COCO_val2017\all_images.txt
del /f  yolo4tiny_int8.rt        # be sure to delete(or move) old tensorRT files
.\test_yolo4tiny.exe           # run the yolo test (is slow)
.\demo.exe yolo4tiny_int8.rt ..\demo\yolo_test.mp4 y

Known issues with tkDNN on Windows

Mobilenet and Centernet demos work properly only when built with msvc 16.7 in Release Mode,when built in debug mode for the mentioned networks one might encounter opencv assert errors

All Darknet models work properly with demo using MSVC version(16.7-16.9)

It is recommended to use Nvidia Driver(465+),Cuda unknown errors have been observed when using older drivers on pascal(SM 61) devices.