Davide Sapienza
96 lines
3.7 KiB
Markdown
96 lines
3.7 KiB
Markdown
# tkDNN on Windows
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## Index
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- [Dependencies-Windows](#dependencies-windows)
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- [Compiling tkDNN on Windows](#compiling-tkdnn-on-windows)
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- [Run the demo on Windows](#run-the-demo-on-windows)
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- [FP16 inference windows](#fp16-inference-windows)
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- [INT8 inference windows](#int8-inference-windows)
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- [Known issues with tkDNN on Windows](#known-issues-with-tkdnn-on-windows)
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### Dependencies-Windows
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This branch should work on every NVIDIA GPU supported in windows with the following dependencies:
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* WINDOWS 10 1803 or HIGHER
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* CUDA 10.0 (Recommended CUDA 11.2 )
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* CUDNN 7.6 (Recommended CUDNN 8.1.1 )
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* TENSORRT 6.0.1 (Recommended TENSORRT 7.2.3.4 )
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* OPENCV 3.4 (Recommended OPENCV 4.2.0 )
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* MSVC 16.7
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* YAML-CPP
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* EIGEN3
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* 7ZIP (ADD TO PATH)
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* NINJA 1.10
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All the above mentioned dependencies except 7ZIP can be installed using Microsoft's [VCPKG](https://github.com/microsoft/vcpkg.git) .
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After bootstrapping VCPKG the dependencies can be built and installed using the following command :
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```
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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
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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
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```
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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
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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
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### Compiling tkDNN on Windows
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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
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```
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git clone https://github.com/ceccocats/tkDNN.git
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cd tkdnn-windows
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mkdir build
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cd build
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cmake -DCMAKE_BUILD_TYPE=Release -G"Ninja" ..
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ninja -j4
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```
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### Run the demo on Windows
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This example uses yolo4_tiny.\
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To run the object detection file create .rt file bu running:
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```
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.\test_yolo4tiny.exe
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```
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Once the rt file has been successfully create,run the demo using the following command:
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```
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.\demo.exe yolo4tiny_fp32.rt ..\demo\yolo_test.mp4 y
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```
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For general info on more demo paramters,check Run the demo section on top
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To run the test_all_tests.sh on windows,use git bash or msys2
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### FP16 inference windows
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This is an untested feature on windows.To run the object detection demo with FP16 interference follow the below steps(example with yolo4tiny):
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```
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set TKDNN_MODE=FP16
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del /f yolo4tiny_fp16.rt
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.\test_yolo4tiny.exe
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.\demo.exe yolo4tiny_fp16.rt ..\demo\yolo_test.mp4
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```
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### INT8 inference windows
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To run object detection demo with INT8 (example with yolo4tiny):
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```
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set TKDNN_MODE=INT8
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set TKDNN_CALIB_LABEL_PATH=..\demo\COCO_val2017\all_labels.txt
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set TKDNN_CALIB_IMG_PATH=..\demo\COCO_val2017\all_images.txt
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del /f yolo4tiny_int8.rt # be sure to delete(or move) old tensorRT files
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.\test_yolo4tiny.exe # run the yolo test (is slow)
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.\demo.exe yolo4tiny_int8.rt ..\demo\yolo_test.mp4 y
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```
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### Known issues with tkDNN on Windows
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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
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All Darknet models work properly with demo using MSVC version(16.7-16.9)
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It is recommended to use Nvidia Driver(465+),Cuda unknown errors have been observed when using older drivers on pascal(SM 61) devices.
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